PandaData Ingest

Use this skill when a task needs stock, listed-fund/ETF, index, or futures market data; reference data; adjustment factors; or futures tick data from the PandaData SDK.

Prerequisites

• Install optional SDK dependencies with uv sync --extra panda_data.
• Set PANDA_DATA_USERNAME and PANDA_DATA_PASSWORD in the environment.
• PandaDataClient fetches data only. Persist normalized OHLCV with skills.store.data_manager.DataManager.

Public API

from skills.ingest import PandaDataClient
from skills.ingest import to_panda_data_symbol, to_quantspace_symbol

PandaDataClient accepts QuantSpace symbols such as SHSE.510300 and panda_data native symbols such as 510300.SH. Returned symbol columns are converted back to QuantSpace format by default.

Wrapped Endpoints

Bars

• fetch_market_data(symbol, start_date, end_date, type="stock")
• fetch_market_min_data(symbol, start_date, end_date, symbol_type="stock", frequency="1m")
• fetch_hk_daily(symbol, start_date, end_date)
• fetch_us_daily(symbol, start_date, end_date)
• get_fund_daily(start_date, end_date, symbol=...)
• get_fund_daily_pre(start_date, end_date, symbol=...)
• get_fund_daily_post(start_date, end_date, symbol=...)

Reference

• get_stock_detail
• get_fund_detail
• get_index_detail
• get_index_indicator
• get_index_weights
• get_industry_detail
• get_industry_constituents
• get_stock_industry
• get_concept_list
• get_concept_constituents
• get_adj_factor

ETF Creation/Redemption

• get_fund_etf_cr_limits
• get_fund_etf_cr_net
• get_fund_etf_constituents
• get_fund_etf_cr

Listed ETFs and LOFs are funds, not A-share stocks. Fetch their bars with get_fund_daily*; do not send them to get_stock_daily, get_factor, or fetch_market_data(..., type="stock"). The get_fund_etf_* methods provide creation/redemption data and are not price-bar replacements.

The three get_fund_daily* methods accept an inclusive YYYYMMDD range of any length. PandaDataClient automatically sends contiguous requests of at most 365 calendar days and concatenates the returned frames in request order. This handling applies only to listed-fund daily bars, not get_fund_etf_* creation/redemption endpoints.

Futures Tick Utility

skills.ingest.panda_future_tick contains offline-testable helpers and CLI building blocks for PandaData futures tick downloads.

Progressive References

Detailed PandaAI docs are split by task under references/. Open only the specific file needed for the endpoint you are using.

Reference	Open when you need	Main methods
pandaai-01-overview-setup.md	setup and auth	init_token
pandaai-02-market-daily.md	A-share/index/futures daily bars	get_market_data
pandaai-03-market-minute.md	A-share/index/futures intraday bars	get_market_min_data
pandaai-04-market-hk-us.md	HK/US daily bars	get_hk_daily, get_us_daily
pandaai-05-reference-securities.md	stock/index metadata	get_stock_detail, get_index_detail
pandaai-06-reference-classification-index.md	classifications and index weights	get_index_weights
pandaai-07-equity-market-events.md	market events	get_lhb_list, get_margin
pandaai-08-equity-corporate-info.md	holders and corporate info	get_top_holders
pandaai-09-financial-reports.md	financial reports	get_fina_reports
pandaai-10-factors-adjustment.md	factors and adjustment events	get_factor, get_adj_factor
pandaai-11-trading-tools.md	calendars and trade lists	get_trade_cal, get_trade_list
pandaai-12-futures.md	futures metadata and dominant contracts	get_future_detail
pandaai-13-funds-etf.md	fund metadata, listed-fund bars, ETF creation/redemption	get_fund_detail, get_fund_daily*, get_fund_etf_*

Recipes

Daily A-share bars

from skills.ingest import PandaDataClient

client = PandaDataClient()
df = client.fetch_market_data("SHSE.600000", "20230101", "20231231", type="stock")

Daily ETF bars

from skills.ingest import PandaDataClient

client = PandaDataClient()
df = client.get_fund_daily(
    "20250610",
    "20250613",
    symbol="SHSE.510300",
    fields=["open", "high", "low", "close", "volume", "amount"],
)

Use get_fund_daily_pre or get_fund_daily_post when the research explicitly requires forward- or backward-adjusted fund prices.

The market-data API frequency remains the real bar interval. For example, adjusted daily bars still use freq="1d" (or the endpoint's daily API); do not send "1d_adj" to an ingest endpoint as a frequency. 1d_adj is only the QuantSpace storage directory/data-set name for adjusted 1d bars. The same rule applies to other intervals: a directory such as 5m_adj contains adjusted 5m bars, while the ingest frequency is still 5m.

Normalize and save bars

import pandas as pd

from skills.ingest import PandaDataClient
from skills.store.data_manager import DataManager

client = PandaDataClient()
raw = client.fetch_market_data("SHSE.600000", "20230101", "20231231", type="stock")

bars = raw.copy()
bars["eob"] = pd.to_datetime(bars["date"])
bars = bars.set_index("eob")[["open", "high", "low", "close", "volume"]].sort_index()

DataManager().save_symbol("SHSE.600000", bars, frequency="1d", source="panda_data")

When saving adjusted bars, pass the storage directory key to DataManager, for example frequency="1d_adj", even though the frequency used to fetch or describe those bars is 1d. Here the DataManager parameter is a directory selector retained by its current API, not the semantic market-data frequency.

The same store boundary applies to listed funds: normalize the returned date column to the timezone-naive eob index, keep OHLCV columns, and call DataManager.save_symbol. PandaDataClient never writes local files.

Symbol conversion

from skills.ingest import to_panda_data_symbol, to_quantspace_symbol

assert to_panda_data_symbol("SHSE.510300") == "510300.SH"
assert to_quantspace_symbol("RB_DOMINANT.SHF") == "SHFE.RB99"