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Trading Strategy Python client version 0.3 released

Trading Strategy protocol Python client is a Jupyter Notebook library for researching and executing algorithmic trading on decentralised exchanges. It is aimed at quantitative finance researches working on blockchains and decentralised finance (DeFi).

An example screenshot of running a Jupyter data science research notebook

The release 0.3 marks the first release with proper multichain support for Ethereum mainnet, Binance Smart Chain and Polygon.

Read the Getting started tutorial, view the package on PyPi and Github.

Release notes

  • Multiple changes to make the multichain backtesting possible.

  • The documentation code examples will be updated to reflect multichain support over time and may work incorrectly at the moment. Getting Started tutorial is already updated.

  • This is a major release deprecating activity flags in the trading pair universe.
    The multichain trading pair data is too big to include inactivate trading pairs (800k+ total trading pairs).
    Thus, the pair universe set only contains active trading pairs after this release,
    making the trading pair universe less than 100k trading pairs again, making it more feasible to download the data.

  • ExchangeUniverse.get_by_chain_and_slug() is now canonical way to refer to an exchange

  • PairUniverse.get_pair_by_ticker_by_exchange() is now canonical way to refer to a trading pair

  • Clarify primary keys may not be stable and should no longer referred permanently

  • Exchange.homepage and Exchange.active_pair_count fields added

Trading Strategy is an algorithmic trading protocol for decentralised markets, enabling automated trading on decentralised exchanges (DEXs). Learn more about algorithmic trading here.

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