Utilities to work with datasets of chemical reactions, reaction templates and template extraction

Before you begin, ensure you have met the following requirements:

• Linux OS (or in principle Windows or macOS)

• You have installed anaconda or miniconda with python 3.8

The tool has been developed and fully tested on a Linux platform, but it is only occassionally tested on Windows and macOS. If you find an issue on a Windows or macOS platform, we might be able to fix, but we might just disable that feature on those platforms.

Setup your python environment and then run

pip install reaction-utils

Consult the documentation for further information.

For some tasks such as atom-mapping with rxnmapper you need to setup additional environment and packages, see here

First clone the repository using Git.

Then execute the following commands in the root of the repository

conda env create -f env-dev.yml
conda activate rxn-env
poetry install

the rxnutils package is now installed in editable mode.

Lastly, make sure to install pre-commits that are run on every commit

pre-commit install

The package is divided into (currently) three sub-packages:

• chem - chemistry routines like template extraction or reaction cleaning
• data - routines for manipulating various reaction data sources
• pipeline - routines for building and executing simple pipelines for modifying and analyzing reactions
• routes - routines for handling synthesis routes

The full auto-generated API document is available here, and the documentation also provides a few examples on common tasks.

Tests uses the pytest package, and is installed by poetry

Run the tests using:

pytest -v

The full command with all flags for CI is available through an invoke command

invoke run-tests

The documentation is generated by Sphinx from hand-written tutorials and docstrings

The HTML documentation can be generated by

invoke build-docs

Linting is done preferably with pylint.

invoke run-linting

Currently we do not use mypy to check type annotations, but this will be switched on in the future.

We welcome contributions, in the form of issues or pull requests.

If you have a question or want to report a bug, please submit an issue.

To contribute with code to the project, follow these steps:

1. Fork this repository.
2. Create a branch: git checkout -b <branch_name>.
3. Make your changes and commit them: git commit -m '<commit_message>'
4. Push to the remote branch: git push
5. Create the pull request.

Please use black package for formatting, and follow pep8 style guide.

• @ckannas
• @SGenheden
• @anniewesterlund
• @Lakshidaa
• @CBA087
• @EBjerrum
• @A-Thakkar

The contributors have limited time for support questions, but please do not hesitate to submit an issue (see above).

The software is licensed under the Apache 2.0 license (see LICENSE file), and is free and provided as-is.

1. Thakkar A, Kogej T, Reymond J-L, et al (2019) Datasets and their influence on the development of computer assisted synthesis planning tools in the pharmaceutical domain. Chem Sci. https://doi.org/10.1039/C9SC04944D

2. Kannas C, Thakkar A, Bjerrum E, Genheden S (2022) rxnutils – A Cheminformatics Python Library for Manipulating Chemical Reaction Data. ChemRxiv. https://doi.org/10.26434/chemrxiv-2022-wt440-v2