tushare-complete

Tushare Complete - Complete Interface Library

Tushare Pro's most complete data interface library, containing 266 data interfaces, covering all fields such as A-shares, Hong Kong stocks, US stocks, funds, futures, bonds, and macroeconomics.

Applicable Scenarios

• Need to obtain any financial market data
• Quantitative investment research
• Financial analysis
• Industry research
• Macroeconomic analysis
• Capital flow analysis
• Margin trading data analysis

Interface Category Index

I. Stock Data (14)

Interface	Method	Description
Stock List	pro.stock_basic()	Obtain basic information for all stocks
Daily Share Capital (Pre-market)	pro.daily_basic()	Daily share capital changes
Trading Calendar	pro.trade_calendar()	Trading calendar query
ST Stock List	pro.st_stock_list()	ST Stock List
Shanghai-Hong Kong Stock Connect Stock List	pro.hs_const()	Shanghai-Hong Kong Stock Connect constituent stocks

II. Market Data (23)

Interface	Method	Description
Historical Daily Line	pro.daily()	Daily line market data
Real-time Daily Line	pro.daily_now()	Real-time Daily Line
Historical Minutes	pro.stk_mins()	Minute line data
Weekly Line Market	pro.weekly()	Weekly line data
Monthly Line Market	pro.monthly()	Monthly line data

III. Financial Data (10)

Interface	Method	Description
Income Statement	pro.income()	Operating revenue, net profit
Balance Sheet	pro.balancesheet()	Construction in progress, total assets
Cash Flow Statement	pro.cashflow()	Capital expenditure, cash flow
Financial Indicator Data	pro.fina_indicator()	ROE, ROA, etc.

Important Field Descriptions：

Balance Sheet (balancesheet)：

• cip - Construction in progress (important!)
• fix_assets - Fixed assets
• total_assets - Total assets

Cash Flow Statement (cashflow)：

• c_pay_acq_const_fiolta - Cash paid for the purchase and construction of fixed assets, intangible assets, and other long-term assets (capital expenditure)
• n_cashflow_act - Net cash flow from operating activities

IV. Macroeconomics (28)

Interface	Method	Description
Shibor Interest Rate	pro.shibor()	Shibor Interest Rate
LPR Loan Prime Rate	pro.lpr()	LPR Interest Rate
Gross Domestic Product (GDP)	pro.gdp()	GDP data
Consumer Price Index (CPI)	pro.cpi()	CPI data
Producer Price Index for Industrial Products (PPI)	pro.ppi()	PPI data
Money Supply	pro.m2()	M2 data
Purchasing Managers' Index (PMI)	pro.pmi()	PMI data

Quick Start

Token Configuration

import tushare as ts
pro = ts.pro_api('your_token_here')

Common Interface Examples

Get stock list

df = pro.stock_basic(exchange='', list_status='L',
                  fields='ts_code,symbol,name,area,industry,list_date')

Get daily quotes

df = pro.daily(ts_code='000001.SZ',
             start_date='20240101',
             end_date='20241231')

Get balance sheet (including construction in progress)

df = pro.balancesheet(ts_code='600000.SH',
                    start_date='20240101',
                    end_date='20241231')
cip_data = df[['ts_code', 'end_date', 'cip', 'fix_assets', 'total_assets']]

Get cash flow statement (including capital expenditure)

df = pro.cashflow(ts_code='600000.SH',
                start_date='20240101',
                end_date='20241231')
capex_data = df[['ts_code', 'end_date', 'c_pay_acq_const_fiolta']]

Get macroeconomic GDP

df = pro.gdp(start_date='20220101', end_date='20221231')

Get CPI

df = pro.cpi(start_date='20220101', end_date='20221231')

Get PMI

df = pro.pmi(start_date='20220101', end_date='20221231')

Get Shibor

df = pro.shibor(start_date='20240101', end_date='20240131')

Data quality inspection rules

According to Rule 3, after retrieving 100 complete data sets, the following must be checked:

def validate_data_quality(df, required_fields):
    """
    数据质量检验
    
    参数:
        df: DataFrame
        required_fields: 必需字段列表
    
    返回:
        dict: 检验结果
    """
    result = {
        'total_records': len(df),
        'missing_values': {},
        'zero_values': {},
        'valid_records': 0
    }
    
    for field in required_fields:
        missing = df[field].isna().sum()
        zeros = (df[field] == 0).sum()
        result['missing_values'][field] = missing
        result['zero_values'][field] = zeros
    
    result['valid_records'] = len(df.dropna(subset=required_fields))
    
    return result

# 使用示例
required_fields = ['cip', 'c_pay_acq_const_fiolta', 'revenue', 'n_income_attr_p']
quality = validate_data_quality(df, required_fields)
print(quality)

API call rate limits

• Free users: 120 times per minute
• Points users: increased according to points tier

Points requirements

Some APIs require specific points:

• Basic data: free
• Financial data: 2000 points
• Advanced data: 5000 points

Reference resources

• Tushare official documentation:https://tushare.pro/document/2
• API testing tool:https://tushare.pro/document/1
• Points description:https://tushare.pro/document/1?doc_id=108

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Last updated: 2026-02-02 10:51