Algorithmic trading data for cryptocurrencies and DEXes like Uniswap, Aave and PancakeSwap
Trading Strategy framework is a Python framework for algorithmic trading on decentralised exchanges.
The trading-strategy library provides data fetching for backtesting and live trading.
It is using backtesting data and real-time price feeds from Trading Strategy Protocol.
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
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
See the Getting Started repository and the rest of the Trading Strategy documentation.
Python 3.10
Understanding Python package management and installation (unless using Dev Container from teh above)
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.
Read more documentation how to develop this package.
GNU AGPL 3.0.
FAQs
Algorithmic trading data for cryptocurrencies and DEXes like Uniswap, Aave and PancakeSwap
We found that trading-strategy demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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