Zvt

](https://github.com/zvtvz/zvt) [ ](https://pypi.org/project/zvt/) [ ](https://github.com/zvtvz/zvt/actions/workflows/build.yml) [ ](https://zvt.readthedocs.io/en/latest/?badge=latest) [ [](https://pepy.tech/project/zvt)

The origin of ZVT

The Three Major Principles of Stock Trading

Declaration

This project does not currently guarantee any backward compatibility, so please upgrade with caution. As the author's thoughts evolve, some things that were once considered important may become less so, and thus may not be maintained. Whether the addition of some new elements will be useful to you needs to be assessed by yourself.

Read this in other languages: [中文](README-cn.md).

Read the docs:[https://zvt.readthedocs.io/en/latest/](https://zvt.readthedocs.io/en/latest/)

Install

python3 -m pip install -U zvt

Main ui

#### Dash & Plotly UI

It's good for backtest and research, but it is not applicable for real-time market data and user interaction.

After the installation is complete, enter zvt on the command line

zvt

open http://127.0.0.1:8050/

The example shown here relies on data, factor, trader, please read docs

The core concept of the system is visual, and the name of the interface corresponds to it one-to-one, so it is also uniform and extensible.

You can write and run the strategy in your favorite ide, and then view its related targets, factor, signal and performance on the UI.

#### Rest api and standalone UI

It is more flexible and more scalable, more suitable for handling real-time market data and user interaction. Combined with the dynamic tag system provided by ZVT, it offers a trading approach that combines AI with human intervention.

• Init tag system

run following scripts:

https://github.com/zvtvz/zvt/blob/master/src/zvt/tasks/init_tag_system.py https://github.com/zvtvz/zvt/blob/master/src/zvt/tasks/stock_pool_runner.py https://github.com/zvtvz/zvt/blob/master/src/zvt/tasks/qmt_data_runner.py https://github.com/zvtvz/zvt/blob/master/src/zvt/tasks/qmt_tick_runner.py

• Install uvicorn

pip install uvicorn

• Run zvt server

After the installation is complete, enter zvt_server on the command line

zvt_server

Or run it from source code: https://github.com/zvtvz/zvt/blob/master/src/zvt/zvt_server.py

• Check the api docs

open http://127.0.0.1:8090/docs

• Deploy the front end service

Front end source code: https://github.com/zvtvz/zvt_ui

Change the env file: https://github.com/zvtvz/zvt_ui/blob/main/.env

Set {your server IP} to zvt_server IP

NEXT_PUBLIC_SERVER = {your server IP}