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Yahoo Equity Daily Bars (PIT) — collection recipe.
Contract (ziplime PIT recipe, design doc §9):
async def fetch(since: datetime) -> pl.DataFrame
Returns rows in the PIT schema for `finance-yahoo-data`:
system: entity_id, event_date, knowledge_date, knowledge_estimated
values: open, high, low, close, volume, price
The shared harness (ingest.py) stamps `ingested_at`, dedups against existing rows and
appends to the Delta bundle. This recipe only fetches and shapes.
"""
from __future__ import annotations
from datetime import datetime, timezone
async def fetch(since: datetime):
import polars as pl # noqa: F401
import yfinance as yf
import polars as pl
universe = ["META", "AAPL", "AMZN", "NFLX", "GOOGL"]
raw = yf.download(
tickers=universe, interval="1d", start=since, threads=1,
group_by="Ticker", auto_adjust=True, multi_level_index=False, progress=False,
)
frames = []
for sym in universe:
d = pl.from_pandas(raw[sym], include_index=True).rename({
"Date": "event_date", "Open": "open", "High": "high",
"Low": "low", "Close": "close", "Volume": "volume",
})
d = d.with_columns(
pl.lit(sym).alias("entity_id"),
# a daily bar is known at its own session close
pl.col("event_date").alias("knowledge_date"),
pl.lit(False).alias("knowledge_estimated"),
pl.col("close").alias("price"),
)
frames.append(d)
return pl.concat(frames)
if __name__ == "__main__":
import asyncio, polars as pl
df = asyncio.run(fetch(datetime(2025, 1, 1, tzinfo=timezone.utc)))
print(df.head())
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