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https://github.com/MolecularAI/reaction_utils

Utilities for working with datasets of chemical reactions, reaction templates and template extraction.
https://github.com/MolecularAI/reaction_utils

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Utilities for working with datasets of chemical reactions, reaction templates and template extraction.

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README 

        
# rxnutils



[![License](https://img.shields.io/github/license/MolecularAI/reaction_utils)](https://github.com/MolecularAI/reaction_utils/blob/master/LICENSE)

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



## Prerequisites



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



* Linux OS (or in principle Windows or macOS)



* You have installed [anaconda](https://www.anaconda.com/) or [miniconda](https://docs.conda.io/en/latest/miniconda.html) 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.



## Installation



### For users



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](https://molecularai.github.io/reaction_utils/uspto.html)



### For developers



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 --with dev



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



## Usage



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](https://molecularai.github.io/reaction_utils/), and the documentation also provides a few examples on common tasks.



## Development



### Testing



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



 ### Documentation generation



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



The HTML documentation can be generated by



    invoke build-docs



### Linting



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.



## Contributing



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 `.

3. Make your changes and commit them: `git commit -m ''`

4. Push to the remote branch: `git push`

5. Create the pull request.



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



## Contributors



* [@ckannas](https://github.com/ckannas)

* [@SGenheden](https://www.github.com/SGenheden)

* [@anniewesterlund](https://www.github.com/anniewesterlund)

* [@Lakshidaa](https://github.com/Lakshidaa) 

* [@CBA087](https://www.github.com/CBA087) 

* [@EBjerrum](https://www.github.com/EBjerrum)

* [@A-Thakkar](https://www.github.com/A-Thakkar)

* [@marcosfelt](https://github.com/marcosfelt)

* [@asiomchen](https://github.com/asiomchen)

* [@yujiag21](https://github.com/yujiag21/)



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



## License



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



## References



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