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gather_financial_snapshot API

Shadow Ingest / API Reference / Task-Oriented
gather_financial_snapshot(
    stock_codes: list[str],
    statement_type: Literal['balance_sheet', 'income_statement', 'cash_flow'],
) -> polars.DataFrame

Returns the latest financial snapshot for each requested stock code.

Before You Run This Example

Parameters

Parameter Required Default Allowed values / shape Meaning
stock_codes yes — list of stock codes such as ['000001.XSHE'] Which stocks to query
statement_type yes — 'income_statement', 'balance_sheet', 'cash_flow' Which financial statement snapshot to return

Discovery Workflow

import shadow_ingest as si

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

financial_df = si.gather_financial_snapshot(
    stock_codes=stock_codes[:2],
    statement_type='income_statement',
)

print(stock_codes[:5])
print(financial_df.columns)

Parameter Notes

stock_codes

If you are not sure which identifiers are valid, use:

import shadow_ingest as si

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

statement_type

Allowed values:

  • income_statement: income statement snapshot
  • balance_sheet: balance sheet snapshot
  • cash_flow: cash flow statement snapshot

Different statement_type values return different financial columns.

If you want to inspect the actual columns currently available for one statement type:

import shadow_ingest as si

financial_df = si.gather_financial_snapshot(
    stock_codes=['000001.XSHE'],
    statement_type='income_statement',
)

print(financial_df.columns)

Copy-Paste Example

import shadow_ingest as si

financial_df = si.gather_financial_snapshot(
    stock_codes=['000001.XSHE', '600000.XSHG'],
    statement_type='income_statement',
)

print(financial_df.head())
print(financial_df.schema)

Example Output

┌─────────────┬───────────────┬─────────┬────────────┐
│ stock_code  ┆ report_period ┆ revenue ┆ net_profit │
│ ---         ┆ ---           ┆ ---     ┆ ---        │
│ str         ┆ str           ┆ f64     ┆ f64        │
╞═════════════╪═══════════════╪═════════╪════════════╡
│ 000001.XSHE ┆ 2023-09-30    ┆ 1.27e11 ┆ 3.97e10    │
│ 600000.XSHG ┆ 2023-09-30    ┆ 1.39e11 ┆ 3.67e10    │
└─────────────┴───────────────┴─────────┴────────────┘

Pandas

financial_pdf = financial_df.to_pandas()