DEX and cryptocurrency trading data for Python - OHCLV, Uniswap, others
Project description
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
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Analyse cryptocurrency investment opportunities on decentralised exchanges (DEXes)
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Creating trading algorithms and trading bots that trade on DEXes
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Deploy trading strategies as on-chain smart contracts where users can invest and withdraw with their wallets
Features
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Supports multiple blockchains like Ethereum mainnet, Binance Smart Chain and Polygon
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Access trading data from on-chain decentralised exchanges like SushiSwap, QuickSwap and PancakeSwap
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Integration with Jupyter Notebook for easy manipulation of data. See example notebooks.
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Write algorithmic trading strategies for decentralised exchange
Getting started
See the Getting Started tutorial and the rest of the Trading Strategy documentation.
Prerequisites
- Python 3.10
Installing the package
Note: Unless you are an experienced Python developer, try the Binder cloud hosted Jupyter notebook examples first.
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]"
Documentation
Community
Read more documentation how to develop this package.
License
GNU AGPL 3.0.
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Source Distribution
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