| from __future__ import annotations | |
| from datetime import datetime, time | |
| import pandas as pd | |
| MARKET_OPEN = time(9, 15) | |
| MARKET_CLOSE = time(15, 30) | |
| HOUR_MARKS = [time(9,15), time(10,15), time(11,15), time(12,15), time(13,15), time(14,15), time(15,15), time(15,30)] | |
| def hour_passed(t: datetime) -> int: | |
| order = [time(10,15), time(11,15), time(12,15), time(13,15), time(14,15), time(15,15)] | |
| return order.index(t.time()) + 1 if t.time() in order else 0 | |
| def filter_timerange(df: pd.DataFrame, col: str, start: datetime, end: datetime) -> pd.DataFrame: | |
| mask = (df[col] >= start) & (df[col] < end) | |
| return df.loc[mask].copy() | |
| def ohlc_day(df: pd.DataFrame, dt_col: str, day: datetime) -> tuple[float,float,float,float]: | |
| d = df[df[dt_col].dt.date == day.date()] | |
| if d.empty: | |
| raise ValueError(f"No data for {day.date()}") | |
| o = float(d.iloc[0]["open"]) | |
| h = float(d["high"].max()) | |
| l = float(d["low"].min()) | |
| c = float(d.iloc[-1]["close"]) | |
| return o, h, l, c | |
| def ohlc_at(df: pd.DataFrame, dt_col: str, ts: datetime) -> tuple[float,float,float,float]: | |
| row = df.loc[df[dt_col] == ts] | |
| if row.empty: | |
| raise ValueError(f"No bar at {ts}") | |
| r = row.iloc[0] | |
| return float(r["open"]), float(r["high"]), float(r["low"]), float(r["close"]) | |
| def hourly_ohlc_dict(df: pd.DataFrame, dt_col: str, now: datetime) -> dict: | |
| """Return a nested dict of each completed hour's OHLC up to `now`.""" | |
| hours = [h for h in HOUR_MARKS if h < now.time()] | |
| out = {} | |
| names = ["first_hour","second_hour","third_hour","fourth_hour","fifth_hour","sixth_hour","last_15_minutes"] | |
| for i, h in enumerate(hours): | |
| try: | |
| o,hhi,llo,c = ohlc_at(df, dt_col, datetime.combine(now.date(), h)) | |
| out[names[i]] = {"open": o, "high": hhi, "low": llo, "close": c} | |
| except Exception: | |
| pass | |
| return out | |