Setting up development environment

Preface

This documentation section covers how to run Trading Strategy code examples and notebooks:

• How to set up a Python-based Trading Strategy development environment on your local computer or a cloud server

Note

If you want to get started fast, you can directly jump to Getting started Github repository and Codespaces.

Prerequisites

Code examples are available able Jupyter notebooks in this documentation.

You to be able work with the examples you need to have

• Python programming basics

• Data sciense basics: Jupyter notebook and Pandas

• Price action and technical indicator basics

Recommended set up

• We recommend trying out with Github Codespaces cloud-based tutorial first

• The next easiest option is with Visual Studio Code Visual Studio Code Dev Container for Jupyter Notebooks

• If you are experienced Python developer you can use any Python editor you wish, and install the source code from Github checkout

Development environment options

We offer different strategy development environments for different level of developers:

• Github Codespaces
• Visual Studio Code Dev Container for Jupyter Notebooks
• Docker development image
• PyCharm
• Local Python installation
• Google Colab
• Binder development

Next steps

After setting up your development environment, go to tutorials section of the documentation.

You find tutorials for:

• How to develop and backtest your own automated trading strategies

• How to analyse DeFi market data

• How to use Trading Strategy API

Getting an API key

To get a Trading Strategy API key needed to access some of the datasets, please visit here.

• Any notebook will prompt you to get and enter the API key if you do not have one yet

• Some binaries like trade-executor docker will read the API key from TRADING_STRATEGY_API_KEY environment variable.

• API key is free

Example:

export TRADING_STRATEGY_API_KEY="secret-token:tradingstrategy-d534e28..."