gather_daily_snapshot API¶

Shadow Ingest / API Reference / Task-Oriented

gather_daily_snapshot(
    trade_date: str,
    stock_codes: list[str],
) -> polars.DataFrame

Returns a daily cross-sectional snapshot for one trading date.

Before You Run This Example¶

Shadow Ingest Local Testing

Parameters¶

Parameter	Required	Default	Allowed values / shape	Meaning
`trade_date`	yes	—	`YYYY-MM-DD`	Which trading date to query
`stock_codes`	yes	—	list of stock codes such as `['000001.XSHE', '600000.XSHG']`	Which stocks to include in the cross section

Discovery Workflow¶

import shadow_ingest as si

trade_dates = si.list_market_calendar(year=2024)
stock_codes = si.list_universe(date=trade_dates[-1])

snapshot_df = si.gather_daily_snapshot(
    trade_date=trade_dates[-1].isoformat(),
    stock_codes=stock_codes[:2],
)

print(trade_dates[:3])
print(stock_codes[:5])
print(snapshot_df.columns)

Parameter Notes¶

`trade_date`¶

Use list_market_calendar(...) when you want a valid trading date:

import shadow_ingest as si

trade_dates = si.list_market_calendar(year=2024)
print(trade_dates[-5:])

`stock_codes`¶

Use list_universe(...) when you want valid identifiers for a trading date:

import shadow_ingest as si

stock_codes = si.list_universe(date='2024-01-03')
print(stock_codes[:10])

Snapshot columns¶

This API does not expose a stable public fields parameter.

If you want to see what columns are currently available in your environment:

import shadow_ingest as si

snapshot_df = si.gather_daily_snapshot(
    trade_date='2024-01-02',
    stock_codes=['000001.XSHE'],
)

print(snapshot_df.columns)

Copy-Paste Example¶

import shadow_ingest as si

snapshot_df = si.gather_daily_snapshot(
    trade_date='2024-01-02',
    stock_codes=['000001.XSHE', '600000.XSHG', '600519.XSHG'],
)

print(snapshot_df.head())
print(snapshot_df.schema)

Example Output¶

┌────────────┬─────────────┬──────┬──────┬───────┬──────────┐
│ trade_date ┆ stock_code  ┆ open ┆ high ┆ close ┆ volume   │
│ ---        ┆ ---         ┆ ---  ┆ ---  ┆ ---   ┆ ---      │
│ date       ┆ str         ┆ f64  ┆ f64  ┆ f64   ┆ f64      │
╞════════════╪═════════════╪══════╪══════╪═══════╪══════════╡
│ 2024-01-02 ┆ 000001.XSHE ┆ 9.39 ┆ 9.4  ┆ 9.21  ┆ 1.14e8   │
│ 2024-01-02 ┆ 600000.XSHG ┆ 7.21 ┆ 7.28 ┆ 7.25  ┆ 8.76e7   │
│ 2024-01-02 ┆ 600519.XSHG ┆ 1688 ┆ 1699 ┆ 1692  ┆ 3.42e6   │
└────────────┴─────────────┴──────┴──────┴───────┴──────────┘

Pandas¶

snapshot_pdf = snapshot_df.to_pandas()