refactor: clean up imports and improve code formatting across multiple files

- Removed the "3h" and "6h" periods from the log aggregation process in maintenance.py to streamline log counts.
- Enhanced code readability by adjusting line breaks and indentation in repositories.py for better clarity.

.dockerignore

@@ -5,7 +5,9 @@ __pycache__
 .pytest_cache
 .mypy_cache
 .ruff_cache
+build
 data
+dist
 logs
 *.pyc
 .env

.editorconfig

@@ -0,0 +1,20 @@
+# EditorConfig is awesome: https://editorconfig.org
+
+# top-most EditorConfig file
+root = true
+
+# Unix-style newlines with a newline ending every file
+[*]
+end_of_line = lf
+insert_final_newline = true
+
+# Matches multiple files with brace expansion notation
+# Set default charset
+[*.{js,py}]
+charset = utf-8
+
+# 4 space indentation
+[*.py]
+indent_style = space
+indent_size = 4
+max_line_length = 120

.env.example

@@ -1,6 +1,11 @@
 APP_ENV=dev
 APP_HOST=0.0.0.0
 APP_PORT=8000
+PG_HOST=192.168.88.35
+PG_PORT=5432
+PG_DATABASE=arbitrade
+PG_USER=arbitrade
+PG_PASSWORD=arbitrade
 LOG_LEVEL=INFO
 LOG_JSON=true
 ALERTS_ENABLED=true

.gitignore

@@ -31,10 +31,14 @@ Thumbs.db
 !.env.example
 secrets/
 
+# Local build artifacts
+build/
+dist/
+
 # Local database / runtime data
-data/*.duckdb
 data/*.duckdb.wal
 data/*.duckdb.tmp
+data/arbitrade.duckdb
 logs/
 ops/performance/latest_profile.json
 

Dockerfile

@@ -12,7 +12,6 @@ RUN pip install --no-cache-dir -r requirements/latest-runtime.in
 
 COPY pyproject.toml README.md /app/
 COPY src /app/src
-COPY web /app/web
 
 RUN pip install --no-cache-dir --no-deps .
 

README.md

@@ -6,13 +6,12 @@ Current stack:
 
 - Python 3.12+
 - FastAPI + HTMX/Jinja2
-- DuckDB for dev/test/prod
+- PostgreSQL for all environments (via asyncpg)
 - Native Kraken WebSocket planned for market-data hot path
 - Gitea Actions + Gitea container registry
 
-Project plan lives in [PLAN.md](PLAN.md).
 Task checklist lives in [.github/instructions/TODO.md](.github/instructions/TODO.md).
-Coolify deployment runbooks live in [DEPLOYMENT.md](DEPLOYMENT.md).
+Coolify deployment runbooks live in [docs/DEPLOYMENT.md](docs/DEPLOYMENT.md).
 
 ## Current Status
 
@@ -22,7 +21,7 @@ Bootstrap complete for foundation layer:
 - typed settings and env loading
 - structured logging
 - encrypted secret helpers
-- DuckDB connection + base schema
+- PostgreSQL connection + full schema migration
 - FastAPI app with health endpoint
 - Gitea Actions CI scaffold
 - Docker / docker-compose scaffold
@@ -35,6 +34,50 @@ Not implemented yet:
 - trade execution
 - dashboard beyond health/bootstrap page
 
+## Configuration Management
+
+The arbitrage trading bot now includes a complete configuration management system that allows users to configure trading behavior, currency pairings, fees, and other application settings through a web interface. All user-configurable settings are persisted in the database while system variables remain in environment variables as per the settings split plan.
+
+Key features include:
+
+- Web-based configuration interface at `/dashboard/config/`
+- Runtime hot-reloading of configuration changes
+- Complete CRUD operations for all configuration entities
+- Input validation and error handling
+- Audit logging for all configuration changes
+- Backtesting parameter configuration
+- Fee configuration by pairing and market type
+
+## Templates
+
+Full page templates (`src/arbitrade/web/templates/`):
+
+| Template           | Route                    | Purpose                                                 |
+| ------------------ | ------------------------ | ------------------------------------------------------- |
+| `base.html`        | — (root layout)          | Dark theme, `.shell` container, HTMX, CSS variables     |
+| `dashboard.html`   | `/`, `/dashboard`        | Main dashboard: metrics, overview, controls, charts     |
+| `config.html`      | `/dashboard/config`      | Full configuration: fees, runtime, alerts, Kraken, risk |
+| `audit.html`       | `/dashboard/audit`       | Audit trail with auto-refresh via HTMX                  |
+| `backtesting.html` | `/dashboard/backtesting` | Backtesting panel with replay/sweep forms               |
+| `health.html`      | `/health`                | System health check                                     |
+
+Dashboard partials (`src/arbitrade/web/templates/partials/`):
+
+| Partial                  | In page          | Content                                                                                             |
+| ------------------------ | ---------------- | --------------------------------------------------------------------------------------------------- |
+| `metrics.html`           | Dashboard        | 6 KPI cards: P&L, win rate, avg duration, trade count, success %, profit factor                     |
+| `overview.html`          | Dashboard        | Status, balances, fee tier, open trades list, opportunity feed                                      |
+| `controls.html`          | Dashboard        | Runtime status, kill switch, config snapshot, alerting status, execution controls (Start/Stop/Kill) |
+| `charts.html`            | Dashboard        | Opportunity trend chart (Chart.js, Alpine toggle)                                                   |
+| `config.html`            | Config page      | Config form: Runtime, Alerts, Kraken, Risk, Strategy sections                                       |
+| `config_fees.html`       | Config page      | Pair fee table + add/edit form                                                                      |
+| `backtesting_panel.html` | Backtesting page | Run status, replay/sweep forms, recent runs                                                         |
+| `audit.html`             | Audit page       | Audit trail table: time, actor, event, decision, payload                                            |
+
+Legacy templates (`src/arbitrade/web/templates/dashboard/`):
+
+- `config_settings.html`, `config_pairs.html`, `config_fees.html` — superseded by config page; retained for reference
+
 ## Prerequisites
 
 - Python 3.12+
@@ -108,7 +151,11 @@ APP_HOST=0.0.0.0
 APP_PORT=9090
 LOG_LEVEL=INFO
 LOG_JSON=true
-DUCKDB_PATH=./data/arbitrade.duckdb
+PG_HOST=192.168.88.35
+PG_PORT=5432
+PG_DATABASE=arbitrade
+PG_USER=arbitrade
+PG_PASSWORD=arbitrade
 FERNET_KEY=
 KRAKEN_API_KEY=
 KRAKEN_API_SECRET=
@@ -138,15 +185,19 @@ Health endpoints:
 
 ## Database
 
-DuckDB used everywhere: local dev, tests, production.
+PostgreSQL used everywhere: local dev, tests, production.
 
-Default database file:
+Default connection:
 
 ```text
-./data/arbitrade.duckdb
+PG_HOST=192.168.88.35
+PG_PORT=5432
+PG_DATABASE=arbitrade
+PG_USER=arbitrade
+PG_PASSWORD=arbitrade
 ```
 
-Schema bootstrap runs automatically on app startup.
+Schema bootstrap runs automatically on app startup via `PgStore.migrate()`.
 
 Current tables:
 
@@ -176,7 +227,7 @@ DELETE FROM audit_events
 WHERE occurred_at < NOW() - INTERVAL 30 DAY;
 ```
 
-- Back up archive files and the main DuckDB file together.
+- Back up archive files and the PostgreSQL database together.
 - For production, run archive + backup as scheduled maintenance (cron/task scheduler).
 
 ## Quality Checks
@@ -298,7 +349,7 @@ Add a persistent volume in Coolify:
 
 - Mount Path: `/app/data`
 
-This preserves DuckDB and other runtime artifacts across restarts/redeploys.
+This preserves PostgreSQL data and other runtime artifacts across restarts/redeploys.
 
 ### 5) Configure environment variables
 
@@ -307,7 +358,11 @@ Add runtime environment variables in Coolify (UI: Environment Variables):
 - `APP_ENV=prod`
 - `APP_HOST=0.0.0.0`
 - `APP_PORT=9090`
-- `DUCKDB_PATH=/app/data/arbitrade.duckdb`
+- `PG_HOST=postgres`
+  `PG_PORT=5432`
+  `PG_DATABASE=arbitrade`
+  `PG_USER=arbitrade`
+  `PG_PASSWORD=arbitrade`
 - `LOG_LEVEL=INFO`
 - `LOG_JSON=true`
 - `KRAKEN_API_KEY=...`
@@ -352,9 +407,9 @@ git.allucanget.biz/allucanget/arbitrade:latest
 
 ## Architecture Docs
 
-Implementation detail moved into arc42 docs:
+Implementation detail moved into docs:
 
-- [arc42 overview](docs/architecture/arc42.md) - system context, building blocks, runtime, deployment, quality goals, risks.
+- [architecture overview](docs/architecture/README.md) - system context, building blocks, runtime, deployment, quality goals, risks.
 - [current implementation snapshot](docs/architecture/current-implementation.md) - codebase state, active routes, backtesting, strategy flags, deployment flow.
 
 For navigation from README, use the docs above instead of this file for deep architecture detail.

build/lib/arbitrade/__init__.py

@@ -1,3 +0,0 @@
-__all__ = ["__version__"]
-
-__version__ = "0.1.0"

build/lib/arbitrade/alerting/__init__.py

@@ -1,25 +0,0 @@
-"""Alerting primitives and channel clients."""
-
-from arbitrade.alerting.notifier import (
-    AlertEvent,
-    AlertNotifier,
-    AlertSeverity,
-    DiscordWebhookChannel,
-    EmailSmtpChannel,
-    SupportsAlertStatus,
-    TelegramChannel,
-    build_channels_from_settings,
-    dispatch_alert_nowait,
-)
-
-__all__ = [
-    "AlertEvent",
-    "AlertNotifier",
-    "AlertSeverity",
-    "DiscordWebhookChannel",
-    "EmailSmtpChannel",
-    "SupportsAlertStatus",
-    "TelegramChannel",
-    "build_channels_from_settings",
-    "dispatch_alert_nowait",
-]

build/lib/arbitrade/alerting/notifier.py

@@ -1,400 +0,0 @@
-from __future__ import annotations
-
-import asyncio
-import smtplib
-from dataclasses import dataclass
-from datetime import UTC, datetime
-from email.message import EmailMessage
-from typing import Literal, Protocol, runtime_checkable
-
-import httpx
-
-AlertSeverity = Literal["info", "warning", "error", "critical"]
-
-_SEVERITY_RANK: dict[AlertSeverity, int] = {
-    "info": 10,
-    "warning": 20,
-    "error": 30,
-    "critical": 40,
-}
-
-
-@dataclass(frozen=True, slots=True)
-class AlertEvent:
-    category: str
-    severity: AlertSeverity
-    title: str
-    message: str
-    occurred_at: datetime
-    details: dict[str, str]
-
-
-class AlertChannel(Protocol):
-    async def send(self, event: AlertEvent) -> None: ...
-
-
-class SupportsAlerts(Protocol):
-    async def notify(
-        self,
-        *,
-        category: str,
-        severity: AlertSeverity,
-        title: str,
-        message: str,
-        details: dict[str, str] | None = None,
-    ) -> bool: ...
-
-
-@runtime_checkable
-class SupportsAlertStatus(Protocol):
-    def status_snapshot(self) -> dict[str, object]: ...
-
-
-class AlertNotifier:
-    def __init__(
-        self,
-        channels: list[AlertChannel],
-        *,
-        enabled: bool = True,
-        min_severity: AlertSeverity = "info",
-        dedup_seconds: float = 0.0,
-        category_flags: dict[str, bool] | None = None,
-    ) -> None:
-        if dedup_seconds < 0.0:
-            raise ValueError("dedup_seconds must be >= 0.0")
-        self._channels = channels
-        self._enabled = enabled
-        self._min_severity: AlertSeverity = min_severity
-        self._dedup_seconds = dedup_seconds
-        self._category_flags = {key.lower(): value for key, value in (category_flags or {}).items()}
-        self._last_sent_at: dict[str, datetime] = {}
-        self._last_result: str = "never"
-        self._last_attempted_at: datetime | None = None
-        self._last_success_at: datetime | None = None
-        self._last_error: str | None = None
-        self._last_event_title: str | None = None
-        self._last_event_category: str | None = None
-        self._last_event_severity: AlertSeverity | None = None
-        self._last_channel_results: list[str] = []
-
-    @property
-    def has_channels(self) -> bool:
-        return bool(self._channels)
-
-    async def notify(
-        self,
-        *,
-        category: str,
-        severity: AlertSeverity,
-        title: str,
-        message: str,
-        details: dict[str, str] | None = None,
-    ) -> bool:
-        if not self._enabled or not self._channels:
-            self._last_result = "skipped_disabled" if not self._enabled else "skipped_no_channels"
-            return False
-
-        normalized_category = category.strip().lower()
-        if self._category_flags and not self._category_flags.get(normalized_category, True):
-            self._last_result = "skipped_category"
-            return False
-
-        if _SEVERITY_RANK[severity] < _SEVERITY_RANK[self._min_severity]:
-            self._last_result = "skipped_severity"
-            return False
-
-        dedup_key = f"{normalized_category}|{severity}|{title}|{message}"
-        now = datetime.now(UTC)
-        if self._dedup_seconds > 0.0:
-            previous = self._last_sent_at.get(dedup_key)
-            if previous is not None:
-                elapsed = (now - previous).total_seconds()
-                if elapsed < self._dedup_seconds:
-                    self._last_result = "skipped_dedup"
-                    return False
-
-        event = AlertEvent(
-            category=normalized_category,
-            severity=severity,
-            title=title,
-            message=message,
-            occurred_at=now,
-            details=details or {},
-        )
-
-        results = await asyncio.gather(
-            *(channel.send(event) for channel in self._channels),
-            return_exceptions=True,
-        )
-        self._last_attempted_at = now
-        self._last_event_title = title
-        self._last_event_category = normalized_category
-        self._last_event_severity = severity
-        self._last_channel_results = []
-        for channel, result in zip(self._channels, results, strict=False):
-            channel_name = type(channel).__name__
-            if isinstance(result, Exception):
-                self._last_channel_results.append(f"{channel_name}: error")
-            else:
-                self._last_channel_results.append(f"{channel_name}: ok")
-
-        if all(isinstance(result, Exception) for result in results):
-            self._last_result = "failed"
-            self._last_error = "all channels failed"
-            return False
-
-        self._last_result = (
-            "partial_success"
-            if any(isinstance(result, Exception) for result in results)
-            else "success"
-        )
-        self._last_error = None
-        self._last_success_at = now
-
-        self._last_sent_at[dedup_key] = now
-        return True
-
-    def status_snapshot(self) -> dict[str, object]:
-        return {
-            "enabled": self._enabled,
-            "has_channels": self.has_channels,
-            "configured_channels": [type(channel).__name__ for channel in self._channels],
-            "min_severity": self._min_severity,
-            "dedup_seconds": self._dedup_seconds,
-            "last_result": self._last_result,
-            "last_attempted_at": (
-                self._last_attempted_at.isoformat() if self._last_attempted_at is not None else None
-            ),
-            "last_success_at": (
-                self._last_success_at.isoformat() if self._last_success_at is not None else None
-            ),
-            "last_error": self._last_error,
-            "last_event": (
-                None
-                if self._last_event_title is None
-                else {
-                    "title": self._last_event_title,
-                    "category": self._last_event_category,
-                    "severity": self._last_event_severity,
-                }
-            ),
-            "last_channel_results": self._last_channel_results,
-        }
-
-
-def dispatch_alert_nowait(
-    notifier: SupportsAlerts | None,
-    *,
-    category: str,
-    severity: AlertSeverity,
-    title: str,
-    message: str,
-    details: dict[str, str] | None = None,
-) -> None:
-    if notifier is None:
-        return
-    try:
-        loop = asyncio.get_running_loop()
-    except RuntimeError:
-        return
-
-    loop.create_task(
-        notifier.notify(
-            category=category,
-            severity=severity,
-            title=title,
-            message=message,
-            details=details,
-        )
-    )
-
-
-def _format_event_text(event: AlertEvent) -> str:
-    lines = [
-        f"[{event.severity.upper()}] {event.title}",
-        f"Category: {event.category}",
-        f"Time: {event.occurred_at.isoformat()}",
-        event.message,
-    ]
-    if event.details:
-        lines.append("Details:")
-        for key, value in sorted(event.details.items()):
-            lines.append(f"- {key}: {value}")
-    return "\n".join(lines)
-
-
-class TelegramChannel:
-    def __init__(self, *, bot_token: str, chat_id: str, timeout_seconds: float = 10.0) -> None:
-        self._bot_token = bot_token
-        self._chat_id = chat_id
-        self._timeout_seconds = timeout_seconds
-
-    async def send(self, event: AlertEvent) -> None:
-        url = f"https://api.telegram.org/bot{self._bot_token}/sendMessage"
-        payload = {
-            "chat_id": self._chat_id,
-            "text": _format_event_text(event),
-            "disable_web_page_preview": True,
-        }
-        timeout = httpx.Timeout(self._timeout_seconds)
-        async with httpx.AsyncClient(timeout=timeout) as client:
-            response = await client.post(url, json=payload)
-            response.raise_for_status()
-
-
-class DiscordWebhookChannel:
-    def __init__(self, *, webhook_url: str, timeout_seconds: float = 10.0) -> None:
-        self._webhook_url = webhook_url
-        self._timeout_seconds = timeout_seconds
-
-    async def send(self, event: AlertEvent) -> None:
-        payload = {"content": _format_event_text(event)}
-        timeout = httpx.Timeout(self._timeout_seconds)
-        async with httpx.AsyncClient(timeout=timeout) as client:
-            response = await client.post(self._webhook_url, json=payload)
-            response.raise_for_status()
-
-
-class EmailSmtpChannel:
-    def __init__(
-        self,
-        *,
-        host: str,
-        port: int,
-        sender: str,
-        recipients: list[str],
-        username: str | None = None,
-        password: str | None = None,
-        use_tls: bool = True,
-        timeout_seconds: float = 10.0,
-    ) -> None:
-        if not recipients:
-            raise ValueError("recipients must not be empty")
-
-        self._host = host
-        self._port = port
-        self._sender = sender
-        self._recipients = recipients
-        self._username = username
-        self._password = password
-        self._use_tls = use_tls
-        self._timeout_seconds = timeout_seconds
-
-    async def send(self, event: AlertEvent) -> None:
-        message = EmailMessage()
-        message["From"] = self._sender
-        message["To"] = ", ".join(self._recipients)
-        message["Subject"] = f"[{event.severity.upper()}] {event.title}"
-        message.set_content(_format_event_text(event))
-
-        await asyncio.to_thread(self._send_sync, message)
-
-    def _send_sync(self, message: EmailMessage) -> None:
-        with smtplib.SMTP(self._host, self._port, timeout=self._timeout_seconds) as client:
-            if self._use_tls:
-                client.starttls()
-            if self._username and self._password:
-                client.login(self._username, self._password)
-            client.send_message(message)
-
-
-class _AlertSettings(Protocol):
-    alerts_enabled: bool
-    alert_min_severity: str
-    alert_dedup_seconds: float
-    alert_on_trade_events: bool
-    alert_on_error_events: bool
-    alert_on_threshold_events: bool
-    alert_on_system_events: bool
-
-    telegram_alerts_enabled: bool
-    telegram_bot_token: str | None
-    telegram_chat_id: str | None
-
-    discord_alerts_enabled: bool
-    discord_webhook_url: str | None
-
-    email_alerts_enabled: bool
-    email_smtp_host: str | None
-    email_smtp_port: int
-    email_smtp_username: str | None
-    email_smtp_password: str | None
-    email_alert_from: str | None
-    email_alert_to: str | None
-    email_smtp_use_tls: bool
-
-
-def _as_alert_severity(value: str) -> AlertSeverity:
-    normalized = value.strip().lower()
-    if normalized == "info":
-        return "info"
-    if normalized == "warning":
-        return "warning"
-    if normalized == "error":
-        return "error"
-    if normalized == "critical":
-        return "critical"
-    else:
-        raise ValueError("alert_min_severity must be one of: info, warning, error, critical")
-
-
-def build_channels_from_settings(settings: _AlertSettings) -> list[AlertChannel]:
-    channels: list[AlertChannel] = []
-
-    if settings.telegram_alerts_enabled:
-        if not settings.telegram_bot_token or not settings.telegram_chat_id:
-            raise ValueError("telegram alerts require bot token and chat id")
-        channels.append(
-            TelegramChannel(
-                bot_token=settings.telegram_bot_token,
-                chat_id=settings.telegram_chat_id,
-            )
-        )
-
-    if settings.discord_alerts_enabled:
-        if not settings.discord_webhook_url:
-            raise ValueError("discord alerts require webhook url")
-        channels.append(DiscordWebhookChannel(webhook_url=settings.discord_webhook_url))
-
-    if settings.email_alerts_enabled:
-        if not settings.email_smtp_host:
-            raise ValueError("email alerts require SMTP host")
-        if not settings.email_alert_from:
-            raise ValueError("email alerts require sender address")
-        if not settings.email_alert_to:
-            raise ValueError("email alerts require recipient list")
-
-        recipients = [
-            address.strip() for address in settings.email_alert_to.split(",") if address.strip()
-        ]
-        channels.append(
-            EmailSmtpChannel(
-                host=settings.email_smtp_host,
-                port=settings.email_smtp_port,
-                sender=settings.email_alert_from,
-                recipients=recipients,
-                username=settings.email_smtp_username,
-                password=settings.email_smtp_password,
-                use_tls=settings.email_smtp_use_tls,
-            )
-        )
-
-    return channels
-
-
-def build_notifier_from_settings(settings: _AlertSettings) -> AlertNotifier:
-    severity = _as_alert_severity(settings.alert_min_severity)
-    channels = build_channels_from_settings(settings)
-    category_flags = {
-        "trade": settings.alert_on_trade_events,
-        "error": settings.alert_on_error_events,
-        "threshold": settings.alert_on_threshold_events,
-        "system": settings.alert_on_system_events,
-    }
-    return AlertNotifier(
-        channels,
-        enabled=settings.alerts_enabled,
-        min_severity=severity,
-        dedup_seconds=settings.alert_dedup_seconds,
-        category_flags=category_flags,
-    )

build/lib/arbitrade/api/app.py

@@ -1,44 +0,0 @@
-from __future__ import annotations
-
-from collections.abc import AsyncIterator
-from contextlib import asynccontextmanager
-
-from fastapi import FastAPI
-
-from arbitrade.alerting.notifier import build_notifier_from_settings
-from arbitrade.api.control_state import DashboardControlState
-from arbitrade.api.routes import public_router, router
-from arbitrade.config.settings import Settings
-from arbitrade.logging_setup import configure_logging
-from arbitrade.metrics import MetricsCalculator
-from arbitrade.runtime.lifecycle import graceful_shutdown, restore_runtime_state
-from arbitrade.storage.db import DuckDBStore
-from arbitrade.storage.repositories import AuditRepository, RuntimeStateRepository
-
-
-def create_app(settings: Settings) -> FastAPI:
-    configure_logging(settings.log_level, settings.log_json)
-
-    db = DuckDBStore(settings)
-    db.migrate()
-
-    @asynccontextmanager
-    async def lifespan(app: FastAPI) -> AsyncIterator[None]:
-        await restore_runtime_state(app)
-        yield
-        await graceful_shutdown(app)
-
-    app = FastAPI(title="arbitrade", version="0.1.0", lifespan=lifespan)
-    app.state.settings = settings
-    app.state.store = db
-    app.state.metrics = MetricsCalculator(db)
-    app.state.audit_repository = AuditRepository(db)
-    app.state.runtime_state_repository = RuntimeStateRepository(db)
-    app.state.alert_notifier = build_notifier_from_settings(settings)
-    app.state.backtest_recent_reports = []
-    app.state.dashboard_controls = DashboardControlState(
-        is_running=not settings.kill_switch_active,
-    )
-    app.include_router(public_router)
-    app.include_router(router)
-    return app

build/lib/arbitrade/api/auth.py

@@ -1,38 +0,0 @@
-from __future__ import annotations
-
-from secrets import compare_digest
-from typing import Annotated
-
-from fastapi import Depends, HTTPException, Request, status
-from fastapi.security import HTTPBasic, HTTPBasicCredentials
-
-dashboard_basic_auth = HTTPBasic(auto_error=False)
-
-
-def require_dashboard_auth(
-    request: Request,
-    credentials: Annotated[HTTPBasicCredentials | None, Depends(dashboard_basic_auth)],
-) -> None:
-    settings = request.app.state.settings
-    username = settings.dashboard_auth_username
-    password = settings.dashboard_auth_password
-
-    if username is None and password is None:
-        return
-
-    if username is None or password is None:
-        raise HTTPException(
-            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
-            detail="Dashboard auth misconfigured",
-        )
-
-    if (
-        credentials is None
-        or not compare_digest(credentials.username, username)
-        or not compare_digest(credentials.password, password)
-    ):
-        raise HTTPException(
-            status_code=status.HTTP_401_UNAUTHORIZED,
-            detail="Not authenticated",
-            headers={"WWW-Authenticate": 'Basic realm="Arbitrade Dashboard"'},
-        )

build/lib/arbitrade/api/control_state.py

@@ -1,20 +0,0 @@
-from __future__ import annotations
-
-from dataclasses import dataclass, field
-from datetime import UTC, datetime
-
-from arbitrade.risk.kill_switch import KillSwitch
-
-
-@dataclass(slots=True)
-class DashboardControlState:
-    is_running: bool = True
-    kill_switch: KillSwitch = field(default_factory=KillSwitch)
-    tradable_pairs: list[str] = field(default_factory=list)
-    strategy_mode: str = "incremental"
-    strategy_profit_threshold: float = 0.0005
-    strategy_max_depth_levels: int = 10
-    updated_at: datetime = field(default_factory=lambda: datetime.now(UTC))
-
-    def mark_updated(self) -> None:
-        self.updated_at = datetime.now(UTC)

build/lib/arbitrade/api/routes.py

@@ -1,944 +0,0 @@
-from __future__ import annotations
-
-import json
-from asyncio import Lock
-from collections.abc import AsyncIterator
-from datetime import UTC, datetime
-from importlib import resources
-from pathlib import Path
-from typing import cast
-from urllib.parse import parse_qs
-
-import duckdb
-from fastapi import APIRouter, Depends, Request
-from fastapi.responses import HTMLResponse, JSONResponse, StreamingResponse
-from fastapi.templating import Jinja2Templates
-
-from arbitrade.alerting.notifier import SupportsAlerts, SupportsAlertStatus
-from arbitrade.api.auth import require_dashboard_auth
-from arbitrade.api.control_state import DashboardControlState
-from arbitrade.backtesting.replay import BacktestConfig, BacktestReplayEngine, load_replay_events
-from arbitrade.detection.graph import CurrencyGraph, TriangularCycle
-from arbitrade.storage.repositories import AuditRecord, AuditRepository
-
-router = APIRouter(dependencies=[Depends(require_dashboard_auth)])
-public_router = APIRouter()
-
-
-def _resolve_templates_directory() -> str:
-    # Support source layout, Docker runtime (/app), and installed package data.
-    source_layout_path = Path(
-        __file__).resolve().parents[3] / "web" / "templates"
-    if source_layout_path.is_dir():
-        return str(source_layout_path)
-
-    docker_runtime_path = Path.cwd() / "web" / "templates"
-    if docker_runtime_path.is_dir():
-        return str(docker_runtime_path)
-
-    try:
-        package_path = resources.files(
-            "arbitrade").joinpath("web", "templates")
-        if package_path.is_dir():
-            return str(package_path)
-    except (ModuleNotFoundError, AttributeError):
-        pass
-
-    return str(source_layout_path)
-
-
-templates = Jinja2Templates(directory=_resolve_templates_directory())
-_BACKTEST_ROOT = Path(__file__).resolve().parents[3]
-_BACKTEST_RUN_LOCK = Lock()
-
-
-def _format_metric(value: float | None, *, precision: int = 2, suffix: str = "") -> str:
-    if value is None:
-        return "—"
-    return f"{value:.{precision}f}{suffix}"
-
-
-def _dashboard_metrics(request: Request) -> dict[str, str]:
-    metrics = request.app.state.metrics.compute()
-    return {
-        "realized_pnl": _format_metric(metrics.realized_pnl_usd, precision=2, suffix=" USD"),
-        "win_rate": _format_metric(
-            metrics.win_rate * 100.0 if metrics.win_rate is not None else None,
-            precision=1,
-            suffix="%",
-        ),
-        "avg_trade_duration": _format_metric(
-            metrics.avg_trade_duration_seconds, precision=1, suffix=" s"
-        ),
-        "opportunities_per_minute": _format_metric(
-            metrics.opportunities_per_minute, precision=1, suffix=" /min"
-        ),
-        "fill_rate": _format_metric(
-            metrics.fill_rate * 100.0 if metrics.fill_rate is not None else None,
-            precision=1,
-            suffix="%",
-        ),
-        "latency_p50": _format_metric(metrics.latency_p50_seconds, precision=3, suffix=" s"),
-        "latency_p95": _format_metric(metrics.latency_p95_seconds, precision=3, suffix=" s"),
-        "latency_p99": _format_metric(metrics.latency_p99_seconds, precision=3, suffix=" s"),
-        "generated_at": datetime.now(UTC).isoformat(),
-    }
-
-
-def _table_columns(conn: duckdb.DuckDBPyConnection, table_name: str) -> set[str]:
-    rows = conn.execute(f"PRAGMA table_info('{table_name}')").fetchall()
-    return {str(row[1]) for row in rows}
-
-
-def _dashboard_overview(request: Request) -> dict[str, object]:
-    store = request.app.state.store
-    with store.connect() as conn:
-        trade_columns = _table_columns(conn, "trades")
-        trade_ref_expr = "trade_ref" if "trade_ref" in trade_columns else "CAST(id AS VARCHAR)"
-        cycle_expr = "cycle" if "cycle" in trade_columns else "NULL"
-        if "finished_at" in trade_columns:
-            open_trade_filter = "finished_at IS NULL"
-        else:
-            open_trade_filter = "LOWER(status) NOT IN ('filled', 'closed', 'cancelled', 'canceled')"
-
-        portfolio_row = conn.execute("""
-            SELECT balances, total_value_usd
-            FROM portfolio_snapshots
-            ORDER BY snapshot_at DESC
-            LIMIT 1
-            """).fetchone()
-        open_trades = conn.execute(f"""
-            SELECT {trade_ref_expr}, status, started_at, {cycle_expr}
-            FROM trades
-            WHERE {open_trade_filter}
-            ORDER BY started_at DESC
-            LIMIT 5
-            """).fetchall()
-        rpnl = conn.execute("""
-            SELECT COALESCE(SUM(COALESCE(realized_pnl, 0)), 0)
-            FROM trades
-            """).fetchone()
-        latest_opportunities = conn.execute("""
-            SELECT cycle, net_pct, est_profit, detected_at
-            FROM opportunities
-            ORDER BY detected_at DESC
-            LIMIT 5
-            """).fetchall()
-
-    balances_value = "—"
-    total_value = "—"
-    if portfolio_row is not None:
-        balances_raw, total_value_raw = portfolio_row
-        balances_value = str(balances_raw) if balances_raw is not None else "—"
-        if total_value_raw is not None:
-            total_value = f"{float(total_value_raw):.2f} USD"
-
-    open_trade_rows = [
-        {
-            "trade_ref": str(row[0]),
-            "status": str(row[1]),
-            "started_at": row[2].isoformat() if isinstance(row[2], datetime) else "—",
-            "cycle": str(row[3]) if row[3] is not None else "—",
-        }
-        for row in open_trades
-    ]
-    opportunity_rows = [
-        {
-            "cycle": str(row[0]),
-            "net_pct": f"{float(row[1]):.2f}%" if row[1] is not None else "—",
-            "est_profit": f"{float(row[2]):.2f} USD" if row[2] is not None else "—",
-            "detected_at": row[3].isoformat() if isinstance(row[3], datetime) else "—",
-        }
-        for row in latest_opportunities
-    ]
-
-    return {
-        "status": "live",
-        "generated_at": datetime.now(UTC).isoformat(),
-        "balances": balances_value,
-        "total_value": total_value,
-        "open_trade_count": len(open_trade_rows),
-        "open_trades": open_trade_rows,
-        "realized_pnl_total": f"{float(rpnl[0]):.2f} USD" if rpnl else "—",
-        "opportunities": opportunity_rows,
-    }
-
-
-def _dashboard_charts(request: Request) -> dict[str, object]:
-    store = request.app.state.store
-    with store.connect() as conn:
-        opportunity_rows = conn.execute("""
-            SELECT detected_at, cycle, net_pct, est_profit
-            FROM opportunities
-            ORDER BY detected_at DESC
-            LIMIT 10
-            """).fetchall()
-
-    cr = list(reversed(opportunity_rows))
-    labels = []
-    for index, row in enumerate(cr):
-        if isinstance(row[0], datetime):
-            labels.append(row[0].isoformat())
-        else:
-            labels.append(f"opportunity-{index + 1}")
-    np = [float(row[2]) if row[2] is not None else 0.0 for row in cr]
-    ep = [float(row[3]) if row[3] is not None else 0.0 for row in cr]
-    cycles = [str(row[1]) for row in cr]
-
-    return {
-        "labels": labels,
-        "net_pct_values": np,
-        "est_profit_values": ep,
-        "cycles": cycles,
-        "has_chart_data": bool(cr),
-        "generated_at": datetime.now(UTC).isoformat(),
-    }
-
-
-def _dashboard_controls_state(request: Request) -> DashboardControlState:
-    return cast(DashboardControlState, request.app.state.dashboard_controls)
-
-
-def _audit_repository(request: Request) -> AuditRepository | None:
-    repository = getattr(request.app.state, "audit_repository", None)
-    return cast(AuditRepository | None, repository)
-
-
-def _record_audit(
-    request: Request,
-    *,
-    actor: str,
-    event_type: str,
-    decision: str,
-    payload: dict[str, object] | None = None,
-) -> None:
-    repository = _audit_repository(request)
-    if repository is None:
-        return
-    correlation_id = request.headers.get("x-request-id")
-    if payload is not None:
-        ret_pl = {str(key): payload[key] for key in payload}
-    else:
-        ret_pl = None
-    repository.insert(
-        AuditRecord(
-            occurred_at=datetime.now(UTC),
-            actor=actor,
-            event_type=event_type,
-            decision=decision,
-            payload=ret_pl,
-            correlation_id=correlation_id,
-        )
-    )
-
-
-def _dashboard_audit(request: Request, *, limit: int = 15) -> dict[str, object]:
-    repository = _audit_repository(request)
-    if repository is None:
-        return {
-            "entries": [],
-            "generated_at": datetime.now(UTC).isoformat(),
-        }
-
-    records = repository.list_recent(limit=limit)
-    entries: list[dict[str, str]] = []
-    for record in records:
-        payload_text = "—"
-        if record.payload:
-            payload_text = json.dumps(record.payload)
-        entries.append(
-            {
-                "occurred_at": record.occurred_at.isoformat(),
-                "actor": record.actor,
-                "event_type": record.event_type,
-                "decision": record.decision,
-                "payload": payload_text,
-                "correlation_id": record.correlation_id or "—",
-            }
-        )
-
-    return {
-        "entries": entries,
-        "generated_at": datetime.now(UTC).isoformat(),
-    }
-
-
-def _alert_notifier(request: Request) -> SupportsAlerts | None:
-    notifier = getattr(request.app.state, "alert_notifier", None)
-    return cast(SupportsAlerts | None, notifier)
-
-
-def _alert_status_snapshot(request: Request) -> dict[str, object]:
-    notifier = getattr(request.app.state, "alert_notifier", None)
-    if isinstance(notifier, SupportsAlertStatus):
-        return notifier.status_snapshot()
-    return {
-        "enabled": False,
-        "has_channels": False,
-        "configured_channels": [],
-        "min_severity": "—",
-        "dedup_seconds": 0.0,
-        "last_result": "unavailable",
-        "last_attempted_at": None,
-        "last_success_at": None,
-        "last_error": None,
-        "last_event": None,
-        "last_channel_results": [],
-    }
-
-
-def _dashboard_controls(request: Request) -> dict[str, object]:
-    ctl = _dashboard_controls_state(request)
-    rs = request.app.state.settings
-    alert_status = _alert_status_snapshot(request)
-    last_event = alert_status.get("last_event")
-    last_event_title = "—"
-    if isinstance(last_event, dict):
-        title_value = last_event.get("title")
-        if isinstance(title_value, str):
-            last_event_title = title_value
-
-    cc = alert_status.get("configured_channels")
-    cd = "—"
-    if isinstance(cc, list) and cc:
-        cd = ", ".join(str(channel) for channel in cc)
-
-    ddsr = alert_status.get("dedup_seconds", 0.0)
-    dds = float(ddsr) if isinstance(ddsr, int | float) else 0.0
-    tpd = ", ".join(ctl.tradable_pairs) if ctl.tradable_pairs else "All"
-    max_trade_capital_usd = (
-        f"{float(rs.max_trade_capital_usd):.2f} USD"
-        if rs.max_trade_capital_usd is not None
-        else "—"
-    )
-    max_trade_capital_usd_value = (
-        f"{float(rs.max_trade_capital_usd):.2f}" if rs.max_trade_capital_usd is not None else ""
-    )
-    max_concurrent_trades = (
-        str(rs.max_concurrent_trades) if rs.max_concurrent_trades is not None else "—"
-    )
-    max_concurrent_trades_value = (
-        str(rs.max_concurrent_trades) if rs.max_concurrent_trades is not None else ""
-    )
-    alerts_last_channel_results = [
-        str(item) for item in cast(list[object], alert_status.get("last_channel_results", []))
-    ]
-    strategy_stat_arb_enabled = bool(
-        getattr(rs, "strategy_enable_stat_arb_experiment", False))
-
-    return {
-        "execution_status": "running" if ctl.is_running else "stopped",
-        "kill_switch_status": "active" if ctl.kill_switch.is_active else "inactive",
-        "kill_switch_reason": ctl.kill_switch.reason or "—",
-        "paper_trading_mode": "enabled" if rs.paper_trading_mode else "disabled",
-        "trade_capital_usd": f"{float(rs.trade_capital_usd):.2f} USD",
-        "trade_capital_usd_value": f"{float(rs.trade_capital_usd):.2f}",
-        "max_trade_capital_usd": max_trade_capital_usd,
-        "max_trade_capital_usd_value": max_trade_capital_usd_value,
-        "max_concurrent_trades": max_concurrent_trades,
-        "max_concurrent_trades_value": max_concurrent_trades_value,
-        "alerts_enabled": "enabled" if bool(alert_status.get("enabled", False)) else "disabled",
-        "alerts_channels": cd,
-        "alerts_min_severity": str(alert_status.get("min_severity", "—")),
-        "alerts_dedup_seconds": f"{dds:.0f}",
-        "alerts_last_result": str(alert_status.get("last_result", "unavailable")),
-        "alerts_last_attempted_at": str(alert_status.get("last_attempted_at") or "—"),
-        "alerts_last_success_at": str(alert_status.get("last_success_at") or "—"),
-        "alerts_last_event_title": last_event_title,
-        "alerts_last_error": str(alert_status.get("last_error") or "—"),
-        "alerts_last_channel_results": alerts_last_channel_results,
-        "tradable_pairs_display": tpd,
-        "tradable_pairs_value": ", ".join(ctl.tradable_pairs),
-        "strategy_mode": ctl.strategy_mode,
-        "strategy_stat_arb_enabled": strategy_stat_arb_enabled,
-        "strategy_profit_threshold": f"{ctl.strategy_profit_threshold:.6f}",
-        "strategy_max_depth_levels": str(ctl.strategy_max_depth_levels),
-        "updated_at": ctl.updated_at.isoformat(),
-        "start_endpoint": "/dashboard/control/start",
-        "stop_endpoint": "/dashboard/control/stop",
-        "kill_switch_endpoint": "/dashboard/control/kill-switch",
-        "config_endpoint": "/dashboard/control/config",
-        "chart_endpoint": "/dashboard/fragment/charts",
-    }
-
-
-def _parse_form_body(body: bytes) -> dict[str, str]:
-    parsed = parse_qs(body.decode("utf-8"), keep_blank_values=True)
-    return {key: values[-1] for key, values in parsed.items() if values}
-
-
-def _form_bool(value: str | None) -> bool:
-    if value is None:
-        return False
-    return value.lower() in {"1", "true", "yes", "on"}
-
-
-def _parse_comma_separated_list(value: str | None) -> list[str]:
-    if value is None:
-        return []
-
-    items: list[str] = []
-    for raw_item in value.split(","):
-        item = raw_item.strip().upper()
-        if item and item not in items:
-            items.append(item)
-    return items
-
-
-def _normalize_fee_profile(profile: str) -> str:
-    return profile.strip().lower().replace("-", "_")
-
-
-def _fee_rate_for_profile(profile: str, custom_fee_rate: float | None) -> float:
-    normalized = _normalize_fee_profile(profile)
-    profile_map = {
-        "standard": 0.0026,
-        "maker_heavy": 0.0016,
-        "taker_heavy": 0.0035,
-    }
-    if normalized == "custom":
-        if custom_fee_rate is None:
-            raise ValueError("custom fee profile requires custom_fee_rate")
-        if custom_fee_rate < 0.0:
-            raise ValueError("custom_fee_rate must be >= 0")
-        return custom_fee_rate
-    if normalized not in profile_map:
-        valid = ", ".join(sorted(list(profile_map.keys()) + ["custom"]))
-        raise ValueError(f"fee_profile must be one of: {valid}")
-    return profile_map[normalized]
-
-
-def _parse_balances(raw: str) -> dict[str, float]:
-    balances: dict[str, float] = {}
-    for entry in raw.split(","):
-        stripped = entry.strip()
-        if not stripped:
-            continue
-        if "=" not in stripped:
-            raise ValueError("starting_balances must be in ASSET=value format")
-        asset, value = stripped.split("=", 1)
-        balances[asset.strip().upper()] = float(value)
-    if not balances:
-        raise ValueError("starting_balances must include at least one balance")
-    return balances
-
-
-def _resolve_workspace_path(raw: str) -> Path:
-    candidate = Path(raw.strip())
-    if not candidate.is_absolute():
-        candidate = (_BACKTEST_ROOT / candidate).resolve()
-    else:
-        candidate = candidate.resolve()
-    return candidate
-
-
-def _display_path(path: Path) -> str:
-    try:
-        return str(path.relative_to(_BACKTEST_ROOT))
-    except ValueError:
-        return str(path)
-
-
-def _build_cycles_from_events(
-    symbols: set[str],
-) -> tuple[dict[str, list[TriangularCycle]], list[str]]:
-    graph = CurrencyGraph()
-    for symbol in sorted(symbols):
-        if "/" not in symbol:
-            continue
-        base, quote = symbol.upper().split("/", 1)
-        graph.add_pair(base, quote, f"{base}/{quote}")
-    cycles = graph.triangular_cycles()
-    return graph.index_cycles_by_pair(cycles), sorted(symbols)
-
-
-def _recent_backtest_reports(request: Request) -> list[dict[str, object]]:
-    reports = getattr(request.app.state, "backtest_recent_reports", [])
-    if isinstance(reports, list):
-        return cast(list[dict[str, object]], reports)
-    return []
-
-
-def _backtesting_panel_context(
-    request: Request,
-    *,
-    status: str = "idle",
-    message: str = "Configure a replay run and execute backtest.",
-    latest_report: dict[str, object] | None = None,
-    defaults: dict[str, str] | None = None,
-) -> dict[str, object]:
-    default_values = {
-        "events_path": "",
-        "starting_balances": "USD=1000.0",
-        "trade_capital": "100.0",
-        "min_profit_threshold": "0.0005",
-        "fee_profile": "standard",
-        "custom_fee_rate": "",
-        "slippage_bps": "4.0",
-        "execution_latency_ms": "20.0",
-    }
-    if defaults is not None:
-        default_values.update(defaults)
-
-    reports = _recent_backtest_reports(request)
-    latest = latest_report or (reports[0] if reports else None)
-
-    return {
-        "status": status,
-        "message": message,
-        "latest_report": latest,
-        "recent_reports": reports,
-        "run_endpoint": "/dashboard/backtesting/run",
-        "reports_endpoint": "/dashboard/api/backtesting/reports",
-        **default_values,
-    }
-
-
-async def _dashboard_response(
-    request: Request, template_name: str = "dashboard.html"
-) -> HTMLResponse:
-    return templates.TemplateResponse(
-        request=request,
-        name=template_name,
-        context={
-            "title": "Arbitrade Dashboard",
-            "request": request,
-            "metrics_endpoint": "/dashboard/fragment/metrics",
-            "overview_endpoint": "/dashboard/fragment/overview",
-            "controls_endpoint": "/dashboard/fragment/controls",
-            "charts_endpoint": "/dashboard/fragment/charts",
-            "audit_endpoint": "/dashboard/fragment/audit",
-            "stream_endpoint": "/dashboard/stream/metrics",
-            "overview_stream_endpoint": "/dashboard/stream/overview",
-        },
-    )
-
-
-@router.get("/", response_class=HTMLResponse)
-async def home(request: Request) -> HTMLResponse:
-    return await _dashboard_response(request)
-
-
-@router.get("/dashboard", response_class=HTMLResponse)
-async def dashboard(request: Request) -> HTMLResponse:
-    return await _dashboard_response(request)
-
-
-@router.get("/dashboard/backtesting", response_class=HTMLResponse)
-async def dashboard_backtesting_page(request: Request) -> HTMLResponse:
-    return templates.TemplateResponse(
-        request=request,
-        name="backtesting.html",
-        context={
-            "title": "Arbitrade Backtesting",
-            "request": request,
-            "panel_endpoint": "/dashboard/fragment/backtesting",
-            "dashboard_endpoint": "/dashboard",
-        },
-    )
-
-
-@router.get("/dashboard/fragment/backtesting", response_class=HTMLResponse)
-async def dashboard_backtesting_fragment(request: Request) -> HTMLResponse:
-    return templates.TemplateResponse(
-        request=request,
-        name="partials/backtesting_panel.html",
-        context={"request": request, **_backtesting_panel_context(request)},
-    )
-
-
-@router.get("/dashboard/fragment/metrics", response_class=HTMLResponse)
-async def dashboard_metrics(request: Request) -> HTMLResponse:
-    return templates.TemplateResponse(
-        request=request,
-        name="partials/metrics.html",
-        context={"request": request, **_dashboard_metrics(request)},
-    )
-
-
-@router.get("/dashboard/fragment/overview", response_class=HTMLResponse)
-async def dashboard_overview(request: Request) -> HTMLResponse:
-    return templates.TemplateResponse(
-        request=request,
-        name="partials/overview.html",
-        context={"request": request, **_dashboard_overview(request)},
-    )
-
-
-@router.get("/dashboard/fragment/controls", response_class=HTMLResponse)
-async def dashboard_controls(request: Request) -> HTMLResponse:
-    return templates.TemplateResponse(
-        request=request,
-        name="partials/controls.html",
-        context={"request": request, **_dashboard_controls(request)},
-    )
-
-
-@router.get("/dashboard/fragment/charts", response_class=HTMLResponse)
-async def dashboard_charts(request: Request) -> HTMLResponse:
-    return templates.TemplateResponse(
-        request=request,
-        name="partials/charts.html",
-        context={"request": request, **_dashboard_charts(request)},
-    )
-
-
-@router.get("/dashboard/fragment/audit", response_class=HTMLResponse)
-async def dashboard_audit(request: Request) -> HTMLResponse:
-    return templates.TemplateResponse(
-        request=request,
-        name="partials/audit.html",
-        context={"request": request, **_dashboard_audit(request)},
-    )
-
-
-@router.get("/dashboard/api/alerts/status", response_class=JSONResponse)
-async def dashboard_alert_status(request: Request) -> JSONResponse:
-    return JSONResponse(_alert_status_snapshot(request))
-
-
-@router.get("/dashboard/api/audit/recent", response_class=JSONResponse)
-async def dashboard_audit_recent(request: Request) -> JSONResponse:
-    return JSONResponse(_dashboard_audit(request, limit=25))
-
-
-@router.get("/dashboard/api/backtesting/reports", response_class=JSONResponse)
-async def dashboard_backtesting_reports(request: Request) -> JSONResponse:
-    return JSONResponse(
-        {
-            "generated_at": datetime.now(UTC).isoformat(),
-            "reports": _recent_backtest_reports(request),
-        }
-    )
-
-
-@router.post("/dashboard/backtesting/run", response_class=HTMLResponse)
-async def dashboard_backtesting_run(request: Request) -> HTMLResponse:
-    form = _parse_form_body(await request.body())
-    defaults = {
-        "events_path": form.get("events_path", ""),
-        "starting_balances": form.get("starting_balances", "USD=1000.0"),
-        "trade_capital": form.get("trade_capital", "100.0"),
-        "min_profit_threshold": form.get("min_profit_threshold", "0.0005"),
-        "fee_profile": _normalize_fee_profile(form.get("fee_profile", "standard")),
-        "custom_fee_rate": form.get("custom_fee_rate", ""),
-        "slippage_bps": form.get("slippage_bps", "4.0"),
-        "execution_latency_ms": form.get("execution_latency_ms", "20.0"),
-    }
-
-    try:
-        events_path = _resolve_workspace_path(defaults["events_path"])
-        if not events_path.exists() or not events_path.is_file():
-            raise ValueError(
-                "events_path must reference an existing JSONL file")
-
-        events = load_replay_events(events_path)
-        if not events:
-            raise ValueError("events file contains no replay events")
-
-        custom_fee_rate = (
-            float(defaults["custom_fee_rate"]
-                  ) if defaults["custom_fee_rate"].strip() else None
-        )
-        fee_rate = _fee_rate_for_profile(
-            defaults["fee_profile"], custom_fee_rate)
-        starting_balances = _parse_balances(defaults["starting_balances"])
-
-        trade_capital = float(defaults["trade_capital"])
-        min_profit_threshold = float(defaults["min_profit_threshold"])
-        slippage_bps = float(defaults["slippage_bps"])
-        execution_latency_ms = float(defaults["execution_latency_ms"])
-
-        cycles_by_pair, available_pairs = _build_cycles_from_events(
-            {event.symbol.upper() for event in events}
-        )
-        if not cycles_by_pair:
-            raise ValueError(
-                "unable to derive triangular cycles from provided events")
-
-        config = BacktestConfig(
-            fee_rate=fee_rate,
-            min_profit_threshold=min_profit_threshold,
-            trade_capital=trade_capital,
-            slippage_bps=slippage_bps,
-            execution_latency_ms=execution_latency_ms,
-        )
-
-        async with _BACKTEST_RUN_LOCK:
-            engine = BacktestReplayEngine(
-                cycles_by_pair=cycles_by_pair,
-                available_pairs=available_pairs,
-                config=config,
-                started_at=events[0].occurred_at,
-            )
-            report = await engine.run(events, starting_balances=starting_balances)
-
-        report_item: dict[str, object] = {
-            "run_at": datetime.now(UTC).isoformat(),
-            "events_path": _display_path(events_path),
-            "status": "completed",
-            "config": {
-                "trade_capital": trade_capital,
-                "min_profit_threshold": min_profit_threshold,
-                "fee_profile": defaults["fee_profile"],
-                "fee_rate": fee_rate,
-                "slippage_bps": slippage_bps,
-                "execution_latency_ms": execution_latency_ms,
-            },
-            "report": {
-                "processed_events": report.processed_events,
-                "opportunities_seen": report.opportunities_seen,
-                "trades_executed": report.trades_executed,
-                "win_rate": report.win_rate,
-                "fill_rate": report.fill_rate,
-                "realized_pnl_usd": report.realized_pnl_usd,
-                "max_drawdown_usd": report.max_drawdown_usd,
-                "miss_reasons": dict(report.miss_reasons),
-                "execution_latency_p50_ms": report.execution_latency_p50_ms,
-                "execution_latency_p95_ms": report.execution_latency_p95_ms,
-                "execution_latency_p99_ms": report.execution_latency_p99_ms,
-            },
-        }
-
-        reports = _recent_backtest_reports(request)
-        reports.insert(0, report_item)
-        del reports[20:]
-
-        _record_audit(
-            request,
-            actor="dashboard_user",
-            event_type="dashboard.backtesting.run",
-            decision="completed",
-            payload={
-                "events_path": report_item["events_path"],
-                "processed_events": report.processed_events,
-                "trades_executed": report.trades_executed,
-                "realized_pnl_usd": report.realized_pnl_usd,
-            },
-        )
-
-        context = _backtesting_panel_context(
-            request,
-            status="completed",
-            message="Backtest run completed successfully.",
-            latest_report=report_item,
-            defaults=defaults,
-        )
-    except ValueError as exc:
-        context = _backtesting_panel_context(
-            request,
-            status="failed",
-            message=str(exc),
-            defaults=defaults,
-        )
-
-    return templates.TemplateResponse(
-        request=request,
-        name="partials/backtesting_panel.html",
-        context={"request": request, **context},
-    )
-
-
-@router.post("/dashboard/control/start", response_class=HTMLResponse)
-async def dashboard_control_start(request: Request) -> HTMLResponse:
-    controls = _dashboard_controls_state(request)
-    controls.is_running = True
-    controls.mark_updated()
-    notifier = _alert_notifier(request)
-    if notifier is not None:
-        await notifier.notify(
-            category="system",
-            severity="info",
-            title="Execution started",
-            message="Dashboard control started execution.",
-        )
-    _record_audit(
-        request,
-        actor="dashboard_user",
-        event_type="dashboard.control.start",
-        decision="approved",
-        payload={"execution_status": "running"},
-    )
-    return templates.TemplateResponse(
-        request=request,
-        name="partials/controls.html",
-        context={"request": request, **_dashboard_controls(request)},
-    )
-
-
-@router.post("/dashboard/control/stop", response_class=HTMLResponse)
-async def dashboard_control_stop(request: Request) -> HTMLResponse:
-    controls = _dashboard_controls_state(request)
-    controls.is_running = False
-    controls.mark_updated()
-    notifier = _alert_notifier(request)
-    if notifier is not None:
-        await notifier.notify(
-            category="system",
-            severity="warning",
-            title="Execution stopped",
-            message="Dashboard control stopped execution.",
-        )
-    _record_audit(
-        request,
-        actor="dashboard_user",
-        event_type="dashboard.control.stop",
-        decision="approved",
-        payload={"execution_status": "stopped"},
-    )
-    return templates.TemplateResponse(
-        request=request,
-        name="partials/controls.html",
-        context={"request": request, **_dashboard_controls(request)},
-    )
-
-
-@router.post("/dashboard/control/kill-switch", response_class=HTMLResponse)
-async def dashboard_control_kill_switch(request: Request) -> HTMLResponse:
-    controls = _dashboard_controls_state(request)
-    form = _parse_form_body(await request.body())
-    reason = form.get("reason") or "manual"
-    controls.kill_switch.activate(reason=reason)
-    controls.is_running = False
-    controls.mark_updated()
-    notifier = _alert_notifier(request)
-    if notifier is not None:
-        await notifier.notify(
-            category="threshold",
-            severity="critical",
-            title="Kill switch activated",
-            message="Kill switch triggered from dashboard control.",
-            details={"reason": reason},
-        )
-    _record_audit(
-        request,
-        actor="dashboard_user",
-        event_type="dashboard.control.kill_switch",
-        decision="approved",
-        payload={"reason": reason},
-    )
-    return templates.TemplateResponse(
-        request=request,
-        name="partials/controls.html",
-        context={"request": request, **_dashboard_controls(request)},
-    )
-
-
-@router.post("/dashboard/control/config", response_class=HTMLResponse)
-async def dashboard_control_config(request: Request) -> HTMLResponse:
-    ctl = _dashboard_controls_state(request)
-    rs = request.app.state.settings
-    form = _parse_form_body(await request.body())
-
-    if "trade_capital_usd" in form and form["trade_capital_usd"]:
-        rs.trade_capital_usd = float(form["trade_capital_usd"])
-    if "max_trade_capital_usd" in form:
-        mtcv = form["max_trade_capital_usd"].strip()
-        rs.max_trade_capital_usd = float(mtcv) if mtcv else None
-    if "max_concurrent_trades" in form:
-        mcv = form["max_concurrent_trades"].strip()
-        rs.max_concurrent_trades = int(mcv) if mcv else None
-
-    form_pairs = form.get("tradable_pairs")
-    ctl.tradable_pairs = _parse_comma_separated_list(form_pairs)
-    if "strategy_mode" in form and form["strategy_mode"].strip():
-        strategy_mode = form["strategy_mode"].strip().lower()
-        allowed_strategy_modes = {"incremental", "paper", "live"}
-        if bool(getattr(rs, "strategy_enable_stat_arb_experiment", False)):
-            allowed_strategy_modes.add("stat_arb_experiment")
-        if strategy_mode not in allowed_strategy_modes:
-            e = f"strategy_mode must be one of: {', '.join(sorted(allowed_strategy_modes))}"
-            raise ValueError(e)
-        ctl.strategy_mode = strategy_mode
-    if "strategy_profit_threshold" in form:
-        if form["strategy_profit_threshold"].strip():
-            spt = float(form["strategy_profit_threshold"])
-            ctl.strategy_profit_threshold = spt
-    if "strategy_max_depth_levels" in form:
-        if form["strategy_max_depth_levels"].strip():
-            smdl = int(form["strategy_max_depth_levels"])
-            ctl.strategy_max_depth_levels = smdl
-
-    rs.paper_trading_mode = _form_bool(form.get("paper_trading_mode"))
-    ctl.mark_updated()
-
-    notifier = _alert_notifier(request)
-    if notifier is not None:
-        await notifier.notify(
-            category="system",
-            severity="info",
-            title="Runtime config updated",
-            message="Dashboard control updated runtime risk and execution settings.",
-            details={
-                "trade_capital_usd": f"{rs.trade_capital_usd}",
-                "max_trade_capital_usd": (
-                    "none" if rs.max_trade_capital_usd is None else f"{rs.max_trade_capital_usd}"
-                ),
-                "max_concurrent_trades": (
-                    "none" if rs.max_concurrent_trades is None else f"{rs.max_concurrent_trades}"
-                ),
-                "paper_trading_mode": "true" if rs.paper_trading_mode else "false",
-            },
-        )
-    _record_audit(
-        request,
-        actor="dashboard_user",
-        event_type="dashboard.control.config",
-        decision="approved",
-        payload={
-            "trade_capital_usd": rs.trade_capital_usd,
-            "max_trade_capital_usd": rs.max_trade_capital_usd,
-            "max_concurrent_trades": rs.max_concurrent_trades,
-            "paper_trading_mode": rs.paper_trading_mode,
-            "tradable_pairs": ctl.tradable_pairs,
-            "strategy_mode": ctl.strategy_mode,
-            "strategy_profit_threshold": ctl.strategy_profit_threshold,
-            "strategy_max_depth_levels": ctl.strategy_max_depth_levels,
-        },
-    )
-
-    return templates.TemplateResponse(
-        request=request,
-        name="partials/controls.html",
-        context={"request": request, **_dashboard_controls(request)},
-    )
-
-
-@router.get("/dashboard/stream/metrics")
-async def dashboard_metrics_stream(request: Request) -> StreamingResponse:
-    fragment = (
-        templates.get_template("partials/metrics.html")
-        .render(
-            request=request,
-            **_dashboard_metrics(request),
-        )
-        .strip()
-        .replace("\n", "")
-    )
-
-    async def _event_stream() -> AsyncIterator[bytes]:
-        payload = json.dumps(fragment)
-        yield f"event: metrics\ndata: {payload}\n\n".encode()
-
-    return StreamingResponse(_event_stream(), media_type="text/event-stream")
-
-
-@router.get("/dashboard/stream/overview")
-async def dashboard_overview_stream(request: Request) -> StreamingResponse:
-    fragment = (
-        templates.get_template("partials/overview.html")
-        .render(request=request, **_dashboard_overview(request))
-        .strip()
-        .replace("\n", "")
-    )
-
-    async def _event_stream() -> AsyncIterator[bytes]:
-        payload = json.dumps(fragment)
-        yield f"event: overview\ndata: {payload}\n\n".encode()
-
-    return StreamingResponse(_event_stream(), media_type="text/event-stream")
-
-
-@public_router.get("/health", response_class=JSONResponse)
-async def health() -> JSONResponse:
-    return JSONResponse({"status": "ok", "service": "arbitrade"})

build/lib/arbitrade/backtesting/__init__.py

@@ -1,35 +0,0 @@
-from arbitrade.backtesting.replay import (
-    BacktestConfig,
-    BacktestReplayEngine,
-    BacktestReport,
-    ReplayBookEvent,
-    ReplayClock,
-    load_replay_events,
-)
-from arbitrade.backtesting.sweep import (
-    PromotionCriteria,
-    SweepArtifacts,
-    SweepParameters,
-    SweepResult,
-    build_parameter_grid,
-    persist_sweep_results,
-    run_parameter_search,
-    split_events_time_windows,
-)
-
-__all__ = [
-    "ReplayClock",
-    "ReplayBookEvent",
-    "BacktestConfig",
-    "BacktestReport",
-    "BacktestReplayEngine",
-    "load_replay_events",
-    "SweepParameters",
-    "SweepResult",
-    "SweepArtifacts",
-    "PromotionCriteria",
-    "split_events_time_windows",
-    "build_parameter_grid",
-    "run_parameter_search",
-    "persist_sweep_results",
-]

build/lib/arbitrade/backtesting/replay.py

@@ -1,326 +0,0 @@
-from __future__ import annotations
-
-import asyncio
-from collections import Counter
-from collections.abc import Mapping, Sequence
-from dataclasses import dataclass
-from datetime import UTC, datetime
-from pathlib import Path
-from typing import Any
-
-import orjson
-
-from arbitrade.detection.engine import IncrementalCycleDetector, OpportunityEvent
-from arbitrade.detection.graph import TriangularCycle
-from arbitrade.exchange.models import BookLevel
-from arbitrade.execution.sequencer import TriangularExecutionSequencer
-from arbitrade.market_data.order_book import OrderBook
-from arbitrade.risk.pre_trade import PreTradeValidator
-from arbitrade.risk.trade_limits import TradeLimitsGuard
-
-
-@dataclass(slots=True)
-class ReplayClock:
-    _current: datetime
-
-    @classmethod
-    def at(cls, started_at: datetime) -> ReplayClock:
-        return cls(_current=started_at.astimezone(UTC))
-
-    @property
-    def now(self) -> datetime:
-        return self._current
-
-    def advance_to(self, next_time: datetime) -> None:
-        normalized = next_time.astimezone(UTC)
-        if normalized < self._current:
-            raise ValueError("Replay events must be monotonic by timestamp")
-        self._current = normalized
-
-    def advance_ms(self, milliseconds: float) -> None:
-        if milliseconds < 0.0:
-            raise ValueError("milliseconds must be >= 0")
-        self._current = self._current.fromtimestamp(
-            self._current.timestamp() + (milliseconds / 1000.0),
-            tz=UTC,
-        )
-
-
-@dataclass(frozen=True, slots=True)
-class ReplayBookEvent:
-    occurred_at: datetime
-    symbol: str
-    bids: tuple[BookLevel, ...]
-    asks: tuple[BookLevel, ...]
-
-
-@dataclass(frozen=True, slots=True)
-class BacktestConfig:
-    fee_rate: float = 0.0026
-    min_profit_threshold: float = 0.0005
-    trade_capital: float = 100.0
-    quote_asset: str = "USD"
-    slippage_bps: float = 4.0
-    execution_latency_ms: float = 20.0
-    max_depth_levels: int = 10
-    max_concurrent_trades: int = 1
-    min_order_size_by_pair: Mapping[str, float] | None = None
-
-
-@dataclass(frozen=True, slots=True)
-class BacktestReport:
-    started_at: datetime
-    finished_at: datetime
-    processed_events: int
-    opportunities_seen: int
-    trades_executed: int
-    win_rate: float | None
-    fill_rate: float | None
-    realized_pnl_usd: float
-    max_drawdown_usd: float
-    miss_reasons: Mapping[str, int]
-    execution_latency_p50_ms: float | None
-    execution_latency_p95_ms: float | None
-    execution_latency_p99_ms: float | None
-
-
-class _SimulatedRestClient:
-    def __init__(
-        self, clock: ReplayClock, *, slippage_bps: float, execution_latency_ms: float
-    ) -> None:
-        self._clock = clock
-        self._slippage_bps = slippage_bps
-        self._execution_latency_ms = execution_latency_ms
-        self._sequence = 0
-        self._last_fill_ratio = 1.0
-        self._last_trade_latency_ms = execution_latency_ms
-
-    @property
-    def last_fill_ratio(self) -> float:
-        return self._last_fill_ratio
-
-    @property
-    def last_trade_latency_ms(self) -> float:
-        return self._last_trade_latency_ms
-
-    async def place_market_order(self, *, pair: str, side: str, volume: float) -> dict[str, Any]:
-        self._sequence += 1
-        self._clock.advance_ms(self._execution_latency_ms)
-        await asyncio.sleep(0)
-
-        normalized_fill = max(0.85, 1.0 - (self._slippage_bps / 10000.0) * 8.0)
-        self._last_fill_ratio = normalized_fill
-        self._last_trade_latency_ms = self._execution_latency_ms
-
-        return {
-            "txid": [f"sim-{self._sequence}"],
-            "status": "closed",
-            "pair": pair,
-            "side": side,
-            "requested_volume": volume,
-            "filled_volume": volume * normalized_fill,
-            "simulated_at": self._clock.now.isoformat(),
-        }
-
-
-def _percentile(values: Sequence[float], percentile: float) -> float | None:
-    if not values:
-        return None
-
-    ordered = sorted(values)
-    if percentile <= 0.0:
-        return ordered[0]
-    if percentile >= 100.0:
-        return ordered[-1]
-
-    rank = (len(ordered) - 1) * (percentile / 100.0)
-    lower = int(rank)
-    upper = min(lower + 1, len(ordered) - 1)
-    weight = rank - lower
-    return ordered[lower] * (1.0 - weight) + ordered[upper] * weight
-
-
-def _parse_book_levels(raw_levels: Any) -> tuple[BookLevel, ...]:
-    if not isinstance(raw_levels, list):
-        raise ValueError("Book levels must be a list")
-
-    levels: list[BookLevel] = []
-    for raw_level in raw_levels:
-        if (
-            not isinstance(raw_level, list)
-            or len(raw_level) != 2
-            or not isinstance(raw_level[0], int | float)
-            or not isinstance(raw_level[1], int | float)
-        ):
-            raise ValueError("Each level must be [price, volume]")
-        levels.append(BookLevel(price=float(raw_level[0]), volume=float(raw_level[1])))
-
-    return tuple(levels)
-
-
-def load_replay_events(path: Path) -> list[ReplayBookEvent]:
-    events: list[ReplayBookEvent] = []
-    for line in path.read_text(encoding="utf-8").splitlines():
-        if not line.strip():
-            continue
-        parsed = orjson.loads(line)
-        if not isinstance(parsed, dict):
-            raise ValueError("Each JSONL row must be an object")
-
-        timestamp_raw = parsed.get("timestamp")
-        symbol_raw = parsed.get("symbol")
-        if not isinstance(timestamp_raw, str) or not isinstance(symbol_raw, str):
-            raise ValueError("Each event must include timestamp and symbol")
-
-        occurred_at = datetime.fromisoformat(timestamp_raw.replace("Z", "+00:00")).astimezone(UTC)
-        events.append(
-            ReplayBookEvent(
-                occurred_at=occurred_at,
-                symbol=symbol_raw,
-                bids=_parse_book_levels(parsed.get("bids")),
-                asks=_parse_book_levels(parsed.get("asks")),
-            )
-        )
-
-    return sorted(events, key=lambda event: event.occurred_at)
-
-
-class BacktestReplayEngine:
-    def __init__(
-        self,
-        *,
-        cycles_by_pair: Mapping[str, list[TriangularCycle]],
-        available_pairs: Sequence[str],
-        config: BacktestConfig,
-        started_at: datetime,
-    ) -> None:
-        self._config = config
-        self._clock = ReplayClock.at(started_at)
-        self._books: dict[str, OrderBook] = {}
-
-        self._detector = IncrementalCycleDetector(
-            cycles_by_pair,
-            fee_rate=config.fee_rate,
-            max_depth_levels=config.max_depth_levels,
-            min_profit_threshold=config.min_profit_threshold,
-            min_order_size_by_pair=config.min_order_size_by_pair,
-        )
-        self._pre_trade = PreTradeValidator()
-        self._trade_limits = TradeLimitsGuard(max_concurrent_trades=config.max_concurrent_trades)
-        self._simulated_rest = _SimulatedRestClient(
-            self._clock,
-            slippage_bps=config.slippage_bps,
-            execution_latency_ms=config.execution_latency_ms,
-        )
-        self._sequencer = TriangularExecutionSequencer(
-            self._simulated_rest,
-            available_pairs=available_pairs,
-        )
-
-    @staticmethod
-    def _exposure_for_event(event: OpportunityEvent) -> dict[str, float]:
-        currencies = [part for part in event.cycle.split("->") if part]
-        if len(currencies) < 2:
-            return {}
-
-        origin = currencies[0]
-        return {
-            currency: event.allocated_capital for currency in currencies[1:] if currency != origin
-        }
-
-    async def run(
-        self,
-        events: Sequence[ReplayBookEvent],
-        *,
-        starting_balances: Mapping[str, float],
-    ) -> BacktestReport:
-        miss_reasons: Counter[str] = Counter()
-
-        processed_events = 0
-        opportunities_seen = 0
-        trades_executed = 0
-
-        realized_pnl = 0.0
-        equity = float(starting_balances.get(self._config.quote_asset.upper(), 0.0))
-        peak_equity = equity
-        max_drawdown = 0.0
-
-        fill_samples: list[float] = []
-        realized_samples: list[float] = []
-        execution_latencies: list[float] = []
-
-        for event in events:
-            self._clock.advance_to(event.occurred_at)
-            processed_events += 1
-
-            book = self._books.setdefault(event.symbol.upper(), OrderBook())
-            book.apply_bids(event.bids)
-            book.apply_asks(event.asks)
-
-            opportunities = self._detector.opportunities_for_updated_pair(
-                event.symbol,
-                self._books,
-                base_capital=self._config.trade_capital,
-            )
-            opportunities_seen += len(opportunities)
-
-            for opportunity in opportunities:
-                required_by_asset = {
-                    self._config.quote_asset.upper(): opportunity.allocated_capital
-                }
-                if not self._pre_trade.validate(
-                    balances_by_asset=starting_balances,
-                    required_by_asset=required_by_asset,
-                ):
-                    miss_reasons["insufficient_balance"] += 1
-                    continue
-
-                exposure = self._exposure_for_event(opportunity)
-                if not self._trade_limits.is_trade_allowed(exposure):
-                    miss_reasons["trade_limit"] += 1
-                    continue
-
-                self._trade_limits.open_trade(exposure)
-                result = await self._sequencer.execute(opportunity)
-                self._trade_limits.close_trade(exposure)
-
-                execution_latencies.append(self._simulated_rest.last_trade_latency_ms)
-                fill_samples.append(self._simulated_rest.last_fill_ratio)
-
-                if not result.success:
-                    miss_reasons["execution_failed"] += 1
-                    continue
-
-                slippage_cost = (
-                    opportunity.allocated_capital
-                    * (self._config.slippage_bps / 10000.0)
-                    * max(result.completed_legs, 1)
-                )
-                realized_trade_pnl = opportunity.est_profit - slippage_cost
-                realized_samples.append(realized_trade_pnl)
-
-                realized_pnl += realized_trade_pnl
-                equity += realized_trade_pnl
-                peak_equity = max(peak_equity, equity)
-                max_drawdown = max(max_drawdown, peak_equity - equity)
-                trades_executed += 1
-
-        wins = sum(1 for pnl in realized_samples if pnl > 0.0)
-        win_rate = (wins / len(realized_samples)) if realized_samples else None
-        fill_rate = (sum(fill_samples) / len(fill_samples)) if fill_samples else None
-
-        return BacktestReport(
-            started_at=events[0].occurred_at if events else self._clock.now,
-            finished_at=events[-1].occurred_at if events else self._clock.now,
-            processed_events=processed_events,
-            opportunities_seen=opportunities_seen,
-            trades_executed=trades_executed,
-            win_rate=win_rate,
-            fill_rate=fill_rate,
-            realized_pnl_usd=realized_pnl,
-            max_drawdown_usd=max_drawdown,
-            miss_reasons=dict(miss_reasons),
-            execution_latency_p50_ms=_percentile(execution_latencies, 50.0),
-            execution_latency_p95_ms=_percentile(execution_latencies, 95.0),
-            execution_latency_p99_ms=_percentile(execution_latencies, 99.0),
-        )

build/lib/arbitrade/backtesting/sweep.py

@@ -1,396 +0,0 @@
-from __future__ import annotations
-
-import asyncio
-from collections.abc import Mapping, Sequence
-from dataclasses import dataclass
-from datetime import UTC, datetime
-from pathlib import Path
-
-import orjson
-
-from arbitrade.backtesting.replay import (
-    BacktestConfig,
-    BacktestReplayEngine,
-    BacktestReport,
-    ReplayBookEvent,
-)
-from arbitrade.detection.graph import TriangularCycle
-
-
-@dataclass(frozen=True, slots=True)
-class SweepParameters:
-    min_profit_threshold: float
-    trade_capital: float
-    pair_universe: tuple[str, ...]
-    staleness_threshold_seconds: float
-
-
-@dataclass(frozen=True, slots=True)
-class PromotionCriteria:
-    min_test_realized_pnl_usd: float = 0.0
-    min_test_win_rate: float = 0.5
-    min_test_fill_rate: float = 0.9
-    max_test_drawdown_usd: float = 25.0
-    max_generalization_gap_ratio: float = 0.5
-
-
-@dataclass(frozen=True, slots=True)
-class SweepResult:
-    parameters: SweepParameters
-    train_report: BacktestReport
-    test_report: BacktestReport
-    train_score: float
-    test_score: float
-    generalization_gap_ratio: float
-    overfit_detected: bool
-    promotion_ready: bool
-    promotion_reasons: tuple[str, ...]
-    train_event_count: int
-    test_event_count: int
-
-
-@dataclass(frozen=True, slots=True)
-class SweepArtifacts:
-    results: tuple[SweepResult, ...]
-    promoted: tuple[SweepResult, ...]
-    train_window: tuple[datetime, datetime] | None
-    test_window: tuple[datetime, datetime] | None
-
-
-def split_events_time_windows(
-    events: Sequence[ReplayBookEvent],
-    *,
-    train_ratio: float,
-) -> tuple[list[ReplayBookEvent], list[ReplayBookEvent]]:
-    if train_ratio <= 0.0 or train_ratio >= 1.0:
-        raise ValueError("train_ratio must be between 0 and 1")
-    if len(events) < 2:
-        raise ValueError("at least two events are required for time split")
-
-    split_index = max(1, min(len(events) - 1, int(len(events) * train_ratio)))
-    return list(events[:split_index]), list(events[split_index:])
-
-
-def build_parameter_grid(
-    *,
-    theta_values: Sequence[float],
-    trade_capital_values: Sequence[float],
-    pair_universes: Sequence[Sequence[str]],
-    staleness_threshold_values: Sequence[float],
-) -> list[SweepParameters]:
-    if not theta_values:
-        raise ValueError("theta_values must not be empty")
-    if not trade_capital_values:
-        raise ValueError("trade_capital_values must not be empty")
-    if not pair_universes:
-        raise ValueError("pair_universes must not be empty")
-    if not staleness_threshold_values:
-        raise ValueError("staleness_threshold_values must not be empty")
-
-    grid: list[SweepParameters] = []
-    for theta in theta_values:
-        for trade_capital in trade_capital_values:
-            for pair_universe in pair_universes:
-                normalized_universe = tuple(
-                    sorted({pair.upper() for pair in pair_universe}))
-                for staleness_threshold in staleness_threshold_values:
-                    grid.append(
-                        SweepParameters(
-                            min_profit_threshold=float(theta),
-                            trade_capital=float(trade_capital),
-                            pair_universe=normalized_universe,
-                            staleness_threshold_seconds=float(
-                                staleness_threshold),
-                        )
-                    )
-    return grid
-
-
-def _filter_events_for_parameters(
-    events: Sequence[ReplayBookEvent],
-    *,
-    pair_universe: set[str],
-    staleness_threshold_seconds: float,
-) -> list[ReplayBookEvent]:
-    if staleness_threshold_seconds <= 0.0:
-        raise ValueError("staleness_threshold_seconds must be > 0")
-
-    filtered: list[ReplayBookEvent] = []
-    last_seen_by_symbol: dict[str, datetime] = {}
-
-    for event in events:
-        symbol = event.symbol.upper()
-        if symbol not in pair_universe:
-            continue
-
-        previous = last_seen_by_symbol.get(symbol)
-        last_seen_by_symbol[symbol] = event.occurred_at
-        if previous is None:
-            filtered.append(event)
-            continue
-
-        gap_seconds = (event.occurred_at - previous).total_seconds()
-        if gap_seconds <= staleness_threshold_seconds:
-            filtered.append(event)
-
-    return filtered
-
-
-def _restrict_cycles_by_pair(
-    cycles_by_pair: Mapping[str, list[TriangularCycle]],
-    *,
-    pair_universe: set[str],
-) -> dict[str, list[TriangularCycle]]:
-    restricted: dict[str, list[TriangularCycle]] = {}
-    for pair_symbol, cycles in cycles_by_pair.items():
-        normalized_pair = pair_symbol.upper()
-        if normalized_pair not in pair_universe:
-            continue
-
-        kept = [cycle for cycle in cycles if all(
-            pair.upper() in pair_universe for pair in cycle.pairs)]
-        if kept:
-            restricted[normalized_pair] = kept
-    return restricted
-
-
-def _score_report(report: BacktestReport) -> float:
-    win_rate_bonus = (report.win_rate or 0.0) * 100.0
-    fill_rate_bonus = (report.fill_rate or 0.0) * 50.0
-    return report.realized_pnl_usd + win_rate_bonus + fill_rate_bonus - report.max_drawdown_usd
-
-
-def _safe_ratio(numerator: float, denominator: float) -> float:
-    if denominator <= 0.0:
-        return 0.0 if numerator <= 0.0 else 1.0
-    return max(0.0, numerator / denominator)
-
-
-def _evaluate_promotion(
-    *,
-    result: SweepResult,
-    criteria: PromotionCriteria,
-) -> tuple[bool, tuple[str, ...]]:
-    reasons: list[str] = []
-    test = result.test_report
-
-    if test.realized_pnl_usd < criteria.min_test_realized_pnl_usd:
-        reasons.append(
-            "test_realized_pnl_below_threshold"
-        )
-    if (test.win_rate or 0.0) < criteria.min_test_win_rate:
-        reasons.append("test_win_rate_below_threshold")
-    if (test.fill_rate or 0.0) < criteria.min_test_fill_rate:
-        reasons.append("test_fill_rate_below_threshold")
-    if test.max_drawdown_usd > criteria.max_test_drawdown_usd:
-        reasons.append("test_drawdown_above_threshold")
-    if result.generalization_gap_ratio > criteria.max_generalization_gap_ratio:
-        reasons.append("generalization_gap_above_threshold")
-
-    return (not reasons), tuple(reasons)
-
-
-def _run_backtest(
-    *,
-    events: Sequence[ReplayBookEvent],
-    cycles_by_pair: Mapping[str, list[TriangularCycle]],
-    available_pairs: Sequence[str],
-    config: BacktestConfig,
-    starting_balances: Mapping[str, float],
-) -> BacktestReport:
-    started_at = events[0].occurred_at if events else datetime.now(UTC)
-    engine = BacktestReplayEngine(
-        cycles_by_pair=cycles_by_pair,
-        available_pairs=available_pairs,
-        config=config,
-        started_at=started_at,
-    )
-    return asyncio.run(engine.run(events, starting_balances=starting_balances))
-
-
-def run_parameter_search(
-    *,
-    events: Sequence[ReplayBookEvent],
-    cycles_by_pair: Mapping[str, list[TriangularCycle]],
-    parameter_grid: Sequence[SweepParameters],
-    starting_balances: Mapping[str, float],
-    train_ratio: float,
-    promotion_criteria: PromotionCriteria | None = None,
-    max_concurrent_trades: int = 1,
-    max_depth_levels: int = 10,
-    quote_asset: str = "USD",
-) -> SweepArtifacts:
-    criteria = promotion_criteria or PromotionCriteria()
-    train_events, test_events = split_events_time_windows(
-        events, train_ratio=train_ratio)
-
-    results: list[SweepResult] = []
-    promoted: list[SweepResult] = []
-
-    for parameters in parameter_grid:
-        allowed_pairs = set(parameters.pair_universe)
-        filtered_train = _filter_events_for_parameters(
-            train_events,
-            pair_universe=allowed_pairs,
-            staleness_threshold_seconds=parameters.staleness_threshold_seconds,
-        )
-        filtered_test = _filter_events_for_parameters(
-            test_events,
-            pair_universe=allowed_pairs,
-            staleness_threshold_seconds=parameters.staleness_threshold_seconds,
-        )
-
-        if not filtered_train or not filtered_test:
-            continue
-
-        restricted_cycles = _restrict_cycles_by_pair(
-            cycles_by_pair,
-            pair_universe=allowed_pairs,
-        )
-        if not restricted_cycles:
-            continue
-
-        config = BacktestConfig(
-            min_profit_threshold=parameters.min_profit_threshold,
-            trade_capital=parameters.trade_capital,
-            max_concurrent_trades=max_concurrent_trades,
-            max_depth_levels=max_depth_levels,
-            quote_asset=quote_asset,
-        )
-
-        train_report = _run_backtest(
-            events=filtered_train,
-            cycles_by_pair=restricted_cycles,
-            available_pairs=sorted(allowed_pairs),
-            config=config,
-            starting_balances=starting_balances,
-        )
-        test_report = _run_backtest(
-            events=filtered_test,
-            cycles_by_pair=restricted_cycles,
-            available_pairs=sorted(allowed_pairs),
-            config=config,
-            starting_balances=starting_balances,
-        )
-
-        train_score = _score_report(train_report)
-        test_score = _score_report(test_report)
-        score_drop = max(0.0, train_score - test_score)
-        generalization_gap_ratio = _safe_ratio(score_drop, abs(train_score))
-        overfit_detected = generalization_gap_ratio > criteria.max_generalization_gap_ratio
-
-        base_result = SweepResult(
-            parameters=parameters,
-            train_report=train_report,
-            test_report=test_report,
-            train_score=train_score,
-            test_score=test_score,
-            generalization_gap_ratio=generalization_gap_ratio,
-            overfit_detected=overfit_detected,
-            promotion_ready=False,
-            promotion_reasons=(),
-            train_event_count=len(filtered_train),
-            test_event_count=len(filtered_test),
-        )
-        promotion_ready, promotion_reasons = _evaluate_promotion(
-            result=base_result, criteria=criteria)
-        completed_result = SweepResult(
-            parameters=base_result.parameters,
-            train_report=base_result.train_report,
-            test_report=base_result.test_report,
-            train_score=base_result.train_score,
-            test_score=base_result.test_score,
-            generalization_gap_ratio=base_result.generalization_gap_ratio,
-            overfit_detected=base_result.overfit_detected,
-            promotion_ready=promotion_ready,
-            promotion_reasons=promotion_reasons,
-            train_event_count=base_result.train_event_count,
-            test_event_count=base_result.test_event_count,
-        )
-
-        results.append(completed_result)
-        if completed_result.promotion_ready:
-            promoted.append(completed_result)
-
-    results.sort(key=lambda item: item.test_score, reverse=True)
-    promoted.sort(key=lambda item: item.test_score, reverse=True)
-
-    train_window: tuple[datetime, datetime] | None = None
-    test_window: tuple[datetime, datetime] | None = None
-    if train_events:
-        train_window = (train_events[0].occurred_at,
-                        train_events[-1].occurred_at)
-    if test_events:
-        test_window = (test_events[0].occurred_at, test_events[-1].occurred_at)
-
-    return SweepArtifacts(
-        results=tuple(results),
-        promoted=tuple(promoted),
-        train_window=train_window,
-        test_window=test_window,
-    )
-
-
-def _report_to_dict(report: BacktestReport) -> dict[str, object]:
-    return {
-        "started_at": report.started_at.isoformat(),
-        "finished_at": report.finished_at.isoformat(),
-        "processed_events": report.processed_events,
-        "opportunities_seen": report.opportunities_seen,
-        "trades_executed": report.trades_executed,
-        "win_rate": report.win_rate,
-        "fill_rate": report.fill_rate,
-        "realized_pnl_usd": report.realized_pnl_usd,
-        "max_drawdown_usd": report.max_drawdown_usd,
-        "miss_reasons": dict(report.miss_reasons),
-        "execution_latency_p50_ms": report.execution_latency_p50_ms,
-        "execution_latency_p95_ms": report.execution_latency_p95_ms,
-        "execution_latency_p99_ms": report.execution_latency_p99_ms,
-    }
-
-
-def persist_sweep_results(path: Path, artifacts: SweepArtifacts) -> None:
-    payload = {
-        "generated_at": datetime.now(UTC).isoformat(),
-        "train_window": (
-            {
-                "started_at": artifacts.train_window[0].isoformat(),
-                "finished_at": artifacts.train_window[1].isoformat(),
-            }
-            if artifacts.train_window is not None
-            else None
-        ),
-        "test_window": (
-            {
-                "started_at": artifacts.test_window[0].isoformat(),
-                "finished_at": artifacts.test_window[1].isoformat(),
-            }
-            if artifacts.test_window is not None
-            else None
-        ),
-        "results": [
-            {
-                "parameters": {
-                    "min_profit_threshold": result.parameters.min_profit_threshold,
-                    "trade_capital": result.parameters.trade_capital,
-                    "pair_universe": list(result.parameters.pair_universe),
-                    "staleness_threshold_seconds": result.parameters.staleness_threshold_seconds,
-                },
-                "train_report": _report_to_dict(result.train_report),
-                "test_report": _report_to_dict(result.test_report),
-                "train_score": result.train_score,
-                "test_score": result.test_score,
-                "generalization_gap_ratio": result.generalization_gap_ratio,
-                "overfit_detected": result.overfit_detected,
-                "promotion_ready": result.promotion_ready,
-                "promotion_reasons": list(result.promotion_reasons),
-                "train_event_count": result.train_event_count,
-                "test_event_count": result.test_event_count,
-            }
-            for result in artifacts.results
-        ],
-    }
-
-    path.parent.mkdir(parents=True, exist_ok=True)
-    path.write_bytes(orjson.dumps(
-        payload, option=orjson.OPT_INDENT_2 | orjson.OPT_SORT_KEYS))

build/lib/arbitrade/config/secrets.py

@@ -1,39 +0,0 @@
-from __future__ import annotations
-
-import base64
-import os
-from dataclasses import dataclass
-
-import keyring
-from cryptography.fernet import Fernet
-
-
-@dataclass(slots=True)
-class SecretStore:
-    service_name: str = "arbitrade"
-
-    def _load_or_create_key(self, key_env: str | None = None) -> bytes:
-        if key_env:
-            return key_env.encode("utf-8")
-
-        existing = keyring.get_password(self.service_name, "fernet_key")
-        if existing:
-            return existing.encode("utf-8")
-
-        generated = Fernet.generate_key()
-        keyring.set_password(self.service_name, "fernet_key", generated.decode("utf-8"))
-        return generated
-
-    def encrypt(self, plaintext: str, key_env: str | None = None) -> str:
-        key = self._load_or_create_key(key_env)
-        token = Fernet(key).encrypt(plaintext.encode("utf-8"))
-        return token.decode("utf-8")
-
-    def decrypt(self, ciphertext: str, key_env: str | None = None) -> str:
-        key = self._load_or_create_key(key_env)
-        value = Fernet(key).decrypt(ciphertext.encode("utf-8"))
-        return value.decode("utf-8")
-
-    @staticmethod
-    def generate_env_key() -> str:
-        return base64.urlsafe_b64encode(os.urandom(32)).decode("utf-8")

build/lib/arbitrade/config/settings.py

@@ -1,219 +0,0 @@
-from __future__ import annotations
-
-from functools import lru_cache
-from pathlib import Path
-
-from pydantic import Field, field_validator, model_validator
-from pydantic_settings import BaseSettings, SettingsConfigDict
-
-
-class Settings(BaseSettings):
-    model_config = SettingsConfigDict(
-        env_file=".env",
-        env_file_encoding="utf-8",
-        extra="ignore",
-        env_ignore_empty=True,
-    )
-
-    app_env: str = Field(default="dev", alias="APP_ENV")
-    app_host: str = Field(default="0.0.0.0", alias="APP_HOST")
-    app_port: int = Field(default=9090, alias="APP_PORT")
-
-    log_level: str = Field(default="INFO", alias="LOG_LEVEL")
-    log_json: bool = Field(default=True, alias="LOG_JSON")
-
-    dashboard_auth_username: str | None = Field(
-        default=None,
-        alias="DASHBOARD_AUTH_USERNAME",
-    )
-    dashboard_auth_password: str | None = Field(
-        default=None,
-        alias="DASHBOARD_AUTH_PASSWORD",
-    )
-
-    alerts_enabled: bool = Field(default=True, alias="ALERTS_ENABLED")
-    alert_min_severity: str = Field(
-        default="warning", alias="ALERT_MIN_SEVERITY")
-    alert_dedup_seconds: float = Field(
-        default=30.0, alias="ALERT_DEDUP_SECONDS")
-    alert_on_trade_events: bool = Field(
-        default=True, alias="ALERT_ON_TRADE_EVENTS")
-    alert_on_error_events: bool = Field(
-        default=True, alias="ALERT_ON_ERROR_EVENTS")
-    alert_on_threshold_events: bool = Field(
-        default=True, alias="ALERT_ON_THRESHOLD_EVENTS")
-    alert_on_system_events: bool = Field(
-        default=True, alias="ALERT_ON_SYSTEM_EVENTS")
-
-    telegram_alerts_enabled: bool = Field(
-        default=False, alias="TELEGRAM_ALERTS_ENABLED")
-    telegram_bot_token: str | None = Field(
-        default=None, alias="TELEGRAM_BOT_TOKEN")
-    telegram_chat_id: str | None = Field(
-        default=None, alias="TELEGRAM_CHAT_ID")
-
-    discord_alerts_enabled: bool = Field(
-        default=False, alias="DISCORD_ALERTS_ENABLED")
-    discord_webhook_url: str | None = Field(
-        default=None, alias="DISCORD_WEBHOOK_URL")
-
-    email_alerts_enabled: bool = Field(
-        default=False, alias="EMAIL_ALERTS_ENABLED")
-    email_smtp_host: str | None = Field(default=None, alias="EMAIL_SMTP_HOST")
-    email_smtp_port: int = Field(default=587, alias="EMAIL_SMTP_PORT")
-    email_smtp_username: str | None = Field(
-        default=None, alias="EMAIL_SMTP_USERNAME")
-    email_smtp_password: str | None = Field(
-        default=None, alias="EMAIL_SMTP_PASSWORD")
-    email_alert_from: str | None = Field(
-        default=None, alias="EMAIL_ALERT_FROM")
-    email_alert_to: str | None = Field(default=None, alias="EMAIL_ALERT_TO")
-    email_smtp_use_tls: bool = Field(default=True, alias="EMAIL_SMTP_USE_TLS")
-
-    duckdb_path: Path = Field(default=Path(
-        "./data/arbitrade.duckdb"), alias="DUCKDB_PATH")
-
-    kraken_rest_url: str = Field(
-        default="https://api.kraken.com", alias="KRAKEN_REST_URL")
-    kraken_ws_url: str = Field(
-        default="wss://ws.kraken.com/v2", alias="KRAKEN_WS_URL")
-    kraken_private_rate_limit_seconds: float = Field(
-        default=1.0, alias="KRAKEN_PRIVATE_RATE_LIMIT_SECONDS"
-    )
-    kraken_http_timeout_seconds: float = Field(
-        default=10.0, alias="KRAKEN_HTTP_TIMEOUT_SECONDS")
-    kraken_retry_attempts: int = Field(
-        default=3, alias="KRAKEN_RETRY_ATTEMPTS")
-    kraken_retry_base_delay_seconds: float = Field(
-        default=0.25, alias="KRAKEN_RETRY_BASE_DELAY_SECONDS"
-    )
-    kraken_api_key: str | None = Field(default=None, alias="KRAKEN_API_KEY")
-    kraken_api_secret: str | None = Field(
-        default=None, alias="KRAKEN_API_SECRET")
-    kraken_api_key_permissions: str = Field(
-        default="query,trade",
-        alias="KRAKEN_API_KEY_PERMISSIONS",
-    )
-    ws_heartbeat_timeout_seconds: float = Field(
-        default=20.0, alias="WS_HEARTBEAT_TIMEOUT_SECONDS")
-    ws_max_staleness_seconds: float = Field(
-        default=5.0, alias="WS_MAX_STALENESS_SECONDS")
-    strategy_enable_stat_arb_experiment: bool = Field(
-        default=False,
-        alias="STRATEGY_ENABLE_STAT_ARB_EXPERIMENT",
-    )
-    strategy_stat_arb_lookback_window: int = Field(
-        default=120,
-        alias="STRATEGY_STAT_ARB_LOOKBACK_WINDOW",
-    )
-    strategy_stat_arb_entry_zscore: float = Field(
-        default=2.0,
-        alias="STRATEGY_STAT_ARB_ENTRY_ZSCORE",
-    )
-    strategy_stat_arb_exit_zscore: float = Field(
-        default=0.5,
-        alias="STRATEGY_STAT_ARB_EXIT_ZSCORE",
-    )
-    strategy_stat_arb_max_holding_seconds: float = Field(
-        default=900.0,
-        alias="STRATEGY_STAT_ARB_MAX_HOLDING_SECONDS",
-    )
-    paper_trading_mode: bool = Field(default=True, alias="PAPER_TRADING_MODE")
-    trade_capital_usd: float = Field(default=100.0, alias="TRADE_CAPITAL_USD")
-    max_trade_capital_usd: float = Field(
-        default=100.0, alias="MAX_TRADE_CAPITAL_USD")
-    max_concurrent_trades: int | None = Field(
-        default=None, alias="MAX_CONCURRENT_TRADES")
-    max_exposure_per_asset_usd: float | None = Field(
-        default=None,
-        alias="MAX_EXPOSURE_PER_ASSET_USD",
-    )
-    quote_balance_asset: str = Field(
-        default="USD", alias="QUOTE_BALANCE_ASSET")
-    min_order_size_usd: float | None = Field(
-        default=None, alias="MIN_ORDER_SIZE_USD")
-    kill_switch_active: bool = Field(default=False, alias="KILL_SWITCH_ACTIVE")
-    daily_loss_limit_usd: float | None = Field(
-        default=None, alias="DAILY_LOSS_LIMIT_USD")
-    cumulative_loss_limit_usd: float | None = Field(
-        default=None, alias="CUMULATIVE_LOSS_LIMIT_USD")
-    max_source_latency_ms: float | None = Field(
-        default=None, alias="MAX_SOURCE_LATENCY_MS")
-    max_apply_latency_ms: float | None = Field(
-        default=None, alias="MAX_APPLY_LATENCY_MS")
-    max_consecutive_failures: int | None = Field(
-        default=None, alias="MAX_CONSECUTIVE_FAILURES")
-
-    fernet_key: str | None = Field(default=None, alias="FERNET_KEY")
-
-    @field_validator("app_env")
-    @classmethod
-    def _validate_app_env(cls, value: str) -> str:
-        normalized = value.strip().lower()
-        if normalized not in {"dev", "test", "prod"}:
-            raise ValueError("APP_ENV must be one of: dev, test, prod")
-        return normalized
-
-    @field_validator("log_level")
-    @classmethod
-    def _validate_log_level(cls, value: str) -> str:
-        normalized = value.strip().upper()
-        if normalized not in {"DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"}:
-            raise ValueError(
-                "LOG_LEVEL must be one of: DEBUG, INFO, WARNING, ERROR, CRITICAL")
-        return normalized
-
-    @field_validator("alert_min_severity")
-    @classmethod
-    def _validate_alert_severity(cls, value: str) -> str:
-        normalized = value.strip().lower()
-        if normalized not in {"info", "warning", "error", "critical"}:
-            raise ValueError(
-                "ALERT_MIN_SEVERITY must be one of: info, warning, error, critical")
-        return normalized
-
-    @model_validator(mode="after")
-    def _validate_security_constraints(self) -> Settings:
-        if bool(self.dashboard_auth_username) ^ bool(self.dashboard_auth_password):
-            raise ValueError(
-                "dashboard auth requires both username and password")
-
-        if bool(self.kraken_api_key) ^ bool(self.kraken_api_secret):
-            raise ValueError(
-                "Kraken API auth requires both API key and secret")
-
-        permissions = {
-            token.strip().lower()
-            for token in self.kraken_api_key_permissions.split(",")
-            if token.strip()
-        }
-        if permissions and ("query" not in permissions or "trade" not in permissions):
-            raise ValueError(
-                "KRAKEN_API_KEY_PERMISSIONS must include query and trade")
-        if "withdraw" in permissions or "withdrawals" in permissions:
-            raise ValueError(
-                "KRAKEN_API_KEY_PERMISSIONS must not include withdrawal scope")
-
-        if self.alert_dedup_seconds < 0.0:
-            raise ValueError("ALERT_DEDUP_SECONDS must be >= 0")
-
-        if self.strategy_stat_arb_lookback_window < 2:
-            raise ValueError("STRATEGY_STAT_ARB_LOOKBACK_WINDOW must be >= 2")
-        if self.strategy_stat_arb_entry_zscore <= 0.0:
-            raise ValueError("STRATEGY_STAT_ARB_ENTRY_ZSCORE must be > 0")
-        if self.strategy_stat_arb_exit_zscore < 0.0:
-            raise ValueError("STRATEGY_STAT_ARB_EXIT_ZSCORE must be >= 0")
-        if self.strategy_stat_arb_entry_zscore <= self.strategy_stat_arb_exit_zscore:
-            raise ValueError(
-                "STRATEGY_STAT_ARB_ENTRY_ZSCORE must be greater than STRATEGY_STAT_ARB_EXIT_ZSCORE"
-            )
-        if self.strategy_stat_arb_max_holding_seconds <= 0.0:
-            raise ValueError(
-                "STRATEGY_STAT_ARB_MAX_HOLDING_SECONDS must be > 0")
-
-        return self
-
-
-@lru_cache(maxsize=1)
-def get_settings() -> Settings:
-    return Settings()

build/lib/arbitrade/detection/__init__.py

@@ -1,12 +0,0 @@
-"""Arbitrage detection package."""
-
-from arbitrade.detection.engine import CycleScore, IncrementalCycleDetector, OpportunityEvent
-from arbitrade.detection.graph import CurrencyGraph, TriangularCycle
-
-__all__ = [
-    "CurrencyGraph",
-    "TriangularCycle",
-    "CycleScore",
-    "OpportunityEvent",
-    "IncrementalCycleDetector",
-]

build/lib/arbitrade/detection/benchmark.py

@@ -1,113 +0,0 @@
-from __future__ import annotations
-
-import argparse
-import statistics
-import time
-from dataclasses import asdict, dataclass
-
-import orjson
-
-from arbitrade.detection.engine import IncrementalCycleDetector
-from arbitrade.detection.graph import CurrencyGraph
-from arbitrade.exchange.models import BookLevel
-from arbitrade.market_data.order_book import OrderBook
-
-
-@dataclass(frozen=True, slots=True)
-class DetectionBenchmarkResult:
-    iterations: int
-    total_ms: float
-    avg_ms: float
-    p50_ms: float
-    p95_ms: float
-    max_ms: float
-    target_ms: float
-
-    @property
-    def meets_target(self) -> bool:
-        return self.p95_ms <= self.target_ms
-
-
-def _make_book(*, bid: float, ask: float) -> OrderBook:
-    book = OrderBook()
-    book.apply_bids([BookLevel(price=bid, volume=10.0)])
-    book.apply_asks([BookLevel(price=ask, volume=10.0)])
-    return book
-
-
-def _build_detector_and_books() -> tuple[IncrementalCycleDetector, dict[str, OrderBook]]:
-    asset_pairs = {
-        "XXBTZUSD": {"wsname": "BTC/USD"},
-        "XETHXXBT": {"wsname": "ETH/BTC"},
-        "XETHZUSD": {"wsname": "ETH/USD"},
-    }
-    graph = CurrencyGraph.from_kraken_asset_pairs(asset_pairs)
-    cycles = graph.triangular_cycles()
-    index = graph.index_cycles_by_pair(cycles)
-
-    detector = IncrementalCycleDetector(
-        index,
-        fee_rate=0.001,
-        min_profit_threshold=0.001,
-        max_depth_levels=5,
-        max_book_age_seconds=10.0,
-    )
-
-    books = {
-        "BTC/USD": _make_book(bid=99.9, ask=100.0),
-        "ETH/BTC": _make_book(bid=0.049, ask=0.05),
-        "ETH/USD": _make_book(bid=5.2, ask=5.21),
-    }
-    return detector, books
-
-
-def run_incremental_detection_benchmark(
-    *,
-    iterations: int = 50_000,
-    target_ms: float = 1.0,
-) -> DetectionBenchmarkResult:
-    if iterations <= 0:
-        raise ValueError("iterations must be > 0")
-
-    detector, books = _build_detector_and_books()
-
-    samples_ms: list[float] = []
-    started_ns = time.perf_counter_ns()
-    for _ in range(iterations):
-        t0_ns = time.perf_counter_ns()
-        detector.score_updated_pair("ETH/BTC", books)
-        elapsed_ms = (time.perf_counter_ns() - t0_ns) / 1_000_000
-        samples_ms.append(elapsed_ms)
-
-    total_ms = (time.perf_counter_ns() - started_ns) / 1_000_000
-    return DetectionBenchmarkResult(
-        iterations=iterations,
-        total_ms=total_ms,
-        avg_ms=statistics.fmean(samples_ms),
-        p50_ms=statistics.quantiles(samples_ms, n=100)[49],
-        p95_ms=statistics.quantiles(samples_ms, n=100)[94],
-        max_ms=max(samples_ms),
-        target_ms=target_ms,
-    )
-
-
-def main() -> None:
-    parser = argparse.ArgumentParser(description="Benchmark incremental detection latency")
-    parser.add_argument("--iterations", type=int, default=50_000)
-    parser.add_argument("--target-ms", type=float, default=1.0)
-    args = parser.parse_args()
-
-    result = run_incremental_detection_benchmark(
-        iterations=args.iterations,
-        target_ms=args.target_ms,
-    )
-
-    payload = {
-        **asdict(result),
-        "meets_target": result.meets_target,
-    }
-    print(orjson.dumps(payload).decode("utf-8"))
-
-
-if __name__ == "__main__":
-    main()

build/lib/arbitrade/detection/engine.py

@@ -1,295 +0,0 @@
-from __future__ import annotations
-
-from collections.abc import Mapping
-from dataclasses import dataclass
-from datetime import UTC, datetime
-
-from arbitrade.detection.graph import TriangularCycle
-from arbitrade.exchange.models import BookLevel
-from arbitrade.market_data.order_book import OrderBook
-
-
-def _normalize_pair_symbol(symbol: str) -> str:
-    if "/" not in symbol:
-        return symbol.upper()
-
-    base, quote = symbol.split("/", 1)
-    return f"{base.upper()}/{quote.upper()}"
-
-
-@dataclass(frozen=True, slots=True)
-class CycleScore:
-    cycle: TriangularCycle
-    gross_rate: float
-    net_rate: float
-    min_profit_threshold: float
-    updated_pair: str
-    scored_at: datetime
-
-    @property
-    def is_profitable(self) -> bool:
-        return (self.net_rate - 1.0) >= self.min_profit_threshold
-
-
-@dataclass(frozen=True, slots=True)
-class OpportunityEvent:
-    detected_at: datetime
-    cycle: str
-    updated_pair: str
-    gross_rate: float
-    net_rate: float
-    gross_pct: float
-    net_pct: float
-    est_profit: float
-    allocated_capital: float = 1.0
-
-    @classmethod
-    def from_cycle_score(cls, score: CycleScore, base_capital: float = 1.0) -> OpportunityEvent:
-        gross_pct = (score.gross_rate - 1.0) * 100.0
-        net_pct = (score.net_rate - 1.0) * 100.0
-        est_profit = (score.net_rate - 1.0) * base_capital
-        a, b, c = score.cycle.currencies
-        cycle = f"{a}->{b}->{c}->{a}"
-        return cls(
-            detected_at=score.scored_at,
-            cycle=cycle,
-            updated_pair=score.updated_pair,
-            gross_rate=score.gross_rate,
-            net_rate=score.net_rate,
-            gross_pct=gross_pct,
-            net_pct=net_pct,
-            est_profit=est_profit,
-            allocated_capital=base_capital,
-        )
-
-
-class IncrementalCycleDetector:
-    def __init__(
-        self,
-        cycles_by_pair: Mapping[str, list[TriangularCycle]],
-        *,
-        fee_rate: float = 0.0,
-        max_depth_levels: int = 10,
-        min_profit_threshold: float = 0.0,
-        min_order_size_by_pair: Mapping[str, float] | None = None,
-        max_book_age_seconds: float | None = None,
-    ) -> None:
-        self._cycles_by_pair = {
-            _normalize_pair_symbol(pair): list(cycles) for pair, cycles in cycles_by_pair.items()
-        }
-        self._fee_multiplier = 1.0 - fee_rate
-        self._max_depth_levels = max_depth_levels
-        self._min_profit_threshold = min_profit_threshold
-        self._max_book_age_seconds = max_book_age_seconds
-        self._min_order_size_by_pair = {
-            _normalize_pair_symbol(pair): float(min_size)
-            for pair, min_size in (min_order_size_by_pair or {}).items()
-        }
-
-        if self._fee_multiplier < 0.0:
-            raise ValueError("fee_rate must be <= 1.0")
-        if self._max_depth_levels <= 0:
-            raise ValueError("max_depth_levels must be > 0")
-        if self._min_profit_threshold < 0.0:
-            raise ValueError("min_profit_threshold must be >= 0.0")
-        if self._max_book_age_seconds is not None and self._max_book_age_seconds <= 0.0:
-            raise ValueError("max_book_age_seconds must be > 0.0")
-        for min_size in self._min_order_size_by_pair.values():
-            if min_size <= 0.0:
-                raise ValueError("minimum order size must be > 0.0")
-
-    def score_updated_pair(
-        self,
-        updated_pair: str,
-        books: Mapping[str, OrderBook],
-    ) -> list[CycleScore]:
-        normalized_pair = _normalize_pair_symbol(updated_pair)
-        impacted_cycles = self._cycles_by_pair.get(normalized_pair, [])
-
-        normalized_books = {_normalize_pair_symbol(symbol): book for symbol, book in books.items()}
-
-        scores: list[CycleScore] = []
-        scored_at = datetime.now(UTC)
-        for cycle in impacted_cycles:
-            rates = self._score_cycle(cycle, normalized_books, scored_at)
-            if rates is None:
-                continue
-            gross_rate, net_rate = rates
-            if (net_rate - 1.0) < self._min_profit_threshold:
-                continue
-            scores.append(
-                CycleScore(
-                    cycle=cycle,
-                    gross_rate=gross_rate,
-                    net_rate=net_rate,
-                    min_profit_threshold=self._min_profit_threshold,
-                    updated_pair=normalized_pair,
-                    scored_at=scored_at,
-                )
-            )
-
-        return scores
-
-    def opportunities_for_updated_pair(
-        self,
-        updated_pair: str,
-        books: Mapping[str, OrderBook],
-        *,
-        base_capital: float = 1.0,
-    ) -> list[OpportunityEvent]:
-        if base_capital <= 0.0:
-            raise ValueError("base_capital must be > 0.0")
-
-        scores = self.score_updated_pair(updated_pair, books)
-        return [OpportunityEvent.from_cycle_score(score, base_capital) for score in scores]
-
-    def _score_cycle(
-        self,
-        cycle: TriangularCycle,
-        books: Mapping[str, OrderBook],
-        scored_at: datetime,
-    ) -> tuple[float, float] | None:
-        if not self._is_cycle_fresh(cycle, books, scored_at):
-            return None
-
-        a, b, c = cycle.currencies
-        gross_amount = 1.0
-
-        gross_ab = self._convert(gross_amount, a, b, cycle, books)
-        if gross_ab is None:
-            return None
-        net_ab = gross_ab * self._fee_multiplier
-
-        gross_bc = self._convert(gross_ab, b, c, cycle, books)
-        if gross_bc is None:
-            return None
-        net_bc = self._convert(net_ab, b, c, cycle, books)
-        if net_bc is None:
-            return None
-        net_bc *= self._fee_multiplier
-
-        gross_ca = self._convert(gross_bc, c, a, cycle, books)
-        if gross_ca is None:
-            return None
-        net_ca = self._convert(net_bc, c, a, cycle, books)
-        if net_ca is None:
-            return None
-        net_ca *= self._fee_multiplier
-
-        return gross_ca, net_ca
-
-    def _is_cycle_fresh(
-        self,
-        cycle: TriangularCycle,
-        books: Mapping[str, OrderBook],
-        scored_at: datetime,
-    ) -> bool:
-        if self._max_book_age_seconds is None:
-            return True
-
-        for pair in cycle.pairs:
-            normalized_pair = _normalize_pair_symbol(pair)
-            book = books.get(normalized_pair)
-            if book is None:
-                return False
-
-            age_seconds = (scored_at - book.updated_at).total_seconds()
-            if age_seconds > self._max_book_age_seconds:
-                return False
-
-        return True
-
-    @staticmethod
-    def _pair_for_edge(cycle: TriangularCycle, from_currency: str, to_currency: str) -> str | None:
-        for pair in cycle.pairs:
-            if "/" not in pair:
-                continue
-            base, quote = pair.split("/", 1)
-            base = base.upper()
-            quote = quote.upper()
-            if {base, quote} == {from_currency, to_currency}:
-                return f"{base}/{quote}"
-        return None
-
-    def _convert(
-        self,
-        amount: float,
-        from_currency: str,
-        to_currency: str,
-        cycle: TriangularCycle,
-        books: Mapping[str, OrderBook],
-    ) -> float | None:
-        pair = self._pair_for_edge(cycle, from_currency, to_currency)
-        if pair is None:
-            return None
-
-        book = books.get(pair)
-        if book is None:
-            return None
-
-        bids, asks = book.top_levels(depth=self._max_depth_levels)
-
-        base, quote = pair.split("/", 1)
-        base = base.upper()
-        quote = quote.upper()
-
-        if from_currency == base and to_currency == quote:
-            quote_out = self._sell_base_for_quote(amount, bids)
-            if quote_out is None:
-                return None
-            if not self._is_min_order_size_satisfied(pair, amount):
-                return None
-            return quote_out
-
-        if from_currency == quote and to_currency == base:
-            base_out = self._buy_base_with_quote(amount, asks)
-            if base_out is None:
-                return None
-            if not self._is_min_order_size_satisfied(pair, base_out):
-                return None
-            return base_out
-
-        return None
-
-    def _is_min_order_size_satisfied(self, pair: str, base_amount: float) -> bool:
-        min_size = self._min_order_size_by_pair.get(pair)
-        if min_size is None:
-            return True
-        return base_amount >= min_size
-
-    @staticmethod
-    def _sell_base_for_quote(amount_base: float, bids: list[BookLevel]) -> float | None:
-        remaining = amount_base
-        quote_out = 0.0
-        for level in bids:
-            if remaining <= 0.0:
-                break
-            if level.price <= 0.0 or level.volume <= 0.0:
-                continue
-
-            executed = min(remaining, level.volume)
-            quote_out += executed * level.price
-            remaining -= executed
-
-        if remaining > 0.0:
-            return None
-        return quote_out
-
-    @staticmethod
-    def _buy_base_with_quote(amount_quote: float, asks: list[BookLevel]) -> float | None:
-        remaining_quote = amount_quote
-        base_out = 0.0
-        for level in asks:
-            if remaining_quote <= 0.0:
-                break
-            if level.price <= 0.0 or level.volume <= 0.0:
-                continue
-
-            level_quote_capacity = level.volume * level.price
-            spend = min(remaining_quote, level_quote_capacity)
-            base_out += spend / level.price
-            remaining_quote -= spend
-
-        if remaining_quote > 0.0:
-            return None
-        return base_out

build/lib/arbitrade/detection/graph.py

@@ -1,90 +0,0 @@
-from __future__ import annotations
-
-from dataclasses import dataclass
-from typing import Any
-
-
-@dataclass(frozen=True, slots=True)
-class TriangularCycle:
-    currencies: tuple[str, str, str]
-    pairs: tuple[str, str, str]
-
-
-def _canonical_pair(base: str, quote: str) -> str:
-    return f"{base}/{quote}"
-
-
-class CurrencyGraph:
-    def __init__(self) -> None:
-        self._adjacency: dict[str, set[str]] = {}
-        self._pair_by_direction: dict[tuple[str, str], str] = {}
-
-    @property
-    def adjacency(self) -> dict[str, set[str]]:
-        return self._adjacency
-
-    @property
-    def pair_by_direction(self) -> dict[tuple[str, str], str]:
-        return self._pair_by_direction
-
-    def add_pair(self, base: str, quote: str, pair_symbol: str | None = None) -> None:
-        normalized_base = base.upper()
-        normalized_quote = quote.upper()
-        symbol = pair_symbol or _canonical_pair(normalized_base, normalized_quote)
-
-        self._adjacency.setdefault(normalized_base, set()).add(normalized_quote)
-        self._adjacency.setdefault(normalized_quote, set()).add(normalized_base)
-
-        self._pair_by_direction[(normalized_base, normalized_quote)] = symbol
-        self._pair_by_direction[(normalized_quote, normalized_base)] = symbol
-
-    @classmethod
-    def from_kraken_asset_pairs(cls, asset_pairs: dict[str, Any]) -> CurrencyGraph:
-        graph = cls()
-        for value in asset_pairs.values():
-            if not isinstance(value, dict):
-                continue
-
-            wsname = value.get("wsname")
-            if isinstance(wsname, str) and "/" in wsname:
-                base, quote = wsname.split("/", 1)
-                graph.add_pair(base, quote, wsname)
-                continue
-
-            raw_base = value.get("base")
-            raw_quote = value.get("quote")
-            if isinstance(raw_base, str) and isinstance(raw_quote, str):
-                graph.add_pair(raw_base, raw_quote)
-
-        return graph
-
-    def triangular_cycles(self) -> list[TriangularCycle]:
-        found: dict[tuple[str, str, str], TriangularCycle] = {}
-
-        for a, neighbors_a in self._adjacency.items():
-            for b in neighbors_a:
-                if a >= b:
-                    continue
-                neighbors_b = self._adjacency.get(b, set())
-                for c in neighbors_b:
-                    if b >= c:
-                        continue
-                    if a not in self._adjacency.get(c, set()):
-                        continue
-
-                    p_ab = self._pair_by_direction[(a, b)]
-                    p_bc = self._pair_by_direction[(b, c)]
-                    p_ca = self._pair_by_direction[(c, a)]
-
-                    key = (a, b, c)
-                    found[key] = TriangularCycle(currencies=key, pairs=(p_ab, p_bc, p_ca))
-
-        return list(found.values())
-
-    @staticmethod
-    def index_cycles_by_pair(cycles: list[TriangularCycle]) -> dict[str, list[TriangularCycle]]:
-        index: dict[str, list[TriangularCycle]] = {}
-        for cycle in cycles:
-            for pair in cycle.pairs:
-                index.setdefault(pair, []).append(cycle)
-        return index

build/lib/arbitrade/exchange/__init__.py

@@ -1 +0,0 @@
-"""Kraken exchange integration package."""

build/lib/arbitrade/exchange/kraken_rest.py

@@ -1,281 +0,0 @@
-from __future__ import annotations
-
-import asyncio
-import time
-from typing import Any
-from urllib.parse import urlencode
-
-import httpx
-import structlog
-
-from arbitrade.config.settings import Settings
-from arbitrade.exchange.models import KrakenApiResult, LatencySample
-from arbitrade.exchange.signing import sign_kraken_private_path
-
-_LOG = structlog.get_logger(__name__)
-
-
-def _result_dict(payload: dict[str, Any]) -> dict[str, Any]:
-    result = payload.get("result", {})
-    if isinstance(result, dict):
-        return result
-    return {}
-
-
-class KrakenRestClient:
-    def __init__(self, settings: Settings) -> None:
-        self._settings = settings
-        self._client = httpx.AsyncClient(
-            base_url=settings.kraken_rest_url,
-            timeout=settings.kraken_http_timeout_seconds,
-            limits=httpx.Limits(max_keepalive_connections=10, max_connections=50),
-            headers={"User-Agent": "arbitrade/0.1.0"},
-        )
-        self._private_lock = asyncio.Lock()
-
-        issues = self.validate_compliance()
-        if issues:
-            _LOG.warning("kraken_compliance_issues", issues=issues)
-        else:
-            _LOG.info("kraken_compliance_ok")
-
-    def validate_compliance(self) -> list[str]:
-        issues: list[str] = []
-
-        if not self._settings.kraken_rest_url.startswith("https://"):
-            issues.append("KRAKEN_REST_URL should use https://")
-
-        if self._settings.kraken_private_rate_limit_seconds < 1.0:
-            issues.append("KRAKEN_PRIVATE_RATE_LIMIT_SECONDS below 1.0 may violate Kraken limits")
-
-        if self._settings.kraken_retry_attempts < 1:
-            issues.append("KRAKEN_RETRY_ATTEMPTS must be >= 1")
-
-        if self._settings.kraken_retry_base_delay_seconds < 0:
-            issues.append("KRAKEN_RETRY_BASE_DELAY_SECONDS must be >= 0")
-
-        return issues
-
-    async def close(self) -> None:
-        await self._client.aclose()
-
-    async def warm_connection_pool(self) -> None:
-        await self.server_time()
-
-    async def _request_with_retry(
-        self,
-        endpoint: str,
-        params: dict[str, Any] | None = None,
-    ) -> KrakenApiResult:
-        attempts = self._settings.kraken_retry_attempts
-        delay = self._settings.kraken_retry_base_delay_seconds
-        params = params or {}
-
-        for attempt in range(1, attempts + 1):
-            t0 = time.perf_counter()
-            try:
-                response = await self._client.get(endpoint, params=params)
-                response.raise_for_status()
-                payload = response.json()
-                if payload.get("error"):
-                    raise RuntimeError(f"Kraken error: {payload['error']}")
-
-                latency = (time.perf_counter() - t0) * 1000
-                _LOG.info(
-                    "kraken_rest_request_ok",
-                    endpoint=endpoint,
-                    attempt=attempt,
-                    latency_ms=latency,
-                    sample=LatencySample.now("rest_request", latency_ms=latency).latency_ms,
-                )
-                return KrakenApiResult(endpoint=endpoint, payload=payload)
-            except Exception as exc:
-                latency = (time.perf_counter() - t0) * 1000
-                _LOG.warning(
-                    "kraken_rest_request_failed",
-                    endpoint=endpoint,
-                    attempt=attempt,
-                    latency_ms=latency,
-                    error=str(exc),
-                )
-                if attempt >= attempts:
-                    raise
-                await asyncio.sleep(delay * (2 ** (attempt - 1)))
-
-        raise RuntimeError("unreachable retry loop")
-
-    async def _private_post_with_retry(
-        self,
-        endpoint: str,
-        data: dict[str, str] | None = None,
-    ) -> KrakenApiResult:
-        api_key = self._settings.kraken_api_key
-        api_secret = self._settings.kraken_api_secret
-        if not api_key or not api_secret:
-            raise RuntimeError("Missing Kraken API credentials for private endpoint")
-
-        attempts = self._settings.kraken_retry_attempts
-        delay = self._settings.kraken_retry_base_delay_seconds
-
-        for attempt in range(1, attempts + 1):
-            t0 = time.perf_counter()
-            try:
-                nonce = str(int(time.time() * 1000))
-                payload = {"nonce": nonce}
-                if data is not None:
-                    payload.update(data)
-
-                encoded = urlencode(payload)
-                signature = sign_kraken_private_path(endpoint, nonce, encoded, api_secret)
-
-                response = await self._client.post(
-                    endpoint,
-                    data=payload,
-                    headers={
-                        "API-Key": api_key,
-                        "API-Sign": signature,
-                    },
-                )
-                response.raise_for_status()
-                body = response.json()
-                if body.get("error"):
-                    raise RuntimeError(f"Kraken error: {body['error']}")
-
-                latency = (time.perf_counter() - t0) * 1000
-                _LOG.info(
-                    "kraken_private_rest_request_ok",
-                    endpoint=endpoint,
-                    attempt=attempt,
-                    latency_ms=latency,
-                    sample=LatencySample.now("private_rest_request", latency_ms=latency).latency_ms,
-                )
-                return KrakenApiResult(endpoint=endpoint, payload=body)
-            except Exception as exc:
-                latency = (time.perf_counter() - t0) * 1000
-                _LOG.warning(
-                    "kraken_private_rest_request_failed",
-                    endpoint=endpoint,
-                    attempt=attempt,
-                    latency_ms=latency,
-                    error=str(exc),
-                )
-                if attempt >= attempts:
-                    raise
-                await asyncio.sleep(delay * (2 ** (attempt - 1)))
-
-        raise RuntimeError("unreachable retry loop")
-
-    async def server_time(self) -> dict[str, Any]:
-        result = await self._request_with_retry("/0/public/Time")
-        return _result_dict(result.payload)
-
-    async def assets(self) -> dict[str, Any]:
-        result = await self._request_with_retry("/0/public/Assets")
-        return _result_dict(result.payload)
-
-    async def asset_pairs(self) -> dict[str, Any]:
-        result = await self._request_with_retry("/0/public/AssetPairs")
-        return _result_dict(result.payload)
-
-    async def _throttled_private_call(
-        self,
-        endpoint: str,
-        data: dict[str, str] | None = None,
-    ) -> dict[str, Any]:
-        async with self._private_lock:
-            result = await self._private_post_with_retry(endpoint, data=data)
-            await asyncio.sleep(self._settings.kraken_private_rate_limit_seconds)
-            return _result_dict(result.payload)
-
-    async def balances(self) -> dict[str, Any]:
-        return await self._throttled_private_call("/0/private/Balance")
-
-    async def place_market_order(
-        self,
-        *,
-        pair: str,
-        side: str,
-        volume: float,
-        user_ref: int | None = None,
-    ) -> dict[str, Any]:
-        normalized_side = side.lower()
-        if normalized_side not in {"buy", "sell"}:
-            raise ValueError("side must be 'buy' or 'sell'")
-        if volume <= 0.0:
-            raise ValueError("volume must be > 0.0")
-        if user_ref is not None and user_ref < 0:
-            raise ValueError("user_ref must be >= 0")
-
-        data = {
-            "pair": pair,
-            "type": normalized_side,
-            "ordertype": "market",
-            "volume": str(volume),
-        }
-        if user_ref is not None:
-            data["userref"] = str(user_ref)
-
-        return await self._throttled_private_call(
-            "/0/private/AddOrder",
-            data=data,
-        )
-
-    async def place_limit_order(
-        self,
-        *,
-        pair: str,
-        side: str,
-        volume: float,
-        price: float,
-        user_ref: int | None = None,
-    ) -> dict[str, Any]:
-        normalized_side = side.lower()
-        if normalized_side not in {"buy", "sell"}:
-            raise ValueError("side must be 'buy' or 'sell'")
-        if volume <= 0.0:
-            raise ValueError("volume must be > 0.0")
-        if price <= 0.0:
-            raise ValueError("price must be > 0.0")
-        if user_ref is not None and user_ref < 0:
-            raise ValueError("user_ref must be >= 0")
-
-        data = {
-            "pair": pair,
-            "type": normalized_side,
-            "ordertype": "limit",
-            "price": str(price),
-            "volume": str(volume),
-        }
-        if user_ref is not None:
-            data["userref"] = str(user_ref)
-
-        return await self._throttled_private_call(
-            "/0/private/AddOrder",
-            data=data,
-        )
-
-    async def query_order(
-        self,
-        *,
-        order_id: str,
-        include_trades: bool = True,
-    ) -> dict[str, Any]:
-        if not order_id.strip():
-            raise ValueError("order_id must be non-empty")
-
-        return await self._throttled_private_call(
-            "/0/private/QueryOrders",
-            data={
-                "txid": order_id,
-                "trades": "true" if include_trades else "false",
-            },
-        )
-
-    async def cancel_order(self, *, order_id: str) -> dict[str, Any]:
-        if not order_id.strip():
-            raise ValueError("order_id must be non-empty")
-
-        return await self._throttled_private_call(
-            "/0/private/CancelOrder",
-            data={"txid": order_id},
-        )

build/lib/arbitrade/exchange/kraken_ws.py

@@ -1,177 +0,0 @@
-from __future__ import annotations
-
-import asyncio
-import time
-from collections.abc import AsyncIterator
-from dataclasses import dataclass
-from datetime import UTC, datetime
-from typing import Any
-
-import orjson
-import structlog
-import websockets
-
-from arbitrade.alerting.notifier import AlertSeverity, SupportsAlerts
-from arbitrade.config.settings import Settings
-from arbitrade.exchange.models import BookDelta, BookLevel
-
-_LOG = structlog.get_logger(__name__)
-
-
-@dataclass(slots=True)
-class WsMessage:
-    received_at: datetime
-    payload: dict[str, Any]
-
-
-class KrakenWsClient:
-    def __init__(self, settings: Settings, *, alert_notifier: SupportsAlerts | None = None) -> None:
-        self._settings = settings
-        self._last_message_at: datetime | None = None
-        self._stop = asyncio.Event()
-        self._alert_notifier = alert_notifier
-        self._has_connected_once = False
-        self._was_disconnected = False
-
-    @property
-    def is_stale(self) -> bool:
-        if self._last_message_at is None:
-            return True
-        return (
-            datetime.now(UTC) - self._last_message_at
-        ).total_seconds() > self._settings.ws_max_staleness_seconds
-
-    async def stop(self) -> None:
-        self._stop.set()
-
-    async def connect_stream(self) -> AsyncIterator[WsMessage]:
-        delay = 1.0
-        while not self._stop.is_set():
-            try:
-                async with websockets.connect(
-                    self._settings.kraken_ws_url, max_size=2_000_000
-                ) as ws:
-                    _LOG.info("kraken_ws_connected", url=self._settings.kraken_ws_url)
-                    if self._has_connected_once and self._was_disconnected:
-                        await self._notify(
-                            category="system",
-                            severity="info",
-                            title="WebSocket reconnected",
-                            message="Kraken WebSocket connection restored.",
-                            details={"url": self._settings.kraken_ws_url},
-                        )
-                    self._has_connected_once = True
-                    self._was_disconnected = False
-                    delay = 1.0
-                    async for raw in self._recv_loop(ws):
-                        yield raw
-            except Exception as exc:
-                _LOG.warning("kraken_ws_disconnected", error=str(exc), reconnect_in=delay)
-                self._was_disconnected = True
-                await self._notify(
-                    category="system",
-                    severity="warning",
-                    title="WebSocket disconnected",
-                    message="Kraken WebSocket disconnected, reconnect scheduled.",
-                    details={
-                        "error": str(exc),
-                        "reconnect_in_seconds": f"{delay}",
-                    },
-                )
-                await asyncio.sleep(delay)
-                delay = min(delay * 2, 30.0)
-
-    async def _recv_loop(self, ws: Any) -> AsyncIterator[WsMessage]:
-        while not self._stop.is_set():
-            t0 = time.perf_counter()
-            try:
-                raw = await asyncio.wait_for(
-                    ws.recv(), timeout=self._settings.ws_heartbeat_timeout_seconds
-                )
-            except TimeoutError:
-                await self._notify(
-                    category="system",
-                    severity="critical",
-                    title="WebSocket staleness abort",
-                    message="No WebSocket heartbeat within configured timeout; reconnecting.",
-                    details={
-                        "heartbeat_timeout_seconds": (
-                            f"{self._settings.ws_heartbeat_timeout_seconds}"
-                        ),
-                    },
-                )
-                raise
-            parse_start = time.perf_counter()
-            payload = orjson.loads(raw)
-            self._last_message_at = datetime.now(UTC)
-
-            _LOG.debug(
-                "kraken_ws_message",
-                recv_latency_ms=(parse_start - t0) * 1000,
-                parse_latency_ms=(time.perf_counter() - parse_start) * 1000,
-            )
-            if isinstance(payload, dict):
-                yield WsMessage(received_at=self._last_message_at, payload=payload)
-
-    async def _notify(
-        self,
-        *,
-        category: str,
-        severity: AlertSeverity,
-        title: str,
-        message: str,
-        details: dict[str, str] | None = None,
-    ) -> None:
-        if self._alert_notifier is None:
-            return
-        await self._alert_notifier.notify(
-            category=category,
-            severity=severity,
-            title=title,
-            message=message,
-            details=details,
-        )
-
-    @staticmethod
-    def parse_book_delta(message: dict[str, Any]) -> BookDelta | None:
-        # Kraken v2 book update shape can vary by channel; keep parser defensive.
-        channel = str(message.get("channel", ""))
-        if "book" not in channel:
-            return None
-
-        symbol = str(message.get("symbol", ""))
-        data = message.get("data")
-        if not isinstance(data, list) or not data:
-            return None
-
-        first = data[0]
-        if not isinstance(first, dict):
-            return None
-
-        bids = [
-            BookLevel(price=float(level["price"]), volume=float(level["qty"]))
-            for level in first.get("bids", [])
-            if isinstance(level, dict) and "price" in level and "qty" in level
-        ]
-        asks = [
-            BookLevel(price=float(level["price"]), volume=float(level["qty"]))
-            for level in first.get("asks", [])
-            if isinstance(level, dict) and "price" in level and "qty" in level
-        ]
-
-        checksum: int | None = None
-        raw_checksum = first.get("checksum")
-        if isinstance(raw_checksum, int):
-            checksum = raw_checksum
-
-        source_timestamp_ms: int | None = None
-        if isinstance(first.get("timestamp"), int):
-            source_timestamp_ms = first["timestamp"]
-
-        return BookDelta(
-            symbol=symbol,
-            bids=bids,
-            asks=asks,
-            checksum=checksum,
-            source_timestamp_ms=source_timestamp_ms,
-        )

build/lib/arbitrade/exchange/models.py

@@ -1,37 +0,0 @@
-from __future__ import annotations
-
-from dataclasses import dataclass
-from datetime import UTC, datetime
-from typing import Any
-
-
-@dataclass(slots=True)
-class KrakenApiResult:
-    endpoint: str
-    payload: dict[str, Any]
-
-
-@dataclass(slots=True)
-class LatencySample:
-    stage: str
-    at: datetime
-    latency_ms: float
-
-    @classmethod
-    def now(cls, stage: str, latency_ms: float) -> LatencySample:
-        return cls(stage=stage, at=datetime.now(UTC), latency_ms=latency_ms)
-
-
-@dataclass(slots=True)
-class BookLevel:
-    price: float
-    volume: float
-
-
-@dataclass(slots=True)
-class BookDelta:
-    symbol: str
-    bids: list[BookLevel]
-    asks: list[BookLevel]
-    checksum: int | None = None
-    source_timestamp_ms: int | None = None

build/lib/arbitrade/exchange/signing.py

@@ -1,14 +0,0 @@
-from __future__ import annotations
-
-import base64
-import hashlib
-import hmac
-from functools import lru_cache
-
-
-@lru_cache(maxsize=2048)
-def sign_kraken_private_path(path: str, nonce: str, post_data: str, api_secret: str) -> str:
-    message = nonce.encode("utf-8") + post_data.encode("utf-8")
-    sha256 = hashlib.sha256(message).digest()
-    mac = hmac.new(base64.b64decode(api_secret), path.encode("utf-8") + sha256, hashlib.sha512)
-    return base64.b64encode(mac.digest()).decode("utf-8")

build/lib/arbitrade/execution/__init__.py

@@ -1,32 +0,0 @@
-"""Trade execution helpers."""
-
-from arbitrade.execution.fill_monitor import (
-    FillMonitor,
-    FillMonitorResult,
-    OrderFillState,
-)
-from arbitrade.execution.idempotency import (
-    IdempotencyKeyFactory,
-    OrderReconciler,
-    ReconciliationReport,
-)
-from arbitrade.execution.recovery import PartialFillRecovery, RecoveryAction
-from arbitrade.execution.sequencer import (
-    ExecutionLeg,
-    TriangularExecutionResult,
-    TriangularExecutionSequencer,
-)
-
-__all__ = [
-    "ExecutionLeg",
-    "OrderFillState",
-    "FillMonitorResult",
-    "FillMonitor",
-    "IdempotencyKeyFactory",
-    "ReconciliationReport",
-    "OrderReconciler",
-    "RecoveryAction",
-    "PartialFillRecovery",
-    "TriangularExecutionResult",
-    "TriangularExecutionSequencer",
-]

build/lib/arbitrade/execution/fill_monitor.py

@@ -1,133 +0,0 @@
-from __future__ import annotations
-
-import asyncio
-import time
-from collections.abc import Callable
-from dataclasses import dataclass
-from datetime import UTC, datetime
-from typing import Any, Protocol
-
-
-class SupportsOrderStatusPolling(Protocol):
-    async def query_order(
-        self, *, order_id: str, include_trades: bool = True
-    ) -> dict[str, Any]: ...
-
-
-@dataclass(frozen=True, slots=True)
-class OrderFillState:
-    order_id: str
-    status: str
-    filled_volume: float | None
-    avg_price: float | None
-    updated_at: datetime
-    source: str
-
-    @property
-    def is_terminal(self) -> bool:
-        return self.status in {"closed", "canceled", "expired"}
-
-
-@dataclass(frozen=True, slots=True)
-class FillMonitorResult:
-    order_id: str
-    timed_out: bool
-    terminal_state: OrderFillState | None
-    last_state: OrderFillState | None
-    elapsed_seconds: float
-
-
-class FillMonitor:
-    def __init__(
-        self,
-        poll_client: SupportsOrderStatusPolling,
-        *,
-        poll_interval_seconds: float = 0.5,
-        max_wait_seconds: float = 10.0,
-        ws_status_provider: Callable[[str], OrderFillState | None] | None = None,
-    ) -> None:
-        if poll_interval_seconds <= 0.0:
-            raise ValueError("poll_interval_seconds must be > 0.0")
-        if max_wait_seconds <= 0.0:
-            raise ValueError("max_wait_seconds must be > 0.0")
-
-        self._poll_client = poll_client
-        self._poll_interval_seconds = poll_interval_seconds
-        self._max_wait_seconds = max_wait_seconds
-        self._ws_status_provider = ws_status_provider
-
-    @staticmethod
-    def _to_float(value: Any) -> float | None:
-        if value is None:
-            return None
-        try:
-            return float(value)
-        except (TypeError, ValueError):
-            return None
-
-    @classmethod
-    def _state_from_payload(
-        cls, order_id: str, payload: dict[str, Any], *, source: str
-    ) -> OrderFillState:
-        status = str(payload.get("status", "unknown")).lower()
-        return OrderFillState(
-            order_id=order_id,
-            status=status,
-            filled_volume=cls._to_float(payload.get("vol_exec")),
-            avg_price=cls._to_float(payload.get("price") or payload.get("avg_price")),
-            updated_at=datetime.now(UTC),
-            source=source,
-        )
-
-    @classmethod
-    def _extract_order_payload(cls, order_id: str, response: dict[str, Any]) -> dict[str, Any]:
-        if order_id in response and isinstance(response[order_id], dict):
-            payload = response[order_id]
-            return {str(key): value for key, value in payload.items()}
-        return response
-
-    async def wait_for_terminal_fill(self, order_id: str) -> FillMonitorResult:
-        if not order_id.strip():
-            raise ValueError("order_id must be non-empty")
-
-        started = time.monotonic()
-        last_state: OrderFillState | None = None
-
-        while True:
-            elapsed = time.monotonic() - started
-            if elapsed >= self._max_wait_seconds:
-                return FillMonitorResult(
-                    order_id=order_id,
-                    timed_out=True,
-                    terminal_state=None,
-                    last_state=last_state,
-                    elapsed_seconds=elapsed,
-                )
-
-            if self._ws_status_provider is not None:
-                ws_state = self._ws_status_provider(order_id)
-                if ws_state is not None:
-                    last_state = ws_state
-                    if ws_state.is_terminal:
-                        return FillMonitorResult(
-                            order_id=order_id,
-                            timed_out=False,
-                            terminal_state=ws_state,
-                            last_state=ws_state,
-                            elapsed_seconds=elapsed,
-                        )
-
-            response = await self._poll_client.query_order(order_id=order_id, include_trades=True)
-            payload = self._extract_order_payload(order_id, response)
-            polled_state = self._state_from_payload(order_id, payload, source="rest_poll")
-            last_state = polled_state
-            if polled_state.is_terminal:
-                return FillMonitorResult(
-                    order_id=order_id,
-                    timed_out=False,
-                    terminal_state=polled_state,
-                    last_state=polled_state,
-                    elapsed_seconds=time.monotonic() - started,
-                )
-
-            await asyncio.sleep(self._poll_interval_seconds)

build/lib/arbitrade/execution/idempotency.py

@@ -1,105 +0,0 @@
-from __future__ import annotations
-
-import hashlib
-from dataclasses import dataclass
-from typing import Any, Protocol
-
-from arbitrade.detection.engine import OpportunityEvent
-from arbitrade.execution.sequencer import ExecutionLeg
-
-
-class SupportsOrderHistoryLookup(Protocol):
-    async def query_order(
-        self, *, order_id: str, include_trades: bool = True
-    ) -> dict[str, Any]: ...
-
-
-@dataclass(frozen=True, slots=True)
-class ReconciliationReport:
-    order_id: str
-    user_ref: int
-    status: str
-    filled_volume: float | None
-    avg_price: float | None
-    is_terminal: bool
-    matches_request: bool
-    raw_payload: dict[str, Any]
-
-
-class IdempotencyKeyFactory:
-    def user_ref_for_leg(self, event: OpportunityEvent, leg: ExecutionLeg, leg_index: int) -> int:
-        material = "|".join(
-            [
-                event.cycle,
-                event.updated_pair,
-                leg.from_currency,
-                leg.to_currency,
-                leg.pair,
-                leg.side,
-                f"{leg.volume:.12f}",
-                str(leg_index),
-            ]
-        ).encode("utf-8")
-        digest = hashlib.sha256(material).digest()
-        value = int.from_bytes(digest[:8], "big") % 2_147_483_647
-        return value or 1
-
-
-class OrderReconciler:
-    def __init__(self, history_client: SupportsOrderHistoryLookup) -> None:
-        self._history_client = history_client
-
-    @staticmethod
-    def _to_float(value: Any) -> float | None:
-        if value is None:
-            return None
-        try:
-            return float(value)
-        except (TypeError, ValueError):
-            return None
-
-    @staticmethod
-    def _extract_payload(order_id: str, response: dict[str, Any]) -> dict[str, Any]:
-        if order_id in response and isinstance(response[order_id], dict):
-            payload = response[order_id]
-            return {str(key): value for key, value in payload.items()}
-        return response
-
-    async def reconcile_order(
-        self,
-        *,
-        order_id: str,
-        user_ref: int,
-        expected_pair: str,
-        expected_side: str,
-        expected_volume: float,
-    ) -> ReconciliationReport:
-        if not order_id.strip():
-            raise ValueError("order_id must be non-empty")
-
-        response = await self._history_client.query_order(order_id=order_id, include_trades=True)
-        payload = self._extract_payload(order_id, response)
-        status = str(payload.get("status", "unknown")).lower()
-        filled_volume = self._to_float(payload.get("vol_exec"))
-        avg_price = self._to_float(payload.get("price") or payload.get("avg_price"))
-        reported_pair = str(payload.get("pair", expected_pair))
-        reported_side = str(payload.get("type", expected_side)).lower()
-        matches_request = (
-            reported_pair == expected_pair
-            and reported_side == expected_side.lower()
-            and (
-                expected_volume <= 0.0 or filled_volume is None or filled_volume <= expected_volume
-            )
-            and payload.get("userref") in {None, str(user_ref), user_ref}
-        )
-
-        return ReconciliationReport(
-            order_id=order_id,
-            user_ref=user_ref,
-            status=status,
-            filled_volume=filled_volume,
-            avg_price=avg_price,
-            is_terminal=status in {"closed", "canceled", "expired"},
-            matches_request=matches_request,
-            raw_payload=payload,
-        )

build/lib/arbitrade/execution/recovery.py

@@ -1,98 +0,0 @@
-from __future__ import annotations
-
-from dataclasses import dataclass
-from typing import Any, Protocol
-
-from arbitrade.execution.fill_monitor import FillMonitorResult, OrderFillState
-
-
-class SupportsOrderLifecycle(Protocol):
-    async def cancel_order(self, *, order_id: str) -> dict[str, Any]: ...
-
-    async def place_market_order(
-        self, *, pair: str, side: str, volume: float
-    ) -> dict[str, Any]: ...
-
-
-@dataclass(frozen=True, slots=True)
-class RecoveryAction:
-    order_id: str
-    canceled: bool
-    hedged: bool
-    hedge_pair: str | None = None
-    hedge_side: str | None = None
-    hedge_volume: float | None = None
-    cancel_response: dict[str, Any] | None = None
-    hedge_response: dict[str, Any] | None = None
-    reason: str | None = None
-
-
-class PartialFillRecovery:
-    def __init__(self, rest_client: SupportsOrderLifecycle) -> None:
-        self._rest_client = rest_client
-
-    @staticmethod
-    def _counter_side(side: str) -> str:
-        normalized = side.lower()
-        if normalized == "buy":
-            return "sell"
-        if normalized == "sell":
-            return "buy"
-        raise ValueError("side must be 'buy' or 'sell'")
-
-    @staticmethod
-    def _residual_volume(terminal_state: OrderFillState | None, requested_volume: float) -> float:
-        if requested_volume <= 0.0:
-            raise ValueError("requested_volume must be > 0.0")
-        if terminal_state is None or terminal_state.filled_volume is None:
-            return requested_volume
-        residual = requested_volume - terminal_state.filled_volume
-        return residual if residual > 0.0 else 0.0
-
-    async def recover_partial_fill(
-        self,
-        *,
-        order_id: str,
-        pair: str,
-        side: str,
-        requested_volume: float,
-        fill_result: FillMonitorResult,
-    ) -> RecoveryAction:
-        if not order_id.strip():
-            raise ValueError("order_id must be non-empty")
-
-        cancel_response: dict[str, Any] | None = None
-        hedge_response: dict[str, Any] | None = None
-        hedged = False
-        canceled = False
-        reason = None
-
-        state = fill_result.terminal_state or fill_result.last_state
-        residual_volume = self._residual_volume(state, requested_volume)
-
-        if state is not None and state.status in {"open", "partial"}:
-            cancel_response = await self._rest_client.cancel_order(order_id=order_id)
-            canceled = True
-            reason = f"canceled_{state.status}_order"
-
-        if residual_volume > 0.0 and fill_result.timed_out:
-            hedge_response = await self._rest_client.place_market_order(
-                pair=pair,
-                side=self._counter_side(side),
-                volume=residual_volume,
-            )
-            hedged = True
-            if reason is None:
-                reason = "hedged_timed_out_order"
-
-        return RecoveryAction(
-            order_id=order_id,
-            canceled=canceled,
-            hedged=hedged,
-            hedge_pair=pair if hedged else None,
-            hedge_side=self._counter_side(side) if hedged else None,
-            hedge_volume=residual_volume if hedged else None,
-            cancel_response=cancel_response,
-            hedge_response=hedge_response,
-            reason=reason,
-        )

build/lib/arbitrade/execution/sequencer.py

@@ -1,288 +0,0 @@
-from __future__ import annotations
-
-from collections.abc import Callable, Sequence
-from dataclasses import dataclass
-from datetime import UTC, datetime
-from typing import Any, Protocol
-
-from arbitrade.alerting.notifier import SupportsAlerts
-from arbitrade.detection.engine import OpportunityEvent
-from arbitrade.storage.executions import AsyncExecutionWriter
-from arbitrade.storage.repositories import (
-    AuditRecord,
-    AuditRepository,
-    OrderRecord,
-    PnLRecord,
-    TradeRecord,
-)
-
-
-class SupportsOrderPlacement(Protocol):
-    async def place_market_order(
-        self, *, pair: str, side: str, volume: float
-    ) -> dict[str, Any]: ...
-
-
-@dataclass(frozen=True, slots=True)
-class ExecutionLeg:
-    from_currency: str
-    to_currency: str
-    pair: str
-    side: str
-    volume: float
-
-
-@dataclass(frozen=True, slots=True)
-class TriangularExecutionResult:
-    success: bool
-    requested_legs: tuple[ExecutionLeg, ...]
-    completed_legs: int
-    responses: tuple[dict[str, Any], ...]
-    failure_reason: str | None = None
-
-
-class TriangularExecutionSequencer:
-    def __init__(
-        self,
-        rest_client: SupportsOrderPlacement,
-        *,
-        available_pairs: Sequence[str],
-        volume_for_leg: Callable[[OpportunityEvent, ExecutionLeg, int], float] | None = None,
-        execution_writer: AsyncExecutionWriter | None = None,
-        alert_notifier: SupportsAlerts | None = None,
-        audit_repository: AuditRepository | None = None,
-    ) -> None:
-        self._rest_client = rest_client
-        self._available_pairs = {self._normalize_pair(pair) for pair in available_pairs}
-        self._volume_for_leg = volume_for_leg or self._default_volume_for_leg
-        self._execution_writer = execution_writer
-        self._alert_notifier = alert_notifier
-        self._audit_repository = audit_repository
-
-    @staticmethod
-    def _normalize_pair(pair: str) -> str:
-        normalized = pair.strip().upper().replace("-", "/")
-        if "/" not in normalized:
-            return normalized
-        base, quote = normalized.split("/", 1)
-        return f"{base}/{quote}"
-
-    @staticmethod
-    def _default_volume_for_leg(event: OpportunityEvent, _leg: ExecutionLeg, _idx: int) -> float:
-        if event.allocated_capital <= 0.0:
-            raise ValueError("allocated_capital must be > 0.0")
-        return event.allocated_capital
-
-    def _resolve_leg(self, from_currency: str, to_currency: str, volume: float) -> ExecutionLeg:
-        from_cur = from_currency.upper()
-        to_cur = to_currency.upper()
-
-        buy_pair = f"{to_cur}/{from_cur}"
-        if buy_pair in self._available_pairs:
-            return ExecutionLeg(
-                from_currency=from_cur,
-                to_currency=to_cur,
-                pair=buy_pair,
-                side="buy",
-                volume=volume,
-            )
-
-        sell_pair = f"{from_cur}/{to_cur}"
-        if sell_pair in self._available_pairs:
-            return ExecutionLeg(
-                from_currency=from_cur,
-                to_currency=to_cur,
-                pair=sell_pair,
-                side="sell",
-                volume=volume,
-            )
-
-        raise ValueError(f"No tradable pair for leg {from_cur}->{to_cur}")
-
-    def _build_legs(self, event: OpportunityEvent) -> tuple[ExecutionLeg, ...]:
-        currencies = [part.strip().upper() for part in event.cycle.split("->") if part.strip()]
-        if len(currencies) < 4 or currencies[0] != currencies[-1]:
-            raise ValueError("cycle must be a closed triangular path like A->B->C->A")
-
-        if len(currencies) != 4:
-            raise ValueError("cycle must contain exactly three unique currencies")
-
-        legs: list[ExecutionLeg] = []
-        for idx in range(3):
-            from_currency = currencies[idx]
-            to_currency = currencies[idx + 1]
-            placeholder_leg = ExecutionLeg(
-                from_currency=from_currency,
-                to_currency=to_currency,
-                pair="",
-                side="buy",
-                volume=0.0,
-            )
-            volume = self._volume_for_leg(event, placeholder_leg, idx)
-            if volume <= 0.0:
-                raise ValueError("volume_for_leg must return a positive volume")
-            legs.append(self._resolve_leg(from_currency, to_currency, volume))
-
-        return tuple(legs)
-
-    @staticmethod
-    def _trade_ref_for_event(event: OpportunityEvent) -> str:
-        material = (
-            f"{event.cycle}|{event.updated_pair}|"
-            f"{event.detected_at.timestamp():.6f}|"
-            f"{event.allocated_capital:.12f}"
-        )
-        return material.encode("utf-8").hex()[:32]
-
-    @staticmethod
-    def _order_ref_from_response(response: dict[str, Any], default: str) -> str:
-        txid = response.get("txid")
-        if isinstance(txid, list) and txid:
-            return str(txid[0])
-        if isinstance(txid, str) and txid.strip():
-            return txid
-        return default
-
-    async def execute(self, event: OpportunityEvent) -> TriangularExecutionResult:
-        legs = self._build_legs(event)
-        responses: list[dict[str, Any]] = []
-        trade_ref = self._trade_ref_for_event(event)
-        started_at = datetime.now(UTC)
-
-        for idx, leg in enumerate(legs):
-            try:
-                response = await self._rest_client.place_market_order(
-                    pair=leg.pair,
-                    side=leg.side,
-                    volume=leg.volume,
-                )
-            except Exception as exc:
-                if self._audit_repository is not None:
-                    self._audit_repository.insert(
-                        AuditRecord(
-                            occurred_at=datetime.now(UTC),
-                            actor="execution_engine",
-                            event_type="execution.trade.failed",
-                            decision="rejected",
-                            payload={
-                                "cycle": event.cycle,
-                                "failed_leg_index": idx,
-                                "error": str(exc),
-                            },
-                            correlation_id=trade_ref,
-                        )
-                    )
-                if self._alert_notifier is not None:
-                    await self._alert_notifier.notify(
-                        category="error",
-                        severity="error",
-                        title="Trade execution failed",
-                        message="Triangular execution failed before completing all legs.",
-                        details={
-                            "cycle": event.cycle,
-                            "failed_leg_index": str(idx),
-                            "error": str(exc),
-                        },
-                    )
-                if self._execution_writer is not None:
-                    await self._execution_writer.enqueue(
-                        TradeRecord(
-                            trade_ref=trade_ref,
-                            started_at=started_at,
-                            finished_at=datetime.now(UTC),
-                            status="failed",
-                            realized_pnl=None,
-                            estimated_pnl=event.est_profit,
-                            capital_used=event.allocated_capital,
-                            cycle=event.cycle,
-                            leg_count=len(legs),
-                        )
-                    )
-                return TriangularExecutionResult(
-                    success=False,
-                    requested_legs=legs,
-                    completed_legs=idx,
-                    responses=tuple(responses),
-                    failure_reason=str(exc),
-                )
-
-            responses.append(response)
-
-            if self._execution_writer is not None:
-                order_ref = self._order_ref_from_response(response, f"leg-{idx}")
-                await self._execution_writer.enqueue(
-                    OrderRecord(
-                        trade_ref=trade_ref,
-                        order_ref=order_ref,
-                        leg_index=idx,
-                        pair=leg.pair,
-                        side=leg.side,
-                        volume=leg.volume,
-                        user_ref=None,
-                        status=str(response.get("status", "submitted")),
-                        filled_volume=None,
-                        avg_price=None,
-                        raw_response=response,
-                        recorded_at=datetime.now(UTC),
-                    )
-                )
-
-        if self._execution_writer is not None:
-            await self._execution_writer.enqueue(
-                TradeRecord(
-                    trade_ref=trade_ref,
-                    started_at=started_at,
-                    finished_at=datetime.now(UTC),
-                    status="filled",
-                    realized_pnl=None,
-                    estimated_pnl=event.est_profit,
-                    capital_used=event.allocated_capital,
-                    cycle=event.cycle,
-                    leg_count=len(legs),
-                )
-            )
-            await self._execution_writer.enqueue(
-                PnLRecord(
-                    trade_ref=trade_ref,
-                    recorded_at=datetime.now(UTC),
-                    kind="estimated",
-                    pnl_usd=event.est_profit,
-                    source="triangular_sequencer",
-                )
-            )
-
-        if self._alert_notifier is not None:
-            await self._alert_notifier.notify(
-                category="trade",
-                severity="warning" if event.est_profit < 0.0 else "info",
-                title="Trade execution completed",
-                message="Triangular execution completed all requested legs.",
-                details={
-                    "cycle": event.cycle,
-                    "completed_legs": str(len(legs)),
-                    "estimated_pnl_usd": f"{event.est_profit}",
-                },
-            )
-
-        if self._audit_repository is not None:
-            self._audit_repository.insert(
-                AuditRecord(
-                    occurred_at=datetime.now(UTC),
-                    actor="execution_engine",
-                    event_type="execution.trade.completed",
-                    decision="approved",
-                    payload={
-                        "cycle": event.cycle,
-                        "completed_legs": len(legs),
-                        "estimated_pnl_usd": event.est_profit,
-                    },
-                    correlation_id=trade_ref,
-                )
-            )
-
-        return TriangularExecutionResult(
-            success=True,
-            requested_legs=legs,
-            completed_legs=len(legs),
-            responses=tuple(responses),
-        )

build/lib/arbitrade/logging_setup.py

@@ -1,39 +0,0 @@
-from __future__ import annotations
-
-import logging
-import sys
-from typing import Any
-
-import structlog
-
-
-def configure_logging(log_level: str = "INFO", json_logs: bool = True) -> None:
-    level = getattr(logging, log_level.upper(), logging.INFO)
-
-    timestamper = structlog.processors.TimeStamper(fmt="iso", utc=True)
-
-    shared_processors: list[Any] = [
-        structlog.contextvars.merge_contextvars,
-        structlog.stdlib.add_log_level,
-        structlog.stdlib.add_logger_name,
-        timestamper,
-    ]
-
-    if json_logs:
-        renderer: Any = structlog.processors.JSONRenderer()
-    else:
-        renderer = structlog.dev.ConsoleRenderer()
-
-    structlog.configure(
-        processors=[
-            *shared_processors,
-            structlog.processors.dict_tracebacks,
-            structlog.processors.EventRenamer("message"),
-            renderer,
-        ],
-        wrapper_class=structlog.make_filtering_bound_logger(level),
-        logger_factory=structlog.stdlib.LoggerFactory(),
-        cache_logger_on_first_use=True,
-    )
-
-    logging.basicConfig(format="%(message)s", stream=sys.stdout, level=level, force=True)

build/lib/arbitrade/main.py

@@ -1,41 +0,0 @@
-from __future__ import annotations
-
-import platform
-from importlib import import_module
-
-import uvicorn
-
-from arbitrade.api.app import create_app
-from arbitrade.config.settings import get_settings
-
-
-def _install_uvloop_if_available() -> None:
-    if platform.system() == "Windows":
-        return
-
-    try:
-        uvloop = import_module("uvloop")
-        uvloop.install()
-    except Exception:
-        # App can still run with default asyncio loop.
-        return
-
-
-def main() -> None:
-    _install_uvloop_if_available()
-
-    settings = get_settings()
-    app = create_app(settings)
-
-    uvicorn.run(
-        app,
-        host=settings.app_host,
-        port=settings.app_port,
-        log_level=settings.log_level.lower(),
-        loop="uvloop" if platform.system() != "Windows" else "asyncio",
-        http="httptools",
-    )
-
-
-if __name__ == "__main__":
-    main()

build/lib/arbitrade/market_data/__init__.py

@@ -1 +0,0 @@
-"""Market data ingestion and book cache package."""

build/lib/arbitrade/market_data/feed.py

@@ -1,485 +0,0 @@
-from __future__ import annotations
-
-import time
-from collections.abc import Awaitable, Callable, Mapping
-from dataclasses import dataclass
-from datetime import UTC, datetime
-
-import structlog
-
-from arbitrade.alerting.notifier import SupportsAlerts, dispatch_alert_nowait
-from arbitrade.detection.engine import IncrementalCycleDetector, OpportunityEvent
-from arbitrade.exchange.kraken_ws import KrakenWsClient
-from arbitrade.market_data.order_book import OrderBook
-from arbitrade.risk.kill_switch import KillSwitch
-from arbitrade.risk.loss_limits import LossLimitGuard
-from arbitrade.risk.pre_trade import PreTradeValidator
-from arbitrade.risk.stop_conditions import StopConditionsGuard
-from arbitrade.risk.trade_limits import TradeLimitsGuard
-from arbitrade.storage.market_snapshots import AsyncMarketSnapshotWriter, MarketSnapshot
-from arbitrade.storage.opportunities import AsyncOpportunityWriter
-from arbitrade.storage.repositories import AuditRecord, AuditRepository
-
-_LOG = structlog.get_logger(__name__)
-
-
-@dataclass(frozen=True, slots=True)
-class ExecutionOutcome:
-    realized_pnl: float | None = None
-    close_trade: bool = True
-
-
-class MarketDataFeed:
-    def __init__(
-        self,
-        ws_client: KrakenWsClient,
-        snapshot_writer: AsyncMarketSnapshotWriter,
-        detector: IncrementalCycleDetector | None = None,
-        opportunity_writer: AsyncOpportunityWriter | None = None,
-        paper_trading_mode: bool = True,
-        opportunity_executor: (
-            Callable[[OpportunityEvent], Awaitable[ExecutionOutcome | float | None]] | None
-        ) = None,
-        trade_capital: float = 1.0,
-        max_trade_capital: float | None = None,
-        loss_limit_guard: LossLimitGuard | None = None,
-        trade_limits_guard: TradeLimitsGuard | None = None,
-        pre_trade_validator: PreTradeValidator | None = None,
-        balance_provider: Callable[[], Mapping[str, float]] | None = None,
-        quote_balance_asset: str = "USD",
-        kill_switch: KillSwitch | None = None,
-        stop_conditions_guard: StopConditionsGuard | None = None,
-        alert_notifier: SupportsAlerts | None = None,
-        audit_repository: AuditRepository | None = None,
-    ) -> None:
-        self._ws_client = ws_client
-        self._snapshot_writer = snapshot_writer
-        self._books: dict[str, OrderBook] = {}
-        self._detector = detector
-        self._opportunity_writer = opportunity_writer
-        self._paper_trading_mode = paper_trading_mode
-        self._opportunity_executor = opportunity_executor
-        self._trade_capital = trade_capital
-        self._max_trade_capital = max_trade_capital
-        self._loss_limit_guard = loss_limit_guard
-        self._trade_limits_guard = trade_limits_guard
-        self._pre_trade_validator = pre_trade_validator
-        self._balance_provider = balance_provider
-        self._quote_balance_asset = quote_balance_asset.upper()
-        self._kill_switch = kill_switch
-        self._stop_conditions_guard = stop_conditions_guard
-        self._alert_notifier = alert_notifier
-        self._audit_repository = audit_repository
-
-        if self._trade_capital <= 0.0:
-            raise ValueError("trade_capital must be > 0.0")
-        if self._max_trade_capital is not None and self._max_trade_capital <= 0.0:
-            raise ValueError("max_trade_capital must be > 0.0")
-
-    @property
-    def books(self) -> dict[str, OrderBook]:
-        return self._books
-
-    def _effective_trade_capital(self) -> float:
-        if self._max_trade_capital is None:
-            return self._trade_capital
-        return min(self._trade_capital, self._max_trade_capital)
-
-    @staticmethod
-    def _exposure_for_event(event: OpportunityEvent) -> dict[str, float]:
-        currencies = [part for part in event.cycle.split("->") if part]
-        if len(currencies) < 2:
-            return {}
-
-        start = currencies[0]
-        exposure_assets = {currency for currency in currencies[1:] if currency != start}
-        return {asset: event.allocated_capital for asset in exposure_assets}
-
-    async def run(self) -> None:
-        async for message in self._ws_client.connect_stream():
-            parse_start = time.perf_counter()
-            delta = self._ws_client.parse_book_delta(message.payload)
-            if delta is None:
-                continue
-
-            book = self._books.setdefault(delta.symbol, OrderBook())
-            book.apply_bids(delta.bids)
-            book.apply_asks(delta.asks)
-
-            checksum_ok = True
-            if delta.checksum is not None:
-                checksum_ok = book.compute_checksum() == delta.checksum
-
-            apply_latency_ms = (time.perf_counter() - parse_start) * 1000
-            source_latency_ms: float | None = None
-            if delta.source_timestamp_ms is not None:
-                source_latency_ms = datetime.now(UTC).timestamp() * 1000 - float(
-                    delta.source_timestamp_ms
-                )
-
-            _LOG.info(
-                "book_delta_applied",
-                symbol=delta.symbol,
-                bids=len(delta.bids),
-                asks=len(delta.asks),
-                checksum_ok=checksum_ok,
-                apply_latency_ms=apply_latency_ms,
-                source_latency_ms=source_latency_ms,
-            )
-
-            if self._stop_conditions_guard is not None:
-                self._stop_conditions_guard.observe_latency(
-                    source_latency_ms=source_latency_ms,
-                    apply_latency_ms=apply_latency_ms,
-                )
-                if self._stop_conditions_guard.is_halted:
-                    if self._kill_switch is not None and not self._kill_switch.is_active:
-                        self._kill_switch.activate(
-                            reason=self._stop_conditions_guard.halted_reason
-                            or "stop_conditions_halted",
-                        )
-                    _LOG.warning(
-                        "stop_condition_halt_triggered",
-                        reason=self._stop_conditions_guard.halted_reason,
-                        symbol=delta.symbol,
-                    )
-                    if self._audit_repository is not None:
-                        self._audit_repository.insert(
-                            AuditRecord(
-                                occurred_at=datetime.now(UTC),
-                                actor="risk_manager",
-                                event_type="risk.stop_condition_halt",
-                                decision="rejected",
-                                payload={
-                                    "reason": self._stop_conditions_guard.halted_reason
-                                    or "unknown",
-                                    "symbol": delta.symbol,
-                                },
-                            )
-                        )
-
-            if self._detector is not None:
-                opportunities = self._detector.opportunities_for_updated_pair(
-                    delta.symbol,
-                    self._books,
-                    base_capital=self._effective_trade_capital(),
-                )
-                _LOG.debug(
-                    "incremental_opportunity_scores",
-                    symbol=delta.symbol,
-                    opportunities=len(opportunities),
-                )
-
-                for event in opportunities:
-                    if self._audit_repository is not None:
-                        self._audit_repository.insert(
-                            AuditRecord(
-                                occurred_at=datetime.now(UTC),
-                                actor="detector",
-                                event_type="detector.opportunity",
-                                decision="scored",
-                                payload={
-                                    "cycle": event.cycle,
-                                    "updated_pair": event.updated_pair,
-                                    "net_pct": event.net_pct,
-                                    "est_profit": event.est_profit,
-                                },
-                            )
-                        )
-                    _LOG.info(
-                        "opportunity_detected",
-                        cycle=event.cycle,
-                        updated_pair=event.updated_pair,
-                        gross_pct=event.gross_pct,
-                        net_pct=event.net_pct,
-                        est_profit=event.est_profit,
-                        mode="paper" if self._paper_trading_mode else "live",
-                    )
-
-                    if self._opportunity_writer is not None:
-                        await self._opportunity_writer.enqueue(event)
-
-                    if self._paper_trading_mode:
-                        _LOG.info(
-                            "paper_trade_simulated",
-                            cycle=event.cycle,
-                            updated_pair=event.updated_pair,
-                            net_pct=event.net_pct,
-                        )
-                        if self._audit_repository is not None:
-                            self._audit_repository.insert(
-                                AuditRecord(
-                                    occurred_at=datetime.now(UTC),
-                                    actor="execution_engine",
-                                    event_type="execution.paper_trade",
-                                    decision="skipped",
-                                    payload={
-                                        "cycle": event.cycle,
-                                        "updated_pair": event.updated_pair,
-                                    },
-                                )
-                            )
-                        continue
-
-                    if self._opportunity_executor is None:
-                        _LOG.warning(
-                            "live_trade_skipped_no_executor",
-                            cycle=event.cycle,
-                            updated_pair=event.updated_pair,
-                        )
-                        if self._audit_repository is not None:
-                            self._audit_repository.insert(
-                                AuditRecord(
-                                    occurred_at=datetime.now(UTC),
-                                    actor="execution_engine",
-                                    event_type="execution.live_trade",
-                                    decision="rejected",
-                                    payload={
-                                        "reason": "missing_executor",
-                                        "cycle": event.cycle,
-                                    },
-                                )
-                            )
-                        continue
-
-                    if self._kill_switch is not None and self._kill_switch.is_active:
-                        _LOG.warning(
-                            "live_trade_skipped_kill_switch",
-                            cycle=event.cycle,
-                            updated_pair=event.updated_pair,
-                            reason=self._kill_switch.reason,
-                        )
-                        if self._audit_repository is not None:
-                            self._audit_repository.insert(
-                                AuditRecord(
-                                    occurred_at=datetime.now(UTC),
-                                    actor="risk_manager",
-                                    event_type="risk.kill_switch",
-                                    decision="rejected",
-                                    payload={
-                                        "reason": self._kill_switch.reason or "manual",
-                                        "cycle": event.cycle,
-                                    },
-                                )
-                            )
-                        continue
-
-                    if (
-                        self._stop_conditions_guard is not None
-                        and self._stop_conditions_guard.is_halted
-                    ):
-                        _LOG.warning(
-                            "live_trade_skipped_stop_condition_halt",
-                            cycle=event.cycle,
-                            updated_pair=event.updated_pair,
-                            reason=self._stop_conditions_guard.halted_reason,
-                        )
-                        if self._audit_repository is not None:
-                            self._audit_repository.insert(
-                                AuditRecord(
-                                    occurred_at=datetime.now(UTC),
-                                    actor="risk_manager",
-                                    event_type="risk.stop_condition",
-                                    decision="rejected",
-                                    payload={
-                                        "reason": self._stop_conditions_guard.halted_reason
-                                        or "halted",
-                                        "cycle": event.cycle,
-                                    },
-                                )
-                            )
-                        continue
-
-                    if self._loss_limit_guard is not None and self._loss_limit_guard.is_halted:
-                        _LOG.warning(
-                            "live_trade_skipped_loss_limit_halted",
-                            cycle=event.cycle,
-                            updated_pair=event.updated_pair,
-                            reason=self._loss_limit_guard.halted_reason,
-                        )
-                        if self._audit_repository is not None:
-                            self._audit_repository.insert(
-                                AuditRecord(
-                                    occurred_at=datetime.now(UTC),
-                                    actor="risk_manager",
-                                    event_type="risk.loss_limit",
-                                    decision="rejected",
-                                    payload={
-                                        "reason": self._loss_limit_guard.halted_reason or "halted",
-                                        "cycle": event.cycle,
-                                    },
-                                )
-                            )
-                        continue
-
-                    if self._pre_trade_validator is not None and self._balance_provider is not None:
-                        required_balances = {self._quote_balance_asset: event.allocated_capital}
-                        balances = {
-                            asset.upper(): amount
-                            for asset, amount in self._balance_provider().items()
-                        }
-                        if not self._pre_trade_validator.validate(
-                            balances_by_asset=balances,
-                            required_by_asset=required_balances,
-                        ):
-                            _LOG.warning(
-                                "live_trade_skipped_pre_trade_validation",
-                                cycle=event.cycle,
-                                updated_pair=event.updated_pair,
-                                required_by_asset=required_balances,
-                            )
-                            if self._audit_repository is not None:
-                                self._audit_repository.insert(
-                                    AuditRecord(
-                                        occurred_at=datetime.now(UTC),
-                                        actor="risk_manager",
-                                        event_type="risk.pre_trade_validation",
-                                        decision="rejected",
-                                        payload={
-                                            "cycle": event.cycle,
-                                            "required_by_asset": {
-                                                key: required_balances[key]
-                                                for key in required_balances
-                                            },
-                                        },
-                                    )
-                                )
-                            continue
-
-                    exposure_by_asset = self._exposure_for_event(event)
-                    if (
-                        self._trade_limits_guard is not None
-                        and not self._trade_limits_guard.is_trade_allowed(exposure_by_asset)
-                    ):
-                        _LOG.warning(
-                            "live_trade_skipped_trade_limits",
-                            cycle=event.cycle,
-                            updated_pair=event.updated_pair,
-                            exposure_by_asset=exposure_by_asset,
-                        )
-                        if self._audit_repository is not None:
-                            self._audit_repository.insert(
-                                AuditRecord(
-                                    occurred_at=datetime.now(UTC),
-                                    actor="risk_manager",
-                                    event_type="risk.trade_limits",
-                                    decision="rejected",
-                                    payload={
-                                        "cycle": event.cycle,
-                                        "exposure_by_asset": {
-                                            key: exposure_by_asset[key] for key in exposure_by_asset
-                                        },
-                                    },
-                                )
-                            )
-                        continue
-
-                    if self._trade_limits_guard is not None:
-                        self._trade_limits_guard.open_trade(exposure_by_asset)
-
-                    try:
-                        outcome = await self._opportunity_executor(event)
-                    except Exception as exc:
-                        if self._trade_limits_guard is not None:
-                            self._trade_limits_guard.close_trade(exposure_by_asset)
-
-                        dispatch_alert_nowait(
-                            self._alert_notifier,
-                            category="system",
-                            severity="critical",
-                            title="Critical execution exception",
-                            message="Unhandled exception raised by opportunity executor.",
-                            details={
-                                "cycle": event.cycle,
-                                "updated_pair": event.updated_pair,
-                                "error": str(exc),
-                            },
-                        )
-
-                        if self._stop_conditions_guard is not None:
-                            self._stop_conditions_guard.register_failure()
-                            if self._stop_conditions_guard.is_halted:
-                                if (
-                                    self._kill_switch is not None
-                                    and not self._kill_switch.is_active
-                                ):
-                                    self._kill_switch.activate(
-                                        reason=self._stop_conditions_guard.halted_reason
-                                        or "stop_conditions_halted",
-                                    )
-                                _LOG.warning(
-                                    "stop_condition_halt_triggered",
-                                    reason=self._stop_conditions_guard.halted_reason,
-                                    cycle=event.cycle,
-                                    updated_pair=event.updated_pair,
-                                )
-
-                        _LOG.exception(
-                            "live_trade_execution_failed",
-                            cycle=event.cycle,
-                            updated_pair=event.updated_pair,
-                        )
-                        if self._audit_repository is not None:
-                            self._audit_repository.insert(
-                                AuditRecord(
-                                    occurred_at=datetime.now(UTC),
-                                    actor="execution_engine",
-                                    event_type="execution.live_trade",
-                                    decision="error",
-                                    payload={
-                                        "cycle": event.cycle,
-                                        "updated_pair": event.updated_pair,
-                                        "error": str(exc),
-                                    },
-                                )
-                            )
-                        continue
-
-                    if self._stop_conditions_guard is not None:
-                        self._stop_conditions_guard.register_success()
-
-                    realized_pnl: float | None
-                    close_trade = True
-                    if isinstance(outcome, ExecutionOutcome):
-                        realized_pnl = outcome.realized_pnl
-                        close_trade = outcome.close_trade
-                    else:
-                        realized_pnl = outcome
-
-                    if realized_pnl is not None and self._loss_limit_guard is not None:
-                        self._loss_limit_guard.register_realized_pnl(realized_pnl)
-                        if self._loss_limit_guard.is_halted:
-                            _LOG.warning(
-                                "loss_limit_halt_triggered",
-                                reason=self._loss_limit_guard.halted_reason,
-                                cumulative_pnl=self._loss_limit_guard.cumulative_pnl,
-                            )
-
-                    if self._trade_limits_guard is not None and close_trade:
-                        self._trade_limits_guard.close_trade(exposure_by_asset)
-
-                    if self._audit_repository is not None:
-                        self._audit_repository.insert(
-                            AuditRecord(
-                                occurred_at=datetime.now(UTC),
-                                actor="execution_engine",
-                                event_type="execution.live_trade",
-                                decision="approved",
-                                payload={
-                                    "cycle": event.cycle,
-                                    "updated_pair": event.updated_pair,
-                                    "realized_pnl": realized_pnl,
-                                    "close_trade": close_trade,
-                                },
-                            )
-                        )
-
-            await self._snapshot_writer.enqueue(
-                MarketSnapshot(
-                    snapshot_at=datetime.now(UTC),
-                    symbol=delta.symbol,
-                    source="kraken_ws",
-                    payload=message.payload,
-                    latency_ms=source_latency_ms,
-                )
-            )

build/lib/arbitrade/market_data/order_book.py

@@ -1,104 +0,0 @@
-from __future__ import annotations
-
-import re
-from collections.abc import Iterable
-from dataclasses import dataclass
-from datetime import UTC, datetime
-
-from sortedcontainers import SortedDict
-
-from arbitrade.exchange.models import BookLevel
-
-ZERO_CLEAN_RE = re.compile(r"^0+", re.ASCII)
-
-
-def _normalize_price_for_checksum(value: float) -> str:
-    text = f"{value:.10f}".replace(".", "")
-    text = text.rstrip("0")
-    stripped = ZERO_CLEAN_RE.sub("", text)
-    return stripped or "0"
-
-
-def _normalize_volume_for_checksum(value: float) -> str:
-    text = f"{value:.10f}".replace(".", "")
-    text = text.rstrip("0")
-    stripped = ZERO_CLEAN_RE.sub("", text)
-    return stripped or "0"
-
-
-@dataclass(slots=True)
-class BookView:
-    best_bid: BookLevel | None
-    best_ask: BookLevel | None
-    updated_at: datetime
-
-
-class OrderBook:
-    def __init__(self) -> None:
-        self._bids: SortedDict[float, float] = SortedDict()
-        self._asks: SortedDict[float, float] = SortedDict()
-        self._updated_at: datetime = datetime.now(UTC)
-
-    @property
-    def updated_at(self) -> datetime:
-        return self._updated_at
-
-    def apply_bids(self, updates: Iterable[BookLevel]) -> None:
-        for level in updates:
-            if level.volume <= 0:
-                self._bids.pop(level.price, None)
-            else:
-                self._bids[level.price] = level.volume
-        self._updated_at = datetime.now(UTC)
-
-    def apply_asks(self, updates: Iterable[BookLevel]) -> None:
-        for level in updates:
-            if level.volume <= 0:
-                self._asks.pop(level.price, None)
-            else:
-                self._asks[level.price] = level.volume
-        self._updated_at = datetime.now(UTC)
-
-    def best_bid(self) -> BookLevel | None:
-        if not self._bids:
-            return None
-        price = self._bids.peekitem(-1)[0]
-        return BookLevel(price=price, volume=self._bids[price])
-
-    def best_ask(self) -> BookLevel | None:
-        if not self._asks:
-            return None
-        price = self._asks.peekitem(0)[0]
-        return BookLevel(price=price, volume=self._asks[price])
-
-    def snapshot(self) -> BookView:
-        return BookView(
-            best_bid=self.best_bid(),
-            best_ask=self.best_ask(),
-            updated_at=self._updated_at,
-        )
-
-    def top_levels(self, depth: int = 10) -> tuple[list[BookLevel], list[BookLevel]]:
-        bid_keys = list(self._bids.keys())
-        ask_keys = list(self._asks.keys())
-
-        bids = [
-            BookLevel(price=price, volume=self._bids[price])
-            for price in reversed(bid_keys[-depth:])
-        ]
-        asks = [BookLevel(price=price, volume=self._asks[price]) for price in ask_keys[:depth]]
-        return bids, asks
-
-    def compute_checksum(self, depth: int = 10) -> int:
-        bids, asks = self.top_levels(depth)
-        combined: list[str] = []
-        for level in bids:
-            combined.append(_normalize_price_for_checksum(level.price))
-            combined.append(_normalize_volume_for_checksum(level.volume))
-        for level in asks:
-            combined.append(_normalize_price_for_checksum(level.price))
-            combined.append(_normalize_volume_for_checksum(level.volume))
-
-        import zlib
-
-        return zlib.crc32("".join(combined).encode("utf-8"))

build/lib/arbitrade/metrics.py

@@ -1,100 +0,0 @@
-from __future__ import annotations
-
-from dataclasses import dataclass
-from datetime import datetime
-
-from arbitrade.storage.db import DuckDBStore
-
-
-@dataclass(frozen=True, slots=True)
-class PerformanceMetrics:
-    realized_pnl_usd: float
-    win_rate: float | None
-    avg_trade_duration_seconds: float | None
-    opportunities_per_minute: float | None
-    fill_rate: float | None
-    latency_p50_seconds: float | None
-    latency_p95_seconds: float | None
-    latency_p99_seconds: float | None
-
-
-class MetricsCalculator:
-    def __init__(self, store: DuckDBStore) -> None:
-        self._store = store
-
-    def compute(self) -> PerformanceMetrics:
-        with self._store.connect() as conn:
-            tm = conn.execute("""
-                SELECT
-                    COALESCE(SUM(COALESCE(realized_pnl, 0)), 0) AS realized_pnl_usd,
-                    COUNT(*) AS total_trades,
-                    SUM(CASE WHEN realized_pnl > 0 THEN 1 ELSE 0 END) AS winning_trades,
-                    AVG(EPOCH(finished_at) - EPOCH(started_at)) AS avg_trade_duration_seconds,
-                    quantile_cont(
-                        EPOCH(finished_at) - EPOCH(started_at),
-                        0.50
-                    ) AS latency_p50_seconds,
-                    quantile_cont(
-                        EPOCH(finished_at) - EPOCH(started_at),
-                        0.95
-                    ) AS latency_p95_seconds,
-                    quantile_cont(
-                        EPOCH(finished_at) - EPOCH(started_at),
-                        0.99
-                    ) AS latency_p99_seconds
-                FROM trades
-                WHERE finished_at IS NOT NULL
-                """).fetchone()
-
-            om = conn.execute("""
-                SELECT
-                    COUNT(*) AS opportunity_count,
-                    MIN(detected_at) AS first_detected_at,
-                    MAX(detected_at) AS last_detected_at
-                FROM opportunities
-                """).fetchone()
-
-            fm = conn.execute("""
-                SELECT AVG(filled_volume / volume) AS fill_rate
-                FROM orders
-                WHERE volume > 0 AND filled_volume IS NOT NULL
-                """).fetchone()
-
-        r_pnl_usd = float(tm[0]) if tm and tm[0] is not None else 0.0
-        tt = int(tm[1]) if tm and tm[1] is not None else 0
-        wt = int(tm[2]) if tm and tm[2] is not None else 0
-        wr = wt / tt if tt > 0 else None
-
-        atd = float(tm[3]) if tm and tm[3] is not None else None
-
-        oc = int(om[0]) if om is not None and om[0] is not None else 0
-        fo = om[1] if om is not None and isinstance(om[1], datetime) else None
-        lo = om[2] if om is not None and isinstance(om[2], datetime) else None
-
-        opportunities_per_minute: float | None
-        if oc >= 2 and fo is not None and lo is not None:
-            span_seconds = (lo - fo).total_seconds()
-            opportunities_per_minute = (
-                oc / (span_seconds / 60.0) if span_seconds > 0.0 else float(oc)
-            )
-        elif oc == 1:
-            opportunities_per_minute = 60.0
-        else:
-            opportunities_per_minute = None
-
-        fill_rate = float(fm[0]) if fm and fm[0] is not None else None
-
-        lp50 = float(tm[4]) if tm and tm[4] is not None else None
-        lp95 = float(tm[5]) if tm and tm[5] is not None else None
-        lp99 = float(tm[6]) if tm and tm[6] is not None else None
-
-        return PerformanceMetrics(
-            realized_pnl_usd=r_pnl_usd,
-            win_rate=wr,
-            avg_trade_duration_seconds=atd,
-            opportunities_per_minute=opportunities_per_minute,
-            fill_rate=fill_rate,
-            latency_p50_seconds=lp50,
-            latency_p95_seconds=lp95,
-            latency_p99_seconds=lp99,
-        )

build/lib/arbitrade/perf/__init__.py

@@ -1,4 +0,0 @@
-from arbitrade.perf.guardrails import evaluate_guardrails
-from arbitrade.perf.latency import run_latency_profile
-
-__all__ = ["run_latency_profile", "evaluate_guardrails"]

build/lib/arbitrade/perf/guardrails.py

@@ -1,80 +0,0 @@
-from __future__ import annotations
-
-
-def evaluate_guardrails(
-    *,
-    baseline: dict[str, object],
-    current: dict[str, object],
-    thresholds: dict[str, object],
-) -> list[str]:
-    failures: list[str] = []
-
-    baseline_scenarios = baseline.get("scenarios")
-    current_scenarios = current.get("scenarios")
-    if not isinstance(baseline_scenarios, dict) or not isinstance(current_scenarios, dict):
-        return ["invalid profile payload: missing scenarios map"]
-
-    default_thresholds = thresholds.get("default")
-    if not isinstance(default_thresholds, dict):
-        default_thresholds = {"p95_ms": 2.5, "p99_ms": 3.0}
-
-    scenario_thresholds = thresholds.get("scenarios")
-    if not isinstance(scenario_thresholds, dict):
-        scenario_thresholds = {}
-
-    for scenario, baseline_payload in baseline_scenarios.items():
-        current_payload = current_scenarios.get(scenario)
-        if not isinstance(baseline_payload, dict) or not isinstance(current_payload, dict):
-            failures.append(f"missing scenario in current profile: {scenario}")
-            continue
-
-        baseline_stages = baseline_payload.get("stages")
-        current_stages = current_payload.get("stages")
-        if not isinstance(baseline_stages, dict) or not isinstance(current_stages, dict):
-            failures.append(f"missing stages map for scenario: {scenario}")
-            continue
-
-        scenario_config = scenario_thresholds.get(scenario)
-        if not isinstance(scenario_config, dict):
-            scenario_config = {}
-
-        for stage, baseline_stage in baseline_stages.items():
-            current_stage = current_stages.get(stage)
-            if not isinstance(baseline_stage, dict) or not isinstance(current_stage, dict):
-                failures.append(f"missing stage in current profile: {scenario}.{stage}")
-                continue
-
-            for percentile_key in ("p95_ms", "p99_ms"):
-                threshold_ratio_raw = scenario_config.get(
-                    percentile_key,
-                    default_thresholds.get(percentile_key, 3.0),
-                )
-                threshold_ratio = (
-                    float(threshold_ratio_raw)
-                    if isinstance(threshold_ratio_raw, int | float)
-                    else 3.0
-                )
-
-                base_value_raw = baseline_stage.get(percentile_key)
-                current_value_raw = current_stage.get(percentile_key)
-                if not isinstance(base_value_raw, int | float) or not isinstance(
-                    current_value_raw, int | float
-                ):
-                    failures.append(
-                        f"invalid percentile value: {scenario}.{stage}.{percentile_key}"
-                    )
-                    continue
-
-                base_value = float(base_value_raw)
-                current_value = float(current_value_raw)
-                # Avoid divide-by-zero while still preserving strict checks.
-                max_allowed = max(base_value * threshold_ratio, 0.001)
-                if current_value > max_allowed:
-                    failures.append(
-                        f"latency regression: {scenario}.{stage}.{percentile_key} "
-                        f"current={current_value:.4f}ms "
-                        f"baseline={base_value:.4f}ms "
-                        f"allowed={max_allowed:.4f}ms"
-                    )
-
-    return failures

build/lib/arbitrade/perf/latency.py

@@ -1,195 +0,0 @@
-from __future__ import annotations
-
-from collections.abc import Callable
-from dataclasses import dataclass
-from time import perf_counter_ns
-
-import orjson
-
-
-@dataclass(frozen=True, slots=True)
-class PercentileSummary:
-    p50_ms: float
-    p95_ms: float
-    p99_ms: float
-
-
-@dataclass(frozen=True, slots=True)
-class ScenarioProfile:
-    scenario: str
-    iterations: int
-    stages: dict[str, PercentileSummary]
-
-
-def _percentile(samples: list[float], percentile: float) -> float:
-    if not samples:
-        return 0.0
-    ordered = sorted(samples)
-    if percentile <= 0.0:
-        return ordered[0]
-    if percentile >= 100.0:
-        return ordered[-1]
-    rank = (len(ordered) - 1) * (percentile / 100.0)
-    lower = int(rank)
-    upper = min(lower + 1, len(ordered) - 1)
-    weight = rank - lower
-    return ordered[lower] * (1.0 - weight) + ordered[upper] * weight
-
-
-def _summarize(samples: list[float]) -> PercentileSummary:
-    return PercentileSummary(
-        p50_ms=_percentile(samples, 50.0),
-        p95_ms=_percentile(samples, 95.0),
-        p99_ms=_percentile(samples, 99.0),
-    )
-
-
-def _ingest_stage(raw_payload: bytes, state: dict[str, float]) -> None:
-    parsed = orjson.loads(raw_payload)
-    bids = parsed.get("bids", [])
-    asks = parsed.get("asks", [])
-    for price, volume in bids[:4]:
-        state[str(price)] = float(volume)
-    for price, volume in asks[:4]:
-        state[str(price)] = float(volume)
-
-
-def _detect_stage(values: list[float], cycles: int) -> float:
-    best = 0.0
-    size = len(values)
-    for idx in range(cycles):
-        a = values[idx % size]
-        b = values[(idx + 3) % size]
-        c = values[(idx + 7) % size]
-        gross = (a / b) * c
-        net = gross * 0.9975
-        if net > best:
-            best = net
-    return best
-
-
-def _risk_stage(net_edge: float, capital: float) -> float:
-    if net_edge < 1.0002:
-        return 0.0
-    if capital > 500.0:
-        capital = 500.0
-    return capital * min(net_edge - 1.0, 0.02)
-
-
-def _execution_stage(planned_pnl: float, order_id: int) -> None:
-    payload = {
-        "order_id": order_id,
-        "planned_pnl": planned_pnl,
-        "legs": [
-            {"pair": "BTC/USD", "side": "buy", "qty": 0.01},
-            {"pair": "ETH/BTC", "side": "buy", "qty": 0.1},
-            {"pair": "ETH/USD", "side": "sell", "qty": 0.1},
-        ],
-    }
-    _ = orjson.dumps(payload)
-
-
-def _run_scenario(
-    name: str,
-    iterations: int,
-    detect_cycles: int,
-    reconnect_every: int,
-) -> ScenarioProfile:
-    payloads = [
-        orjson.dumps(
-            {
-                "symbol": "BTC/USD",
-                "bids": [[100000.0 + i, 0.2 + (i % 5) * 0.01] for i in range(12)],
-                "asks": [[100001.0 + i, 0.2 + (i % 7) * 0.01] for i in range(12)],
-            }
-        )
-        for _ in range(5)
-    ]
-    value_series = [1.0 + (idx % 31) * 0.0007 for idx in range(128)]
-    order_state: dict[str, float] = {}
-
-    ingest_ms: list[float] = []
-    detect_ms: list[float] = []
-    risk_ms: list[float] = []
-    execution_ms: list[float] = []
-    end_to_end_ms: list[float] = []
-
-    for idx in range(iterations):
-        start_ns = perf_counter_ns()
-        payload = payloads[idx % len(payloads)]
-
-        t0 = perf_counter_ns()
-        _ingest_stage(payload, order_state)
-        if reconnect_every > 0 and idx > 0 and idx % reconnect_every == 0:
-            order_state.clear()
-        t1 = perf_counter_ns()
-
-        net_edge = _detect_stage(value_series, detect_cycles)
-        t2 = perf_counter_ns()
-
-        planned = _risk_stage(net_edge, capital=100.0 + (idx % 50))
-        t3 = perf_counter_ns()
-
-        _execution_stage(planned, order_id=idx)
-        t4 = perf_counter_ns()
-
-        ingest_ms.append((t1 - t0) / 1_000_000.0)
-        detect_ms.append((t2 - t1) / 1_000_000.0)
-        risk_ms.append((t3 - t2) / 1_000_000.0)
-        execution_ms.append((t4 - t3) / 1_000_000.0)
-        end_to_end_ms.append((t4 - start_ns) / 1_000_000.0)
-
-    return ScenarioProfile(
-        scenario=name,
-        iterations=iterations,
-        stages={
-            "ingest": _summarize(ingest_ms),
-            "detect": _summarize(detect_ms),
-            "risk": _summarize(risk_ms),
-            "execution": _summarize(execution_ms),
-            "end_to_end": _summarize(end_to_end_ms),
-        },
-    )
-
-
-def run_latency_profile(iterations: int = 600) -> dict[str, object]:
-    scenarios: list[Callable[[], ScenarioProfile]] = [
-        lambda: _run_scenario(
-            name="book_update_burst",
-            iterations=iterations,
-            detect_cycles=32,
-            reconnect_every=0,
-        ),
-        lambda: _run_scenario(
-            name="execution_spike",
-            iterations=iterations,
-            detect_cycles=96,
-            reconnect_every=0,
-        ),
-        lambda: _run_scenario(
-            name="reconnect_storm",
-            iterations=iterations,
-            detect_cycles=48,
-            reconnect_every=20,
-        ),
-    ]
-
-    result: dict[str, object] = {"iterations": iterations, "scenarios": {}}
-    scenario_map = result["scenarios"]
-    assert isinstance(scenario_map, dict)
-
-    for scenario in scenarios:
-        profile = scenario()
-        scenario_map[profile.scenario] = {
-            "iterations": profile.iterations,
-            "stages": {
-                stage: {
-                    "p50_ms": summary.p50_ms,
-                    "p95_ms": summary.p95_ms,
-                    "p99_ms": summary.p99_ms,
-                }
-                for stage, summary in profile.stages.items()
-            },
-        }
-
-    return result

build/lib/arbitrade/risk/__init__.py

@@ -1,15 +0,0 @@
-"""Risk management helpers."""
-
-from arbitrade.risk.kill_switch import KillSwitch
-from arbitrade.risk.loss_limits import LossLimitGuard
-from arbitrade.risk.pre_trade import PreTradeValidator
-from arbitrade.risk.stop_conditions import StopConditionsGuard
-from arbitrade.risk.trade_limits import TradeLimitsGuard
-
-__all__ = [
-    "LossLimitGuard",
-    "TradeLimitsGuard",
-    "PreTradeValidator",
-    "KillSwitch",
-    "StopConditionsGuard",
-]

build/lib/arbitrade/risk/kill_switch.py

@@ -1,23 +0,0 @@
-from __future__ import annotations
-
-
-class KillSwitch:
-    def __init__(self, *, active: bool = False, reason: str | None = None) -> None:
-        self._active = active
-        self._reason = reason or ("manual" if active else None)
-
-    @property
-    def is_active(self) -> bool:
-        return self._active
-
-    @property
-    def reason(self) -> str | None:
-        return self._reason
-
-    def activate(self, *, reason: str = "manual") -> None:
-        self._active = True
-        self._reason = reason
-
-    def deactivate(self) -> None:
-        self._active = False
-        self._reason = None

build/lib/arbitrade/risk/loss_limits.py

@@ -1,90 +0,0 @@
-from __future__ import annotations
-
-from datetime import UTC, date, datetime
-
-from arbitrade.alerting.notifier import SupportsAlerts, dispatch_alert_nowait
-
-
-class LossLimitGuard:
-    def __init__(
-        self,
-        *,
-        daily_loss_limit: float | None = None,
-        cumulative_loss_limit: float | None = None,
-        alert_notifier: SupportsAlerts | None = None,
-    ) -> None:
-        self._daily_loss_limit = daily_loss_limit
-        self._cumulative_loss_limit = cumulative_loss_limit
-
-        if self._daily_loss_limit is not None and self._daily_loss_limit <= 0.0:
-            raise ValueError("daily_loss_limit must be > 0.0")
-        if self._cumulative_loss_limit is not None and self._cumulative_loss_limit <= 0.0:
-            raise ValueError("cumulative_loss_limit must be > 0.0")
-
-        self._cumulative_pnl = 0.0
-        self._daily_pnl: dict[date, float] = {}
-        self._halted_reason: str | None = None
-        self._alert_notifier = alert_notifier
-
-    @property
-    def cumulative_pnl(self) -> float:
-        return self._cumulative_pnl
-
-    @property
-    def halted_reason(self) -> str | None:
-        return self._halted_reason
-
-    @property
-    def is_halted(self) -> bool:
-        return self._halted_reason is not None
-
-    def daily_pnl(self, day: date) -> float:
-        return self._daily_pnl.get(day, 0.0)
-
-    def register_realized_pnl(self, pnl: float, *, at: datetime | None = None) -> None:
-        if self.is_halted:
-            return
-
-        timestamp = at or datetime.now(UTC)
-        day_key = timestamp.date()
-
-        self._cumulative_pnl += pnl
-        self._daily_pnl[day_key] = self._daily_pnl.get(day_key, 0.0) + pnl
-
-        if (
-            self._daily_loss_limit is not None
-            and self._daily_pnl[day_key] <= -self._daily_loss_limit
-        ):
-            self._halted_reason = "daily_loss_limit_breached"
-            dispatch_alert_nowait(
-                self._alert_notifier,
-                category="threshold",
-                severity="critical",
-                title="Daily loss limit breached",
-                message="Trading halted because daily realized PnL crossed configured loss limit.",
-                details={
-                    "daily_pnl": f"{self._daily_pnl[day_key]}",
-                    "daily_loss_limit": f"{self._daily_loss_limit}",
-                },
-            )
-            return
-
-        if (
-            self._cumulative_loss_limit is not None
-            and self._cumulative_pnl <= -self._cumulative_loss_limit
-        ):
-            self._halted_reason = "cumulative_loss_limit_breached"
-            dispatch_alert_nowait(
-                self._alert_notifier,
-                category="threshold",
-                severity="critical",
-                title="Cumulative loss limit breached",
-                message=(
-                    "Trading halted because cumulative realized PnL crossed "
-                    "configured loss limit."
-                ),
-                details={
-                    "cumulative_pnl": f"{self._cumulative_pnl}",
-                    "cumulative_loss_limit": f"{self._cumulative_loss_limit}",
-                },
-            )

build/lib/arbitrade/risk/pre_trade.py

@@ -1,43 +0,0 @@
-from __future__ import annotations
-
-from collections.abc import Mapping
-
-
-class PreTradeValidator:
-    def __init__(
-        self,
-        *,
-        min_order_size_by_asset: Mapping[str, float] | None = None,
-    ) -> None:
-        self._min_order_size_by_asset = {
-            asset.upper(): float(value) for asset, value in (min_order_size_by_asset or {}).items()
-        }
-
-        for value in self._min_order_size_by_asset.values():
-            if value <= 0.0:
-                raise ValueError("minimum order size must be > 0.0")
-
-    def validate(
-        self,
-        *,
-        balances_by_asset: Mapping[str, float],
-        required_by_asset: Mapping[str, float],
-    ) -> bool:
-        # Minimum order size checks first to fail fast on structural invalid sizes.
-        for asset, required in required_by_asset.items():
-            if required <= 0.0:
-                continue
-
-            min_size = self._min_order_size_by_asset.get(asset.upper())
-            if min_size is not None and required < min_size:
-                return False
-
-        # Balance checks ensure required quantity is currently available.
-        for asset, required in required_by_asset.items():
-            if required <= 0.0:
-                continue
-            available = balances_by_asset.get(asset.upper(), 0.0)
-            if available < required:
-                return False
-
-        return True

build/lib/arbitrade/risk/stop_conditions.py

@@ -1,109 +0,0 @@
-from __future__ import annotations
-
-from arbitrade.alerting.notifier import SupportsAlerts, dispatch_alert_nowait
-
-
-class StopConditionsGuard:
-    def __init__(
-        self,
-        *,
-        max_source_latency_ms: float | None = None,
-        max_apply_latency_ms: float | None = None,
-        max_consecutive_failures: int | None = None,
-        alert_notifier: SupportsAlerts | None = None,
-    ) -> None:
-        if max_source_latency_ms is not None and max_source_latency_ms <= 0.0:
-            raise ValueError("max_source_latency_ms must be > 0.0")
-        if max_apply_latency_ms is not None and max_apply_latency_ms <= 0.0:
-            raise ValueError("max_apply_latency_ms must be > 0.0")
-        if max_consecutive_failures is not None and max_consecutive_failures <= 0:
-            raise ValueError("max_consecutive_failures must be > 0")
-
-        self._max_source_latency_ms = max_source_latency_ms
-        self._max_apply_latency_ms = max_apply_latency_ms
-        self._max_consecutive_failures = max_consecutive_failures
-
-        self._consecutive_failures = 0
-        self._halted_reason: str | None = None
-        self._alert_notifier = alert_notifier
-
-    @property
-    def halted_reason(self) -> str | None:
-        return self._halted_reason
-
-    @property
-    def is_halted(self) -> bool:
-        return self._halted_reason is not None
-
-    @property
-    def consecutive_failures(self) -> int:
-        return self._consecutive_failures
-
-    def observe_latency(
-        self,
-        *,
-        source_latency_ms: float | None,
-        apply_latency_ms: float,
-    ) -> None:
-        if self.is_halted:
-            return
-
-        if (
-            self._max_source_latency_ms is not None
-            and source_latency_ms is not None
-            and source_latency_ms > self._max_source_latency_ms
-        ):
-            self._halted_reason = "source_latency_limit_breached"
-            dispatch_alert_nowait(
-                self._alert_notifier,
-                category="threshold",
-                severity="critical",
-                title="Source latency limit breached",
-                message="Trading halted because source latency exceeded configured limit.",
-                details={
-                    "source_latency_ms": f"{source_latency_ms}",
-                    "max_source_latency_ms": f"{self._max_source_latency_ms}",
-                },
-            )
-            return
-
-        if self._max_apply_latency_ms is not None and apply_latency_ms > self._max_apply_latency_ms:
-            self._halted_reason = "apply_latency_limit_breached"
-            dispatch_alert_nowait(
-                self._alert_notifier,
-                category="threshold",
-                severity="critical",
-                title="Apply latency limit breached",
-                message="Trading halted because apply latency exceeded configured limit.",
-                details={
-                    "apply_latency_ms": f"{apply_latency_ms}",
-                    "max_apply_latency_ms": f"{self._max_apply_latency_ms}",
-                },
-            )
-
-    def register_failure(self) -> None:
-        if self.is_halted:
-            return
-
-        self._consecutive_failures += 1
-        if (
-            self._max_consecutive_failures is not None
-            and self._consecutive_failures >= self._max_consecutive_failures
-        ):
-            self._halted_reason = "consecutive_failures_limit_breached"
-            dispatch_alert_nowait(
-                self._alert_notifier,
-                category="threshold",
-                severity="critical",
-                title="Consecutive failures limit breached",
-                message="Trading halted because consecutive failures exceeded configured limit.",
-                details={
-                    "consecutive_failures": f"{self._consecutive_failures}",
-                    "max_consecutive_failures": f"{self._max_consecutive_failures}",
-                },
-            )
-
-    def register_success(self) -> None:
-        if self.is_halted:
-            return
-        self._consecutive_failures = 0

build/lib/arbitrade/risk/trade_limits.py

@@ -1,98 +0,0 @@
-from __future__ import annotations
-
-from collections.abc import Mapping
-
-from arbitrade.alerting.notifier import SupportsAlerts, dispatch_alert_nowait
-
-
-class TradeLimitsGuard:
-    def __init__(
-        self,
-        *,
-        max_concurrent_trades: int | None = None,
-        max_exposure_per_asset: float | None = None,
-        alert_notifier: SupportsAlerts | None = None,
-    ) -> None:
-        if max_concurrent_trades is not None and max_concurrent_trades <= 0:
-            raise ValueError("max_concurrent_trades must be > 0")
-        if max_exposure_per_asset is not None and max_exposure_per_asset <= 0.0:
-            raise ValueError("max_exposure_per_asset must be > 0.0")
-
-        self._max_concurrent_trades = max_concurrent_trades
-        self._max_exposure_per_asset = max_exposure_per_asset
-        self._active_trades = 0
-        self._asset_exposure: dict[str, float] = {}
-        self._alert_notifier = alert_notifier
-
-    @property
-    def active_trades(self) -> int:
-        return self._active_trades
-
-    def exposure_for_asset(self, asset: str) -> float:
-        return self._asset_exposure.get(asset.upper(), 0.0)
-
-    def is_trade_allowed(self, exposure_by_asset: Mapping[str, float]) -> bool:
-        if (
-            self._max_concurrent_trades is not None
-            and self._active_trades >= self._max_concurrent_trades
-        ):
-            dispatch_alert_nowait(
-                self._alert_notifier,
-                category="threshold",
-                severity="warning",
-                title="Concurrent trade limit reached",
-                message="Trade rejected by concurrent trade cap.",
-                details={
-                    "active_trades": f"{self._active_trades}",
-                    "max_concurrent_trades": f"{self._max_concurrent_trades}",
-                },
-            )
-            return False
-
-        if self._max_exposure_per_asset is None:
-            return True
-
-        for asset, exposure in exposure_by_asset.items():
-            if exposure <= 0.0:
-                continue
-            key = asset.upper()
-            next_exposure = self._asset_exposure.get(key, 0.0) + exposure
-            if next_exposure > self._max_exposure_per_asset:
-                dispatch_alert_nowait(
-                    self._alert_notifier,
-                    category="threshold",
-                    severity="warning",
-                    title="Asset exposure limit reached",
-                    message="Trade rejected by per-asset exposure cap.",
-                    details={
-                        "asset": key,
-                        "next_exposure": f"{next_exposure}",
-                        "max_exposure_per_asset": f"{self._max_exposure_per_asset}",
-                    },
-                )
-                return False
-
-        return True
-
-    def open_trade(self, exposure_by_asset: Mapping[str, float]) -> None:
-        self._active_trades += 1
-        for asset, exposure in exposure_by_asset.items():
-            if exposure <= 0.0:
-                continue
-            key = asset.upper()
-            self._asset_exposure[key] = self._asset_exposure.get(key, 0.0) + exposure
-
-    def close_trade(self, exposure_by_asset: Mapping[str, float]) -> None:
-        if self._active_trades > 0:
-            self._active_trades -= 1
-
-        for asset, exposure in exposure_by_asset.items():
-            if exposure <= 0.0:
-                continue
-            key = asset.upper()
-            current = self._asset_exposure.get(key, 0.0)
-            next_exposure = max(current - exposure, 0.0)
-            if next_exposure == 0.0:
-                self._asset_exposure.pop(key, None)
-            else:
-                self._asset_exposure[key] = next_exposure

build/lib/arbitrade/runtime/__init__.py

@@ -1,15 +0,0 @@
-"""Runtime lifecycle and recovery helpers."""
-
-from arbitrade.runtime.lifecycle import (
-    RuntimeRecoveryReport,
-    graceful_shutdown,
-    persist_runtime_snapshot,
-    restore_runtime_state,
-)
-
-__all__ = [
-    "RuntimeRecoveryReport",
-    "graceful_shutdown",
-    "persist_runtime_snapshot",
-    "restore_runtime_state",
-]

build/lib/arbitrade/runtime/lifecycle.py

@@ -1,223 +0,0 @@
-from __future__ import annotations
-
-import inspect
-from dataclasses import dataclass
-from datetime import UTC, datetime
-from typing import Any, cast
-
-from fastapi import FastAPI
-
-from arbitrade.api.control_state import DashboardControlState
-from arbitrade.storage.db import DuckDBStore
-from arbitrade.storage.repositories import (
-    AuditRecord,
-    AuditRepository,
-    RuntimeStateRecord,
-    RuntimeStateRepository,
-)
-
-
-@dataclass(slots=True)
-class RuntimeRecoveryReport:
-    restored_from_snapshot: bool
-    snapshot_at: str | None
-    open_trades_detected: int
-    restart_guard_active: bool
-
-
-def _controls(app: FastAPI) -> DashboardControlState:
-    return cast(DashboardControlState, app.state.dashboard_controls)
-
-
-def _store(app: FastAPI) -> DuckDBStore:
-    return cast(DuckDBStore, app.state.store)
-
-
-def _audit_repository(app: FastAPI) -> AuditRepository | None:
-    repository = getattr(app.state, "audit_repository", None)
-    return repository if isinstance(repository, AuditRepository) else None
-
-
-def _runtime_repository(app: FastAPI) -> RuntimeStateRepository | None:
-    repository = getattr(app.state, "runtime_state_repository", None)
-    return repository if isinstance(repository, RuntimeStateRepository) else None
-
-
-def _open_trade_count(store: DuckDBStore) -> int:
-    with store.connect() as conn:
-        row = conn.execute("""
-            SELECT COUNT(*)
-            FROM trades
-            WHERE finished_at IS NULL
-            """).fetchone()
-    return int(row[0]) if row is not None else 0
-
-
-def _latest_balances(store: DuckDBStore) -> dict[str, Any] | None:
-    with store.connect() as conn:
-        row = conn.execute("""
-            SELECT balances
-            FROM portfolio_snapshots
-            ORDER BY snapshot_at DESC
-            LIMIT 1
-            """).fetchone()
-
-    if row is None or row[0] is None:
-        return None
-    raw_balances = row[0]
-    if isinstance(raw_balances, str):
-        return {"raw": raw_balances}
-    return {"raw": str(raw_balances)}
-
-
-def _record_audit(
-    app: FastAPI,
-    *,
-    event_type: str,
-    decision: str,
-    payload: dict[str, Any] | None = None,
-) -> None:
-    repository = _audit_repository(app)
-    if repository is None:
-        return
-    repository.insert(
-        AuditRecord(
-            occurred_at=datetime.now(UTC),
-            actor="runtime",
-            event_type=event_type,
-            decision=decision,
-            payload=payload,
-            correlation_id=None,
-        )
-    )
-
-
-async def _run_startup_reconciler(app: FastAPI) -> None:
-    reconciler = getattr(app.state, "startup_reconciler", None)
-    if reconciler is None:
-        return
-
-    reconcile_member = getattr(reconciler, "reconcile_open_trades", None)
-    if reconcile_member is None or not callable(reconcile_member):
-        return
-
-    result = reconcile_member()
-    if inspect.isawaitable(result):
-        await result
-
-
-def persist_runtime_snapshot(app: FastAPI, *, note: str | None = None) -> RuntimeStateRecord | None:
-    repository = _runtime_repository(app)
-    if repository is None:
-        return None
-
-    controls = _controls(app)
-    store = _store(app)
-    snapshot = RuntimeStateRecord(
-        snapshot_at=datetime.now(UTC),
-        is_running=controls.is_running,
-        kill_switch_active=controls.kill_switch.is_active,
-        kill_switch_reason=controls.kill_switch.reason,
-        open_trade_count=_open_trade_count(store),
-        last_known_balances=_latest_balances(store),
-        note=note,
-    )
-    repository.insert(snapshot)
-    return snapshot
-
-
-async def restore_runtime_state(app: FastAPI) -> RuntimeRecoveryReport:
-    ctl = _controls(app)
-    store = _store(app)
-    repo = _runtime_repository(app)
-
-    restored_from_snapshot = False
-    snapshot_at: str | None = None
-
-    latest = repo.latest() if repo is not None else None
-    if latest is not None:
-        restored_from_snapshot = True
-        snapshot_at = latest.snapshot_at.isoformat()
-        ctl.is_running = latest.is_running
-        if latest.kill_switch_active:
-            r = latest.kill_switch_reason or "recovered"
-            ctl.kill_switch.activate(reason=r)
-        else:
-            ctl.kill_switch.deactivate()
-        ctl.mark_updated()
-
-    open_trades = _open_trade_count(store)
-    restart_guard_active = False
-    if open_trades > 0:
-        ctl.is_running = False
-        if not ctl.kill_switch.is_active:
-            ctl.kill_switch.activate(reason="recovery_open_trades_detected")
-        ctl.mark_updated()
-        restart_guard_active = True
-
-    report = RuntimeRecoveryReport(
-        restored_from_snapshot=restored_from_snapshot,
-        snapshot_at=snapshot_at,
-        open_trades_detected=open_trades,
-        restart_guard_active=restart_guard_active,
-    )
-    app.state.recovery_report = report
-
-    _record_audit(
-        app,
-        event_type="runtime.startup_recovery",
-        decision="applied",
-        payload={
-            "restored_from_snapshot": restored_from_snapshot,
-            "open_trades_detected": open_trades,
-            "restart_guard_active": restart_guard_active,
-        },
-    )
-
-    await _run_startup_reconciler(app)
-
-    return report
-
-
-async def drain_background_workers(app: FastAPI) -> None:
-    workers: list[object] = []
-
-    declared = getattr(app.state, "background_workers", None)
-    if isinstance(declared, list):
-        workers.extend(declared)
-
-    for attr_name in ("execution_writer", "opportunity_writer", "snapshot_writer"):
-        worker = getattr(app.state, attr_name, None)
-        if worker is not None:
-            workers.append(worker)
-
-    seen: set[int] = set()
-    for worker in workers:
-        worker_id = id(worker)
-        if worker_id in seen:
-            continue
-        seen.add(worker_id)
-
-        stop_member = getattr(worker, "stop", None)
-        if stop_member is None or not callable(stop_member):
-            continue
-
-        result = stop_member()
-        if inspect.isawaitable(result):
-            await result
-
-
-async def graceful_shutdown(app: FastAPI) -> None:
-    controls = _controls(app)
-    controls.is_running = False
-    controls.mark_updated()
-
-    _record_audit(
-        app,
-        event_type="runtime.shutdown",
-        decision="initiated",
-        payload={"execution_status": "stopped"},
-    )
-
-    await drain_background_workers(app)
-    persist_runtime_snapshot(app, note="graceful_shutdown")

build/lib/arbitrade/storage/__init__.py

@@ -1 +0,0 @@
-"""Storage helpers."""

build/lib/arbitrade/storage/db.py

@@ -1,128 +0,0 @@
-from __future__ import annotations
-
-from collections.abc import Iterator
-from contextlib import contextmanager
-from pathlib import Path
-
-import duckdb
-import structlog
-
-from arbitrade.config.settings import Settings
-
-_LOG = structlog.get_logger(__name__)
-
-SCHEMA_SQL = """
-CREATE TABLE IF NOT EXISTS schema_migrations (
-    version INTEGER PRIMARY KEY,
-    applied_at TIMESTAMP DEFAULT current_timestamp
-);
-
-CREATE TABLE IF NOT EXISTS opportunities (
-    id UUID DEFAULT uuid(),
-    detected_at TIMESTAMP NOT NULL,
-    cycle VARCHAR NOT NULL,
-    gross_pct DOUBLE,
-    net_pct DOUBLE,
-    est_profit DOUBLE,
-    executed BOOLEAN DEFAULT FALSE
-);
-
-CREATE TABLE IF NOT EXISTS trades (
-    id UUID DEFAULT uuid(),
-    trade_ref VARCHAR NOT NULL,
-    started_at TIMESTAMP NOT NULL,
-    finished_at TIMESTAMP,
-    status VARCHAR NOT NULL,
-    realized_pnl DOUBLE,
-    estimated_pnl DOUBLE,
-    capital_used DOUBLE,
-    cycle VARCHAR,
-    leg_count INTEGER
-);
-
-CREATE TABLE IF NOT EXISTS orders (
-    id UUID DEFAULT uuid(),
-    trade_ref VARCHAR NOT NULL,
-    order_ref VARCHAR NOT NULL,
-    leg_index INTEGER NOT NULL,
-    pair VARCHAR NOT NULL,
-    side VARCHAR NOT NULL,
-    volume DOUBLE NOT NULL,
-    user_ref INTEGER,
-    status VARCHAR,
-    filled_volume DOUBLE,
-    avg_price DOUBLE,
-    raw_response JSON,
-    recorded_at TIMESTAMP NOT NULL
-);
-
-CREATE TABLE IF NOT EXISTS pnl_events (
-    id UUID DEFAULT uuid(),
-    trade_ref VARCHAR NOT NULL,
-    recorded_at TIMESTAMP NOT NULL,
-    kind VARCHAR NOT NULL,
-    pnl_usd DOUBLE NOT NULL,
-    source VARCHAR NOT NULL
-);
-
-CREATE TABLE IF NOT EXISTS portfolio_snapshots (
-    snapshot_at TIMESTAMP NOT NULL,
-    balances JSON,
-    total_value_usd DOUBLE
-);
-
-CREATE TABLE IF NOT EXISTS market_snapshots (
-    snapshot_at TIMESTAMP NOT NULL,
-    symbol VARCHAR NOT NULL,
-    source VARCHAR NOT NULL,
-    payload JSON NOT NULL,
-    latency_ms DOUBLE
-);
-
-CREATE TABLE IF NOT EXISTS audit_events (
-    id UUID DEFAULT uuid(),
-    occurred_at TIMESTAMP NOT NULL,
-    actor VARCHAR NOT NULL,
-    event_type VARCHAR NOT NULL,
-    decision VARCHAR NOT NULL,
-    payload JSON,
-    correlation_id VARCHAR
-);
-
-CREATE TABLE IF NOT EXISTS runtime_state_snapshots (
-    snapshot_at TIMESTAMP NOT NULL,
-    is_running BOOLEAN NOT NULL,
-    kill_switch_active BOOLEAN NOT NULL,
-    kill_switch_reason VARCHAR,
-    open_trade_count INTEGER NOT NULL,
-    last_known_balances JSON,
-    note VARCHAR
-);
-"""
-
-
-class DuckDBStore:
-    def __init__(self, settings: Settings) -> None:
-        self._db_path = Path(settings.duckdb_path)
-        self._db_path.parent.mkdir(parents=True, exist_ok=True)
-        self._use_memory_fallback = False
-
-    @contextmanager
-    def connect(self) -> Iterator[duckdb.DuckDBPyConnection]:
-        try:
-            conn = duckdb.connect(str(self._db_path))
-        except duckdb.IOException:
-            if not self._use_memory_fallback:
-                _LOG.warning(
-                    "duckdb_path_unavailable_falling_back_to_memory", path=str(self._db_path)
-                )
-                self._use_memory_fallback = True
-            conn = duckdb.connect(":memory:")
-        try:
-            yield conn
-        finally:
-            conn.close()
-
-    def migrate(self) -> None:
-        with self.connect() as conn:
-            conn.execute(SCHEMA_SQL)

build/lib/arbitrade/storage/executions.py

@@ -1,66 +0,0 @@
-from __future__ import annotations
-
-import asyncio
-
-import structlog
-
-from arbitrade.storage.repositories import (
-    OrderRecord,
-    OrderRepository,
-    PnLRecord,
-    PnLRepository,
-    TradeRecord,
-    TradeRepository,
-)
-
-_LOG = structlog.get_logger(__name__)
-
-
-class AsyncExecutionWriter:
-    def __init__(
-        self,
-        trade_repository: TradeRepository,
-        order_repository: OrderRepository,
-        pnl_repository: PnLRepository,
-        max_queue_size: int = 50_000,
-    ) -> None:
-        self._trade_repository = trade_repository
-        self._order_repository = order_repository
-        self._pnl_repository = pnl_repository
-        self._queue: asyncio.Queue[TradeRecord | OrderRecord | PnLRecord] = asyncio.Queue(
-            maxsize=max_queue_size
-        )
-        self._task: asyncio.Task[None] | None = None
-        self._stop = asyncio.Event()
-
-    async def start(self) -> None:
-        if self._task is None or self._task.done():
-            self._stop.clear()
-            self._task = asyncio.create_task(self._run(), name="execution-writer")
-
-    async def stop(self) -> None:
-        self._stop.set()
-        if self._task is not None:
-            await self._task
-
-    async def enqueue(self, record: TradeRecord | OrderRecord | PnLRecord) -> None:
-        await self._queue.put(record)
-
-    async def _run(self) -> None:
-        while not (self._stop.is_set() and self._queue.empty()):
-            try:
-                record = await asyncio.wait_for(self._queue.get(), timeout=0.5)
-            except TimeoutError:
-                continue
-
-            try:
-                if isinstance(record, TradeRecord):
-                    self._trade_repository.insert(record)
-                elif isinstance(record, OrderRecord):
-                    self._order_repository.insert(record)
-                else:
-                    self._pnl_repository.insert(record)
-            except Exception as exc:
-                _LOG.error("execution_write_failed", error=str(exc))
-            finally:
-                self._queue.task_done()

build/lib/arbitrade/storage/market_snapshots.py

@@ -1,64 +0,0 @@
-from __future__ import annotations
-
-import asyncio
-from dataclasses import dataclass
-from datetime import datetime
-from typing import Any
-
-import structlog
-
-from arbitrade.storage.repositories import MarketSnapshotRecord, MarketSnapshotRepository
-
-_LOG = structlog.get_logger(__name__)
-
-
-@dataclass(slots=True)
-class MarketSnapshot:
-    snapshot_at: datetime
-    symbol: str
-    source: str
-    payload: dict[str, Any]
-    latency_ms: float | None
-
-
-class AsyncMarketSnapshotWriter:
-    def __init__(self, repository: MarketSnapshotRepository, max_queue_size: int = 50_000) -> None:
-        self._repository = repository
-        self._queue: asyncio.Queue[MarketSnapshot] = asyncio.Queue(maxsize=max_queue_size)
-        self._task: asyncio.Task[None] | None = None
-        self._stop = asyncio.Event()
-
-    async def start(self) -> None:
-        if self._task is None or self._task.done():
-            self._stop.clear()
-            self._task = asyncio.create_task(self._run(), name="market-snapshot-writer")
-
-    async def stop(self) -> None:
-        self._stop.set()
-        if self._task is not None:
-            await self._task
-
-    async def enqueue(self, snapshot: MarketSnapshot) -> None:
-        await self._queue.put(snapshot)
-
-    async def _run(self) -> None:
-        while not (self._stop.is_set() and self._queue.empty()):
-            try:
-                item = await asyncio.wait_for(self._queue.get(), timeout=0.5)
-            except TimeoutError:
-                continue
-
-            try:
-                self._repository.insert(
-                    MarketSnapshotRecord(
-                        snapshot_at=item.snapshot_at,
-                        symbol=item.symbol,
-                        source=item.source,
-                        payload=item.payload,
-                        latency_ms=item.latency_ms,
-                    )
-                )
-            except Exception as exc:
-                _LOG.error("market_snapshot_write_failed", error=str(exc), symbol=item.symbol)
-            finally:
-                self._queue.task_done()

build/lib/arbitrade/storage/opportunities.py

@@ -1,58 +0,0 @@
-from __future__ import annotations
-
-import asyncio
-
-import structlog
-
-from arbitrade.detection.engine import OpportunityEvent
-from arbitrade.storage.repositories import OpportunityRecord, OpportunityRepository
-
-_LOG = structlog.get_logger(__name__)
-
-
-class AsyncOpportunityWriter:
-    def __init__(self, repository: OpportunityRepository, max_queue_size: int = 50_000) -> None:
-        self._repository = repository
-        self._queue: asyncio.Queue[OpportunityEvent] = asyncio.Queue(maxsize=max_queue_size)
-        self._task: asyncio.Task[None] | None = None
-        self._stop = asyncio.Event()
-
-    async def start(self) -> None:
-        if self._task is None or self._task.done():
-            self._stop.clear()
-            self._task = asyncio.create_task(self._run(), name="opportunity-writer")
-
-    async def stop(self) -> None:
-        self._stop.set()
-        if self._task is not None:
-            await self._task
-
-    async def enqueue(self, event: OpportunityEvent) -> None:
-        await self._queue.put(event)
-
-    async def _run(self) -> None:
-        while not (self._stop.is_set() and self._queue.empty()):
-            try:
-                event = await asyncio.wait_for(self._queue.get(), timeout=0.5)
-            except TimeoutError:
-                continue
-
-            try:
-                self._repository.insert(
-                    OpportunityRecord(
-                        detected_at=event.detected_at,
-                        cycle=event.cycle,
-                        gross_pct=event.gross_pct,
-                        net_pct=event.net_pct,
-                        est_profit=event.est_profit,
-                    )
-                )
-            except Exception as exc:
-                _LOG.error(
-                    "opportunity_write_failed",
-                    error=str(exc),
-                    cycle=event.cycle,
-                    updated_pair=event.updated_pair,
-                )
-            finally:
-                self._queue.task_done()

build/lib/arbitrade/storage/repositories.py

@@ -1,378 +0,0 @@
-from __future__ import annotations
-
-from dataclasses import dataclass
-from datetime import datetime
-from typing import Any
-
-import orjson
-
-from arbitrade.storage.db import DuckDBStore
-
-
-@dataclass(slots=True)
-class MarketSnapshotRecord:
-    snapshot_at: datetime
-    symbol: str
-    source: str
-    payload: dict[str, Any]
-    latency_ms: float | None
-
-
-@dataclass(slots=True)
-class OpportunityRecord:
-    detected_at: datetime
-    cycle: str
-    gross_pct: float
-    net_pct: float
-    est_profit: float
-    executed: bool = False
-
-
-@dataclass(slots=True)
-class TradeRecord:
-    trade_ref: str
-    started_at: datetime
-    finished_at: datetime | None
-    status: str
-    realized_pnl: float | None
-    estimated_pnl: float | None
-    capital_used: float | None
-    cycle: str | None = None
-    leg_count: int | None = None
-
-
-@dataclass(slots=True)
-class OrderRecord:
-    trade_ref: str
-    order_ref: str
-    leg_index: int
-    pair: str
-    side: str
-    volume: float
-    user_ref: int | None
-    status: str | None
-    filled_volume: float | None
-    avg_price: float | None
-    raw_response: dict[str, Any]
-    recorded_at: datetime
-
-
-@dataclass(slots=True)
-class PnLRecord:
-    trade_ref: str
-    recorded_at: datetime
-    kind: str
-    pnl_usd: float
-    source: str
-
-
-@dataclass(slots=True)
-class AuditRecord:
-    occurred_at: datetime
-    actor: str
-    event_type: str
-    decision: str
-    payload: dict[str, Any] | None = None
-    correlation_id: str | None = None
-
-
-@dataclass(slots=True)
-class RuntimeStateRecord:
-    snapshot_at: datetime
-    is_running: bool
-    kill_switch_active: bool
-    kill_switch_reason: str | None
-    open_trade_count: int
-    last_known_balances: dict[str, Any] | None = None
-    note: str | None = None
-
-
-class MarketSnapshotRepository:
-    def __init__(self, store: DuckDBStore) -> None:
-        self._store = store
-
-    def insert(self, record: MarketSnapshotRecord) -> None:
-        with self._store.connect() as conn:
-            conn.execute(
-                """
-                INSERT INTO market_snapshots (snapshot_at, symbol, source, payload, latency_ms)
-                VALUES (?, ?, ?, ?, ?)
-                """,
-                [
-                    record.snapshot_at,
-                    record.symbol,
-                    record.source,
-                    orjson.dumps(record.payload).decode("utf-8"),
-                    record.latency_ms,
-                ],
-            )
-
-
-class OpportunityRepository:
-    def __init__(self, store: DuckDBStore) -> None:
-        self._store = store
-
-    def insert(self, record: OpportunityRecord) -> None:
-        with self._store.connect() as conn:
-            conn.execute(
-                """
-                INSERT INTO opportunities (
-                    detected_at,
-                    cycle,
-                    gross_pct,
-                    net_pct,
-                    est_profit,
-                    executed
-                )
-                VALUES (?, ?, ?, ?, ?, ?)
-                """,
-                [
-                    record.detected_at,
-                    record.cycle,
-                    record.gross_pct,
-                    record.net_pct,
-                    record.est_profit,
-                    record.executed,
-                ],
-            )
-
-
-class TradeRepository:
-    def __init__(self, store: DuckDBStore) -> None:
-        self._store = store
-
-    def insert(self, record: TradeRecord) -> None:
-        with self._store.connect() as conn:
-            conn.execute(
-                """
-                INSERT INTO trades (
-                    trade_ref,
-                    started_at,
-                    finished_at,
-                    status,
-                    realized_pnl,
-                    estimated_pnl,
-                    capital_used,
-                    cycle,
-                    leg_count
-                )
-                VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)
-                """,
-                [
-                    record.trade_ref,
-                    record.started_at,
-                    record.finished_at,
-                    record.status,
-                    record.realized_pnl,
-                    record.estimated_pnl,
-                    record.capital_used,
-                    record.cycle,
-                    record.leg_count,
-                ],
-            )
-
-
-class OrderRepository:
-    def __init__(self, store: DuckDBStore) -> None:
-        self._store = store
-
-    def insert(self, record: OrderRecord) -> None:
-        with self._store.connect() as conn:
-            conn.execute(
-                """
-                INSERT INTO orders (
-                    trade_ref,
-                    order_ref,
-                    leg_index,
-                    pair,
-                    side,
-                    volume,
-                    user_ref,
-                    status,
-                    filled_volume,
-                    avg_price,
-                    raw_response,
-                    recorded_at
-                )
-                VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
-                """,
-                [
-                    record.trade_ref,
-                    record.order_ref,
-                    record.leg_index,
-                    record.pair,
-                    record.side,
-                    record.volume,
-                    record.user_ref,
-                    record.status,
-                    record.filled_volume,
-                    record.avg_price,
-                    orjson.dumps(record.raw_response).decode("utf-8"),
-                    record.recorded_at,
-                ],
-            )
-
-
-class PnLRepository:
-    def __init__(self, store: DuckDBStore) -> None:
-        self._store = store
-
-    def insert(self, record: PnLRecord) -> None:
-        with self._store.connect() as conn:
-            conn.execute(
-                """
-                INSERT INTO pnl_events (
-                    trade_ref,
-                    recorded_at,
-                    kind,
-                    pnl_usd,
-                    source
-                )
-                VALUES (?, ?, ?, ?, ?)
-                """,
-                [
-                    record.trade_ref,
-                    record.recorded_at,
-                    record.kind,
-                    record.pnl_usd,
-                    record.source,
-                ],
-            )
-
-
-class AuditRepository:
-    def __init__(self, store: DuckDBStore) -> None:
-        self._store = store
-
-    def insert(self, record: AuditRecord) -> None:
-        with self._store.connect() as conn:
-            conn.execute(
-                """
-                INSERT INTO audit_events (
-                    occurred_at,
-                    actor,
-                    event_type,
-                    decision,
-                    payload,
-                    correlation_id
-                )
-                VALUES (?, ?, ?, ?, ?, ?)
-                """,
-                [
-                    record.occurred_at,
-                    record.actor,
-                    record.event_type,
-                    record.decision,
-                    (
-                        None
-                        if record.payload is None
-                        else orjson.dumps(record.payload).decode("utf-8")
-                    ),
-                    record.correlation_id,
-                ],
-            )
-
-    def list_recent(self, *, limit: int = 25) -> list[AuditRecord]:
-        with self._store.connect() as conn:
-            rows = conn.execute(
-                """
-                SELECT occurred_at, actor, event_type, decision, payload, correlation_id
-                FROM audit_events
-                ORDER BY occurred_at DESC
-                LIMIT ?
-                """,
-                [limit],
-            ).fetchall()
-
-        records: list[AuditRecord] = []
-        for row in rows:
-            payload: dict[str, Any] | None = None
-            raw_payload = row[4]
-            if isinstance(raw_payload, str) and raw_payload:
-                decoded = orjson.loads(raw_payload)
-                if isinstance(decoded, dict):
-                    payload = {str(k): decoded[k] for k in decoded}
-
-            records.append(
-                AuditRecord(
-                    occurred_at=row[0],
-                    actor=str(row[1]),
-                    event_type=str(row[2]),
-                    decision=str(row[3]),
-                    payload=payload,
-                    correlation_id=str(row[5]) if row[5] is not None else None,
-                )
-            )
-
-        return records
-
-
-class RuntimeStateRepository:
-    def __init__(self, store: DuckDBStore) -> None:
-        self._store = store
-
-    def insert(self, record: RuntimeStateRecord) -> None:
-        with self._store.connect() as conn:
-            conn.execute(
-                """
-                INSERT INTO runtime_state_snapshots (
-                    snapshot_at,
-                    is_running,
-                    kill_switch_active,
-                    kill_switch_reason,
-                    open_trade_count,
-                    last_known_balances,
-                    note
-                )
-                VALUES (?, ?, ?, ?, ?, ?, ?)
-                """,
-                [
-                    record.snapshot_at,
-                    record.is_running,
-                    record.kill_switch_active,
-                    record.kill_switch_reason,
-                    record.open_trade_count,
-                    (
-                        None
-                        if record.last_known_balances is None
-                        else orjson.dumps(record.last_known_balances).decode("utf-8")
-                    ),
-                    record.note,
-                ],
-            )
-
-    def latest(self) -> RuntimeStateRecord | None:
-        with self._store.connect() as conn:
-            row = conn.execute("""
-                SELECT
-                    snapshot_at,
-                    is_running,
-                    kill_switch_active,
-                    kill_switch_reason,
-                    open_trade_count,
-                    last_known_balances,
-                    note
-                FROM runtime_state_snapshots
-                ORDER BY snapshot_at DESC
-                LIMIT 1
-                """).fetchone()
-
-        if row is None:
-            return None
-
-        balances: dict[str, Any] | None = None
-        raw_balances = row[5]
-        if isinstance(raw_balances, str) and raw_balances:
-            decoded = orjson.loads(raw_balances)
-            if isinstance(decoded, dict):
-                balances = {str(key): decoded[key] for key in decoded}
-
-        return RuntimeStateRecord(
-            snapshot_at=row[0],
-            is_running=bool(row[1]),
-            kill_switch_active=bool(row[2]),
-            kill_switch_reason=str(row[3]) if row[3] is not None else None,
-            open_trade_count=int(row[4]),
-            last_known_balances=balances,
-            note=str(row[6]) if row[6] is not None else None,
-        )

build/lib/arbitrade/strategy/__init__.py

@@ -1,5 +0,0 @@
-"""Experimental strategy modules."""
-
-from arbitrade.strategy.stat_arb import StatArbExperiment, StatArbExperimentConfig, StatArbSignal
-
-__all__ = ["StatArbExperiment", "StatArbExperimentConfig", "StatArbSignal"]

build/lib/arbitrade/strategy/stat_arb.py

@@ -1,152 +0,0 @@
-from __future__ import annotations
-
-from collections import deque
-from dataclasses import dataclass
-from datetime import UTC, datetime
-from statistics import fmean, pstdev
-from typing import Literal
-
-
-@dataclass(frozen=True, slots=True)
-class StatArbExperimentConfig:
-    pair_a: str
-    pair_b: str
-    lookback_window: int = 120
-    entry_zscore: float = 2.0
-    exit_zscore: float = 0.5
-    max_holding_seconds: float = 900.0
-
-
-@dataclass(frozen=True, slots=True)
-class StatArbSignal:
-    action: Literal[
-        "warmup",
-        "hold",
-        "enter_long_spread",
-        "enter_short_spread",
-        "exit_position",
-    ]
-    observed_at: datetime
-    spread: float
-    zscore: float | None
-    position: Literal["long", "short", "flat"]
-
-
-class StatArbExperiment:
-    """Simple mean-reversion experiment scaffold behind feature flags."""
-
-    def __init__(self, config: StatArbExperimentConfig) -> None:
-        if config.lookback_window < 2:
-            raise ValueError("lookback_window must be >= 2")
-        if config.entry_zscore <= 0.0:
-            raise ValueError("entry_zscore must be > 0")
-        if config.exit_zscore < 0.0:
-            raise ValueError("exit_zscore must be >= 0")
-        if config.entry_zscore <= config.exit_zscore:
-            raise ValueError("entry_zscore must be > exit_zscore")
-        if config.max_holding_seconds <= 0.0:
-            raise ValueError("max_holding_seconds must be > 0")
-
-        self._config = config
-        self._spreads: deque[float] = deque(maxlen=config.lookback_window)
-        self._position: Literal["long", "short", "flat"] = "flat"
-        self._position_opened_at: datetime | None = None
-
-    @property
-    def config(self) -> StatArbExperimentConfig:
-        return self._config
-
-    def reset(self) -> None:
-        self._spreads.clear()
-        self._position = "flat"
-        self._position_opened_at = None
-
-    def observe(
-        self,
-        *,
-        price_a: float,
-        price_b: float,
-        observed_at: datetime,
-    ) -> StatArbSignal:
-        if price_a <= 0.0 or price_b <= 0.0:
-            raise ValueError("prices must be > 0")
-
-        at = observed_at.astimezone(UTC)
-        spread = price_a - price_b
-        self._spreads.append(spread)
-
-        if len(self._spreads) < self._config.lookback_window:
-            return StatArbSignal(
-                action="warmup",
-                observed_at=at,
-                spread=spread,
-                zscore=None,
-                position=self._position,
-            )
-
-        mean_spread = fmean(self._spreads)
-        std_spread = pstdev(self._spreads)
-        if std_spread == 0.0:
-            return StatArbSignal(
-                action="hold",
-                observed_at=at,
-                spread=spread,
-                zscore=0.0,
-                position=self._position,
-            )
-
-        zscore = (spread - mean_spread) / std_spread
-
-        if self._position == "flat":
-            if zscore >= self._config.entry_zscore:
-                self._position = "short"
-                self._position_opened_at = at
-                return StatArbSignal(
-                    action="enter_short_spread",
-                    observed_at=at,
-                    spread=spread,
-                    zscore=zscore,
-                    position=self._position,
-                )
-            if zscore <= -self._config.entry_zscore:
-                self._position = "long"
-                self._position_opened_at = at
-                return StatArbSignal(
-                    action="enter_long_spread",
-                    observed_at=at,
-                    spread=spread,
-                    zscore=zscore,
-                    position=self._position,
-                )
-            return StatArbSignal(
-                action="hold",
-                observed_at=at,
-                spread=spread,
-                zscore=zscore,
-                position=self._position,
-            )
-
-        assert self._position_opened_at is not None
-        held_seconds = (at - self._position_opened_at).total_seconds()
-        should_exit = abs(zscore) <= self._config.exit_zscore
-        if held_seconds >= self._config.max_holding_seconds:
-            should_exit = True
-
-        if should_exit:
-            self._position = "flat"
-            self._position_opened_at = None
-            return StatArbSignal(
-                action="exit_position",
-                observed_at=at,
-                spread=spread,
-                zscore=zscore,
-                position=self._position,
-            )
-
-        return StatArbSignal(
-            action="hold",
-            observed_at=at,
-            spread=spread,
-            zscore=zscore,
-            position=self._position,
-        )

build/lib/arbitrade/web/templates/backtesting.html

@@ -1,24 +0,0 @@
-{% extends "base.html" %} {% block title %}{{ title }}{% endblock %} {% block
-content %}
-<section class="hero">
-  <div>
-    <h1 class="title">Backtesting</h1>
-    <p class="subtitle">
-      Replay controls, run status, and recent summary reports.
-    </p>
-  </div>
-  <div class="toolbar">
-    <a class="button secondary" href="{{ dashboard_endpoint }}">Dashboard</a>
-  </div>
-</section>
-
-<section
-  id="backtesting-shell"
-  hx-get="{{ panel_endpoint }}"
-  hx-target="this"
-  hx-trigger="load"
-  hx-swap="outerHTML"
->
-  {% include "partials/backtesting_panel.html" %}
-</section>
-{% endblock %}

build/lib/arbitrade/web/templates/dashboard.html

@@ -1,180 +0,0 @@
-{% extends "base.html" %} {% block title %}{{ title }}{% endblock %} {% block
-head_scripts %}
-<script defer src="https://unpkg.com/alpinejs@3.x.x/dist/cdn.min.js"></script>
-<script src="https://cdn.jsdelivr.net/npm/chart.js@4.4.3/dist/chart.umd.min.js"></script>
-{% endblock %} {% block main_class %}shell{% endblock %} {% block content %}
-<section class="hero">
-  <div>
-    <h1 class="title">Arbitrade Dashboard</h1>
-    <p class="subtitle">Live execution, P&amp;L, and system state.</p>
-  </div>
-  <div class="toolbar">
-    <a
-      class="button"
-      href="{{ metrics_endpoint }}"
-      hx-get="{{ metrics_endpoint }}"
-      hx-target="#metrics-panel"
-      hx-swap="outerHTML"
-      >Refresh metrics</a
-    >
-    <a class="button secondary" href="/health">Health</a>
-    <a class="button secondary" href="/dashboard/backtesting">Backtesting</a>
-  </div>
-</section>
-
-<section
-  id="metrics-shell"
-  hx-get="{{ metrics_endpoint }}"
-  hx-target="this"
-  hx-trigger="load, every 15s"
-  hx-swap="outerHTML"
->
-  {% include "partials/metrics.html" %}
-</section>
-
-<section
-  id="overview-shell"
-  hx-get="{{ overview_endpoint }}"
-  hx-target="this"
-  hx-trigger="load, every 10s"
-  hx-swap="outerHTML"
->
-  {% include "partials/overview.html" %}
-</section>
-
-<section
-  id="controls-shell"
-  hx-get="{{ controls_endpoint }}"
-  hx-target="this"
-  hx-trigger="load, every 20s"
-  hx-swap="outerHTML"
->
-  {% include "partials/controls.html" %}
-</section>
-
-<section
-  id="charts-shell"
-  hx-get="{{ charts_endpoint }}"
-  hx-target="this"
-  hx-trigger="load, every 30s"
-  hx-swap="outerHTML"
->
-  {% include "partials/charts.html" %}
-</section>
-
-<section
-  id="audit-shell"
-  hx-get="{{ audit_endpoint }}"
-  hx-target="this"
-  hx-trigger="load, every 20s"
-  hx-swap="outerHTML"
->
-  {% include "partials/audit.html" %}
-</section>
-{% endblock %} {% block scripts %}
-<script>
-  window.arbitradeRenderCharts = (payload) => {
-    const chartHost = document.getElementById("opportunity-chart");
-    if (!chartHost || typeof Chart === "undefined") {
-      return;
-    }
-
-    const existing = Chart.getChart(chartHost);
-    if (existing) {
-      existing.destroy();
-    }
-
-    const data = JSON.parse(payload);
-    if (!data.has_chart_data) {
-      return;
-    }
-
-    new Chart(chartHost, {
-      type: "line",
-      data: {
-        labels: data.labels,
-        datasets: [
-          {
-            label: "Net %",
-            data: data.net_pct_values,
-            borderColor: "#2d6cdf",
-            backgroundColor: "rgba(45, 108, 223, 0.18)",
-            tension: 0.3,
-            fill: true,
-            yAxisID: "y",
-          },
-          {
-            label: "Est profit USD",
-            data: data.est_profit_values,
-            borderColor: "#52c41a",
-            backgroundColor: "rgba(82, 196, 26, 0.12)",
-            tension: 0.3,
-            fill: false,
-            yAxisID: "y1",
-          },
-        ],
-      },
-      options: {
-        responsive: true,
-        maintainAspectRatio: false,
-        interaction: {
-          mode: "index",
-          intersect: false,
-        },
-        plugins: {
-          legend: {
-            labels: {
-              color: "#e5eefb",
-            },
-          },
-        },
-        scales: {
-          x: {
-            ticks: {
-              color: "#9fb2d0",
-              maxRotation: 0,
-              autoSkip: true,
-            },
-            grid: {
-              color: "rgba(255, 255, 255, 0.06)",
-            },
-          },
-          y: {
-            position: "left",
-            ticks: {
-              color: "#9fb2d0",
-            },
-            grid: {
-              color: "rgba(255, 255, 255, 0.06)",
-            },
-          },
-          y1: {
-            position: "right",
-            ticks: {
-              color: "#9fb2d0",
-            },
-            grid: {
-              drawOnChartArea: false,
-            },
-          },
-        },
-      },
-    });
-  };
-
-  const stream = new EventSource("{{ stream_endpoint }}");
-  stream.addEventListener("metrics", (event) => {
-    const panel = document.getElementById("metrics-panel");
-    if (panel) {
-      panel.outerHTML = JSON.parse(event.data);
-    }
-  });
-  const overviewStream = new EventSource("{{ overview_stream_endpoint }}");
-  overviewStream.addEventListener("overview", (event) => {
-    const panel = document.getElementById("overview-panel");
-    if (panel) {
-      panel.outerHTML = JSON.parse(event.data);
-    }
-  });
-</script>
-{% endblock %}

build/lib/arbitrade/web/templates/health.html

@@ -1,14 +0,0 @@
-{% extends "base.html" %}
-
-{% block content %}
-  <section class="card">
-    <h1>Arbitrade Bootstrap Complete</h1>
-    <p><span class="badge">Status: {{ status }}</span></p>
-    <p>UTC: {{ time }}</p>
-    <p>
-      Health JSON:
-      <a href="/health" hx-get="/health" hx-target="#health-json" hx-swap="innerHTML">refresh</a>
-    </p>
-    <pre id="health-json">{"status":"ok","service":"arbitrade"}</pre>
-  </section>
-{% endblock %}

build/lib/arbitrade/web/templates/partials/audit.html

@@ -1,37 +0,0 @@
-<div id="audit-panel" class="panel" style="margin-top: 16px">
-  <div class="label">Audit Trail</div>
-  <div class="meta">Generated {{ generated_at }}</div>
-
-  <div style="overflow-x: auto; margin-top: 12px">
-    <table style="width: 100%; border-collapse: collapse; font-size: 0.9rem">
-      <thead>
-        <tr>
-          <th style="text-align: left; padding: 8px">Time</th>
-          <th style="text-align: left; padding: 8px">Actor</th>
-          <th style="text-align: left; padding: 8px">Event</th>
-          <th style="text-align: left; padding: 8px">Decision</th>
-          <th style="text-align: left; padding: 8px">Payload</th>
-          <th style="text-align: left; padding: 8px">Correlation</th>
-        </tr>
-      </thead>
-      <tbody>
-        {% if entries %}
-        {% for entry in entries %}
-        <tr>
-          <td style="padding: 8px; color: #9fb2d0">{{ entry.occurred_at }}</td>
-          <td style="padding: 8px">{{ entry.actor }}</td>
-          <td style="padding: 8px">{{ entry.event_type }}</td>
-          <td style="padding: 8px">{{ entry.decision }}</td>
-          <td style="padding: 8px; color: #9fb2d0">{{ entry.payload }}</td>
-          <td style="padding: 8px; color: #9fb2d0">{{ entry.correlation_id }}</td>
-        </tr>
-        {% endfor %}
-        {% else %}
-        <tr>
-          <td colspan="6" style="padding: 8px; color: #9fb2d0">No audit entries yet.</td>
-        </tr>
-        {% endif %}
-      </tbody>
-    </table>
-  </div>
-</div>

build/lib/arbitrade/web/templates/partials/backtesting_panel.html

@@ -1,142 +0,0 @@
-<div id="backtesting-shell" class="panel">
-  <div
-    class="grid"
-    style="grid-template-columns: repeat(auto-fit, minmax(280px, 1fr))"
-  >
-    <article class="card">
-      <div class="label">Run Status</div>
-      <div class="value">{{ status }}</div>
-      <div class="meta">{{ message }}</div>
-    </article>
-    <article class="card">
-      <div class="label">Latest Report</div>
-      {% if latest_report %}
-      <div class="meta">Run at {{ latest_report.run_at }}</div>
-      <div class="meta">Events: {{ latest_report.events_path }}</div>
-      <div class="meta">
-        Processed: {{ latest_report.report.processed_events }}
-      </div>
-      <div class="meta">
-        Opportunities: {{ latest_report.report.opportunities_seen }}
-      </div>
-      <div class="meta">Trades: {{ latest_report.report.trades_executed }}</div>
-      <div class="meta">
-        Realized P&amp;L: {{
-        '%.4f'|format(latest_report.report.realized_pnl_usd) }} USD
-      </div>
-      <div class="meta">
-        Max drawdown: {{ '%.4f'|format(latest_report.report.max_drawdown_usd) }}
-        USD
-      </div>
-      {% else %}
-      <div class="meta">No runs yet.</div>
-      {% endif %}
-    </article>
-  </div>
-
-  <article class="card" style="margin-top: 16px">
-    <div class="label">Run Backtest</div>
-    <form
-      class="form-grid"
-      hx-post="{{ run_endpoint }}"
-      hx-target="#backtesting-shell"
-      hx-swap="outerHTML"
-    >
-      <label class="field">
-        <span>Replay events path (JSONL)</span>
-        <input
-          name="events_path"
-          type="text"
-          value="{{ events_path }}"
-          placeholder="data/replay.jsonl"
-        />
-      </label>
-      <label class="field">
-        <span>Starting balances</span>
-        <input
-          name="starting_balances"
-          type="text"
-          value="{{ starting_balances }}"
-          placeholder="USD=1000.0,BTC=0.0"
-        />
-      </label>
-      <label class="field">
-        <span>Trade capital</span>
-        <input
-          name="trade_capital"
-          type="number"
-          min="0"
-          step="0.01"
-          value="{{ trade_capital }}"
-        />
-      </label>
-      <label class="field">
-        <span>Min profit threshold</span>
-        <input
-          name="min_profit_threshold"
-          type="number"
-          min="0"
-          step="0.0001"
-          value="{{ min_profit_threshold }}"
-        />
-      </label>
-      <label class="field">
-        <span>Fee profile</span>
-        <select name="fee_profile">
-          {% set sel = "selected" if fee_profile == "standard" else "" %}
-          <option value="standard" {{ sel }}>standard</option>
-          {% set sel = "selected" if fee_profile == "maker_heavy" else "" %}
-          <option value="maker_heavy" {{ sel }}>maker_heavy</option>
-          {% set sel = "selected" if fee_profile == "taker_heavy" else "" %}
-          <option value="taker_heavy" {{ sel }}>taker_heavy</option>
-          {% set sel = "selected" if fee_profile == "custom" else "" %}
-          <option value="custom" {{ sel }}>custom</option>
-        </select>
-      </label>
-      <label class="field">
-        <span>Custom fee rate (if fee profile = custom)</span>
-        <input
-          name="custom_fee_rate"
-          type="number"
-          min="0"
-          step="0.0001"
-          value="{{ custom_fee_rate }}"
-        />
-      </label>
-      <label class="field">
-        <span>Slippage (bps)</span>
-        <input
-          name="slippage_bps"
-          type="number"
-          min="0"
-          step="0.1"
-          value="{{ slippage_bps }}"
-        />
-      </label>
-      <label class="field">
-        <span>Execution latency (ms)</span>
-        <input
-          name="execution_latency_ms"
-          type="number"
-          min="0"
-          step="0.1"
-          value="{{ execution_latency_ms }}"
-        />
-      </label>
-      <button type="submit" class="button">Run backtest</button>
-    </form>
-  </article>
-
-  <article class="card" style="margin-top: 16px">
-    <div class="label">Recent Runs</div>
-    {% if recent_reports %} {% for item in recent_reports %}
-    <div class="meta">
-      {{ item.run_at }} | {{ item.events_path }} | trades={{
-      item.report.trades_executed }} | pnl={{
-      '%.4f'|format(item.report.realized_pnl_usd) }} USD
-    </div>
-    {% endfor %} {% else %}
-    <div class="meta">No recent reports yet.</div>
-    {% endif %}
-  </article>
-</div>

build/lib/arbitrade/web/templates/partials/charts.html

@@ -1,37 +0,0 @@
-<div
-  id="charts-panel"
-  class="panel"
-  style="margin-top: 16px"
-  x-data="{ expanded: true }"
->
-  <div class="chart-head">
-    <div>
-      <div class="label">Opportunity Trend</div>
-      <div class="meta">Recent opportunities from DuckDB. Updated {{ generated_at }}</div>
-    </div>
-    <button type="button" class="button secondary" x-on:click="expanded = !expanded">
-      <span x-text="expanded ? 'Hide chart' : 'Show chart'"></span>
-    </button>
-  </div>
-
-  <div x-show="expanded" x-transition style="margin-top: 16px">
-    <div class="card" style="padding: 12px">
-      {% if has_chart_data %}
-      <canvas id="opportunity-chart" class="chart-canvas"></canvas>
-      <script>
-        window.arbitradeRenderCharts(
-          {{ {
-            "has_chart_data": has_chart_data,
-            "labels": labels,
-            "net_pct_values": net_pct_values,
-            "est_profit_values": est_profit_values,
-            "cycles": cycles,
-          } | tojson }}
-        );
-      </script>
-      {% else %}
-      <div class="meta">No opportunity data yet.</div>
-      {% endif %}
-    </div>
-  </div>
-</div>

build/lib/arbitrade/web/templates/partials/controls.html

@@ -1,171 +0,0 @@
-<div id="controls-panel" class="panel" style="margin-top: 16px">
-  <div class="grid">
-    <article class="card">
-      <div class="label">Runtime Status</div>
-      <div class="value">{{ execution_status }}</div>
-      <div class="meta">Updated {{ updated_at }}</div>
-    </article>
-    <article class="card">
-      <div class="label">Kill Switch</div>
-      <div class="value">{{ kill_switch_status }}</div>
-      <div class="meta">Reason {{ kill_switch_reason }}</div>
-    </article>
-    <article class="card">
-      <div class="label">Config Snapshot</div>
-      <div class="meta">Paper trading: {{ paper_trading_mode }}</div>
-      <div class="meta">Trade capital: {{ trade_capital_usd }}</div>
-      <div class="meta">Max trade capital: {{ max_trade_capital_usd }}</div>
-      <div class="meta">Max concurrent trades: {{ max_concurrent_trades }}</div>
-      <div class="meta">Tradable pairs: {{ tradable_pairs_display }}</div>
-      <div class="meta">Strategy mode: {{ strategy_mode }}</div>
-      <div class="meta">Profit threshold: {{ strategy_profit_threshold }}</div>
-      <div class="meta">Max depth levels: {{ strategy_max_depth_levels }}</div>
-    </article>
-    <article class="card">
-      <div class="label">Alerting</div>
-      <div class="meta">Status: {{ alerts_enabled }}</div>
-      <div class="meta">Channels: {{ alerts_channels }}</div>
-      <div class="meta">Min severity: {{ alerts_min_severity }}</div>
-      <div class="meta">Dedup window: {{ alerts_dedup_seconds }}s</div>
-      <div class="meta">Last result: {{ alerts_last_result }}</div>
-      <div class="meta">Last attempted: {{ alerts_last_attempted_at }}</div>
-      <div class="meta">Last success: {{ alerts_last_success_at }}</div>
-      <div class="meta">Last event: {{ alerts_last_event_title }}</div>
-      <div class="meta">Last error: {{ alerts_last_error }}</div>
-      {% if alerts_last_channel_results %} {% for item in
-      alerts_last_channel_results %}
-      <div class="meta">{{ item }}</div>
-      {% endfor %} {% endif %}
-    </article>
-  </div>
-
-  <div
-    class="grid"
-    style="
-      margin-top: 16px;
-      grid-template-columns: repeat(auto-fit, minmax(260px, 1fr));
-    "
-  >
-    <article class="card">
-      <div class="label">Execution Controls</div>
-      <div class="control-actions">
-        <form
-          hx-post="{{ start_endpoint }}"
-          hx-target="#controls-panel"
-          hx-swap="outerHTML"
-        >
-          <button type="submit" class="button">Start</button>
-        </form>
-        <form
-          hx-post="{{ stop_endpoint }}"
-          hx-target="#controls-panel"
-          hx-swap="outerHTML"
-        >
-          <button type="submit" class="button secondary">Stop</button>
-        </form>
-        <form
-          hx-post="{{ kill_switch_endpoint }}"
-          hx-target="#controls-panel"
-          hx-swap="outerHTML"
-        >
-          <input type="hidden" name="reason" value="manual" />
-          <button type="submit" class="button danger">
-            Trigger Kill Switch
-          </button>
-        </form>
-      </div>
-    </article>
-    <article class="card">
-      <div class="label">Edit Config</div>
-      <form
-        class="form-grid"
-        hx-post="{{ config_endpoint }}"
-        hx-target="#controls-panel"
-        hx-swap="outerHTML"
-      >
-        <label class="field">
-          <span>Trade capital USD</span>
-          <input
-            name="trade_capital_usd"
-            type="number"
-            min="0"
-            step="0.01"
-            value="{{ trade_capital_usd_value }}"
-          />
-        </label>
-        <label class="field">
-          <span>Max trade capital USD</span>
-          <input
-            name="max_trade_capital_usd"
-            type="number"
-            min="0"
-            step="0.01"
-            value="{{ max_trade_capital_usd_value }}"
-          />
-        </label>
-        <label class="field">
-          <span>Max concurrent trades</span>
-          <input
-            name="max_concurrent_trades"
-            type="number"
-            min="1"
-            step="1"
-            value="{{ max_concurrent_trades_value }}"
-          />
-        </label>
-        <label class="field">
-          <span>Tradable pairs</span>
-          <input
-            name="tradable_pairs"
-            type="text"
-            placeholder="BTC/USD, ETH/BTC"
-            value="{{ tradable_pairs_value }}"
-          />
-        </label>
-        <label class="field">
-          <span>Strategy mode</span>
-          <select name="strategy_mode">
-            {% set sel = "selected" if strategy_mode == "incremental" else "" %}
-            <option value="incremental" {{ sel }}>incremental</option>
-            {% set sel = "selected" if strategy_mode == "paper" else "" %}
-            <option value="paper" {{ sel }}>paper</option>
-            {% set sel = "selected" if strategy_mode == "live" else "" %}
-            <option value="live" {{ sel }}>live</option>
-            {% if strategy_stat_arb_enabled %} {% set sel = "selected" if
-            strategy_mode == "stat_arb_experiment" else "" %}
-            <option value="stat_arb_experiment" {{ sel }}>
-              stat_arb_experiment
-            </option>
-            {% endif %}
-          </select>
-        </label>
-        <label class="field">
-          <span>Strategy profit threshold</span>
-          <input
-            name="strategy_profit_threshold"
-            type="number"
-            min="0"
-            step="0.0001"
-            value="{{ strategy_profit_threshold }}"
-          />
-        </label>
-        <label class="field">
-          <span>Max depth levels</span>
-          <input
-            name="strategy_max_depth_levels"
-            type="number"
-            min="1"
-            step="1"
-            value="{{ strategy_max_depth_levels }}"
-          />
-        </label>
-        <label class="field checkbox">
-          {% set check = "checked" if paper_trading_mode == "enabled" else "" %}
-          <input name="paper_trading_mode" type="checkbox" {{ check }} />
-          <span>Paper trading mode</span>
-        </label>
-        <button type="submit" class="button">Save config</button>
-      </form>
-    </article>
-  </div>
-</div>

build/lib/arbitrade/web/templates/partials/metrics.html

@@ -1,31 +0,0 @@
-<div id="metrics-panel" class="panel">
-  <div class="grid">
-    <article class="card">
-      <div class="label">Realized P&amp;L</div>
-      <div class="value">{{ realized_pnl }}</div>
-    </article>
-    <article class="card">
-      <div class="label">Win Rate</div>
-      <div class="value">{{ win_rate }}</div>
-    </article>
-    <article class="card">
-      <div class="label">Avg Trade Duration</div>
-      <div class="value">{{ avg_trade_duration }}</div>
-    </article>
-    <article class="card">
-      <div class="label">Opportunities / Min</div>
-      <div class="value">{{ opportunities_per_minute }}</div>
-    </article>
-    <article class="card">
-      <div class="label">Fill Rate</div>
-      <div class="value">{{ fill_rate }}</div>
-    </article>
-    <article class="card">
-      <div class="label">Latency p50 / p95 / p99</div>
-      <div class="value">
-        {{ latency_p50 }} | {{ latency_p95 }} | {{ latency_p99 }}
-      </div>
-    </article>
-  </div>
-  <div class="meta">Updated {{ generated_at }}</div>
-</div>

build/lib/arbitrade/web/templates/partials/overview.html

@@ -1,67 +0,0 @@
-<div id="overview-panel" class="panel" style="margin-top: 16px">
-  <div class="grid">
-    <article class="card">
-      <div class="label">Status</div>
-      <div class="value">{{ status }}</div>
-    </article>
-    <article class="card">
-      <div class="label">Balances</div>
-      <div class="value">{{ balances }}</div>
-    </article>
-    <article class="card">
-      <div class="label">Open Trades</div>
-      <div class="value">{{ open_trade_count }}</div>
-    </article>
-    <article class="card">
-      <div class="label">Realized P&amp;L</div>
-      <div class="value">{{ realized_pnl_total }}</div>
-    </article>
-  </div>
-
-  <div
-    class="grid"
-    style="
-      margin-top: 16px;
-      grid-template-columns: repeat(auto-fit, minmax(260px, 1fr));
-    "
-  >
-    <article class="card">
-      <div class="label">Open Trades</div>
-      <ul>
-        {% for trade in open_trades %}
-        <li>
-          {{ trade.trade_ref }} - {{ trade.status }} - {{ trade.cycle }} - {{
-          trade.started_at }}
-        </li>
-        {% else %}
-        <li>No open trades.</li>
-        {% endfor %}
-      </ul>
-    </article>
-    <article class="card">
-      <div class="label">Balances Snapshot</div>
-      <div
-        class="value"
-        style="font-size: 1rem; font-weight: 500; word-break: break-word"
-      >
-        {{ balances }}
-      </div>
-      <div class="meta">Total value {{ total_value }}</div>
-    </article>
-    <article class="card">
-      <div class="label">Opportunity Feed</div>
-      <ul>
-        {% for opp in opportunities %}
-        <li>
-          {{ opp.cycle }} - {{ opp.net_pct }} - {{ opp.est_profit }} - {{
-          opp.detected_at }}
-        </li>
-        {% else %}
-        <li>No opportunities.</li>
-        {% endfor %}
-      </ul>
-    </article>
-  </div>
-
-  <div class="meta">Updated {{ generated_at }}</div>
-</div>

docs/DEPLOYMENT.md

@@ -7,16 +7,16 @@ This guide provides two supported deployment paths for Arbitrade on Coolify:
 
 Reference docs:
 
-- Coolify Applications: https://coolify.io/docs/applications
-- Coolify Build Packs: https://coolify.io/docs/applications/build-packs
-- Coolify Dockerfile Build Pack: https://coolify.io/docs/applications/build-packs/dockerfile
-- Coolify Nixpacks Build Pack: https://coolify.io/docs/applications/build-packs/nixpacks
-- Coolify CI/CD (Git providers): https://coolify.io/docs/applications/ci-cd
-- Coolify Gitea integration: https://coolify.io/docs/applications/ci-cd/gitea/integration
-- Coolify environment variables: https://coolify.io/docs/knowledge-base/environment-variables
-- Coolify persistent storage: https://coolify.io/docs/knowledge-base/persistent-storage
-- Coolify health checks: https://coolify.io/docs/knowledge-base/health-checks
-- Coolify Docker registry credentials: https://coolify.io/docs/knowledge-base/docker/registry
+- [Coolify Applications](https://coolify.io/docs/applications)
+- [Coolify Build Packs](https://coolify.io/docs/applications/build-packs)
+- [Coolify Dockerfile Build Pack](https://coolify.io/docs/applications/build-packs/dockerfile)
+- [Coolify Nixpacks Build Pack](https://coolify.io/docs/applications/build-packs/nixpacks)
+- [Coolify CI/CD (Git providers)](https://coolify.io/docs/applications/ci-cd)
+- [Coolify Gitea integration](https://coolify.io/docs/applications/ci-cd/gitea/integration)
+- [Coolify environment variables](https://coolify.io/docs/knowledge-base/environment-variables)
+- [Coolify persistent storage](https://coolify.io/docs/knowledge-base/persistent-storage)
+- [Coolify health checks](https://coolify.io/docs/knowledge-base/health-checks)
+- [Coolify Docker registry credentials](https://coolify.io/docs/knowledge-base/docker/registry)
 
 ## Common Runtime Configuration
 
@@ -32,14 +32,14 @@ Use these values in both deployment modes.
 
 - Add a persistent volume
 - Mount path: `/app/data`
-- Set DB path to: `DUCKDB_PATH=/app/data/arbitrade.duckdb`
+- Set PG connection: `PG_HOST=postgres`, `PG_PORT=5432`, `PG_DATABASE=arbitrade`, `PG_USER=arbitrade`, `PG_PASSWORD=arbitrade`
 
 ### Required environment variables
 
 - `APP_ENV=prod`
 - `APP_HOST=0.0.0.0`
 - `APP_PORT=9090`
-- `DUCKDB_PATH=/app/data/arbitrade.duckdb`
+- `PG_DATABASE=arbitrade`
 - `LOG_LEVEL=INFO`
 - `LOG_JSON=true`
 - `KRAKEN_API_KEY=<set-in-coolify-secret>`
@@ -58,39 +58,32 @@ Recommended when you want Coolify to build from source and optionally auto-deplo
 
 1. Open your Coolify project and select Create New Resource.
 2. Choose deployment source:
-
    - Public repo: use `Public repository` and provide HTTPS URL.
    - Private Gitea repo: use deploy key flow from the Gitea guide.
 
 3. Set repository URL for this project:
-
    - `https://git.allucanget.biz/allucanget/arbitrade.git` (public)
    - or SSH URL if private deploy key is used.
 
 4. Choose build pack:
-
    - Prefer `Dockerfile` for this repo, because Docker build behavior is explicitly defined.
    - Use `Nixpacks` only if you intentionally want auto-detected build logic.
 
 5. Configure branch and base directory:
-
    - Branch: your deploy branch (for example `main`)
    - Base directory: `/`
 
 6. Configure network:
-
    - Exposed port: `9090`
    - Domain: set your Coolify domain/custom domain
 
 7. Configure environment variables and secrets from the Common Runtime Configuration section.
 8. Add persistent storage mount `/app/data`.
 9. Configure health check:
-
    - Path: `/health`
    - Ensure container includes `curl` or `wget` if using UI-defined checks.
 
 10. Click Deploy and verify:
-
     - Deployment logs complete successfully.
     - `GET /health` returns success.
 
@@ -113,21 +106,18 @@ Image:
 2. In Coolify, select Create New Resource.
 3. Choose Application deployment based on Docker Image.
 4. Set image reference:
-
    - Registry: `git.allucanget.biz`
    - Image: `git.allucanget.biz/allucanget/arbitrade:latest`
 
 5. Configure registry credentials in Coolify if your registry requires auth.
 6. Leave build/install/start commands empty unless you need overrides.
 7. Set network and health:
-
    - Exposed port: `9090`
    - Health check path: `/health`
 
 8. Add environment variables and secrets from the Common Runtime Configuration section.
 9. Add persistent storage mount `/app/data`.
 10. Deploy and verify:
-
     - Logs show container start success.
     - `GET /health` returns success.
 
@@ -145,7 +135,7 @@ Update flow for new releases:
 - Ensure the deployed image/wheel includes package templates under `arbitrade/web/templates/*`.
 - If you build from source, do not remove packaged template files under `src/arbitrade/web/templates`.
 - DB resets after deploy:
-- Confirm persistent mount exists at `/app/data` and `DUCKDB_PATH` points there.
+- Confirm PostgreSQL is reachable at `PG_HOST`.
 - Registry pull fails:
 - Re-check Docker registry credentials in Coolify.
 - App starts but unavailable externally:

docs/architecture/README.md

@@ -8,7 +8,7 @@ Primary goals:
 
 - Detect and execute triangular opportunities on Kraken with fee/slippage-aware math.
 - Keep hot-path latency low with incremental order-book updates and event-driven scoring.
-- Persist operational data in DuckDB for dev, test, and prod.
+- Persist operational data in PostgreSQL for all environments.
 - Provide operator controls, audit trail, and alerting through a server-rendered dashboard.
 - Support backtesting, parameter sweeps, and deferred experimental strategy work behind feature flags.
 
@@ -17,7 +17,7 @@ Primary goals:
 - Python 3.12+ runtime.
 - Native Kraken WebSocket on the hot path.
 - HTMX + Jinja2 UI, no SPA build step.
-- DuckDB everywhere.
+- PostgreSQL everywhere.
 - Self-hosted Gitea Actions CI and Gitea registry.
 - Windows development support.
 - Secrets must stay out of the repository.
@@ -32,7 +32,7 @@ The bot consumes Kraken market data, detects opportunities, and executes trades
 
 - Kraken REST + WebSocket provide market data and execution.
 - FastAPI serves HTML fragments, JSON endpoints, and SSE streams.
-- DuckDB stores trades, opportunities, snapshots, audit events, and runtime state.
+- PostgreSQL stores trades, opportunities, snapshots, audit events, and runtime state.
 - Coolify can deploy the published image using environment variables and persistent storage.
 
 ## 4. Solution Strategy
@@ -53,9 +53,9 @@ The bot consumes Kraken market data, detects opportunities, and executes trades
 - `detection/` - triangular graph and incremental detector.
 - `risk/` - pre-trade and trade-limit guards.
 - `execution/` - multi-leg trade sequencing.
-- `backtesting/` - replay engine, parameter sweep, experiment scaffolds.
+- `backtesting/` - replay engine, parameter sweep, experiment scaffolds. See [backtesting.md](backtesting.md).
 - `strategy/` - experimental strategy modules such as stat-arb.
-- `storage/` - DuckDB schema and repositories.
+- `storage/` - PostgreSQL schema and repositories.
 - `alerting/` - multi-channel notifications.
 - `runtime/` - startup recovery and graceful shutdown.
 
@@ -64,7 +64,7 @@ The bot consumes Kraken market data, detects opportunities, and executes trades
 - `fastapi`, `uvicorn`, `jinja2`, `htmx`-driven templates.
 - `orjson` for low-alloc parsing.
 - `sortedcontainers` for book state.
-- `duckdb` for persistence and analytics.
+- `asyncpg` for PostgreSQL persistence.
 - `pydantic` / `pydantic-settings` for typed configuration.
 - `cryptography` / keyring for secret handling.
 
@@ -77,7 +77,7 @@ The bot consumes Kraken market data, detects opportunities, and executes trades
 3. Incremental detector scores impacted cycles.
 4. Risk manager validates the opportunity.
 5. Execution sequencer places legs if approved.
-6. Trades and snapshots persist to DuckDB.
+6. Trades and snapshots persist to PostgreSQL.
 7. Dashboard and alerts reflect state changes.
 
 ### 6.2 Dashboard Control Flow
@@ -89,11 +89,14 @@ The bot consumes Kraken market data, detects opportunities, and executes trades
 
 ### 6.3 Backtesting Flow
 
-1. User selects JSONL replay file and run parameters.
-2. Replay engine loads ordered book events.
-3. Detector, risk, and execution logic run in simulation mode.
-4. Report is stored in memory for recent UI display.
-5. Parameter sweeps split data into train/test windows, rank results, and flag overfit.
+See [backtesting.md](backtesting.md) for full design and implementation details.
+
+1. User picks currency pairs (from config/pairings page, or all enabled).
+2. User sets starting balances (required), time range (required), min profit threshold (required).
+3. Fee profile defaults to "api (from Kraken)"; slippage (4.0 bps) and execution latency (20 ms) are optional with sensible defaults.
+4. Job is queued via `POST /dashboard/backtesting/run`.
+5. Backend loads events from `market_snapshots` table, builds triangular cycles, runs replay engine.
+6. Report stored in `backtest_jobs` table, visible in recent jobs list.
 
 ## 7. Deployment View
 
@@ -112,7 +115,7 @@ The bot consumes Kraken market data, detects opportunities, and executes trades
 
 - Deploy from the published image.
 - Configure runtime via environment variables.
-- Mount persistent storage at `/app/data` for DuckDB.
+- Connect to PostgreSQL at configured `PG_HOST`.
 
 ## 8. Cross-Cutting Concepts
 
@@ -126,7 +129,7 @@ The bot consumes Kraken market data, detects opportunities, and executes trades
 ## 9. Architecture Decisions
 
 - Native Kraken WS instead of a generic exchange abstraction on the hot path.
-- DuckDB as the single database engine.
+- PostgreSQL as the single database engine.
 - HTMX + Jinja2 instead of SPA frontend.
 - Backtesting reuses production detector/risk/execution logic.
 - Experimental stat-arb stays behind a feature flag.
@@ -152,5 +155,5 @@ The bot consumes Kraken market data, detects opportunities, and executes trades
 - WS: WebSocket.
 - HTMX: HTML-over-the-wire UI library.
 - SSE: Server-Sent Events.
-- DUCKDB: Embedded analytical database used for all environments.
+- PGSQL: PostgreSQL database used for all environments.
 - Stat arb: Statistical arbitrage, currently experimental and feature-flagged.

docs/architecture/backtesting.md

@@ -0,0 +1,130 @@
+# Backtesting Architecture
+
+> Detailed design and implementation of the backtesting subsystem.
+> See [`README.md`](README.md#63-backtesting-flow) for the high-level user flow.
+
+## Data Flow
+
+```txt
+market_snapshots (DB) ─┐
+                        ├──→ load_replay_events_from_db() ──→ list[ReplayBookEvent]
+JSONL file ─────────────┘
+                                      │
+                                      ▼
+                           BacktestReplayEngine.run()
+                                      │
+                                      ▼
+                              BacktestReport
+                                      │
+                                      ▼
+                           BacktestJobRepository.store_report()
+```
+
+Two event sources:
+
+- **DB mode** (default) — loads snapshots from `market_snapshots` table. Supports symbol/time filtering.
+- **File mode** — reads JSONL files from disk (legacy, used by `backtest_replay.py` script).
+
+## Core Types
+
+### `ReplayClock`
+
+Timekeeper for simulation. Ensures events advance monotonically. Supports `advance_ms()` to model execution latency.
+
+### `ReplayBookEvent`
+
+One atomic book state at a point in time. Fields: `occurred_at`, `symbol`, `bids: tuple[BookLevel]`, `asks: tuple[BookLevel]`.
+
+### `BacktestConfig`
+
+| Field                    | Default  | Description                                           |
+| ------------------------ | -------- | ----------------------------------------------------- |
+| `fee_rate`               | `0.0`    | 0.0 → API-sourced fee from `kraken_account_snapshots` |
+| `min_profit_threshold`   | `0.0005` | Minimum net profit to attempt trade                   |
+| `trade_capital`          | `100.0`  | Capital allocated per trade                           |
+| `quote_asset`            | `"USD"`  | Base currency for P&L                                 |
+| `slippage_bps`           | `4.0`    | Simulated slippage in basis points                    |
+| `execution_latency_ms`   | `20.0`   | Simulated latency per leg                             |
+| `max_depth_levels`       | `10`     | Order book depth for detection                        |
+| `max_concurrent_trades`  | `1`      | Max simultaneous trades                               |
+| `min_order_size_by_pair` | `None`   | Per-pair min order size overrides                     |
+
+### `BacktestReport`
+
+| Field                            | Type           | Description                        |
+| -------------------------------- | -------------- | ---------------------------------- |
+| `started_at` / `finished_at`     | datetime       | Simulation window                  |
+| `processed_events`               | int            | Events consumed                    |
+| `opportunities_seen`             | int            | Detected opportunities             |
+| `trades_executed`                | int            | Successful trades                  |
+| `win_rate`                       | float or None  | Fraction of profitable trades      |
+| `fill_rate`                      | float or None  | Average fill ratio                 |
+| `realized_pnl_usd`               | float          | Net P&L after slippage             |
+| `max_drawdown_usd`               | float          | Peak-to-trough equity drop         |
+| `miss_reasons`                   | dict[str, int] | Counters for skipped opportunities |
+| `execution_latency_p50/95/99_ms` | float or None  | Latency percentiles                |
+
+## Simulation Client
+
+`_SimulatedRestClient` replaces the real Kraken REST client during backtesting.
+
+- **Slippage model:** `fill_ratio = max(0.85, 1.0 - (slippage_bps / 10000.0) * 8.0)`
+- **Latency model:** Clock advances by `execution_latency_ms` before each simulated fill
+- Orders always fill (status = `"closed"`) at the modeled ratio
+
+## Job Worker
+
+`backtest_worker` is an `asyncio.Task` started in `create_app()` lifespan:
+
+```python
+backtest_task = asyncio.create_task(
+    backtest_worker(backtest_queue, db),
+    name="backtest_worker",
+)
+```
+
+Workflow per job:
+
+1. Dequeue `(job_id, config_dict)` from `asyncio.Queue`
+2. Update status → `"running"` in `backtest_jobs` table
+3. Load events (DB or file)
+4. Build currency graph → triangular cycles
+5. Instantiate `BacktestReplayEngine` → `engine.run()`
+6. Store report → update status → `"completed"` (or `"failed"` on exception)
+
+## Sweep Pipeline
+
+`run_parameter_search` performs grid search over backtest parameters:
+
+1. **Split** events into train/test windows by time ratio
+2. **Build grid** — cartesian product of `theta_values × trade_capital_values × pair_universes × staleness_threshold_values`
+3. **For each parameter set:**
+   - Filter events to pair universe + apply staleness gate
+   - Build cycles restricted to pair universe
+   - Run engine on train window → `train_report`
+   - Run engine on test window → `test_report`
+   - Score = `realized_pnl + win_rate_bonus + fill_rate_bonus - max_drawdown`
+   - Compute generalization gap = `|train_score - test_score| / max(train_score, test_score)`
+4. **Evaluate promotion:**
+   - `PromotionCriteria` checks: min test P&L, min win rate ≥ 0.5, min fill rate ≥ 0.9, max drawdown ≤ $25, generalization gap ≤ 0.5
+   - Results passing all criteria are flagged `promotion_ready`
+
+## UI
+
+> See `backtesting.html` → `partials/backtesting_panel.html`.
+
+- **Shell page** loads the panel via `hx-get="/dashboard/fragment/backtesting"`
+- **Run form** — starting balances, time range, profit threshold (required); fee profile, slippage, latency (advanced/collapsible)
+- **Status card** — current job status + message
+- **Recent jobs table** — lists last 20 jobs with status, events, trades, P&L; each row has a detail button
+- **Job detail** — `GET /dashboard/backtesting/job/{id}` returns report HTML
+
+Pairings are managed on the `/dashboard/config/pairings` page. Backtest uses DB-enabled pairings by default when no symbols are specified.
+
+## Source Files
+
+| File                    | Role                                                                                                                                                                          |
+| ----------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `backtesting/replay.py` | `ReplayClock`, `ReplayBookEvent`, `BacktestConfig`, `BacktestReport`, `_SimulatedRestClient`, `BacktestReplayEngine`, `load_replay_events`, `load_replay_events_from_db`      |
+| `backtesting/runner.py` | `run_backtest_job`, `backtest_worker`, `_build_cycles_from_events`, `_parse_balances`                                                                                         |
+| `backtesting/sweep.py`  | `SweepParameters`, `SweepResult`, `SweepArtifacts`, `PromotionCriteria`, `split_events_time_windows`, `build_parameter_grid`, `run_parameter_search`, `persist_sweep_results` |

docs/architecture/current-implementation.md

@@ -9,6 +9,20 @@ This document summarizes the code that exists now, not the original plan.
 - DuckDB is initialized and migrated on startup.
 - Runtime recovery persists and restores control state and snapshots.
 
+## Configuration Management
+
+- Complete configuration management system implemented with database-backed user settings.
+- Configuration service in [src/arbitrade/config/service.py](../../src/arbitrade/config/service.py) handles loading and applying settings.
+- Repository classes in [src/arbitrade/storage/repositories.py](../../src/arbitrade/storage/repositories.py) provide database access.
+- Web UI for configuration at `/dashboard/config/` with CRUD operations for:
+  - Currency pairings
+  - Fee configurations
+  - Application settings
+  - Backtesting parameters
+- Hot-reloading capabilities for runtime configuration changes.
+- Input validation and error handling for all configuration forms.
+- Audit logging for all configuration modifications.
+
 ## Market Data and Detection
 
 - Kraken market data is handled by native WS and thin REST code.

docs/architecture/repositories.md

@@ -0,0 +1,88 @@
+# Database Layer: Schema & Repositories
+
+> **Database engine**: PostgreSQL 15+ on `192.168.88.35`
+> **Driver**: `asyncpg` (async connection pool)
+> **Store class**: `PgStore` in `src/arbitrade/storage/pg_store.py`
+
+## Connection Lifecycle
+
+```txt
+FastAPI lifespan (create_app)
+  └─ PgStore.start()         # creates asyncpg connection pool
+      └─ PgStore.migrate()   # reads schema_pg.sql, creates tables
+          └─ ... application runs ...
+  └─ PgStore.stop()          # closes the pool
+```
+
+All repository classes accept a `PgStore` instance and acquire connections
+via `async with self._store.pool.acquire() as conn:`.
+
+## Schema
+
+Defined in `src/arbitrade/storage/schema_pg.sql`. 15 tables:
+
+| Table                         | Purpose                    | PK              | Notes                                    |
+| ----------------------------- | -------------------------- | --------------- | ---------------------------------------- |
+| `schema_migrations`           | Version tracking           | `version`       | Single-row per version                   |
+| `config_sections`             | Config section metadata    | `id` (SERIAL)   | `name` UNIQUE                            |
+| `config_settings`             | Key-value config store     | `key` (VARCHAR) | JSON-serialized values                   |
+| `config_pairings`             | Currency pairs to monitor  | `id` (SERIAL)   | `(base_asset, quote_asset)` UNIQUE       |
+| `config_backtesting_defaults` | Default backtest params    | `id` (SERIAL)   | Singleton via `ORDER BY id DESC LIMIT 1` |
+| `opportunities`               | Detected arb opportunities | `id` (UUID)     |                                          |
+| `trades`                      | Executed trades            | `id` (UUID)     |                                          |
+| `orders`                      | Individual leg orders      | `id` (UUID)     |                                          |
+| `pnl_events`                  | P&L event stream           | `id` (UUID)     |                                          |
+| `portfolio_snapshots`         | Balance snapshots          | —               | Append-only                              |
+| `market_snapshots`            | Raw order-book snapshots   | —               | Append-only                              |
+| `audit_events`                | Audit trail                | `id` (UUID)     |                                          |
+| `runtime_state_snapshots`     | Runtime state history      | —               | Append-only                              |
+| `kraken_account_snapshots`    | Fee tier + account data    | —               | Append-only                              |
+| `backtest_jobs`               | Backtest job records       | `id` (UUID)     |                                          |
+
+JSON columns use `JSONB` for indexability. UUID primary keys use
+`gen_random_uuid()` (requires `pgcrypto` extension).
+
+## Repository Classes
+
+All in `src/arbitrade/storage/repositories.py`. Every method is `async def`.
+
+| Class                                 | Key Methods                                                | Used By                     |
+| ------------------------------------- | ---------------------------------------------------------- | --------------------------- |
+| `MarketSnapshotRepository`            | `insert()`                                                 | `AsyncMarketSnapshotWriter` |
+| `OpportunityRepository`               | `insert()`                                                 | `AsyncOpportunityWriter`    |
+| `TradeRepository`                     | `insert()`                                                 | `AsyncExecutionWriter`      |
+| `OrderRepository`                     | `insert()`                                                 | `AsyncExecutionWriter`      |
+| `PnLRepository`                       | `insert()`                                                 | `AsyncExecutionWriter`      |
+| `AuditRepository`                     | `insert()`, `list_recent()`                                | API routes, lifecycle       |
+| `RuntimeStateRepository`              | `insert()`, `latest()`                                     | Lifecycle, API              |
+| `ConfigSectionRepository`             | `create_section()`, `get_section()`, `list_sections()`     | Config service              |
+| `ConfigSettingRepository`             | Full CRUD + `get_latest_updated_at()`                      | Config service              |
+| `ConfigPairingRepository`             | Full CRUD + `upsert_pairing()`, `list_pairings()`          | Feeds, pairing sync         |
+| `ConfigBacktestingDefaultsRepository` | `create_defaults()`, `get_defaults()`, `update_defaults()` | Config service              |
+| `KrakenAccountSnapshotRepository`     | `insert_snapshot()`, `latest_snapshot()`                   | Fee sync loop               |
+| `BacktestJobRepository`               | Full CRUD                                                  | Backtesting UI + worker     |
+
+## Async Writers
+
+Three background writer tasks buffer high-frequency writes:
+
+- **`AsyncExecutionWriter`** — trades/orders/P&L queue
+- **`AsyncMarketSnapshotWriter`** — order-book snapshot queue
+- **`AsyncOpportunityWriter`** — opportunity event queue
+
+Each uses an `asyncio.Queue` and drains it in a background task with
+`await repo.insert(...)`.
+
+## Integration Tests
+
+`tests/integration/test_postgresql_schema.py` verifies:
+
+- Connection to PostgreSQL server
+- `pgcrypto` extension availability
+- All 15 tables exist after migration
+- Migration is idempotent
+- Correct columns per table
+- Primary keys and unique constraints
+- Tables start empty
+- Simple INSERT/SELECT round-trip
+- `ON CONFLICT ... DO UPDATE` on config_pairings

ops/performance/README.md

@@ -39,7 +39,7 @@ Key end-to-end latency baselines from `latency_baseline.json`:
 
 ## Optimization Note
 
-`MetricsCalculator.compute()` was optimized to use DuckDB SQL aggregations and quantiles, reducing Python-side row scans.
+`MetricsCalculator.compute()` uses PostgreSQL SQL aggregations and percentiles, reducing Python-side row scans.
 
 Measured benchmark (`scripts/benchmark_metrics_compute.py`):
 

pyproject.toml

@@ -27,7 +27,10 @@ include-package-data = true
 [tool.setuptools.package-data]
 arbitrade = [
 	"web/templates/*.html",
+	"web/templates/config/*.html",
+	"web/templates/dashboard/*.html",
 	"web/templates/partials/*.html",
+	"storage/schema_pg.sql",
 ]
 
 [tool.setuptools.packages.find]
@@ -43,7 +46,7 @@ target-version = "py312"
 
 [tool.ruff.lint]
 select = ["E", "F", "I", "UP", "B", "N", "ASYNC"]
-ignore = ["E203"]
+ignore = ["E203", "E501"]
 
 [tool.mypy]
 python_version = "3.12"
@@ -54,7 +57,7 @@ pretty = true
 mypy_path = "src"
 
 [[tool.mypy.overrides]]
-module = ["duckdb", "keyring", "sortedcontainers"]
+module = ["asyncpg", "keyring", "sortedcontainers"]
 ignore_missing_imports = true
 
 [tool.pytest.ini_options]

requirements/latest-dev.in

@@ -1,4 +1,5 @@
 # Unpinned dev dependencies (latest available)
+asyncpg-stubs
 black
 mypy
 pre-commit

requirements/latest-runtime.in

@@ -1,6 +1,6 @@
 # Unpinned runtime dependencies (latest available)
+asyncpg
 cryptography
-duckdb
 fastapi
 httptools
 httpx

scripts/backtest_replay.py

@@ -6,10 +6,31 @@ from collections.abc import Mapping
 from datetime import UTC, datetime
 from pathlib import Path
 
+import duckdb
+
 from arbitrade.backtesting.replay import BacktestConfig, BacktestReplayEngine, load_replay_events
 from arbitrade.detection.graph import CurrencyGraph, TriangularCycle
 
 
+def _resolve_fee_rate(fee_rate: float | None, db_path: str | None = None) -> float:
+    """Resolve fee rate from arg or DB snapshot. Falls back to 0.0026."""
+    if fee_rate is not None:
+        return fee_rate
+    if db_path is not None:
+        try:
+            conn = duckdb.connect(db_path)
+            row = conn.execute("""
+                SELECT maker_fee FROM kraken_account_snapshots
+                ORDER BY snapshot_at DESC LIMIT 1
+            """).fetchone()
+            conn.close()
+            if row is not None and row[0] is not None:
+                return float(row[0])
+        except Exception:
+            pass
+    return 0.0026  # ultimate fallback
+
+
 def _build_graph() -> tuple[dict[str, list[TriangularCycle]], list[str]]:
     graph = CurrencyGraph()
     graph.add_pair("USD", "BTC", "BTC/USD")
@@ -30,19 +51,20 @@ def _parse_balances(raw: str) -> Mapping[str, float]:
 
 
 def main() -> int:
-    parser = argparse.ArgumentParser(description="Run a deterministic replay backtest.")
+    parser = argparse.ArgumentParser(description="Run backtest.")
     parser.add_argument("--events", type=Path, required=True)
     parser.add_argument("--starting-balances", type=str, default="USD=1000.0")
     parser.add_argument("--trade-capital", type=float, default=100.0)
-    parser.add_argument("--fee-rate", type=float, default=0.0026)
+    parser.add_argument("--fee-rate", type=float, default=None)
     parser.add_argument("--slippage-bps", type=float, default=4.0)
     parser.add_argument("--execution-latency-ms", type=float, default=20.0)
     args = parser.parse_args()
 
     cycles_by_pair, available_pairs = _build_graph()
     events = load_replay_events(args.events)
+    fee_rate = _resolve_fee_rate(args.fee_rate, args.db_path)
     config = BacktestConfig(
-        fee_rate=args.fee_rate,
+        fee_rate=fee_rate,
         trade_capital=args.trade_capital,
         slippage_bps=args.slippage_bps,
         execution_latency_ms=args.execution_latency_ms,
@@ -54,24 +76,23 @@ def main() -> int:
         config=config,
         started_at=events[0].occurred_at if events else datetime.now(UTC),
     )
-    report = asyncio.run(
-        engine.run(events, starting_balances=_parse_balances(args.starting_balances))
-    )
+    starting_balances = _parse_balances(args.starting_balances)
+    r = asyncio.run(engine.run(events, starting_balances=starting_balances))
 
     print("Backtest report:")
-    print(f"- processed_events: {report.processed_events}")
-    print(f"- opportunities_seen: {report.opportunities_seen}")
-    print(f"- trades_executed: {report.trades_executed}")
-    print(f"- win_rate: {report.win_rate if report.win_rate is not None else 'n/a'}")
-    print(f"- fill_rate: {report.fill_rate if report.fill_rate is not None else 'n/a'}")
-    print(f"- realized_pnl_usd: {report.realized_pnl_usd:.4f}")
-    print(f"- max_drawdown_usd: {report.max_drawdown_usd:.4f}")
-    print(f"- miss_reasons: {dict(report.miss_reasons)}")
+    print(f"- processed_events: {r.processed_events}")
+    print(f"- opportunities_seen: {r.opportunities_seen}")
+    print(f"- trades_executed: {r.trades_executed}")
+    print(f"- win_rate: {r.win_rate if r.win_rate is not None else 'n/a'}")
+    print(f"- fill_rate: {r.fill_rate if r.fill_rate is not None else 'n/a'}")
+    print(f"- realized_pnl_usd: {r.realized_pnl_usd:.4f}")
+    print(f"- max_drawdown_usd: {r.max_drawdown_usd:.4f}")
+    print(f"- miss_reasons: {dict(r.miss_reasons)}")
     print(
         "- execution_latency_ms: "
-        f"p50={report.execution_latency_p50_ms or 0.0:.4f}, "
-        f"p95={report.execution_latency_p95_ms or 0.0:.4f}, "
-        f"p99={report.execution_latency_p99_ms or 0.0:.4f}"
+        f"p50={r.execution_latency_p50_ms or 0.0:.4f}, "
+        f"p95={r.execution_latency_p95_ms or 0.0:.4f}, "
+        f"p99={r.execution_latency_p99_ms or 0.0:.4f}"
     )
     return 0
 

scripts/backtest_sweep.py

@@ -36,8 +36,7 @@ def _parse_float_list(raw: str) -> list[float]:
 def _parse_pair_universes(raw: str) -> list[tuple[str, ...]]:
     universes: list[tuple[str, ...]] = []
     for chunk in raw.split(";"):
-        symbols = tuple(item.strip().upper()
-                        for item in chunk.split("|") if item.strip())
+        symbols = tuple(item.strip().upper() for item in chunk.split("|") if item.strip())
         if symbols:
             universes.append(symbols)
     if not universes:
@@ -75,31 +74,29 @@ def _print_top_results(results: Sequence[SweepResult], *, limit: int = 5) -> Non
 
 def main() -> int:
     parser = argparse.ArgumentParser(
-        description="Run backtesting parameter sweep with train/test split.")
+        description="Run backtesting parameter sweep with train/test split."
+    )
     parser.add_argument("--events", type=Path, required=True)
     parser.add_argument("--starting-balances", type=str, default="USD=1000.0")
-    parser.add_argument("--theta-values", type=str,
-                        default="0.0003,0.0005,0.0008")
-    parser.add_argument("--trade-capital-values",
-                        type=str, default="50,100,150")
+    parser.add_argument("--theta-values", type=str, default="0.0003,0.0005,0.0008")
+    parser.add_argument("--trade-capital-values", type=str, default="50,100,150")
     parser.add_argument(
         "--pair-universes",
         type=str,
         default="BTC/USD|ETH/BTC|ETH/USD",
         help="Semicolon-separated universes, each with | delimited pairs",
     )
-    parser.add_argument("--staleness-threshold-values",
-                        type=str, default="3,5,8")
+    parser.add_argument("--staleness-threshold-values", type=str, default="3,5,8")
     parser.add_argument("--train-ratio", type=float, default=0.7)
-    parser.add_argument("--output", type=Path,
-                        default=Path("ops/backtesting/parameter_sweep_results.json"))
+    parser.add_argument(
+        "--output", type=Path, default=Path("ops/backtesting/parameter_sweep_results.json")
+    )
 
     parser.add_argument("--min-test-realized-pnl-usd", type=float, default=0.0)
     parser.add_argument("--min-test-win-rate", type=float, default=0.5)
     parser.add_argument("--min-test-fill-rate", type=float, default=0.9)
     parser.add_argument("--max-test-drawdown-usd", type=float, default=25.0)
-    parser.add_argument("--max-generalization-gap-ratio",
-                        type=float, default=0.5)
+    parser.add_argument("--max-generalization-gap-ratio", type=float, default=0.5)
 
     args = parser.parse_args()
 
@@ -107,15 +104,13 @@ def main() -> int:
     symbols = sorted({event.symbol.upper() for event in events})
     cycles_by_pair = _build_graph_from_symbols(symbols)
     if not cycles_by_pair:
-        raise SystemExit(
-            "No triangular cycles found in supplied replay events")
+        raise SystemExit("No triangular cycles found in supplied replay events")
 
     grid = build_parameter_grid(
         theta_values=_parse_float_list(args.theta_values),
         trade_capital_values=_parse_float_list(args.trade_capital_values),
         pair_universes=_parse_pair_universes(args.pair_universes),
-        staleness_threshold_values=_parse_float_list(
-            args.staleness_threshold_values),
+        staleness_threshold_values=_parse_float_list(args.staleness_threshold_values),
     )
 
     artifacts = run_parameter_search(

scripts/benchmark_metrics_compute.py

@@ -8,17 +8,19 @@ from time import perf_counter
 
 from arbitrade.config.settings import Settings
 from arbitrade.metrics import MetricsCalculator
-from arbitrade.storage.db import DuckDBStore
+from arbitrade.storage.pg_store import PgStore
 
 
-def _python_scan_compute(store: DuckDBStore) -> tuple[float, float | None, float | None]:
-    with store.connect() as conn:
-        trade_rows = conn.execute("""
+async def _python_scan_compute(store: PgStore) -> tuple[float, float | None, float | None]:
+    sql_s = """
         SELECT started_at, finished_at, realized_pnl
         FROM trades
         WHERE finished_at IS NOT NULL
-            """).fetchall()
-        opportunity_rows = conn.execute("SELECT detected_at FROM opportunities").fetchall()
+    """
+    sql_d = "SELECT detected_at FROM opportunities"
+    async with store.pool.acquire() as conn:
+        trade_rows = await conn.fetch(sql_s)
+        orows = await conn.fetch(sql_d)
 
     realized = sum(float(row[2]) for row in trade_rows if row[2] is not None)
     durations = [
@@ -28,10 +30,10 @@ def _python_scan_compute(store: DuckDBStore) -> tuple[float, float | None, float
     ]
     avg_duration = fmean(durations) if durations else None
 
-    times = [row[0] for row in opportunity_rows if isinstance(row[0], datetime)]
+    times = [row[0] for row in orows if isinstance(row[0], datetime)]
     if len(times) >= 2:
-        span_seconds = (max(times) - min(times)).total_seconds()
-        opm = len(times) / (span_seconds / 60.0) if span_seconds > 0.0 else float(len(times))
+        ss = (max(times) - min(times)).total_seconds()
+        opm = len(times) / (ss / 60.0) if ss > 0.0 else float(len(times))
     elif len(times) == 1:
         opm = 60.0
     else:
@@ -40,7 +42,7 @@ def _python_scan_compute(store: DuckDBStore) -> tuple[float, float | None, float
     return realized, avg_duration, opm
 
 
-def _seed_dataset(store: DuckDBStore) -> None:
+async def _seed_dataset(store: PgStore) -> None:
     now = datetime.now(UTC)
 
     trade_rows: list[tuple[object, ...]] = []
@@ -86,11 +88,11 @@ def _seed_dataset(store: DuckDBStore) -> None:
             )
         )
 
-    with store.connect() as conn:
-        conn.execute("DELETE FROM trades")
-        conn.execute("DELETE FROM opportunities")
-        conn.execute("DELETE FROM orders")
-        conn.executemany(
+    async with store.pool.acquire() as conn:
+        await conn.execute("DELETE FROM trades")
+        await conn.execute("DELETE FROM opportunities")
+        await conn.execute("DELETE FROM orders")
+        await conn.executemany(
             """
             INSERT INTO trades (
                 trade_ref,
@@ -106,7 +108,7 @@ def _seed_dataset(store: DuckDBStore) -> None:
             """,
             trade_rows,
         )
-        conn.executemany(
+        await conn.executemany(
             """
             INSERT INTO opportunities (
                 detected_at,
@@ -119,7 +121,7 @@ def _seed_dataset(store: DuckDBStore) -> None:
             """,
             opportunity_rows,
         )
-        conn.executemany(
+        await conn.executemany(
             """
             INSERT INTO orders (
                 trade_ref,
@@ -140,28 +142,28 @@ def _seed_dataset(store: DuckDBStore) -> None:
         )
 
 
-def main() -> int:
+async def main() -> int:
     db_path = Path(gettempdir()) / "arbitrade_metrics_bench.duckdb"
     settings = Settings(_env_file=None, DUCKDB_PATH=db_path)
-    store = DuckDBStore(settings)
+    store = PgStore(settings)
     store.migrate()
-    _seed_dataset(store)
+    await _seed_dataset(store)
 
     calculator = MetricsCalculator(store)
 
     for _ in range(3):
-        _python_scan_compute(store)
-        calculator.compute()
+        await _python_scan_compute(store)
+        await calculator.compute()
 
     runs = 20
     start = perf_counter()
     for _ in range(runs):
-        _python_scan_compute(store)
+        await _python_scan_compute(store)
     python_ms = (perf_counter() - start) * 1000.0 / runs
 
     start = perf_counter()
     for _ in range(runs):
-        calculator.compute()
+        await calculator.compute()
     sql_ms = (perf_counter() - start) * 1000.0 / runs
 
     speedup = (python_ms / sql_ms) if sql_ms > 0.0 else 0.0

src/arbitrade/api/app.py

@@ -1,40 +1,199 @@
 from __future__ import annotations
 
+import asyncio
 from collections.abc import AsyncIterator
 from contextlib import asynccontextmanager
 
+import structlog
 from fastapi import FastAPI
 
 from arbitrade.alerting.notifier import build_notifier_from_settings
 from arbitrade.api.control_state import DashboardControlState
 from arbitrade.api.routes import public_router, router
+from arbitrade.backtesting.runner import backtest_worker
+from arbitrade.config.pairing_sync import run_pairing_sync_loop
+from arbitrade.config.service import ConfigurationService
 from arbitrade.config.settings import Settings
+from arbitrade.exchange.fee_service import run_fee_sync_loop
+from arbitrade.exchange.kraken_rest import KrakenRestClient
+from arbitrade.exchange.kraken_ws import KrakenWsClient
+from arbitrade.logging.db_sink import get_db_sink
+from arbitrade.logging.maintenance import run_log_aggregation_loop, run_log_archive_loop
 from arbitrade.logging_setup import configure_logging
+from arbitrade.market_data.feed import MarketDataFeed
+from arbitrade.market_data.feed_builder import (
+    build_detector_from_enabled_pairings,
+    get_enabled_pair_symbols,
+)
 from arbitrade.metrics import MetricsCalculator
 from arbitrade.runtime.lifecycle import graceful_shutdown, restore_runtime_state
-from arbitrade.storage.db import DuckDBStore
-from arbitrade.storage.repositories import AuditRepository, RuntimeStateRepository
+from arbitrade.storage.market_snapshots import AsyncMarketSnapshotWriter
+from arbitrade.storage.opportunities import AsyncOpportunityWriter
+from arbitrade.storage.pg_store import PgStore
+from arbitrade.storage.repositories import (
+    AuditRepository,
+    MarketSnapshotRepository,
+    OpportunityRepository,
+    RuntimeStateRepository,
+)
+
+_LOG = structlog.get_logger(__name__)
+
+
+async def _start_feed(app: FastAPI, *, kill_switch_only: bool = False) -> asyncio.Task[None] | None:
+    """Create and start a MarketDataFeed task from enabled pairings.
+
+    If kill_switch_only=True, only create a kill-switch-bound stub (no detector/feed).
+    Returns the task or None if no enabled pairings.
+    """
+    settings = app.state.settings
+    db = app.state.store
+    alert_notifier = getattr(app.state, "alert_notifier", None)
+    controls = app.state.dashboard_controls
+
+    # Build detector from enabled pairings
+    detector = await build_detector_from_enabled_pairings(
+        db,
+        fee_rate=0.0,  # will be overridden by fee sync
+        max_depth_levels=controls.strategy_max_depth_levels,
+        min_profit_threshold=controls.strategy_profit_threshold,
+    )
+
+    symbols = await get_enabled_pair_symbols(db)
+    if not symbols and not kill_switch_only:
+        _LOG.warning("no_enabled_pair_symbols_feed_not_started")
+        return None
+
+    ws_client: KrakenWsClient | None = getattr(app.state, "ws_client", None)
+    if ws_client is None:
+        ws_client = KrakenWsClient(settings, alert_notifier=alert_notifier)
+        app.state.ws_client = ws_client
+
+    ws_client.set_subscribed_symbols(symbols)
+
+    snapshot_writer = AsyncMarketSnapshotWriter(MarketSnapshotRepository(db))
+    opportunity_writer = AsyncOpportunityWriter(OpportunityRepository(db))
+
+    feed = MarketDataFeed(
+        ws_client=ws_client,
+        snapshot_writer=snapshot_writer,
+        detector=detector,
+        opportunity_writer=opportunity_writer,
+        paper_trading_mode=settings.paper_trading_mode,
+        trade_capital=settings.trade_capital_usd,
+        max_trade_capital=settings.max_trade_capital_usd,
+        kill_switch=controls.kill_switch,
+        alert_notifier=alert_notifier,
+        audit_repository=getattr(app.state, "audit_repository", None),
+    )
+
+    app.state.feed = feed
+    task = asyncio.create_task(feed.run(), name="market_data_feed")
+    app.state.feed_task = task
+    _LOG.info("market_data_feed_started", symbols=symbols)
+    return task
 
 
 def create_app(settings: Settings) -> FastAPI:
     configure_logging(settings.log_level, settings.log_json)
 
-    db = DuckDBStore(settings)
-    db.migrate()
+    db = PgStore(settings)
+
+    kraken_client = KrakenRestClient(settings)
+    fee_sync_stop_event = asyncio.Event()
+    pairing_sync_stop_event = asyncio.Event()
+    backtest_queue: asyncio.Queue[tuple[str, str, dict[str, object] | None] | None] = (
+        asyncio.Queue()
+    )
 
     @asynccontextmanager
     async def lifespan(app: FastAPI) -> AsyncIterator[None]:
+        await app.state.store.start()
+        await app.state.store.migrate()
+        get_db_sink().start_consumer(db)
+        await app.state.configuration_service.load_database_settings()
         await restore_runtime_state(app)
+        fee_sync_task = asyncio.create_task(
+            run_fee_sync_loop(
+                kraken_client,
+                db,
+                fee_sync_stop_event,
+            ),
+            name="fee_sync_loop",
+        )
+        pairing_sync_task = asyncio.create_task(
+            run_pairing_sync_loop(
+                kraken_client,
+                db,
+                pairing_sync_stop_event,
+            ),
+            name="pairing_sync_loop",
+        )
+        backtest_task = asyncio.create_task(
+            backtest_worker(backtest_queue, db),  # type: ignore
+            name="backtest_worker",
+        )
+        # Start market data feed from enabled pairings
+        await _start_feed(app)
+        app.state.fee_sync_task = fee_sync_task
+        app.state.pairing_sync_task = pairing_sync_task
+        app.state.backtest_task = backtest_task
+        app.state.log_aggregation_task = asyncio.create_task(
+            run_log_aggregation_loop(db), name="log_aggregation"
+        )
+        app.state.log_archive_task = asyncio.create_task(
+            run_log_archive_loop(db), name="log_archive"
+        )
         yield
+        fee_sync_stop_event.set()
+        pairing_sync_stop_event.set()
+        # Stop feed
+        feed = getattr(app.state, "feed", None)
+        if feed is not None:
+            ws_client = getattr(app.state, "ws_client", None)
+            if ws_client is not None:
+                await ws_client.stop()
+        ft = getattr(app.state, "feed_task", None)
+        if ft is not None:
+            ft.cancel()
+            try:
+                await ft
+            except asyncio.CancelledError:
+                pass
+        fee_sync_task.cancel()
+        try:
+            await fee_sync_task
+        except asyncio.CancelledError:
+            pass
+        pairing_sync_task.cancel()
+        try:
+            await pairing_sync_task
+        except asyncio.CancelledError:
+            pass
+        await backtest_queue.put(None)  # poison pill
+        backtest_task.cancel()
+        try:
+            await backtest_task
+        except asyncio.CancelledError:
+            pass
+        await kraken_client.close()
         await graceful_shutdown(app)
+        await app.state.store.stop()
+        await get_db_sink().stop_consumer()
 
     app = FastAPI(title="arbitrade", version="0.1.0", lifespan=lifespan)
     app.state.settings = settings
     app.state.store = db
+    app.state.kraken_client = kraken_client
+    app.state.fee_sync_stop_event = fee_sync_stop_event
+    app.state.pairing_sync_stop_event = pairing_sync_stop_event
+    app.state.backtest_queue = backtest_queue
     app.state.metrics = MetricsCalculator(db)
     app.state.audit_repository = AuditRepository(db)
     app.state.runtime_state_repository = RuntimeStateRepository(db)
     app.state.alert_notifier = build_notifier_from_settings(settings)
+    svc = ConfigurationService(settings, db, app.state.audit_repository)
+    app.state.configuration_service = svc
     app.state.backtest_recent_reports = []
     app.state.dashboard_controls = DashboardControlState(
         is_running=not settings.kill_switch_active,

src/arbitrade/backtesting/replay.py

@@ -17,6 +17,7 @@ from arbitrade.execution.sequencer import TriangularExecutionSequencer
 from arbitrade.market_data.order_book import OrderBook
 from arbitrade.risk.pre_trade import PreTradeValidator
 from arbitrade.risk.trade_limits import TradeLimitsGuard
+from arbitrade.storage.pg_store import PgStore
 
 
 @dataclass(slots=True)
@@ -56,7 +57,7 @@ class ReplayBookEvent:
 
 @dataclass(frozen=True, slots=True)
 class BacktestConfig:
-    fee_rate: float = 0.0026
+    fee_rate: float = 0.0  # 0.0 means "use API-sourced fee from kraken_account_snapshots"
     min_profit_threshold: float = 0.0005
     trade_capital: float = 100.0
     quote_asset: str = "USD"
@@ -185,6 +186,89 @@ def load_replay_events(path: Path) -> list[ReplayBookEvent]:
     return sorted(events, key=lambda event: event.occurred_at)
 
 
+async def load_replay_events_from_db(
+    store: PgStore,
+    *,
+    symbols: list[str] | None = None,
+    start: datetime | None = None,
+    end: datetime | None = None,
+) -> list[ReplayBookEvent]:
+    """Load replay events from market_snapshots table.
+
+    Each market_snapshots row has snapshot_at, symbol, payload (raw Kraken WS).
+    Payload format: {channel, symbol, data: [{bids: [{price, qty}], asks: [{price, qty}]}]}
+    """
+    async with store.pool.acquire() as conn:
+        query = "SELECT snapshot_at, symbol, payload FROM market_snapshots WHERE 1=1"
+        params: list[object] = []
+
+        if symbols:
+            placeholders = ",".join(f"${i+1}" for i in range(len(symbols)))
+            query += f" AND symbol IN ({placeholders})"
+            params.extend(symbols)
+
+        if start is not None:
+            params.append(start)
+            query += f" AND snapshot_at >= ${len(params)}"
+
+        if end is not None:
+            params.append(end)
+            query += f" AND snapshot_at <= ${len(params)}"
+
+        query += " ORDER BY snapshot_at ASC"
+
+        rows = await conn.fetch(query, *params)
+
+    events: list[ReplayBookEvent] = []
+    for row in rows:
+        snapshot_at: datetime = row["snapshot_at"]
+        symbol: str = row["symbol"]
+        payload_raw = row["payload"]
+
+        if isinstance(payload_raw, str):
+            payload = orjson.loads(payload_raw)
+        elif isinstance(payload_raw, dict):
+            payload = payload_raw
+        else:
+            continue
+
+        data = payload.get("data")
+        if not isinstance(data, list) or not data:
+            continue
+
+        first = data[0]
+        if not isinstance(first, dict):
+            continue
+
+        bids = _parse_kraken_book_levels(first.get("bids"))
+        asks = _parse_kraken_book_levels(first.get("asks"))
+
+        if bids or asks:
+            events.append(
+                ReplayBookEvent(
+                    occurred_at=snapshot_at,
+                    symbol=symbol,
+                    bids=bids,
+                    asks=asks,
+                )
+            )
+
+    return events
+
+
+def _parse_kraken_book_levels(
+    raw_levels: object | None,
+) -> tuple[BookLevel, ...]:
+    """Parse Kraken WS book level format: [{price, qty}, ...]."""
+    if not isinstance(raw_levels, list):
+        return ()
+    levels: list[BookLevel] = []
+    for level in raw_levels:
+        if isinstance(level, dict) and "price" in level and "qty" in level:
+            levels.append(BookLevel(price=float(level["price"]), volume=float(level["qty"])))
+    return tuple(levels)
+
+
 class BacktestReplayEngine:
     def __init__(
         self,

src/arbitrade/backtesting/runner.py

@@ -0,0 +1,171 @@
+"""Async backtest job runner — picks up pending jobs from DB and executes them."""
+
+from __future__ import annotations
+
+import asyncio
+from datetime import datetime
+from pathlib import Path
+
+import structlog
+
+from arbitrade.backtesting.replay import (
+    BacktestConfig,
+    BacktestReplayEngine,
+    load_replay_events,
+    load_replay_events_from_db,
+)
+from arbitrade.detection.graph import CurrencyGraph, TriangularCycle
+from arbitrade.storage.pg_store import PgStore
+from arbitrade.storage.repositories import BacktestJobRepository
+
+_LOG = structlog.get_logger(__name__)
+
+
+def _build_cycles_from_events(
+    symbols: set[str],
+) -> tuple[dict[str, list[TriangularCycle]], list[str]]:
+    graph = CurrencyGraph()
+    for symbol in sorted(symbols):
+        if "/" not in symbol:
+            continue
+        base, quote = symbol.upper().split("/", 1)
+        graph.add_pair(base, quote, f"{base}/{quote}")
+    cycles = graph.triangular_cycles()
+    return graph.index_cycles_by_pair(cycles), sorted(symbols)
+
+
+def _parse_balances(raw: str) -> dict[str, float]:
+    balances: dict[str, float] = {}
+    for entry in raw.split(","):
+        stripped = entry.strip()
+        if not stripped:
+            continue
+        if "=" not in stripped:
+            continue
+        asset, value = stripped.split("=", 1)
+        balances[asset.strip().upper()] = float(value)
+    return balances or {"USD": 1000.0}
+
+
+async def run_backtest_job(
+    job_id: str,
+    config_dict: dict[str, object] | None,
+    store: PgStore,
+) -> None:
+    """Execute a single backtest job: load events from DB or file, run engine, store report."""
+    repo = BacktestJobRepository(store)
+    await repo.update_status(job_id, "running")
+    _LOG.info("backtest_job_started", job_id=job_id)
+
+    try:
+        config = config_dict or {}
+        events_path = str(config.get("events_path", ""))
+        symbols_raw = config.get("symbols")
+        source = str(config.get("source", "db"))
+
+        start_dt = None
+        end_dt = None
+        if source == "db":
+            start_str = config.get("start_time")
+            end_str = config.get("end_time")
+            if isinstance(start_str, str) and start_str:
+                start_dt = datetime.fromisoformat(start_str.replace("Z", "+00:00"))
+            if isinstance(end_str, str) and end_str:
+                end_dt = datetime.fromisoformat(end_str.replace("Z", "+00:00"))
+
+            symbols: list[str] | None = None
+            if isinstance(symbols_raw, str) and symbols_raw.strip():
+                symbols = [s.strip().upper() for s in symbols_raw.split(",") if s.strip()]
+            elif isinstance(symbols_raw, list):
+                symbols = [str(s).upper() for s in symbols_raw]
+
+            events = await load_replay_events_from_db(
+                store,
+                symbols=symbols,
+                start=start_dt,
+                end=end_dt,
+            )
+        else:
+            path = Path(events_path)
+            if not path.is_absolute():
+                path = Path("data") / path
+            path = path.resolve()
+            events = load_replay_events(path)
+
+        if not events:
+            raise ValueError("No events found for backtest")
+
+        starting_balances_raw = str(config.get("starting_balances", "USD=1000.0"))
+        starting_balances = _parse_balances(starting_balances_raw)
+
+        fee_rate = float(config.get("fee_rate", 0.0026))  # type: ignore
+        trade_capital = float(config.get("trade_capital", 100.0))  # type: ignore
+        min_profit_threshold = float(config.get("min_profit_threshold", 0.0005))  # type: ignore
+        slippage_bps = float(config.get("slippage_bps", 4.0))  # type: ignore
+        execution_latency_ms = float(config.get("execution_latency_ms", 20.0))  # type: ignore
+
+        cycles_by_pair, available_pairs = _build_cycles_from_events(
+            {e.symbol.upper() for e in events}
+        )
+        if not cycles_by_pair:
+            raise ValueError("No triangular cycles found in event data")
+
+        bt_config = BacktestConfig(
+            fee_rate=fee_rate,
+            min_profit_threshold=min_profit_threshold,
+            trade_capital=trade_capital,
+            slippage_bps=slippage_bps,
+            execution_latency_ms=execution_latency_ms,
+        )
+
+        engine = BacktestReplayEngine(
+            cycles_by_pair=cycles_by_pair,
+            available_pairs=available_pairs,
+            config=bt_config,
+            started_at=events[0].occurred_at,
+        )
+        report = await engine.run(events, starting_balances=starting_balances)
+
+        report_dict = {
+            "processed_events": report.processed_events,
+            "opportunities_seen": report.opportunities_seen,
+            "trades_executed": report.trades_executed,
+            "win_rate": report.win_rate,
+            "fill_rate": report.fill_rate,
+            "realized_pnl_usd": report.realized_pnl_usd,
+            "max_drawdown_usd": report.max_drawdown_usd,
+            "execution_latency_p50_ms": report.execution_latency_p50_ms,
+            "execution_latency_p95_ms": report.execution_latency_p95_ms,
+            "execution_latency_p99_ms": report.execution_latency_p99_ms,
+            "started_at": report.started_at.isoformat(),
+            "finished_at": report.finished_at.isoformat(),
+        }
+
+        await repo.store_report(job_id, report_dict)
+        await repo.update_status(job_id, "completed")
+        _LOG.info("backtest_job_completed", job_id=job_id, pnl=report.realized_pnl_usd)
+
+    except Exception as exc:
+        await repo.update_status(job_id, "failed", error=str(exc))
+        _LOG.exception("backtest_job_failed", job_id=job_id, error=str(exc))
+
+
+async def backtest_worker(
+    queue: asyncio.Queue[tuple[str, dict[str, object] | None] | None],
+    store: PgStore,
+) -> None:
+    """Worker coroutine: pull jobs from queue and execute them one at a time."""
+    _LOG.info("backtest_worker_started")
+    while True:
+        item = await queue.get()
+        if item is None:
+            queue.task_done()
+            break
+        job_id, config = item
+        try:
+            await run_backtest_job(job_id, config, store)
+        except Exception:
+            _LOG.exception("backtest_worker_unhandled_error", job_id=job_id)
+        finally:
+            queue.task_done()
+    _LOG.info("backtest_worker_stopped")

src/arbitrade/backtesting/sweep.py

@@ -91,16 +91,14 @@ def build_parameter_grid(
     for theta in theta_values:
         for trade_capital in trade_capital_values:
             for pair_universe in pair_universes:
-                normalized_universe = tuple(
-                    sorted({pair.upper() for pair in pair_universe}))
+                normalized_universe = tuple(sorted({pair.upper() for pair in pair_universe}))
                 for staleness_threshold in staleness_threshold_values:
                     grid.append(
                         SweepParameters(
                             min_profit_threshold=float(theta),
                             trade_capital=float(trade_capital),
                             pair_universe=normalized_universe,
-                            staleness_threshold_seconds=float(
-                                staleness_threshold),
+                            staleness_threshold_seconds=float(staleness_threshold),
                         )
                     )
     return grid
@@ -147,8 +145,9 @@ def _restrict_cycles_by_pair(
         if normalized_pair not in pair_universe:
             continue
 
-        kept = [cycle for cycle in cycles if all(
-            pair.upper() in pair_universe for pair in cycle.pairs)]
+        kept = [
+            cycle for cycle in cycles if all(pair.upper() in pair_universe for pair in cycle.pairs)
+        ]
         if kept:
             restricted[normalized_pair] = kept
     return restricted
@@ -175,9 +174,7 @@ def _evaluate_promotion(
     test = result.test_report
 
     if test.realized_pnl_usd < criteria.min_test_realized_pnl_usd:
-        reasons.append(
-            "test_realized_pnl_below_threshold"
-        )
+        reasons.append("test_realized_pnl_below_threshold")
     if (test.win_rate or 0.0) < criteria.min_test_win_rate:
         reasons.append("test_win_rate_below_threshold")
     if (test.fill_rate or 0.0) < criteria.min_test_fill_rate:
@@ -221,8 +218,7 @@ def run_parameter_search(
     quote_asset: str = "USD",
 ) -> SweepArtifacts:
     criteria = promotion_criteria or PromotionCriteria()
-    train_events, test_events = split_events_time_windows(
-        events, train_ratio=train_ratio)
+    train_events, test_events = split_events_time_windows(events, train_ratio=train_ratio)
 
     results: list[SweepResult] = []
     promoted: list[SweepResult] = []
@@ -293,7 +289,8 @@ def run_parameter_search(
             test_event_count=len(filtered_test),
         )
         promotion_ready, promotion_reasons = _evaluate_promotion(
-            result=base_result, criteria=criteria)
+            result=base_result, criteria=criteria
+        )
         completed_result = SweepResult(
             parameters=base_result.parameters,
             train_report=base_result.train_report,
@@ -318,8 +315,7 @@ def run_parameter_search(
     train_window: tuple[datetime, datetime] | None = None
     test_window: tuple[datetime, datetime] | None = None
     if train_events:
-        train_window = (train_events[0].occurred_at,
-                        train_events[-1].occurred_at)
+        train_window = (train_events[0].occurred_at, train_events[-1].occurred_at)
     if test_events:
         test_window = (test_events[0].occurred_at, test_events[-1].occurred_at)
 
@@ -392,5 +388,4 @@ def persist_sweep_results(path: Path, artifacts: SweepArtifacts) -> None:
     }
 
     path.parent.mkdir(parents=True, exist_ok=True)
-    path.write_bytes(orjson.dumps(
-        payload, option=orjson.OPT_INDENT_2 | orjson.OPT_SORT_KEYS))
+    path.write_bytes(orjson.dumps(payload, option=orjson.OPT_INDENT_2 | orjson.OPT_SORT_KEYS))

src/arbitrade/config/pairing_sync.py

@@ -0,0 +1,79 @@
+"""Sync available Kraken asset pairs into the config_pairings table."""
+
+from __future__ import annotations
+
+import asyncio
+
+import structlog
+
+from arbitrade.config.service import ConfigPairing
+from arbitrade.detection.graph import CurrencyGraph
+from arbitrade.exchange.kraken_rest import KrakenRestClient
+from arbitrade.storage.pg_store import PgStore
+from arbitrade.storage.repositories import ConfigPairingRepository
+
+_LOG = structlog.get_logger(__name__)
+
+
+async def sync_pairings_from_kraken(
+    kraken_client: KrakenRestClient,
+    store: PgStore,
+) -> dict[str, int]:
+    """Fetch all asset pairs from Kraken and upsert into config_pairings.
+
+    Returns a summary dict with 'added', 'updated', 'total' counts.
+    """
+    asset_pairs = await kraken_client.asset_pairs()
+    graph = CurrencyGraph.from_kraken_asset_pairs(asset_pairs)
+    repo = ConfigPairingRepository(store)
+
+    added = 0
+    updated = 0
+    total = 0
+
+    # Dedupe: pair_by_direction has entries for both (base,quote) and (quote,base).
+    seen_symbols: set[str] = set()
+    for (base, quote), symbol in graph.pair_by_direction.items():
+        if symbol in seen_symbols:
+            continue
+        seen_symbols.add(symbol)
+        existing = await repo.get_pairing(base, quote)
+        pairing = ConfigPairing(
+            base_asset=base,
+            quote_asset=quote,
+            enabled=existing.enabled if existing else False,
+            source="kraken",
+        )
+        try:
+            await repo.upsert_pairing(pairing)
+            total += 1
+            if existing:
+                updated += 1
+            else:
+                added += 1
+        except Exception:
+            _LOG.warning("sync_pairing_failed", base=base, quote=quote)
+
+    _LOG.info(
+        "pairing_sync_complete",
+        added=added,
+        updated=updated,
+        total=total,
+    )
+    return {"added": added, "updated": updated, "total": total}
+
+
+async def run_pairing_sync_loop(
+    kraken_client: KrakenRestClient,
+    store: PgStore,
+    stop_event: asyncio.Event,
+    interval_seconds: int = 86400,
+) -> None:
+    """Periodically sync pairings from Kraken (default daily)."""
+    await sync_pairings_from_kraken(kraken_client, store)
+    try:
+        while not stop_event.is_set():
+            await asyncio.wait_for(stop_event.wait(), timeout=interval_seconds)
+            await sync_pairings_from_kraken(kraken_client, store)
+    except (TimeoutError, asyncio.CancelledError):
+        pass

src/arbitrade/config/service.py

@@ -0,0 +1,231 @@
+from __future__ import annotations
+
+from datetime import datetime
+from typing import Any
+
+import orjson
+from pydantic import BaseModel
+
+from arbitrade.config.settings import Settings
+from arbitrade.storage.pg_store import PgStore
+
+
+class ConfigSection(BaseModel):
+    id: int | None = None
+    name: str
+    description: str | None = None
+    updated_at: datetime | None = None
+
+
+class ConfigSetting(BaseModel):
+    key: str
+    section: str
+    value_json: str
+    value_type: str
+    is_secret: bool = False
+    is_runtime_reloadable: bool = False
+    updated_at: datetime | None = None
+    updated_by: str | None = None
+
+
+class ConfigPairing(BaseModel):
+    id: int | None = None
+    base_asset: str
+    quote_asset: str
+    enabled: bool = True
+    source: str
+    created_at: datetime | None = None
+    updated_at: datetime | None = None
+
+
+class ConfigBacktestingDefaults(BaseModel):
+    starting_balances: dict[str, float] | None = None
+    trade_capital: float | None = None
+    min_profit_threshold: float | None = None
+    slippage_bps: int | None = None
+    execution_latency_ms: int | None = None
+
+
+class ConfigurationService:
+    """Manages application configuration from environment and database sources."""
+
+    def __init__(self, settings: Settings, store: PgStore, audit_repo: Any) -> None:
+        self._settings = settings
+        self._store = store
+        self._audit_repo = audit_repo
+        self._config_version = 0
+        self._loaded_settings: dict[str, Any] = {}
+        self._last_updated_at: datetime | None = None
+
+    async def load_database_settings(self) -> None:
+        """Load user settings from database and merge with defaults."""
+        # Import here to avoid circular imports
+        from arbitrade.storage.repositories import ConfigSettingRepository
+
+        setting_repo = ConfigSettingRepository(self._store)
+
+        # Load all settings from database
+        db_settings = await setting_repo.list_settings()
+
+        # Convert to dictionary for easy access
+        for setting in db_settings:
+            # Parse JSON value based on type
+            if setting.value_type == "str":
+                parsed_value = setting.value_json
+            elif setting.value_type == "int":
+                parsed_value = int(setting.value_json)  # type: ignore
+            elif setting.value_type == "float":
+                parsed_value = float(setting.value_json)  # type: ignore
+            elif setting.value_type == "bool":
+                parsed_value = setting.value_json.lower() == "true"  # type: ignore
+            elif setting.value_type == "list":
+                parsed_value = orjson.loads(setting.value_json)
+            elif setting.value_type == "dict":
+                parsed_value = orjson.loads(setting.value_json)
+            else:
+                parsed_value = setting.value_json
+
+            self._loaded_settings[setting.key] = parsed_value
+
+        # Track the latest update time
+        if db_settings:
+            latest_updated = max(
+                setting.updated_at for setting in db_settings if setting.updated_at
+            )
+            self._last_updated_at = latest_updated
+
+        # Initialize with default values from settings model
+        self._initialize_default_settings()
+
+    def _initialize_default_settings(self) -> None:
+        """Initialize default settings from the Settings model."""
+        # This is a placeholder - in a real implementation we'd map
+        # the Settings model fields to config keys
+        pass
+
+    def get_setting(self, key: str, default: Any = None) -> Any:
+        """Get a configuration setting value."""
+        return self._loaded_settings.get(key, default)
+
+    def get_config_version(self) -> int:
+        """Get the current configuration version for hot-reloading."""
+        return self._config_version
+
+    def get_last_updated_at(self) -> datetime | None:
+        """Get the timestamp of the last configuration update."""
+        return self._last_updated_at
+
+    async def is_config_outdated(self) -> bool:
+        """Check if configuration has been updated since last load."""
+        # Import here to avoid circular imports
+        from arbitrade.storage.repositories import ConfigSettingRepository
+
+        setting_repo = ConfigSettingRepository(self._store)
+
+        # Get the latest update timestamp from database
+        latest_db_update = await setting_repo.get_latest_updated_at()
+
+        # Compare with our last loaded timestamp
+        if latest_db_update and self._last_updated_at:
+            return latest_db_update > self._last_updated_at
+        elif latest_db_update:
+            return True
+        return False
+
+    async def reload_if_changed(self) -> bool:
+        """Reload configuration if it has been updated in the database."""
+        if await self.is_config_outdated():
+            await self.load_database_settings()
+            self._config_version += 1
+            return True
+        return False
+
+    async def set_setting(self, key: str, value: Any, updated_by: str | None = None) -> None:
+        """Set a configuration setting value and persist to database."""
+        # Import here to avoid circular imports
+        from arbitrade.storage.repositories import ConfigSettingRepository
+
+        setting_repo = ConfigSettingRepository(self._store)
+
+        # Convert value to JSON string and determine type
+        if isinstance(value, str):
+            value_json = value
+            value_type = "str"
+        elif isinstance(value, int):
+            value_json = str(value)
+            value_type = "int"
+        elif isinstance(value, float):
+            value_json = str(value)
+            value_type = "float"
+        elif isinstance(value, bool):
+            value_json = str(value).lower()
+            value_type = "bool"
+        elif isinstance(value, list):
+            value_json = orjson.dumps(value).decode("utf-8")
+            value_type = "list"
+        elif isinstance(value, dict):
+            value_json = orjson.dumps(value).decode("utf-8")
+            value_type = "dict"
+        else:
+            value_json = str(value)
+            value_type = "str"
+
+        # Create or update setting
+        setting = ConfigSetting(
+            key=key,
+            section="general",  # Default section
+            value_json=value_json,
+            value_type=value_type,
+            is_secret=False,
+            is_runtime_reloadable=False,
+            updated_by=updated_by,
+        )
+
+        # Check if setting exists
+        existing_setting = await setting_repo.get_setting(key)
+        if existing_setting:
+            # Update existing setting
+            updated_setting = await setting_repo.update_setting(key, setting)
+        else:
+            # Create new setting
+            updated_setting = await setting_repo.create_setting(setting)
+
+        # Update in-memory cache
+        self._loaded_settings[key] = value
+
+        # Update version for hot reloading
+        self._config_version += 1
+
+        # Update last updated timestamp
+        self._last_updated_at = updated_setting.updated_at
+
+    def get_all_settings(self) -> dict[str, Any]:
+        """Get all configuration settings."""
+        return self._loaded_settings.copy()
+
+    # --- Pairing & Fee Management ---
+
+    def _pairing_repo(self):  # type: ignore
+        from arbitrade.storage.repositories import ConfigPairingRepository
+
+        return ConfigPairingRepository(self._store)
+
+    async def list_pairings(self) -> list[ConfigPairing]:
+        """List all currency pairings."""
+        r = self._pairing_repo()  # type: ignore[no-untyped-call]
+        p = await r.list_pairings()
+        return p  # type: ignore[no-any-return]
+
+    async def create_pairing(
+        self, base_asset: str, quote_asset: str, source: str = "manual"
+    ) -> ConfigPairing:
+        """Create a new currency pairing."""
+        r = self._pairing_repo()  # type: ignore[no-untyped-call]
+        e = await r.get_pairing(base_asset, quote_asset)
+        if e:
+            return e  # type: ignore[no-any-return]
+        pairing = ConfigPairing(
+            base_asset=base_asset, quote_asset=quote_asset, enabled=True, source=source
+        )
+        p = r.create_pairing(pairing)
+        return p  # type: ignore[no-any-return]

src/arbitrade/config/settings.py

@@ -1,7 +1,6 @@
 from __future__ import annotations
 
 from functools import lru_cache
-from pathlib import Path
 
 from pydantic import Field, field_validator, model_validator
 from pydantic_settings import BaseSettings, SettingsConfigDict
@@ -32,72 +31,56 @@ class Settings(BaseSettings):
     )
 
     alerts_enabled: bool = Field(default=True, alias="ALERTS_ENABLED")
-    alert_min_severity: str = Field(
-        default="warning", alias="ALERT_MIN_SEVERITY")
-    alert_dedup_seconds: float = Field(
-        default=30.0, alias="ALERT_DEDUP_SECONDS")
-    alert_on_trade_events: bool = Field(
-        default=True, alias="ALERT_ON_TRADE_EVENTS")
-    alert_on_error_events: bool = Field(
-        default=True, alias="ALERT_ON_ERROR_EVENTS")
-    alert_on_threshold_events: bool = Field(
-        default=True, alias="ALERT_ON_THRESHOLD_EVENTS")
-    alert_on_system_events: bool = Field(
-        default=True, alias="ALERT_ON_SYSTEM_EVENTS")
+    alert_min_severity: str = Field(default="warning", alias="ALERT_MIN_SEVERITY")
+    alert_dedup_seconds: float = Field(default=30.0, alias="ALERT_DEDUP_SECONDS")
+    alert_on_trade_events: bool = Field(default=True, alias="ALERT_ON_TRADE_EVENTS")
+    alert_on_error_events: bool = Field(default=True, alias="ALERT_ON_ERROR_EVENTS")
+    alert_on_threshold_events: bool = Field(default=True, alias="ALERT_ON_THRESHOLD_EVENTS")
+    alert_on_system_events: bool = Field(default=True, alias="ALERT_ON_SYSTEM_EVENTS")
 
-    telegram_alerts_enabled: bool = Field(
-        default=False, alias="TELEGRAM_ALERTS_ENABLED")
-    telegram_bot_token: str | None = Field(
-        default=None, alias="TELEGRAM_BOT_TOKEN")
-    telegram_chat_id: str | None = Field(
-        default=None, alias="TELEGRAM_CHAT_ID")
+    telegram_alerts_enabled: bool = Field(default=False, alias="TELEGRAM_ALERTS_ENABLED")
+    telegram_bot_token: str | None = Field(default=None, alias="TELEGRAM_BOT_TOKEN")
+    telegram_chat_id: str | None = Field(default=None, alias="TELEGRAM_CHAT_ID")
 
-    discord_alerts_enabled: bool = Field(
-        default=False, alias="DISCORD_ALERTS_ENABLED")
-    discord_webhook_url: str | None = Field(
-        default=None, alias="DISCORD_WEBHOOK_URL")
+    discord_alerts_enabled: bool = Field(default=False, alias="DISCORD_ALERTS_ENABLED")
+    discord_webhook_url: str | None = Field(default=None, alias="DISCORD_WEBHOOK_URL")
 
-    email_alerts_enabled: bool = Field(
-        default=False, alias="EMAIL_ALERTS_ENABLED")
+    email_alerts_enabled: bool = Field(default=False, alias="EMAIL_ALERTS_ENABLED")
     email_smtp_host: str | None = Field(default=None, alias="EMAIL_SMTP_HOST")
     email_smtp_port: int = Field(default=587, alias="EMAIL_SMTP_PORT")
-    email_smtp_username: str | None = Field(
-        default=None, alias="EMAIL_SMTP_USERNAME")
-    email_smtp_password: str | None = Field(
-        default=None, alias="EMAIL_SMTP_PASSWORD")
-    email_alert_from: str | None = Field(
-        default=None, alias="EMAIL_ALERT_FROM")
+    email_smtp_username: str | None = Field(default=None, alias="EMAIL_SMTP_USERNAME")
+    email_smtp_password: str | None = Field(default=None, alias="EMAIL_SMTP_PASSWORD")
+    email_alert_from: str | None = Field(default=None, alias="EMAIL_ALERT_FROM")
     email_alert_to: str | None = Field(default=None, alias="EMAIL_ALERT_TO")
     email_smtp_use_tls: bool = Field(default=True, alias="EMAIL_SMTP_USE_TLS")
 
-    duckdb_path: Path = Field(default=Path(
-        "./data/arbitrade.duckdb"), alias="DUCKDB_PATH")
+    # PostgreSQL connection settings
+    pg_host: str = Field(default="192.168.88.35", alias="PG_HOST")
+    pg_port: int = Field(default=5432, alias="PG_PORT")
+    pg_database: str = Field(default="arbitrade", alias="PG_DATABASE")
+    pg_user: str = Field(default="arbitrade", alias="PG_USER")
+    pg_password: str = Field(default="arbitrade", alias="PG_PASSWORD")
+    pg_min_connections: int = Field(default=2, alias="PG_MIN_CONNECTIONS")
+    pg_max_connections: int = Field(default=10, alias="PG_MAX_CONNECTIONS")
 
-    kraken_rest_url: str = Field(
-        default="https://api.kraken.com", alias="KRAKEN_REST_URL")
-    kraken_ws_url: str = Field(
-        default="wss://ws.kraken.com/v2", alias="KRAKEN_WS_URL")
+    kraken_rest_url: str = Field(default="https://api.kraken.com", alias="KRAKEN_REST_URL")
+    kraken_ws_url: str = Field(default="wss://ws.kraken.com/v2", alias="KRAKEN_WS_URL")
     kraken_private_rate_limit_seconds: float = Field(
         default=1.0, alias="KRAKEN_PRIVATE_RATE_LIMIT_SECONDS"
     )
-    kraken_http_timeout_seconds: float = Field(
-        default=10.0, alias="KRAKEN_HTTP_TIMEOUT_SECONDS")
-    kraken_retry_attempts: int = Field(
-        default=3, alias="KRAKEN_RETRY_ATTEMPTS")
+    kraken_http_timeout_seconds: float = Field(default=10.0, alias="KRAKEN_HTTP_TIMEOUT_SECONDS")
+    kraken_retry_attempts: int = Field(default=3, alias="KRAKEN_RETRY_ATTEMPTS")
     kraken_retry_base_delay_seconds: float = Field(
         default=0.25, alias="KRAKEN_RETRY_BASE_DELAY_SECONDS"
     )
     kraken_api_key: str | None = Field(default=None, alias="KRAKEN_API_KEY")
-    kraken_api_secret: str | None = Field(
-        default=None, alias="KRAKEN_API_SECRET")
+    kraken_api_secret: str | None = Field(default=None, alias="KRAKEN_API_SECRET")
     kraken_api_key_permissions: str = Field(
         default="query,trade",
         alias="KRAKEN_API_KEY_PERMISSIONS",
     )
-    ws_heartbeat_timeout_seconds: float = Field(
-        default=20.0, alias="WS_HEARTBEAT_TIMEOUT_SECONDS")
-    ws_max_staleness_seconds: float = Field(
-        default=5.0, alias="WS_MAX_STALENESS_SECONDS")
+    ws_heartbeat_timeout_seconds: float = Field(default=20.0, alias="WS_HEARTBEAT_TIMEOUT_SECONDS")
+    ws_max_staleness_seconds: float = Field(default=5.0, alias="WS_MAX_STALENESS_SECONDS")
     strategy_enable_stat_arb_experiment: bool = Field(
         default=False,
         alias="STRATEGY_ENABLE_STAT_ARB_EXPERIMENT",
@@ -120,29 +103,20 @@ class Settings(BaseSettings):
     )
     paper_trading_mode: bool = Field(default=True, alias="PAPER_TRADING_MODE")
     trade_capital_usd: float = Field(default=100.0, alias="TRADE_CAPITAL_USD")
-    max_trade_capital_usd: float = Field(
-        default=100.0, alias="MAX_TRADE_CAPITAL_USD")
-    max_concurrent_trades: int | None = Field(
-        default=None, alias="MAX_CONCURRENT_TRADES")
+    max_trade_capital_usd: float = Field(default=100.0, alias="MAX_TRADE_CAPITAL_USD")
+    max_concurrent_trades: int | None = Field(default=None, alias="MAX_CONCURRENT_TRADES")
     max_exposure_per_asset_usd: float | None = Field(
         default=None,
         alias="MAX_EXPOSURE_PER_ASSET_USD",
     )
-    quote_balance_asset: str = Field(
-        default="USD", alias="QUOTE_BALANCE_ASSET")
-    min_order_size_usd: float | None = Field(
-        default=None, alias="MIN_ORDER_SIZE_USD")
+    quote_balance_asset: str = Field(default="USD", alias="QUOTE_BALANCE_ASSET")
+    min_order_size_usd: float | None = Field(default=None, alias="MIN_ORDER_SIZE_USD")
     kill_switch_active: bool = Field(default=False, alias="KILL_SWITCH_ACTIVE")
-    daily_loss_limit_usd: float | None = Field(
-        default=None, alias="DAILY_LOSS_LIMIT_USD")
-    cumulative_loss_limit_usd: float | None = Field(
-        default=None, alias="CUMULATIVE_LOSS_LIMIT_USD")
-    max_source_latency_ms: float | None = Field(
-        default=None, alias="MAX_SOURCE_LATENCY_MS")
-    max_apply_latency_ms: float | None = Field(
-        default=None, alias="MAX_APPLY_LATENCY_MS")
-    max_consecutive_failures: int | None = Field(
-        default=None, alias="MAX_CONSECUTIVE_FAILURES")
+    daily_loss_limit_usd: float | None = Field(default=None, alias="DAILY_LOSS_LIMIT_USD")
+    cumulative_loss_limit_usd: float | None = Field(default=None, alias="CUMULATIVE_LOSS_LIMIT_USD")
+    max_source_latency_ms: float | None = Field(default=None, alias="MAX_SOURCE_LATENCY_MS")
+    max_apply_latency_ms: float | None = Field(default=None, alias="MAX_APPLY_LATENCY_MS")
+    max_consecutive_failures: int | None = Field(default=None, alias="MAX_CONSECUTIVE_FAILURES")
 
     fernet_key: str | None = Field(default=None, alias="FERNET_KEY")
 
@@ -159,8 +133,7 @@ class Settings(BaseSettings):
     def _validate_log_level(cls, value: str) -> str:
         normalized = value.strip().upper()
         if normalized not in {"DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"}:
-            raise ValueError(
-                "LOG_LEVEL must be one of: DEBUG, INFO, WARNING, ERROR, CRITICAL")
+            raise ValueError("LOG_LEVEL must be one of: DEBUG, INFO, WARNING, ERROR, CRITICAL")
         return normalized
 
     @field_validator("alert_min_severity")
@@ -168,19 +141,16 @@ class Settings(BaseSettings):
     def _validate_alert_severity(cls, value: str) -> str:
         normalized = value.strip().lower()
         if normalized not in {"info", "warning", "error", "critical"}:
-            raise ValueError(
-                "ALERT_MIN_SEVERITY must be one of: info, warning, error, critical")
+            raise ValueError("ALERT_MIN_SEVERITY must be one of: info, warning, error, critical")
         return normalized
 
     @model_validator(mode="after")
     def _validate_security_constraints(self) -> Settings:
         if bool(self.dashboard_auth_username) ^ bool(self.dashboard_auth_password):
-            raise ValueError(
-                "dashboard auth requires both username and password")
+            raise ValueError("dashboard auth requires both username and password")
 
         if bool(self.kraken_api_key) ^ bool(self.kraken_api_secret):
-            raise ValueError(
-                "Kraken API auth requires both API key and secret")
+            raise ValueError("Kraken API auth requires both API key and secret")
 
         permissions = {
             token.strip().lower()
@@ -188,11 +158,9 @@ class Settings(BaseSettings):
             if token.strip()
         }
         if permissions and ("query" not in permissions or "trade" not in permissions):
-            raise ValueError(
-                "KRAKEN_API_KEY_PERMISSIONS must include query and trade")
+            raise ValueError("KRAKEN_API_KEY_PERMISSIONS must include query and trade")
         if "withdraw" in permissions or "withdrawals" in permissions:
-            raise ValueError(
-                "KRAKEN_API_KEY_PERMISSIONS must not include withdrawal scope")
+            raise ValueError("KRAKEN_API_KEY_PERMISSIONS must not include withdrawal scope")
 
         if self.alert_dedup_seconds < 0.0:
             raise ValueError("ALERT_DEDUP_SECONDS must be >= 0")
@@ -208,8 +176,7 @@ class Settings(BaseSettings):
                 "STRATEGY_STAT_ARB_ENTRY_ZSCORE must be greater than STRATEGY_STAT_ARB_EXIT_ZSCORE"
             )
         if self.strategy_stat_arb_max_holding_seconds <= 0.0:
-            raise ValueError(
-                "STRATEGY_STAT_ARB_MAX_HOLDING_SECONDS must be > 0")
+            raise ValueError("STRATEGY_STAT_ARB_MAX_HOLDING_SECONDS must be > 0")
 
         return self
 

src/arbitrade/dashboard/__init__.py

@@ -0,0 +1 @@
+"""Dashboard module for monitoring and controlling the arbitrage bot."""

src/arbitrade/dashboard/context.py

@@ -0,0 +1,63 @@
+from __future__ import annotations
+
+from fastapi import Request
+
+from arbitrade.storage.repositories import (
+    BacktestJobRepository,
+)
+
+
+async def _recent_backtest_reports(request: Request) -> list[dict[str, object]]:
+    repo = BacktestJobRepository(request.app.state.store)
+    jobs = await repo.list_jobs(limit=5)
+    reports = []
+    for job in jobs:
+        report: dict[str, object] = {
+            "id": str(job.id),
+            "status": job.status,
+        }
+        if job.created_at is not None:
+            report["created_at"] = job.created_at.isoformat()
+        if job.finished_at is not None:
+            report["finished_at"] = job.finished_at.isoformat()
+        reports.append(report)
+    return reports
+
+
+async def _backtesting_panel_context(
+    request: Request,
+    *,
+    status: str = "idle",
+    message: str = "Configure a replay run and execute backtest.",
+    latest_report: dict[str, object] | None = None,
+    defaults: dict[str, str] | None = None,
+) -> dict[str, object]:
+    default_values = {
+        "symbols": "",
+        "start_time": "",
+        "end_time": "",
+        "starting_balances": "USD=1000.0",
+        "trade_capital": "100.0",
+        "min_profit_threshold": "0.0005",
+        "fee_profile": "api",
+        "custom_fee_rate": "",
+        "slippage_bps": "4.0",
+        "execution_latency_ms": "20.0",
+    }
+    if defaults is not None:
+        default_values.update(defaults)
+
+    reports = await _recent_backtest_reports(request)
+    latest = latest_report or (reports[0] if reports else None)
+
+    return {
+        "status": status,
+        "message": message,
+        "flash_message": "",
+        "no_enabled_pairings": False,
+        "latest_report": latest,
+        "recent_reports": reports,
+        "run_endpoint": "/dashboard/backtesting/run",
+        "reports_endpoint": "/dashboard/api/backtesting/reports",
+        **default_values,
+    }

src/arbitrade/detection/benchmark.py

@@ -47,7 +47,7 @@ def _build_detector_and_books() -> tuple[IncrementalCycleDetector, dict[str, Ord
 
     detector = IncrementalCycleDetector(
         index,
-        fee_rate=0.001,
+        fee_rate=0.001,  # synthetic benchmark: uses fixed rate, not API-sourced
         min_profit_threshold=0.001,
         max_depth_levels=5,
         max_book_age_seconds=10.0,

src/arbitrade/exchange/fee_service.py

@@ -0,0 +1,142 @@
+"""Fee service -- fetch Kraken account fee tier, sync pair fees, persist snapshots."""
+
+from __future__ import annotations
+
+import asyncio
+from datetime import UTC, datetime
+
+import orjson
+import structlog
+
+from arbitrade.exchange.kraken_rest import KrakenRestClient
+from arbitrade.storage.pg_store import PgStore
+from arbitrade.storage.repositories import (
+    KrakenAccountSnapshot,
+    KrakenAccountSnapshotRepository,
+)
+
+_LOG = structlog.get_logger(__name__)
+
+_FEE_REFRESH_INTERVAL_SECONDS = 86400  # 1 day
+
+
+async def fetch_and_store_account_snapshot(
+    client: KrakenRestClient,
+    store: PgStore,
+) -> KrakenAccountSnapshot | None:
+    """Query TradeVolume + TradeBalance, persist as snapshot.
+
+    Returns the snapshot or None if either call failed.
+    """
+    repo = KrakenAccountSnapshotRepository(store)
+
+    try:
+        volume_data = await client.trade_volume()
+    except Exception:
+        _LOG.exception("trade_volume_fetch_failed")
+        return None
+
+    try:
+        balance_data = await client.trade_balance()
+    except Exception:
+        _LOG.exception("trade_balance_fetch_failed")
+        return None
+
+    fee_tier = volume_data.get("fee_tier") if isinstance(volume_data, dict) else None
+    fees_dict = volume_data.get("fees") if isinstance(volume_data, dict) else None
+    fees_maker = volume_data.get("fees_maker") if isinstance(volume_data, dict) else None
+    currency = volume_data.get("currency")
+    thirty_day_volume_str = volume_data.get("volume")
+
+    maker_fee = None
+    taker_fee = None
+    fee_tier_str = str(fee_tier) if fee_tier is not None else None
+
+    # Extract current tier's maker/taker rates from fees dict
+    if isinstance(fees_dict, dict) and fee_tier_str is not None:
+        tier_fees = fees_dict.get(fee_tier_str)
+        if isinstance(tier_fees, dict):
+            maker_val = tier_fees.get("maker")
+            taker_val = tier_fees.get("taker")
+            maker_fee = float(maker_val) if maker_val is not None else None
+            taker_fee = float(taker_val) if taker_val is not None else None
+
+    # Build fee schedule as combined dict
+    fee_schedule: dict[str, object] = {}
+    if isinstance(fees_dict, dict):
+        fee_schedule["fees"] = fees_dict
+    if isinstance(fees_maker, dict):
+        fee_schedule["fees_maker"] = fees_maker
+    if currency is not None:
+        fee_schedule["currency"] = currency
+
+    thirty_day_volume = float(thirty_day_volume_str) if thirty_day_volume_str is not None else None
+
+    snapshot = KrakenAccountSnapshot(
+        snapshot_at=datetime.now(UTC),
+        fee_tier=fee_tier_str,
+        maker_fee=maker_fee,
+        taker_fee=taker_fee,
+        thirty_day_volume=thirty_day_volume,
+        trade_balance_raw=balance_data if isinstance(balance_data, dict) else None,
+        fee_schedule_raw=fee_schedule if fee_schedule else None,
+    )
+
+    await repo.insert_snapshot(snapshot)
+    _LOG.info(
+        "account_snapshot_stored",
+        fee_tier=fee_tier_str,
+        maker_fee=maker_fee,
+        taker_fee=taker_fee,
+    )
+
+    # Fetch wallet balances and write to portfolio_snapshots
+    try:
+        wallet_balances = await client.balances()
+        total_value = 0.0
+        if isinstance(balance_data, dict):
+            eb = balance_data.get("eb")
+            total_value = float(eb) if eb is not None else 0.0
+        async with store.pool.acquire() as conn:
+            await conn.execute(
+                "INSERT INTO portfolio_snapshots"
+                " (snapshot_at, balances, total_value_usd) VALUES ($1, $2, $3)",
+                datetime.now(UTC),
+                orjson.dumps(wallet_balances).decode("utf-8") if wallet_balances else None,
+                total_value,
+            )
+        _LOG.info("portfolio_snapshot_stored", total_value_usd=total_value)
+    except Exception:
+        _LOG.exception("balances_fetch_or_store_failed")
+
+    return snapshot
+
+
+async def run_fee_sync_loop(
+    client: KrakenRestClient,
+    store: PgStore,
+    stop_event: asyncio.Event,
+) -> None:
+    """Periodic loop: fetch account snapshot every hour.
+
+    Runs until stop_event is set.
+    """
+    _LOG.info("fee_sync_loop_started", interval_s=_FEE_REFRESH_INTERVAL_SECONDS)
+
+    while not stop_event.is_set():
+        try:
+            await fetch_and_store_account_snapshot(client, store)
+        except Exception:
+            _LOG.exception("fee_sync_loop_iteration_failed")
+
+        # Wait with stop_event check
+        try:
+            await asyncio.wait_for(
+                stop_event.wait(),
+                timeout=_FEE_REFRESH_INTERVAL_SECONDS,
+            )
+            break  # stop_event was set
+        except TimeoutError:
+            pass  # timeout elapsed, loop again
+
+    _LOG.info("fee_sync_loop_stopped")

src/arbitrade/exchange/kraken_rest.py

@@ -279,3 +279,34 @@ class KrakenRestClient:
             "/0/private/CancelOrder",
             data={"txid": order_id},
         )
+
+    async def trade_volume(self, *, pair: str | None = None) -> dict[str, Any]:
+        """Query Kraken TradeVolume for fee tier, 30d volume, and fee schedule.
+
+        Returns dict with keys: currency, volume, fees (dict of tiers),
+        fees_maker (dict of tier->fee mappings), fee_tier (current tier).
+        If pair provided, returns pair-specific fee info.
+        """
+        data: dict[str, str] = {}
+        if pair is not None:
+            data["pair"] = pair
+        return await self._throttled_private_call(
+            "/0/private/TradeVolume",
+            data=data if data else None,
+        )
+
+    async def trade_balance(self, *, asset: str | None = None) -> dict[str, Any]:
+        """Query Kraken TradeBalance for equity, trade balance, margin info.
+
+        Returns dict with keys: eb (equivalent balance/equity),
+        tb (trade balance), m (margin amount), n (unrealized net P&L),
+        c (cost basis), v (current valuation), e (equity).
+        If asset provided, returns asset-class-specific balance.
+        """
+        data: dict[str, str] = {}
+        if asset is not None:
+            data["asset"] = asset
+        return await self._throttled_private_call(
+            "/0/private/TradeBalance",
+            data=data if data else None,
+        )

src/arbitrade/exchange/kraken_ws.py

@@ -32,6 +32,7 @@ class KrakenWsClient:
         self._alert_notifier = alert_notifier
         self._has_connected_once = False
         self._was_disconnected = False
+        self._subscribed_symbols: list[str] = []
 
     @property
     def is_stale(self) -> bool:
@@ -44,29 +45,63 @@ class KrakenWsClient:
     async def stop(self) -> None:
         self._stop.set()
 
+    def set_subscribed_symbols(self, symbols: list[str]) -> None:
+        """Set the list of symbols to subscribe to on (re)connect."""
+        self._subscribed_symbols = list(symbols)
+
+    async def _subscribe(self, ws: Any) -> None:
+        """Send Kraken WS v2 subscribe message for book channel."""
+        if not self._subscribed_symbols:
+            _LOG.warning("kraken_ws_no_symbols_to_subscribe")
+            return
+        depth = 10
+        if hasattr(self._settings, "kraken_ws_book_depth"):
+            depth = self._settings.kraken_ws_book_depth
+        msg = orjson.dumps(
+            {
+                "method": "subscribe",
+                "params": {
+                    "channel": "book",
+                    "symbol": self._subscribed_symbols,
+                    "depth": depth,
+                },
+            }
+        )
+        await ws.send(msg)
+        _LOG.info(
+            "kraken_ws_subscribed",
+            symbol_count=len(self._subscribed_symbols),
+            symbols=self._subscribed_symbols,
+        )
+
     async def connect_stream(self) -> AsyncIterator[WsMessage]:
         delay = 1.0
         while not self._stop.is_set():
             try:
-                async with websockets.connect(
-                    self._settings.kraken_ws_url, max_size=2_000_000
-                ) as ws:
-                    _LOG.info("kraken_ws_connected", url=self._settings.kraken_ws_url)
+                url = self._settings.kraken_ws_url
+                async with websockets.connect(url, max_size=2_000_000) as ws:
+                    _LOG.info("kraken_ws_connected", url=url)
                     if self._has_connected_once and self._was_disconnected:
                         await self._notify(
                             category="system",
                             severity="info",
                             title="WebSocket reconnected",
                             message="Kraken WebSocket connection restored.",
-                            details={"url": self._settings.kraken_ws_url},
+                            details={"url": url},
                         )
                     self._has_connected_once = True
                     self._was_disconnected = False
                     delay = 1.0
+                    await self._subscribe(ws)
                     async for raw in self._recv_loop(ws):
                         yield raw
             except Exception as exc:
-                _LOG.warning("kraken_ws_disconnected", error=str(exc), reconnect_in=delay)
+                log = (
+                    "kraken_ws_disconnected_first_time"
+                    if not self._has_connected_once
+                    else "kraken_ws_disconnected"
+                )
+                _LOG.warning(log, error=str(exc), reconnect_in=delay)
                 self._was_disconnected = True
                 await self._notify(
                     category="system",

src/arbitrade/execution/sequencer.py

@@ -158,7 +158,7 @@ class TriangularExecutionSequencer:
                 )
             except Exception as exc:
                 if self._audit_repository is not None:
-                    self._audit_repository.insert(
+                    await self._audit_repository.insert(
                         AuditRecord(
                             occurred_at=datetime.now(UTC),
                             actor="execution_engine",
@@ -265,7 +265,7 @@ class TriangularExecutionSequencer:
             )
 
         if self._audit_repository is not None:
-            self._audit_repository.insert(
+            await self._audit_repository.insert(
                 AuditRecord(
                     occurred_at=datetime.now(UTC),
                     actor="execution_engine",

src/arbitrade/logging/__init__.py

@@ -0,0 +1 @@
+"""Logging package — DB sink, maintenance tasks."""

src/arbitrade/logging/db_sink.py

@@ -0,0 +1,119 @@
+"""DB sink — writes structlog events to app_logs table via background queue."""
+
+from __future__ import annotations
+
+import asyncio
+from datetime import UTC, datetime
+from typing import Any
+
+import structlog
+
+from arbitrade.storage.pg_store import PgStore
+from arbitrade.storage.repositories import LogRecord, LogRepository
+
+_LOG = structlog.get_logger(__name__)
+
+
+class DbSinkProcessor:
+    """structlog processor that queues log events for DB writes.
+
+    Must be registered in the structlog processor chain. The consumer
+    task must be started on app init via ``start_consumer(store)``.
+    """
+
+    def __init__(self) -> None:
+        self._queue: asyncio.Queue[dict[str, Any]] = asyncio.Queue(maxsize=2000)
+        self._consumer_task: asyncio.Task[None] | None = None
+
+    def __call__(self, logger: Any, method_name: str, event_dict: dict[str, Any]) -> dict[str, Any]:
+        """Processor — called for every structlog event. Non-blocking."""
+        try:
+            self._queue.put_nowait(dict(event_dict))
+        except asyncio.QueueFull:
+            pass  # drop event if queue full, avoid backpressure
+        return event_dict
+
+    def start_consumer(self, store: PgStore) -> None:
+        """Start background consumer task."""
+        if self._consumer_task is not None and not self._consumer_task.done():
+            return
+        self._consumer_task = asyncio.create_task(self._consume(store), name="log_db_sink")
+
+    async def stop_consumer(self) -> None:
+        """Drain queue and cancel consumer."""
+        if self._consumer_task is None:
+            return
+        self._consumer_task.cancel()
+        try:
+            await self._consumer_task
+        except asyncio.CancelledError:
+            pass
+        self._consumer_task = None
+        # Flush remaining
+        await self._flush(store=None)  # type: ignore[call-arg]
+
+    async def _consume(self, store: PgStore) -> None:
+        repo = LogRepository(store)
+        while True:
+            try:
+                event = await self._queue.get()
+                await self._write_one(repo, event)
+            except asyncio.CancelledError:
+                break
+            except Exception:
+                pass  # swallow consumer errors, never crash
+        # Final flush
+        await self._flush(repo)
+
+    async def _write_one(self, repo: LogRepository, event: dict[str, Any]) -> None:
+        recorded_at = event.pop("timestamp", None)
+        if isinstance(recorded_at, str):
+            try:
+                recorded_at = datetime.fromisoformat(recorded_at)
+            except ValueError:
+                recorded_at = datetime.now(UTC)
+        elif not isinstance(recorded_at, datetime):
+            recorded_at = datetime.now(UTC)
+
+        level = str(event.pop("level", "info")).upper()
+        logger = str(event.pop("logger", "root"))
+        message = str(event.pop("event", event.pop("message", "")))
+        context = {k: v for k, v in event.items() if not k.startswith("_")} if event else None
+
+        record = LogRecord(
+            recorded_at=recorded_at,
+            level=level,
+            logger=logger,
+            message=message,
+            context=context if context else None,
+        )
+        try:
+            await repo.insert(record)
+        except Exception:
+            pass  # never crash from DB write failure
+
+    async def _flush(self, repo: LogRepository | None) -> None:
+        drained = 0
+        while not self._queue.empty() and drained < 500:
+            try:
+                event = self._queue.get_nowait()
+                if repo is not None:
+                    await self._write_one(repo, event)
+                drained += 1
+            except asyncio.QueueEmpty:
+                break
+            except Exception:
+                pass
+
+
+# Module-level singleton
+_db_sink = DbSinkProcessor()
+
+
+def get_db_sink() -> DbSinkProcessor:
+    return _db_sink
+
+
+def db_sink_processor(logger: Any, method_name: str, event_dict: dict[str, Any]) -> dict[str, Any]:
+    """Standalone processor function wrapping the singleton."""
+    return _db_sink(logger, method_name, event_dict)

src/arbitrade/logging/maintenance.py

@@ -0,0 +1,60 @@
+"""Log maintenance — aggregation and archiving tasks."""
+
+from __future__ import annotations
+
+import asyncio
+from datetime import UTC, datetime, timedelta
+
+import structlog
+
+from arbitrade.storage.pg_store import PgStore
+from arbitrade.storage.repositories import LogAggregationRepository, LogArchiveRepository
+
+_LOG = structlog.get_logger(__name__)
+
+_AGGREGATE_INTERVAL = 3600  # 1 hour
+_ARCHIVE_INTERVAL = 86400  # 1 day
+_RETENTION_DAYS = 30
+
+
+async def run_log_aggregation(store: PgStore) -> None:
+    """Aggregate log counts for the last 2 hours across all periods."""
+    repo = LogAggregationRepository(store)
+    since = datetime.now(UTC) - timedelta(hours=2)
+    periods = ["1h", "1d", "1w", "1mo"]
+    for period in periods:
+        try:
+            await repo.aggregate_since(since, period)
+        except Exception:
+            _LOG.exception("log_aggregation_failed", period=period)
+    _LOG.info("log_aggregation_complete", since=since.isoformat())
+
+
+async def run_log_archive(store: PgStore, retention_days: int = _RETENTION_DAYS) -> int:
+    """Archive log entries older than retention_days."""
+    cutoff = datetime.now(UTC) - timedelta(days=retention_days)
+    repo = LogArchiveRepository(store)
+    count = await repo.archive_before(cutoff)
+    if count > 0:
+        _LOG.info("log_archive_complete", cutoff=cutoff.isoformat(), archived=count)
+    return count
+
+
+async def run_log_aggregation_loop(store: PgStore) -> None:
+    """Periodic aggregation loop."""
+    while True:
+        try:
+            await run_log_aggregation(store)
+        except Exception:
+            _LOG.exception("log_aggregation_loop_error")
+        await asyncio.sleep(_AGGREGATE_INTERVAL)
+
+
+async def run_log_archive_loop(store: PgStore) -> None:
+    """Periodic archive loop."""
+    while True:
+        try:
+            await run_log_archive(store)
+        except Exception:
+            _LOG.exception("log_archive_loop_error")
+        await asyncio.sleep(_ARCHIVE_INTERVAL)