Core coverage
Maintain listed, delisted and market-segment records
Research use
Map securities to SW industry classifications
Extended capability
Query open and closed days by exchange
REST API · PYTHON SDK · MCP
One request into your workflow
Every endpoint uses consistent authentication, security symbols and JSON responses, with REST API, Python SDK and MCP access available.
# pip install quantcoda import quantcoda as qc qc.set_token("qc_live_your_key") df = qc.stocks(exchange="SSE", list_status="L")
What this China market dataset includes
Reference is exposed through 3 documented endpoints. Each response preserves exchange-qualified security symbols, explicit trading or reporting dates and stable field meanings so that the same query can be reviewed in code, a backtest or an agent workflow.
Stock list
Typical filters: symbol, name, market, list_status
SW industry classification
Typical filters: symbol
Trading calendar (default SSE)
Typical filters: start_date, end_date, exchange, is_open
CONSISTENT INPUTS
Symbols and dates that remain explicit
China stock symbols include their exchange suffix, such as 600519.SH, 000001.SZ or 430047.BJ. Calendar dates use YYYYMMDD; financial endpoints distinguish announcement dates from reporting periods.
RESEARCH OUTPUT
JSON for APIs, DataFrames for Python
REST responses use typed JSON values. The official Python SDK converts the same records into pandas DataFrames, while MCP exposes the same authenticated data contract to compatible AI clients.
FIELD-LEVEL DOCS
Inspect meaning before modelling
The documentation lists request parameters, response columns, units and plan requirements for every endpoint. Missing values remain explicit rather than being silently imputed by the API.