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# AKShare Python Financial Data Library
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AKShare is a comprehensive Python library for financial data acquisition, providing access to over 1,000 functions across 37 categories covering Chinese and global financial markets. The library offers real-time and historical data for multiple asset classes including stocks, bonds, futures, options, funds, commodities, and macroeconomic indicators.
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## Package Information
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**Name:** akshare  
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**Language:** Python  
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**Installation:** `pip install akshare`  
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**Version:** 1.17.44  
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**Dependencies:** pandas, requests, beautifulsoup4, lxml
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## Core Imports
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```python { .api }
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import akshare as ak
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import pandas as pd
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from typing import Optional
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# AKShare provides 1,046+ functions across 37 categories
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# All functions return pandas.DataFrame objects
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```
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## Basic Usage
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### Real-time Market Data
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```python { .api }
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import akshare as ak
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# Get real-time A-share market data
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df: pd.DataFrame = ak.stock_zh_a_spot_em()
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print(df.head())
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#      序号    代码    名称   最新价  涨跌幅  涨跌额    成交量        成交额
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# 0    1  000001  平安银行  10.50   1.45   0.15  1234567  12950123456
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# 1    2  000002   万科A   8.92  -0.89  -0.08   987654   8800765432
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# Get historical data for specific stock
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hist_df: pd.DataFrame = ak.stock_zh_a_hist(
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    symbol="000001", 
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    period="daily", 
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    start_date="20240101", 
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    end_date="20241201"
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)
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```
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### Macroeconomic Data
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```python { .api }
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import akshare as ak
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# Chinese Consumer Price Index
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cpi_df: pd.DataFrame = ak.macro_china_cpi()
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print(cpi_df.head())
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#         日期     全国CPI    城市CPI    农村CPI
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# 0  2024-11-01    102.3     102.1     102.8
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# 1  2024-10-01    102.0     101.8     102.5
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# US Non-farm Payrolls
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nonfarm_df: pd.DataFrame = ak.macro_usa_non_farm()
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# Chinese GDP Data
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gdp_df: pd.DataFrame = ak.macro_china_gdp()
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```
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### Fund and ETF Data
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```python { .api }
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import akshare as ak
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# Real-time ETF data
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etf_df: pd.DataFrame = ak.fund_etf_spot_em()
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# Open-end fund daily data
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fund_df: pd.DataFrame = ak.fund_open_fund_daily_em(symbol="000001")
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```
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## Architecture
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AKShare follows a modular architecture organized by data source and asset class:
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### Data Source Integration
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- **East Money (东方财富)** - Functions suffixed with `_em`
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- **Sina Finance (新浪财经)** - Functions suffixed with `_sina`
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- **Tonghuashun (同花顺)** - Functions suffixed with `_ths`
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- **JiSiLu (集思录)** - Functions suffixed with `_jsl`
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- **CNInfo (巨潮资讯网)** - Functions suffixed with `_cninfo`
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### Module Organization
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```
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akshare/
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├── stock/           # Core stock market data
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├── stock_feature/   # Advanced stock analysis
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├── economic/        # Macroeconomic indicators  
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├── fund/           # Mutual funds and ETFs
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├── bond/           # Bond market data
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├── futures/        # Futures and derivatives
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├── option/         # Options market data
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├── index/          # Market indices
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└── utils/          # Shared utilities
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```
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### Consistent API Design
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- All functions return `pandas.DataFrame` objects
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- Standardized parameter patterns (symbol, period, start_date, end_date)
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- Consistent column naming and data typing
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- No API keys required for most functions
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## Capabilities
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### [Stock Market Data](./stock-data.md)
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**Core stock market data and advanced analysis features**
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```python { .api }
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# Real-time A-share quotes
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df: pd.DataFrame = ak.stock_zh_a_spot_em()
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# Historical stock data  
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hist_df: pd.DataFrame = ak.stock_zh_a_hist(symbol="000001", period="daily")
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# US stock real-time data
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us_df: pd.DataFrame = ak.stock_us_spot()
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# Hong Kong stock data
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hk_df: pd.DataFrame = ak.stock_hk_spot()
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# Stock Connect capital flows
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hsgt_df: pd.DataFrame = ak.stock_hsgt_fund_flow_summary_em()
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```
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**Functions:** 325+ functions across STOCK (120) and STOCK_FEATURE (205) categories  
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**Coverage:** Chinese A-shares, Hong Kong stocks, US stocks, technical indicators, capital flows
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### [Economic Indicators](./economic-data.md)
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**Comprehensive macroeconomic data from multiple countries**
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```python { .api }
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# Chinese economic indicators
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cpi_df: pd.DataFrame = ak.macro_china_cpi()
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gdp_df: pd.DataFrame = ak.macro_china_gdp()
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pmi_df: pd.DataFrame = ak.macro_china_pmi()
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# US economic data
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us_gdp_df: pd.DataFrame = ak.macro_usa_gdp()
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unemployment_df: pd.DataFrame = ak.macro_usa_unemployment_rate()
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# European economic indicators
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euro_cpi_df: pd.DataFrame = ak.macro_euro_cpi()
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```
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**Functions:** 226 functions covering China, US, Europe, Japan, Australia, Canada, UK  
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**Coverage:** GDP, CPI, PMI, employment, trade, monetary policy indicators
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### [Financial Instruments](./financial-instruments.md)
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**Funds, bonds, futures, and options market data**
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```python { .api }
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# ETF and fund data
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etf_df: pd.DataFrame = ak.fund_etf_spot_em()
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fund_daily_df: pd.DataFrame = ak.fund_open_fund_daily_em(symbol="000001")
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# Bond market data
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bond_df: pd.DataFrame = ak.bond_zh_hs_daily()
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convertible_df: pd.DataFrame = ak.bond_convert_list()
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# Futures data
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futures_df: pd.DataFrame = ak.futures_zh_daily_sina(symbol="RB0000")
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# Options data
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option_df: pd.DataFrame = ak.option_finance_board()
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```
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**Functions:** 224 functions across FUND (79), BOND (41), FUTURES (62), OPTION (42) categories  
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**Coverage:** Mutual funds, ETFs, government bonds, corporate bonds, commodity futures, stock options
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### [Market Indices](./market-indices.md)
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**Market indices and composite indicators**
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```python { .api }
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# Chinese market indices
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index_df: pd.DataFrame = ak.stock_zh_index_spot_em()
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index_daily_df: pd.DataFrame = ak.stock_zh_index_daily(symbol="000001")
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# Global market indices  
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global_df: pd.DataFrame = ak.index_investing_global()
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# Commodity indices
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commodity_df: pd.DataFrame = ak.index_cx_commodity()
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# Volatility indices
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vix_df: pd.DataFrame = ak.index_vix()
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```
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**Functions:** 95 functions covering domestic and international indices  
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**Coverage:** Stock indices, commodity indices, volatility indices, economic composite indicators
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### [Fundamental Analysis](./fundamental-analysis.md)
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**Financial statements and company fundamental data**
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```python { .api }
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# Financial analysis indicators
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financial_df: pd.DataFrame = ak.stock_financial_analysis_indicator_em(symbol="000001")
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# Income statement data
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income_df: pd.DataFrame = ak.stock_financial_abstract(symbol="000001")
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# Balance sheet indicators
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balance_df: pd.DataFrame = ak.stock_balance_sheet_by_report_em(symbol="000001")
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# Earnings forecasts
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forecast_df: pd.DataFrame = ak.stock_profit_forecast()
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# Analyst recommendations  
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recommend_df: pd.DataFrame = ak.stock_recommend()
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```
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**Functions:** 47 functions for comprehensive fundamental analysis  
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**Coverage:** Income statements, balance sheets, cash flows, financial ratios, analyst coverage
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## Key Features
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- **No API Keys Required** - Most functions work without authentication
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- **Real-time Data Access** - Live market quotes and real-time indicators
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- **Extensive Historical Data** - Years of historical data across all asset classes
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- **Multiple Data Sources** - Redundant sources for reliability and coverage
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- **Consistent Output Format** - All functions return pandas DataFrames
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- **Chinese Market Focus** - Comprehensive coverage of Chinese financial markets
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- **International Data** - US, European, and other major market data
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- **Regular Updates** - Active development with frequent data source maintenance
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- **Open Source** - MIT license with active community development
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## Common Patterns
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### Parameter Conventions
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```python { .api }
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# Symbol parameter for specific instruments
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df = ak.stock_zh_a_hist(symbol="000001")  # Individual stock
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df = ak.fund_open_fund_daily_em(symbol="000001")  # Specific fund
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# Date range parameters  
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df = ak.stock_zh_a_hist(
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    symbol="000001",
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    start_date="20240101",  # Format: YYYYMMDD
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    end_date="20241201"
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)
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# Period parameter for data frequency
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df = ak.stock_zh_a_hist(symbol="000001", period="daily")  # daily, weekly, monthly
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```
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### Return Data Format
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```python { .api }
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# All functions return pandas DataFrame
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df: pd.DataFrame = ak.stock_zh_a_spot_em()
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# Consistent data types
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assert isinstance(df, pd.DataFrame)
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assert df.shape[0] > 0  # Always returns data when available
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```
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### Error Handling
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```python { .api }
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try:
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    df = ak.stock_zh_a_hist(symbol="000001")
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    if df.empty:
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        print("No data available for this symbol")
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except Exception as e:
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    print(f"Data retrieval error: {e}")
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```
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AKShare provides comprehensive, reliable access to financial data essential for quantitative analysis, research, and application development in the Chinese and global markets.