[](https://github.com/tradingstrategy-ai/trading-strategy/actions/workflows/python-app.yml)
[](https://github.com/tradingstrategy-ai/trading-strategy/actions/workflows/pip-install.yml)
[](https://tradingstrategy.ai)
# Trading Strategy framework for Python
Trading Strategy framework is a Python framework for algorithmic trading on decentralised exchanges.
It is using [backtesting data](https://tradingstrategy.ai/trading-view/backtesting) and [real-time price feeds](https://tradingstrategy.ai/trading-view)
from [Trading Strategy Protocol](https://tradingstrategy.ai/).
# Use cases
* Analyse cryptocurrency investment opportunities on [decentralised exchanges (DEXes)](https://tradingstrategy.ai/trading-view/exchanges)
* 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](https://tradingstrategy.ai/trading-view/ethereum), [Binance Smart Chain](https://tradingstrategy.ai/trading-view/binance) and [Polygon](https://tradingstrategy.ai/trading-view/polygon)
* Access trading data from on-chain decentralised exchanges like [SushiSwap](https://tradingstrategy.ai/trading-view/ethereum/sushiswap), [QuickSwap](https://tradingstrategy.ai/trading-view/polygon/quickswap) and [PancakeSwap](https://tradingstrategy.ai/trading-view/binance/pancakeswap-v2)
* Integration with [Jupyter Notebook](https://jupyter.org/) for easy manipulation of data
* Utilise Python quantita frameworks like [Backtrader](https://github.com/tradingstrategy-ai/backtrader) and [QSTrader](https://github.com/tradingstrategy-ai/qstrader) to create, analyse and backtest DEX trading algorithms
# Example and getting started
See [the Getting Started notebook](https://tradingstrategy.ai/docs/programming/examples/getting-started.html) and the rest of the [Trading Strategy documentation](https://tradingstrategy.ai/docs/).
# Prerequisites
Python 3.9+
# Installing the package
**Note**: Unless you are an experienced Python developer, [the suggested usage of Trading Algorithm framework is using Google Colab hosted environments](https://tradingstrategy.ai/docs/programming/examples/getting-started.html).
You can install this package with `poetry` or `pip`
```shell
poetry add trading-strategy
```
```shell
pip install trading-strategy
```
For [QSTrader](https://pypi.org/project/trading-strategy-qstrader/) based trading algorithm support you need to install the related optional dependencies:
```shell
poetry add trading-strategy[qstrader]
```
# Documentation
[Read documentation online](https://tradingstrategy.ai/docs/).
Community
---------
* [Trading Strategy website](https://tradingstrategy.ai)
* [Blog](https://tradingstrategy.ai/blog)
* [Twitter](https://twitter.com/TradingProtocol)
* [Discord](https://tradingstrategy.ai/community#discord)
* [Telegram channel](https://t.me/trading_protocol)
* [Changelog and version history](https://github.com/tradingstrategy-ai/trading-strategy/blob/master/CHANGELOG.md)
[Read more documentation how to develop this package](https://tradingstrategy.ai/docs/programming/development.html).
# License
GNU AGPL 3.0.
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