Data API¶

Retrieve historical quotes, real-time data, financial information, A-share specific data, etc.

get_price¶

Retrieve historical price data.

get_price(security, start_date=None, end_date=None, frequency='daily', fields=None, count=None)

Parameter	Type	Required	Description
`security`	`str` or `list`	Yes	Stock code
`start_date`	`str`/`date`	No	Start date
`end_date`	`str`/`date`	No	End date
`frequency`	`str`	No	Only `'daily'` is supported
`fields`	`list`	No	Specify returned fields
`count`	`int`	No	Return the most recent N bars

Returns a DataFrame (single stock) or dict[str, DataFrame] (multiple stocks).

history¶

Retrieve count bars of data looking back from the current backtest time. Only available inside strategy callbacks.

history(count, unit='1d', field='close', security=None, df=False)

attribute_history¶

Retrieve historical attribute data for a single stock.

attribute_history(security, count, unit='1d', fields=('close',), df=True, skip_paused=True, fq='pre')

Returns a DataFrame with columns: open, high, low, close, volume, money, pct_change, turnover.

get_current_data¶

Retrieve real-time snapshots for all A-shares. Returns dict[str, dict] containing fields such as code, name, price, pct_change, volume, pe, pb, total_value, etc.

get_security_info¶

Retrieve basic information for a single stock. Returns a SecurityInfo object (code, name, industry, total_shares, float_shares, total_value, list_date).

get_valuation¶

Retrieve valuation data. Returns dict or None.

scan_market¶

Scan A-shares with filters.

scan_market(min_price=10, min_pct_change=3, max_pct_change=5, max_pe=50)

get_financial_screen¶

Screen by financial metrics.

get_financial_screen(min_pe=None, max_pe=None, min_pb=None, max_pb=None, min_roe=None)

get_all_securities¶

Retrieve a list of all A-shares. Returns a DataFrame (code, name).

get_trade_days¶

Retrieve the trading calendar. Returns list[date].

Indices & Industry¶

API	Description	Returns
`get_index_stocks(index_code)`	Index constituent stocks	`DataFrame`
`get_industry_list()`	All industry sectors	`list[str]`
`get_industry_stocks(industry_name)`	Stocks in a given industry	`DataFrame`
`get_industry(code)`	Industry classification for a single stock	`dict` or `None`
`get_index_weights(index_code, date=None)`	Index constituent weights	`DataFrame`

Concept Sectors¶

API	Description	Returns
`get_concept_list()`	All concept sectors	`list[str]`
`get_concept_stocks(concept_name)`	Constituent stocks of a concept	`DataFrame`

Minute-Level Data¶

fetch_minute_data(code, period='5m', start_date=None, end_date=None, adjust='qfq')
get_price_minute(security, count=None, period='5m', fields=None, adjust='qfq')

Supported periods: 1m, 5m, 15m, 30m, 60m.

Tick Data¶

get_tick_data(code, trade_date=None)

Money Flow & Billboard¶

get_money_flow(code, start_date=None, end_date=None, count=None)
get_billboard_list(stock_list=None, date=None, start_date=None, end_date=None)

get_north_money_flow¶

Northbound money flow (Shanghai-Hong Kong Stock Connect + Shenzhen-Hong Kong Stock Connect aggregate).

get_north_money_flow(start_date=None, end_date=None)

Parameter	Type	Description
`start_date`	`str`/`date`	Start date; defaults to 30 days ago
`end_date`	`str`/`date`	End date; defaults to today (China timezone)

Returns a DataFrame with the following columns:

Column	Description
`date`	Trading date
`net_buy`	Net buy amount (100 million yuan)
`total_buy`	Total buy amount (100 million yuan)
`total_sell`	Total sell amount (100 million yuan)

from eqlib import get_north_money_flow

# Get northbound flow for the last 3 months
north = get_north_money_flow(start_date="2024-01-01", end_date="2024-03-31")

# Calculate net buy over the last 5 days
recent_5d = north["net_buy"].tail(5).sum()
if recent_5d > 50:
    print("Strong northbound capital inflow")

Note: Uses China timezone (UTC+8) to determine "today"; cached for 1 hour.

get_margin_data¶

Margin trading data (market-wide aggregate).

get_margin_data(start_date=None, end_date=None)

Returns a DataFrame with the following columns:

Column	Description
`date`	Trading date
`margin_balance`	Margin balance (100 million yuan)
`margin_buy`	Margin buy amount (100 million yuan)
`margin_repay`	Margin repayment amount (100 million yuan) — NaN for the first row
`short_balance`	Short selling balance (100 million yuan)

from eqlib import get_margin_data

margin = get_margin_data(start_date="2024-01-01", end_date="2024-03-31")

# Margin balance rate of change
margin["change_pct"] = margin["margin_balance"].diff(5) / margin["margin_balance"].shift(5) * 100

Note: margin_repay is NaN for the first row (no prior balance to compute from). Users can handle this with dropna() or fillna().

get_limit_up_down_stats¶

Limit up/down statistics (daily count of stocks hitting price limit up / limit down).

get_limit_up_down_stats(start_date=None, end_date=None)

Returns a DataFrame with the following columns:

Column	Description
`date`	Trading date
`limit_up_count`	Number of stocks hitting the upper price limit
`limit_down_count`	Number of stocks hitting the lower price limit
`api_error_count`	Number of failed API calls (for data quality monitoring)

from eqlib import get_limit_up_down_stats

stats = get_limit_up_down_stats()

# Systemic risk alert
latest_down = stats["limit_down_count"].iloc[-1]
if latest_down > 100:
    print("⚠️ Systemic risk alert")

Note: The API only supports the most recent 30 trading days; a warning is issued if the requested range exceeds this limit.

get_restriction_release¶

Restricted share unlock schedule (list of upcoming unlocks within the next N days).

get_restriction_release(days=30)

Parameter	Type	Description
`days`	`int`	Number of days to look ahead; defaults to 30

Returns a DataFrame with the following columns:

Column	Description
`code`	Stock code
`name`	Stock name
`release_date`	Unlock date
`release_amount`	Unlock quantity (10,000 shares)
`release_value`	Unlock market value (100 million yuan)
`release_pct`	Percentage of pre-unlock float market cap

from eqlib import get_restriction_release

# Get unlocks for the next 30 days
releases = get_restriction_release(days=30)

# Alert on large unlocks
large = releases[releases["release_value"] > 50]
print(f"Large unlocks: {len(large)} stocks")

Financial Data¶

get_financial_abstract(code)

Chained Stock Selection API¶

query(*fields)
get_fundamentals(query_or_code, date=None)

Available fields are accessed via the valuation namespace: code, market_cap, total_value, float_value, pe, pb, turnover, price, pct_change.

Chained methods: .filter(), .order_by(), .limit().

q = query(valuation.code, valuation.market_cap, valuation.pe) \
    .filter(valuation.market_cap.between(20, 30), valuation.pe > 0) \
    .order_by(valuation.market_cap.asc()) \
    .limit(5)
df = get_fundamentals(q)

get_current_data_object¶

Retrieve real-time market snapshots with attribute access. Returns dict[str, _StockDataObj].

get_extras¶

Retrieve additional data fields ('is_st' or 'net_value').

Universe Management¶

set_universe(security_list)   # Set the strategy universe
get_universe()                 # Get the current universe

Local Files¶

API	Description
`download_stock_data(code, start_date, end_date, adjust='qfq', output_dir=None)`	Download daily data as CSV
`load_csv(path, index_col='date', parse_dates=True)`	Load data from a local CSV
`clear_cache()`	Clear in-memory cache
`save_stock_local(security, start_date, end_date)`	Download and save locally
`load_stock_local(security, start_date, end_date)`	Load from local storage
`has_local_data(security)`	Check if local data exists
`list_local_stocks()`	List all local files
`remove_local_data(security)`	Delete a single local file
`clear_all_local_data()`	Delete all local files

Data API¶

get_price¶

history¶

attribute_history¶

get_current_data¶

get_security_info¶

get_valuation¶

scan_market¶

get_financial_screen¶

get_all_securities¶

get_trade_days¶

Indices & Industry¶

Concept Sectors¶

Minute-Level Data¶

Tick Data¶

Money Flow & Billboard¶

A-Share Specific Data¶

get_north_money_flow¶

get_margin_data¶

get_limit_up_down_stats¶

get_restriction_release¶

Financial Data¶

Chained Stock Selection API¶

get_current_data_object¶

get_extras¶

Universe Management¶

Local Files¶