import pandas as pd
import pytest
from fastapi.testclient import TestClient

from app import main
from app.services import data_service


def annual_frame(rows: dict[str, list[float]]) -> pd.DataFrame:
    columns = pd.to_datetime(["2024-09-30", "2023-09-30", "2022-09-30", "2021-09-30"])
    return pd.DataFrame(rows, index=columns).T


def quarterly_frame(rows: dict[str, list[float]]) -> pd.DataFrame:
    columns = pd.to_datetime(["2025-12-31", "2025-09-30", "2025-06-30", "2025-03-31"])
    return pd.DataFrame(rows, index=columns).T


def clear_valuation_cache() -> None:
    data_service.VALUATION_CACHE.clear()


def advanced_payload() -> dict[str, float | int | list[float]]:
    return {
        "base_revenue": 1_000.0,
        "revenue_growth": [0.10, 0.05],
        "ebitda_margin": [0.30, 0.32],
        "dna_pct_revenue": [0.05, 0.05],
        "capex_pct_revenue": [0.07, 0.07],
        "nwc_chg_pct_delta_rev": [0.02, 0.02],
        "tax_rate": [0.25, 0.25],
        "wacc": 0.10,
        "terminal_growth": 0.03,
        "projection_years": 2,
    }


def test_simple_valuation_includes_five_by_five_sensitivity_grid(monkeypatch: pytest.MonkeyPatch) -> None:
    # Given: historical free cash flow data for the simple DCF endpoint.
    clear_valuation_cache()
    cash_flow = annual_frame({
        "Operating Cash Flow": [100.0, 90.0, 80.0, 70.0],
        "Capital Expenditure": [-10.0, -9.0, -8.0, -7.0],
    })
    monkeypatch.setattr(data_service, "get_cash_flow", lambda symbol, quarterly=False: pd.DataFrame() if quarterly else cash_flow)
    monkeypatch.setattr(data_service, "get_income_statement", lambda symbol, quarterly=False: pd.DataFrame())
    monkeypatch.setattr(data_service, "get_balance_sheet", lambda symbol, quarterly=False: pd.DataFrame())
    monkeypatch.setattr(data_service, "get_company_info", lambda symbol: {"currentPrice": 150.0})
    monkeypatch.setattr(data_service, "get_shares_outstanding", lambda symbol: 1_000_000_000.0)

    # When: the simple valuation service is called.
    result = data_service.get_valuation("ref")

    # Then: the DCF result includes the mandated WACC x terminal-growth matrix.
    dcf = result["dcf"]
    sensitivity = dcf["sensitivity"]
    assert result["currency"] == "USD"
    assert result["currency_warning"] is None
    assert sensitivity["wacc"] == [0.08, 0.09, 0.10, 0.11, 0.12]
    assert sensitivity["terminal_growth"] == [0.015, 0.02, 0.03, 0.04, 0.045]
    assert len(sensitivity["implied_prices"]) == 5
    assert all(len(row) == 5 for row in sensitivity["implied_prices"])
    assert sensitivity["implied_prices"][2][2] == pytest.approx(dcf["intrinsic_value_per_share"])


def test_advanced_valuation_endpoint_returns_inputs_and_sensitivity(monkeypatch: pytest.MonkeyPatch) -> None:
    # Given: symbol-level balance sheet inputs and a base valuation shell.
    clear_valuation_cache()
    monkeypatch.setattr(
        data_service,
        "get_valuation",
        lambda symbol: {
            "symbol": "REF",
            "current_price": 42.0,
            "shares_outstanding": 100.0,
            "dcf": {"available": False, "wacc": 0.10, "terminal_growth": 0.03, "projection_years": 5},
            "ev_ebitda": {"available": False},
            "ev_revenue": {"available": False},
            "price_to_book": {"available": False},
        },
    )
    monkeypatch.setattr(data_service, "get_shares_outstanding", lambda symbol: 100.0)
    monkeypatch.setattr(
        data_service,
        "get_balance_sheet",
        lambda symbol, quarterly=False: quarterly_frame({
            "Total Debt": [50.0, 0.0, 0.0, 0.0],
            "Cash And Cash Equivalents": [10.0, 0.0, 0.0, 0.0],
            "Preferred Stock": [5.0, 0.0, 0.0, 0.0],
            "Minority Interest": [3.0, 0.0, 0.0, 0.0],
        }),
    )
    client = TestClient(main.app)

    # When: the advanced valuation endpoint receives an explicit build payload.
    response = client.post("/api/tickers/REF/valuation/advanced", json=advanced_payload())

    # Then: it returns a full valuation response with base-case-centered sensitivity.
    assert response.status_code == 200
    body = response.json()
    dcf = body["dcf"]
    sensitivity = dcf["sensitivity"]
    assert body["symbol"] == "REF"
    assert body["currency"] == "USD"
    assert body["currency_warning"] is None
    assert dcf["advanced_inputs"] == advanced_payload()
    assert dcf["intrinsic_value_per_share"] == pytest.approx(29.838067203890013)
    assert sensitivity["wacc"] == [0.08, 0.09, 0.10, 0.11, 0.12]
    assert sensitivity["terminal_growth"] == [0.015, 0.02, 0.03, 0.04, 0.045]
    assert len(sensitivity["implied_prices"]) == 5
    assert all(len(row) == 5 for row in sensitivity["implied_prices"])
    assert sensitivity["implied_prices"][2][2] == pytest.approx(dcf["intrinsic_value_per_share"])


def test_advanced_valuation_endpoint_rejects_short_projection_arrays() -> None:
    # Given: a payload whose per-year arrays do not cover projection_years.
    payload = advanced_payload()
    payload["revenue_growth"] = [0.10]
    client = TestClient(main.app)

    # When: the invalid payload is submitted.
    response = client.post("/api/tickers/REF/valuation/advanced", json=payload)

    # Then: FastAPI returns a validation response instead of an unhandled exception.
    assert response.status_code == 422
    assert "projection_years" in response.text