from __future__ import annotations

from datetime import datetime

import pandas as pd
import streamlit as st
import yfinance as yf


@st.cache_data(ttl=60, show_spinner=False)
def fetch_ohlc(symbol: str, interval: str, period: str) -> pd.DataFrame:
    ticker = yf.Ticker(symbol)
    df = ticker.history(period=period, interval=interval, auto_adjust=False, actions=False)
    if df.empty:
        raise ValueError("No data returned. Check symbol/interval/period compatibility.")

    df = df.rename(columns=str.title)
    required = ["Open", "High", "Low", "Close", "Volume"]
    missing = [c for c in required if c not in df.columns]
    if missing:
        raise ValueError(f"Missing required columns: {missing}")

    return df[required].dropna().copy()


def maybe_drop_live_bar(df: pd.DataFrame, interval: str, enabled: bool) -> pd.DataFrame:
    if not enabled or len(df) < 2:
        return df

    last_ts = df.index[-1]
    if last_ts.tzinfo is None:
        now = datetime.utcnow()
    else:
        now = datetime.now(tz=last_ts.tzinfo)

    delta = now - last_ts.to_pydatetime()

    intraday_intervals = {
        "1m": 1,
        "2m": 2,
        "5m": 5,
        "15m": 15,
        "30m": 30,
        "60m": 60,
        "90m": 90,
        "1h": 60,
    }
    minutes = intraday_intervals.get(interval)
    if minutes is not None and delta.total_seconds() < minutes * 60:
        return df.iloc[:-1].copy()

    return df