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tushare

Query Chinese financial market datasets via standardized API parameters and return pandas DataFrames.

Updated Mar 15, 2026
Search Tags:#api#pandas#time-series#market-data#financial-data#tushare#china-markets
One-click install
npx skills add https://github.com/Jaykaijack/openclaw-backup --skill tushare-jaykaijack
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: tushare
Source: https://github.com/Jaykaijack/openclaw-backup/tree/main/skills/tushare-data
Command: npx skills add https://github.com/Jaykaijack/openclaw-backup --skill tushare-jaykaijack

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires tushare, pandas, and includes scripts (resource) and references (resource) components.

What problem does it solve?

Provide unified, programmatic access to a wide range of Chinese financial datasets so analysts and engineers no longer need to scrape, normalize, and stitch together market, fund, futures, bond, and macro data from disparate sources.

Core Features & Use Cases

  • Standardized API access to stocks, ETFs, funds, futures, options, bonds, macroeconomic series, and corporate disclosures with documented query parameters.
  • Reference catalog of endpoints and field descriptions for many topics (ETF, bonds, indices, funds, macro, news, Hong Kong/US markets).
  • Example scripts demonstrating common workflows (fetch stock lists, retrieve daily bars, download fund NAVs) that return pandas DataFrames for downstream analysis and modeling.
  • Use case: data scientists can quickly pull historical daily bars and fundamental indicators for backtesting and machine learning pipelines without building custom scrapers.

Quick Start

Use the tushare skill to initialize a pro API with TUSHARE_TOKEN from the environment and fetch the last 30 days of daily prices for ts_code 000001.SZ into a pandas DataFrame.

Frequently Asked Questions about tushare

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I pull historical Chinese financial market data into a pandas DataFrame?▼

To pull historical Chinese financial market data into a pandas DataFrame, use a standardized API with parameters like ts_code, trade_date, start_date, end_date, and freq to query stocks, ETFs, funds, and macroeconomic series directly.

What datasets are available for China markets besides stocks?▼

Available China markets datasets include ETFs, funds, futures, options, bonds, macroeconomic series, and corporate disclosures, providing a unified programmatic interface to query historical and real-time time series and fundamentals.

Do I need a token to access financial data through this API?▼

Yes, you need a token to access financial data through this API, as it requires token-based authentication to initialize the pro API and respects rate and permission limits for querying datasets.

Can I use this to fetch real-time time series for backtesting pipelines?▼

Yes, you can fetch real-time and historical time series for backtesting pipelines, retrieving daily bars and fundamental indicators without building custom scrapers for downstream analysis and modeling.

What are the limitations when querying macroeconomic series and corporate disclosures?▼

Limitations when querying macroeconomic series and corporate disclosures include respecting API rate limits and token permission limits, which restrict the volume and frequency of programmatic data retrieval.

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