"""Shared fixtures: a synthetic data store with 12 stocks in four currencies."""

from __future__ import annotations

import numpy as np
import pandas as pd
import pytest

from quantcore.config import Settings
from quantcore.data.market_data import MarketDataService
from quantcore.data.store import DataStore

N, T = 12, 3000
SYMBOLS = [f"S{i}" for i in range(N)]
CURRENCIES = ["CHF", "USD", "EUR", "GBP"] * 3
SECTORS = ["Information Technology", "Financials", "Health Care", "Energy"] * 3


def make_prices(seed: int = 0) -> tuple[pd.DataFrame, np.ndarray]:
    rng = np.random.default_rng(seed)
    dates = pd.bdate_range("2013-01-01", periods=T)
    f = rng.standard_normal((T, 2)) * 0.01
    beta = rng.uniform(0.5, 1.5, size=(N, 2))
    eps = rng.standard_t(5, size=(T, N)) * 0.01
    r = f @ beta.T + eps + 0.0002
    return pd.DataFrame(100 * np.exp(np.cumsum(r, axis=0)), index=dates, columns=SYMBOLS), r


@pytest.fixture(scope="session")
def settings(tmp_path_factory) -> Settings:
    return Settings(data_dir=tmp_path_factory.mktemp("data"), cuopt_url="http://127.0.0.1:9", solver_fallback=True)


@pytest.fixture(scope="session")
def store(settings) -> DataStore:
    store = DataStore(settings)
    store.ensure_dirs()
    prices, _ = make_prices()
    rng = np.random.default_rng(1)
    uni = pd.DataFrame({
        "symbol": SYMBOLS, "name": [f"Company {s}" for s in SYMBOLS], "region": ["US"] * 6 + ["Europe"] * 6,
        "country": ["United States"] * 6 + ["Switzerland"] * 6, "listing_currency": CURRENCIES, "exchange": "",
        "exchange_code": "", "gics_sector": SECTORS, "gics_sub_industry": "", "yahoo_sector": "", "yahoo_industry": "",
        "market_cap": 1e9, "market_cap_base": rng.uniform(1e9, 1e11, N), "shares_outstanding": rng.uniform(1e7, 1e9, N),
        "last_price": prices.iloc[-1].values, "first_price_date": "2013-01-01", "price_coverage": 1.0,
        "index_weight": np.nan, "source": "synthetic", "rank_in_region": range(1, N + 1),
    })
    store.save_universe(uni)
    store.save_prices(prices)
    fx = pd.DataFrame({
        "USD": 0.85 * np.exp(np.cumsum(rng.standard_normal(T) * 0.004)),
        "EUR": 0.95 * np.exp(np.cumsum(rng.standard_normal(T) * 0.003)),
        "GBP": 1.10 * np.exp(np.cumsum(rng.standard_normal(T) * 0.004)), "CHF": 1.0,
    }, index=prices.index)
    store.save_fx(fx)
    store.update_manifest(last_price_date=str(prices.index[-1].date()), n_universe=N)
    return store


@pytest.fixture(scope="session")
def md(settings, store) -> MarketDataService:
    return MarketDataService(settings, store)