trading-strategy 0.22.1

Algorithmic trading, token and cryptocurrency DEX trading data, for Uniswap, Aave, PancakeSwap, Sushi, Trader Joe, others

Trading Strategy framework for Python

Trading Strategy framework is a Python framework for algorithmic trading on decentralised exchanges. It is using backtesting data and real-time price feeds from Trading Strategy Protocol.

Use cases

• Analyse cryptocurrency investment opportunities on decentralised exchanges (DEXes)

• Creating trading algorithms and trading bots that trade on DEXes

• Deploy trading strategies as on-chain smart contracts where users can invest and withdraw with their wallets

Features

• Supports multiple blockchains like Ethereum mainnet, Binance Smart Chain and Polygon

• Access trading data from on-chain decentralised exchanges like SushiSwap, QuickSwap and PancakeSwap

• Integration with Jupyter Notebook for easy manipulation of data. See example notebooks.

• Write algorithmic trading strategies for decentralised exchange

Getting started

See the Getting Started tutorial and the rest of the Trading Strategy documentation. The easiest way to get started is ready Dev Container for Visual Studio Code.

Prerequisites

• Python 3.10

• Understanding Python package management and installation (unless using Dev Container from teh above)

Installing the package

You can install this package with

Poetry as a dependency:

poetry add trading-strategy -E direct-feed

Poetry, local development:

poetry install -E direct-feed

Pip:

pip install "trading-strategy[direct-feed]" 

Note: trading-strategy package provides trading data download and management functionality only. If you want to developed automated trading strategies you need to install trade-executor package as well.

Documentation

• Read Trading Strategy documentation.

Community

• Trading Strategy website

• Blog

• Twitter

• Discord

• Telegram channel

• Changelog and version history

Read more documentation how to develop this package.

License

GNU AGPL 3.0.