jindaxiang/akshare
Akshare
AkShare is a Python financial data library and programmatic interface designed for fetching real-time and historical stock, currency, and economic market data. It serves as a quantitative data acquisition tool for gathering the large-scale financial datasets required for economic research and quantitative analysis.
The library provides a unified interface to retrieve datasets from various official and commercial providers, removing the need to write custom scrapers for individual financial sources. It maps standardized function calls to diverse third-party sources to normalize varying response formats.
The project covers broad capability areas including financial data acquisition, investment market monitoring, and economic research automation. It enables the collection of macroeconomic indicators and market trends for use in mathematical trading strategies and automated reporting.
Features
- Market Data APIs - Serves as a programmatic interface for fetching real-time and historical stock, currency, and economic market data.
- Financial Data Adapters - Implements unique handling logic to normalize varying financial data source formats into consistent outputs.
- Quantitative Research Tools - Provides a specialized tool for gathering large-scale financial datasets required for quantitative analysis.
- Financial Data Connectors - Provides simplified interfaces to fetch real-time and historical market data from external financial exchanges.
- Market Data Providers - Provides interfaces for fetching historical and real-time stock and currency market data.
- Market Data Aggregators - Standardizes and merges heterogeneous financial data streams from multiple third-party providers into a unified interface.
- Financial Data Libraries - Provides a Python library for fetching structured financial market data to avoid writing custom scrapers.
- Quantitative Trading Platforms - Provides the necessary historical and real-time data required to build and backtest quantitative trading strategies.
- Request-Response Models - Encapsulates raw network responses into high-level pandas DataFrames for immediate financial analysis.
- Economic Analysis Tools - Collects large-scale macroeconomic indicators and financial statistics to support automated economic research.
- Market Insight Monitors - Enables tracking of diverse financial assets and market trends by pulling data into a local environment.
- Financial Data Sources - Open-source library for diverse financial data interfaces.
- Market Data Sources - Financial data interface library for Python.
- Trading and Derivatives - Comprehensive library for fetching financial market data.
- Downloaders - Financial data interface library.
