syntheseus 0.9.0

Navigating the labyrinth of synthesis planning

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Docs • CLI • Tutorials • Paper

Overview

Syntheseus is a package for end-to-end retrosynthetic planning.

• ⚒️ Combines search algorithms and reaction models in a standardized way
• 🧭 Includes implementations of common search algorithms
• 🧪 Includes wrappers for state-of-the-art reaction models
• ⚙️ Exposes a simple API to plug in custom models and algorithms
• 📈 Can be used to benchmark components of a retrosynthesis pipeline

Quick Start

To install syntheseus with all the extras, run

conda env create -f environment_full.yml
conda activate syntheseus-full

pip install "syntheseus[all]"

This sample environment pins torch to version 2.2.2. To run the models under 1.x please downgrade to syntheseus 0.6.0.

See here if you prefer a more lightweight installation that only includes the parts you actually need.

Citation and usage

Since the release of our package, we've been thrilled to see syntheseus be used in the following projects:

If you use syntheseus in an academic project, please consider citing our associated paper from Faraday Discussions (bibtex below). You can also message us or submit a PR to have your project added to the table above!

@article{maziarz2024re,
  title={Re-evaluating retrosynthesis algorithms with syntheseus},
  author={Maziarz, Krzysztof and Tripp, Austin and Liu, Guoqing and Stanley, Megan and Xie, Shufang and Gainski, Piotr and Seidl, Philipp and Segler, Marwin},
  journal={Faraday Discussions},
  year={2024},
  publisher={Royal Society of Chemistry}
}

Development

Syntheseus is currently under active development. If you want to help us develop syntheseus please install and run pre-commit checks before committing code.

We use pytest for testing. Please make sure tests pass on your branch before submitting a PR (and try to maintain high test coverage).

python -m pytest --cov syntheseus/tests

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

Trademarks

This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft's Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.