dataset / app /utils.py
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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