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tessl/pypi-akshare

Comprehensive Python library for financial data acquisition providing access to Chinese and global market data.

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AKShare Python Financial Data Library

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.

Package Information

Name: akshare
Language: Python
Installation: pip install akshare
Version: 1.17.44
Dependencies: pandas, requests, beautifulsoup4, lxml

Core Imports

import akshare as ak
import pandas as pd
from typing import Optional

# AKShare provides 1,046+ functions across 37 categories
# All functions return pandas.DataFrame objects

Basic Usage

Real-time Market Data

import akshare as ak

# Get real-time A-share market data
df: pd.DataFrame = ak.stock_zh_a_spot_em()
print(df.head())
#      序号    代码    名称   最新价  涨跌幅  涨跌额    成交量        成交额
# 0    1  000001  平安银行  10.50   1.45   0.15  1234567  12950123456
# 1    2  000002   万科A   8.92  -0.89  -0.08   987654   8800765432

# Get historical data for specific stock
hist_df: pd.DataFrame = ak.stock_zh_a_hist(
    symbol="000001", 
    period="daily", 
    start_date="20240101", 
    end_date="20241201"
)

Macroeconomic Data

import akshare as ak

# Chinese Consumer Price Index
cpi_df: pd.DataFrame = ak.macro_china_cpi()
print(cpi_df.head())
#         日期     全国CPI    城市CPI    农村CPI
# 0  2024-11-01    102.3     102.1     102.8
# 1  2024-10-01    102.0     101.8     102.5

# US Non-farm Payrolls
nonfarm_df: pd.DataFrame = ak.macro_usa_non_farm()

# Chinese GDP Data
gdp_df: pd.DataFrame = ak.macro_china_gdp()

Fund and ETF Data

import akshare as ak

# Real-time ETF data
etf_df: pd.DataFrame = ak.fund_etf_spot_em()

# Open-end fund daily data
fund_df: pd.DataFrame = ak.fund_open_fund_daily_em(symbol="000001")

Architecture

AKShare follows a modular architecture organized by data source and asset class:

Data Source Integration

  • East Money (东方财富) - Functions suffixed with _em
  • Sina Finance (新浪财经) - Functions suffixed with _sina
  • Tonghuashun (同花顺) - Functions suffixed with _ths
  • JiSiLu (集思录) - Functions suffixed with _jsl
  • CNInfo (巨潮资讯网) - Functions suffixed with _cninfo

Module Organization

akshare/
├── stock/           # Core stock market data
├── stock_feature/   # Advanced stock analysis
├── economic/        # Macroeconomic indicators  
├── fund/           # Mutual funds and ETFs
├── bond/           # Bond market data
├── futures/        # Futures and derivatives
├── option/         # Options market data
├── index/          # Market indices
└── utils/          # Shared utilities

Consistent API Design

  • All functions return pandas.DataFrame objects
  • Standardized parameter patterns (symbol, period, start_date, end_date)
  • Consistent column naming and data typing
  • No API keys required for most functions

Capabilities

Stock Market Data

Core stock market data and advanced analysis features

# Real-time A-share quotes
df: pd.DataFrame = ak.stock_zh_a_spot_em()

# Historical stock data  
hist_df: pd.DataFrame = ak.stock_zh_a_hist(symbol="000001", period="daily")

# US stock real-time data
us_df: pd.DataFrame = ak.stock_us_spot()

# Hong Kong stock data
hk_df: pd.DataFrame = ak.stock_hk_spot()

# Stock Connect capital flows
hsgt_df: pd.DataFrame = ak.stock_hsgt_fund_flow_summary_em()

Functions: 325+ functions across STOCK (120) and STOCK_FEATURE (205) categories
Coverage: Chinese A-shares, Hong Kong stocks, US stocks, technical indicators, capital flows

Economic Indicators

Comprehensive macroeconomic data from multiple countries

# Chinese economic indicators
cpi_df: pd.DataFrame = ak.macro_china_cpi()
gdp_df: pd.DataFrame = ak.macro_china_gdp()
pmi_df: pd.DataFrame = ak.macro_china_pmi()

# US economic data
us_gdp_df: pd.DataFrame = ak.macro_usa_gdp()
unemployment_df: pd.DataFrame = ak.macro_usa_unemployment_rate()

# European economic indicators
euro_cpi_df: pd.DataFrame = ak.macro_euro_cpi()

Functions: 226 functions covering China, US, Europe, Japan, Australia, Canada, UK
Coverage: GDP, CPI, PMI, employment, trade, monetary policy indicators

Financial Instruments

Funds, bonds, futures, and options market data

# ETF and fund data
etf_df: pd.DataFrame = ak.fund_etf_spot_em()
fund_daily_df: pd.DataFrame = ak.fund_open_fund_daily_em(symbol="000001")

# Bond market data
bond_df: pd.DataFrame = ak.bond_zh_hs_daily()
convertible_df: pd.DataFrame = ak.bond_convert_list()

# Futures data
futures_df: pd.DataFrame = ak.futures_zh_daily_sina(symbol="RB0000")

# Options data
option_df: pd.DataFrame = ak.option_finance_board()

Functions: 224 functions across FUND (79), BOND (41), FUTURES (62), OPTION (42) categories
Coverage: Mutual funds, ETFs, government bonds, corporate bonds, commodity futures, stock options

Market Indices

Market indices and composite indicators

# Chinese market indices
index_df: pd.DataFrame = ak.stock_zh_index_spot_em()
index_daily_df: pd.DataFrame = ak.stock_zh_index_daily(symbol="000001")

# Global market indices  
global_df: pd.DataFrame = ak.index_investing_global()

# Commodity indices
commodity_df: pd.DataFrame = ak.index_cx_commodity()

# Volatility indices
vix_df: pd.DataFrame = ak.index_vix()

Functions: 95 functions covering domestic and international indices
Coverage: Stock indices, commodity indices, volatility indices, economic composite indicators

Fundamental Analysis

Financial statements and company fundamental data

# Financial analysis indicators
financial_df: pd.DataFrame = ak.stock_financial_analysis_indicator_em(symbol="000001")

# Income statement data
income_df: pd.DataFrame = ak.stock_financial_abstract(symbol="000001")

# Balance sheet indicators
balance_df: pd.DataFrame = ak.stock_balance_sheet_by_report_em(symbol="000001")

# Earnings forecasts
forecast_df: pd.DataFrame = ak.stock_profit_forecast()

# Analyst recommendations  
recommend_df: pd.DataFrame = ak.stock_recommend()

Functions: 47 functions for comprehensive fundamental analysis
Coverage: Income statements, balance sheets, cash flows, financial ratios, analyst coverage

Key Features

  • No API Keys Required - Most functions work without authentication
  • Real-time Data Access - Live market quotes and real-time indicators
  • Extensive Historical Data - Years of historical data across all asset classes
  • Multiple Data Sources - Redundant sources for reliability and coverage
  • Consistent Output Format - All functions return pandas DataFrames
  • Chinese Market Focus - Comprehensive coverage of Chinese financial markets
  • International Data - US, European, and other major market data
  • Regular Updates - Active development with frequent data source maintenance
  • Open Source - MIT license with active community development

Common Patterns

Parameter Conventions

# Symbol parameter for specific instruments
df = ak.stock_zh_a_hist(symbol="000001")  # Individual stock
df = ak.fund_open_fund_daily_em(symbol="000001")  # Specific fund

# Date range parameters  
df = ak.stock_zh_a_hist(
    symbol="000001",
    start_date="20240101",  # Format: YYYYMMDD
    end_date="20241201"
)

# Period parameter for data frequency
df = ak.stock_zh_a_hist(symbol="000001", period="daily")  # daily, weekly, monthly

Return Data Format

# All functions return pandas DataFrame
df: pd.DataFrame = ak.stock_zh_a_spot_em()

# Consistent data types
assert isinstance(df, pd.DataFrame)
assert df.shape[0] > 0  # Always returns data when available

Error Handling

try:
    df = ak.stock_zh_a_hist(symbol="000001")
    if df.empty:
        print("No data available for this symbol")
except Exception as e:
    print(f"Data retrieval error: {e}")

AKShare provides comprehensive, reliable access to financial data essential for quantitative analysis, research, and application development in the Chinese and global markets.

Install with Tessl CLI

npx tessl i tessl/pypi-akshare
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