- Consolidated multiline string formatting into single-line for SQL queries in multiple files.
- Adjusted argument formatting in function calls for better alignment and readability.
- Removed unnecessary line breaks and improved spacing in various sections of the codebase.
- Updated test cases to maintain consistency in formatting and improve clarity.
- Introduced a new HTML template for configuring pair fees, allowing users to add, edit, and delete fees for trading pairs.
- Implemented a responsive fee table displaying existing fees with options for editing and deleting.
- Added a form for adding new fees, including fields for base asset, quote asset, market type, and fee rates.
- Removed outdated templates related to backtesting, dashboard, health, and various partials to streamline the codebase.
- Ensured the new fee configuration panel integrates seamlessly with existing endpoints and uses htmx for dynamic updates.
- Introduced new HTML templates for the dashboard, metrics, overview, and backtesting functionalities.
- Implemented partial templates for metrics, overview, audit, controls, and charts to enhance modularity.
- Updated the Jinja2 template resolution logic to support different deployment environments.
- Added a health check template to display the service status.
- Included a test suite to verify the template resolution logic.
- Updated `pyproject.toml` to include new HTML templates in the package data.
- Introduced backtesting page and fragment in the dashboard for running backtests and viewing recent reports.
- Implemented backtest run logic with configuration options including event path, starting balances, trade capital, and fee profiles.
- Added recent backtest reports storage and retrieval.
- Created a new strategy module for statistical arbitrage experiments with validation on configuration parameters.
- Updated settings to include parameters for the statistical arbitrage strategy.
- Enhanced dashboard controls to support the new strategy mode.
- Added unit tests for backtesting functionality and strategy validation.
- Updated templates for backtesting UI integration.
- Added synthetic latency profiler scenarios and CLI scripts for baseline generation and regression checks.
- Introduced latency baseline and threshold artifacts for CI enforcement.
- Enhanced CI workflow with latency guardrail checks.
- Updated documentation to include latency profiling commands and performance metrics.
- Added unit tests for latency guardrail evaluation.
- Introduced new tables for audit events and runtime state snapshots in the database schema.
- Created data classes for AuditRecord and RuntimeStateRecord to represent the new entities.
- Implemented AuditRepository and RuntimeStateRepository for inserting and retrieving records.
- Enhanced the dashboard to include an audit trail section, displaying recent audit events.
- Added tests for the new audit repository and runtime lifecycle functionalities.
- Updated settings validation to ensure proper configuration for alerting features.
- Integrated alert notifications across various components, including execution sequencer and loss limits.
- Add IdempotencyKeyFactory for generating unique user references based on execution legs.
- Introduce OrderReconciler to reconcile order statuses with historical data.
- Implement PartialFillRecovery to handle partial fills by canceling orders and placing hedges.
- Create TriangularExecutionSequencer for executing triangular arbitrage strategies.
- Enhance storage with new tables for trades, orders, and PnL events.
- Develop AsyncExecutionWriter for asynchronous writing of execution records to the database.
- Add unit tests for execution persistence, sequencer behavior, fill monitoring, and idempotency checks.
- Update KrakenRestClient to ensure proper payloads for order placement and querying.
- Introduced OpportunityEvent class for structured opportunity data.
- Enhanced IncrementalCycleDetector to generate opportunities based on updated pairs.
- Implemented AsyncOpportunityWriter for persisting opportunities to the database.
- Updated MarketDataFeed to handle opportunity detection and execution in both paper and live trading modes.
- Added unit tests for opportunity detection and persistence.
- Implement IncrementalCycleDetector for scoring based on updated market data.
- Introduce CycleScore class to encapsulate cycle scoring details.
- Update CurrencyGraph and MarketDataFeed to integrate cycle detection.
- Add unit tests for IncrementalCycleDetector functionality.
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