tushare

Name: tushare
Availability: InStock
Author: hxhyyy

Retrieve equities, funds, bonds, and macroeconomic data via Python SDK and RESTful API.

Updated Jul 8, 2026

Search Tags:#api #data #finance #stocks #market #quantitative

Ready to run

npx skills add https://github.com/hxhyyy/Vibe-Trading --skill tushare-hxhyyy

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: tushare
Source: https://github.com/hxhyyy/Vibe-Trading/tree/main/agent/src/skills/tushare
Command: npx skills add https://github.com/hxhyyy/Vibe-Trading --skill tushare-hxhyyy

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill solves the challenge of accessing fragmented financial data by providing a unified, standardized API for stocks, funds, bonds, and macroeconomic indicators.

Core Features & Use Cases

Multi-Asset Coverage: Retrieve real-time and historical data for stocks, funds, futures, and digital currencies.
Macroeconomic Insights: Access global economic calendars, interest rates, and national policy databases.
Use Case: A quantitative researcher can use this Skill to pull historical ETF minute-level data and combine it with macroeconomic indicators to backtest trading strategies without manually scraping multiple exchange websites.

Quick Start

Use the tushare skill to fetch the latest daily stock data for the ticker 000001.SZ and print the results.

Frequently Asked Questions about tushare

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

FAQPage Schema

How do I retrieve historical stock market data using a Python SDK?▼

You can retrieve historical stock market data by using the standardized Python SDK and RESTful API to fetch equities, funds, and bonds programmatically. It facilitates quantitative analysis by providing unified access across multiple asset classes.

Can I use pandas to analyze macroeconomic indicators fetched from the API?▼

Yes, pandas is a required dependency for this API, allowing you to analyze macroeconomic indicators like global economic calendars and interest rates directly. This integration supports quantitative research without manual web scraping.

Does the API support fetching real-time data for multiple asset classes like funds and futures?▼

The API supports fetching real-time and historical financial data across multiple asset classes, including equities, funds, futures, and digital currencies. It provides a standardized interface to access these fragmented markets comprehensively.

What is the best way to access fragmented financial data for backtesting trading strategies?▼

The best way to access fragmented financial data for backtesting is using a unified interface that aggregates equities, funds, bonds, and macroeconomic indicators. This avoids manually scraping multiple exchange websites for quantitative research.

Are there limitations when ingesting minute-level ETF data through a RESTful API?▼

While the interface facilitates programmatic data ingestion of minute-level ETF data through a unified API, performance depends on the underlying API constraints and your technical environment setup for handling large datasets.