zwitschi
434be86b76
- Added new summary fields: variance, 5th percentile, 95th percentile, VaR (95%), and expected shortfall (95%) to the dashboard. - Updated the display logic for summary metrics to handle non-finite values gracefully. - Modified the chart rendering to include additional percentile points and tail risk metrics in tooltips. test: Introduce unit tests for consumption, costs, and other modules - Created a comprehensive test suite for consumption, costs, equipment, maintenance, production, reporting, and simulation modules. - Implemented fixtures for database setup and teardown using an in-memory SQLite database for isolated testing. - Added tests for creating, listing, and validating various entities, ensuring proper error handling and response validation. refactor: Consolidate parameter tests and remove deprecated files - Merged parameter-related tests into a new test file for better organization and clarity. - Removed the old parameter test file that was no longer in use. - Improved test coverage for parameter creation, listing, and validation scenarios. fix: Ensure proper validation and error handling in API endpoints - Added validation to reject negative amounts in consumption and production records. - Implemented checks to prevent duplicate scenario creation and ensure proper error messages are returned. - Enhanced reporting endpoint tests to validate input formats and expected outputs.
83 lines
2.5 KiB
Python
83 lines
2.5 KiB
Python
from typing import Any, Dict, List, cast
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from fastapi import APIRouter, HTTPException, Request, status
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from pydantic import BaseModel
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from config.database import SessionLocal
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from services.reporting import generate_report
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router = APIRouter(prefix="/api/reporting", tags=["Reporting"])
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def get_db():
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db = SessionLocal()
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try:
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yield db
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finally:
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db.close()
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def _validate_payload(payload: Any) -> List[Dict[str, float]]:
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if not isinstance(payload, list):
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raise HTTPException(
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status_code=status.HTTP_400_BAD_REQUEST,
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detail="Invalid input format",
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)
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typed_payload = cast(List[Any], payload)
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validated: List[Dict[str, float]] = []
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for index, item in enumerate(typed_payload):
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if not isinstance(item, dict):
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raise HTTPException(
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status_code=status.HTTP_400_BAD_REQUEST,
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detail=f"Entry at index {index} must be an object",
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)
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value = cast(Dict[str, Any], item).get("result")
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if not isinstance(value, (int, float)):
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raise HTTPException(
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status_code=status.HTTP_400_BAD_REQUEST,
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detail=f"Entry at index {index} must include numeric 'result'",
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)
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validated.append({"result": float(value)})
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return validated
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class ReportSummary(BaseModel):
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count: int
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mean: float
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median: float
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min: float
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max: float
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std_dev: float
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variance: float
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percentile_10: float
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percentile_90: float
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percentile_5: float
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percentile_95: float
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value_at_risk_95: float
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expected_shortfall_95: float
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@router.post("/summary", response_model=ReportSummary)
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async def summary_report(request: Request):
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payload = await request.json()
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validated_payload = _validate_payload(payload)
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summary = generate_report(validated_payload)
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return ReportSummary(
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count=int(summary["count"]),
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mean=float(summary["mean"]),
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median=float(summary["median"]),
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min=float(summary["min"]),
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max=float(summary["max"]),
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std_dev=float(summary["std_dev"]),
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variance=float(summary["variance"]),
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percentile_10=float(summary["percentile_10"]),
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percentile_90=float(summary["percentile_90"]),
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percentile_5=float(summary["percentile_5"]),
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percentile_95=float(summary["percentile_95"]),
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value_at_risk_95=float(summary["value_at_risk_95"]),
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expected_shortfall_95=float(summary["expected_shortfall_95"]),
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)
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