from typing import Any, Dict, List, cast

from fastapi import APIRouter, HTTPException, Request, status
from pydantic import BaseModel

from config.database import SessionLocal
from services.reporting import generate_report


router = APIRouter(prefix="/api/reporting", tags=["Reporting"])


def get_db():
    db = SessionLocal()
    try:
        yield db
    finally:
        db.close()


def _validate_payload(payload: Any) -> List[Dict[str, float]]:
    if not isinstance(payload, list):
        raise HTTPException(
            status_code=status.HTTP_400_BAD_REQUEST,
            detail="Invalid input format",
        )

    typed_payload = cast(List[Any], payload)

    validated: List[Dict[str, float]] = []
    for index, item in enumerate(typed_payload):
        if not isinstance(item, dict):
            raise HTTPException(
                status_code=status.HTTP_400_BAD_REQUEST,
                detail=f"Entry at index {index} must be an object",
            )
        value = cast(Dict[str, Any], item).get("result")
        if not isinstance(value, (int, float)):
            raise HTTPException(
                status_code=status.HTTP_400_BAD_REQUEST,
                detail=f"Entry at index {index} must include numeric 'result'",
            )
        validated.append({"result": float(value)})
    return validated


class ReportSummary(BaseModel):
    count: int
    mean: float
    median: float
    min: float
    max: float
    std_dev: float
    variance: float
    percentile_10: float
    percentile_90: float
    percentile_5: float
    percentile_95: float
    value_at_risk_95: float
    expected_shortfall_95: float


@router.post("/summary", response_model=ReportSummary)
async def summary_report(request: Request):
    payload = await request.json()
    validated_payload = _validate_payload(payload)
    summary = generate_report(validated_payload)
    return ReportSummary(
        count=int(summary["count"]),
        mean=float(summary["mean"]),
        median=float(summary["median"]),
        min=float(summary["min"]),
        max=float(summary["max"]),
        std_dev=float(summary["std_dev"]),
        variance=float(summary["variance"]),
        percentile_10=float(summary["percentile_10"]),
        percentile_90=float(summary["percentile_90"]),
        percentile_5=float(summary["percentile_5"]),
        percentile_95=float(summary["percentile_95"]),
        value_at_risk_95=float(summary["value_at_risk_95"]),
        expected_shortfall_95=float(summary["expected_shortfall_95"]),
    )