TdxQuant - TongDaXin Quantitative Platform

(通达信量化平台)

Project Introduction

TdxQuant is a professional quantitative investment research platform developed by Shenzhen Wealth Trend Technology Co., Ltd., focusing on providing a full-process solution from strategy research to investment decisions for domestic quantitative investors. This project provides the conversion of the core Python components of the TongDaXin quantitative platform into an editable Python installation package.

The project content is consistent with the files in the <TongDaXin Installation Directory>/PYPlugins/user/ directory. A pyproject.toml file has been added to manage project dependencies.

Runtime Environment Requirements

System Requirements

Operating System: Windows platform
Python Version: Python 3.13 (recommended)

Core Dependencies

backtrader>=1.9.78.123
numpy>=2.4.3
pandas>=3.0.1
vectorbt>=0.28.2

Prerequisites

Must start TongDaXin client first: Need to use TongDaXin Professional Research Edition, Quantitative Simulation Edition, or Futures Edition that supports TQ strategy functionality
Must login to TongDaXin account: Ensure the client has logged in normally and has the corresponding data permissions

Installation Method

⚠️ Important Note: Path Dependency and Installation Mode

This project, as a component of the TongDaXin quantitative platform, has fixed path dependencies, and the Python package does not support release mode. During development and use, project dependencies must be installed through editable mode.

Installation Steps

1. Confirm Project Path

Ensure the project is located in the correct path of the TongDaXin client:

<TongDaXin Installation Directory>/PYPlugins/user/

2. Editable Mode Installation (Required)

Execute the following command in the project root directory:

pip install -e .

Explanation:

The -e parameter indicates installation in editable mode, allowing developers to modify code directly without reinstalling
This installation method ensures the project can correctly access the TongDaXin client's DLL files and other dependent resources
After installation, you can directly import the tqcenter module for use

3. Verify Installation

from tqcenter import tq
print("TdxQuant installed successfully!")

Path Dependency Instructions

Core Dependency Files

The project depends on the core dynamic link library provided by the TongDaXin client:

<TongDaXin Installation Directory>/PYPlugins/TPythClient.dll

Path Resolution Mechanism

The project automatically locates DLL files through relative paths: Path(__file__).resolve().parents[1] / 'TPythClient.dll'
This requires the project to remain in the standard directory structure of the TongDaXin client
Never move or rename the project directory, otherwise DLL loading will fail

Core Functional Modules

1. Data Acquisition Module

K-Line Data Acquisition

from tqcenter import tq

tq.initialize(__file__)

df = tq.get_market_data(
    field_list=['Open', 'High', 'Low', 'Close', 'Volume'],
    stock_list=['688318.SH'],
    start_time='20250101',
    end_time='20250601',
    period='1d',
    dividend_type='none'
)

Supported K-line periods: 1d, 1w, 1m, 5m, 15m, 30m, 60m, etc.

Adjustment types:

none: No adjustment
front: Forward adjustment
back: Backward adjustment

Market Snapshot Data

snapshot = tq.get_market_snapshot(stock_code='688318.SH')

Financial Data Acquisition

basic_financial = tq.get_stock_info(stock_code='688318.SH')

professional_financial = tq.get_financial_data(
    stock_list=['688318.SH'],
    field_list=['Fn193', 'Fn194'],
    start_time='20250101',
    report_type='announce_time'
)

2. Trading Calendar and Stock List

Trading Date Acquisition

trade_dates = tq.get_trading_dates(
    market='SH',
    start_time='20250101',
    end_time='20251231'
)

Stock List Acquisition

all_stocks = tq.get_stock_list('5')
etf_list = tq.get_stock_list('31')

List type codes:

5: All A-shares
31: ETF funds
32: Convertible bonds
51: ChiNext
52: STAR Market
53: Beijing Stock Exchange

3. Sector Management

Get Sector List

block_list = tq.get_sector_list()

Get Sector Constituents

stocks = tq.get_stock_list_in_sector('Titanium Metal')

Custom Sector Management

tq.create_sector(block_code='MYBK', block_name='My Sector')
tq.send_user_block(block_code='MYBK', stocks=['688318.SH', '600519.SH'])
tq.delete_sector(block_code='MYBK')

4. TongDaXin Formula Integration

Indicator Formula Call

macd_result = tq.formula_zb(formula_name='MACD', formula_arg='12,26,9')

Condition Stock Selection Formula

selected_stocks = tq.formula_xg(formula_name='UPN', formula_arg='3')

Batch Formula Processing

results = tq.formula_process_mul_zb(
    formula_name='MACD',
    formula_arg='12,26,9',
    stock_list=['688318.SH', '600519.SH'],
    stock_period='1d',
    count=100
)

5. Real-time Subscription and Alerts

Subscribe to Stock Updates

def my_callback(data_str):
    import json
    data = json.loads(data_str)
    print(f"Stock {data['Code']} has an update")

tq.subscribe_hq(stock_list=['688318.SH'], callback=my_callback)

Send Alert Signal

tq.send_warn(
    stock_list=['688318.SH'],
    time_list=['20250620143000'],
    price_list=['123.45'],
    close_list=['122.50'],
    volum_list=['1000'],
    reason_list=['Price breakthrough alert line'],
    count=1
)

6. Data Export and Visualization

Export Factor Data

import pandas as pd

df = pd.DataFrame({
    'Date': ['2025-01-01', '2025-01-02'],
    'Factor1': [1.2, 1.3],
    'Factor2': [2.1, 2.2]
})

tq.print_to_tdx(
    df_list=[df],
    sp_name='My Factor',
    xml_filename='factor.xml'
)

Integration Points with TongDaXin Quantitative Platform

1. Initialize Connection

All strategies must first call the initialization function:

from tqcenter import tq

tq.initialize(__file__)

This function will:

Establish connection with the TongDaXin client
Load necessary DLL resources
Initialize data channels

2. Data Permissions and Download

Some historical data needs to be downloaded in the TongDaXin client first
Professional financial data needs to be pre-downloaded in the client
It is recommended to refresh the market cache before running the strategy:

tq.refresh_cache()

3. Strategy Lifecycle Management

from tqcenter import tq

try:
    tq.initialize(__file__)
    
    # Strategy logic code
    # ...
    
finally:
    # Ensure proper connection closure
    tq.close()

Important:

The connection will be automatically disconnected when the program exits
If there is an abnormal exit, you need to manually delete the strategy record in the TongDaXin strategy manager

4. Stock Code Format Specification

Must use standard format: 6-digit code.market suffix

Examples:

Shanghai Stock Exchange: 600519.SH, 688318.SH
Shenzhen Stock Exchange: 000001.SZ, 300750.SZ
Beijing Stock Exchange: 832566.BJ

5. Time Format Specification

Date format: YYYYMMDD (e.g.: 20250620)
Datetime format: YYYYMMDDHHMMSS (e.g.: 20250620143000)

6. Data Unit Description

Price data: Unit is Yuan
Volume: Unit is lots
Turnover: Unit is ten thousand Yuan
Financial data (share capital, assets, liabilities, etc.): Unit is ten thousand Yuan

Quick Start Example

Complete Strategy Example

from tqcenter import tq
import pandas as pd

def simple_strategy():
    try:
        # 1. Initialize connection
        tq.initialize(__file__)
        
        # 2. Get stock list
        stock_list = tq.get_stock_list('5')
        
        # 3. Get K-line data
        df = tq.get_market_data(
            stock_list=['688318.SH'],
            start_time='20250101',
            end_time='20250601',
            period='1d',
            dividend_type='front'
        )
        
        # 4. Calculate simple indicator
        close_prices = tq.price_df(df, 'Close')
        ma20 = close_prices.rolling(window=20).mean()
        
        # 5. Send message to client
        tq.send_message("Strategy completed | 20-day moving average calculated")
        
        # 6. Export factor data
        tq.print_to_tdx(
            df_list=[ma20],
            sp_name='MA20 Factor',
            xml_filename='ma20_factor.xml'
        )
        
        print("Strategy executed successfully!")
        
    except Exception as e:
        print(f"Strategy execution error: {e}")
        tq.send_message(f"Strategy error: {str(e)}")
        
    finally:
        # 7. Close connection
        tq.close()

if __name__ == '__main__':
    simple_strategy()

Precautions

⚠️ Important Warnings

Must use editable mode installation
- The project does not support the regular installation mode of pip install
- Must use pip install -e . for editable mode installation
- Does not support publishing to PyPI or other package management platforms
Path dependency cannot be changed
- The project must run in the standard directory structure of the TongDaXin client
- Never move, rename the project directory, or modify the relative path structure
Client dependency
- Must start the TongDaXin client and login before running
- Need to use a client version that supports TQ strategy functionality
- Ensure the client has the corresponding data permissions
Data preparation
- Historical K-line data needs to be pre-downloaded in the client
- Professional financial data needs to be pre-downloaded in the client
- It is recommended to refresh the market cache regularly
Connection management
- Be sure to call tq.close() to close the connection when the strategy ends
- After abnormal exit, you need to clean up the strategy record in the strategy manager
- Avoid running multiple strategy instances with the same name simultaneously

💡 Best Practices

Error handling

try:
    tq.initialize(__file__)
    # Strategy logic
except Exception as e:
    print(f"Error: {e}")
    tq.send_message(f"Strategy exception: {str(e)}")
finally:
    tq.close()

Data validation

# Validate stock code format
if not check_stock_code_format('688318.SH'):
    print("Stock code format error")

Performance optimization
- Batch data retrieval instead of fetching stock by stock
- Reasonable use of caching mechanisms
- Avoid frequent market data refresh

Technical Support

Official Documentation: https://help.tdx.com.cn/quant/docs/markdown/mindoc-1cfsjkbf8f3is/

License Statement

This project is a core component of the TongDaXin quantitative platform, and its use must comply with the relevant license agreements of TongDaXin. Unauthorized use for commercial purposes or secondary distribution is prohibited.

Name		Name	Last commit message	Last commit date
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.gitignore		.gitignore
.python-version		.python-version
README.md		README.md
README.zh-CN.md		README.zh-CN.md
pyproject.toml		pyproject.toml
tdxdata_test.py		tdxdata_test.py
tdxdemo.ipynb		tdxdemo.ipynb
tqcenter.py		tqcenter.py
uv.lock		uv.lock

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