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Helpers for handling chemical formulas in Python

Project description

https://travis-ci.org/ginkgobioworks/pychemy.svg?branch=master

Helpers for handling chemical formulas in Python. Mostly adopted from work of Christoph Gohlke. Added methods that are useful for mass spec data analysis.

Depends on Open Babel and its Python bindings for handling InChI strings.

Development

Development requires Docker and Make on your host system. Everything else, including Open Babel, is taken care of inside the Docker containers.

Spin up your container using the provided docker-compose.yml file and Makefile by running make image. This creates an image with a correct git configuration for your user, which makes it easy to release. All of the commands you should need to run are defined the Makefile as targets. All of the targets except for image, are meant to be run inside the Docker container, but can be run from the host machine by having -ext appended to them. For example, to run tests, you could either call make test from a shell inside the container, or make test-ext from the host.

This project supports both Python 2 and Python 3. To test Python 3, make run the make test and make test-ext with the TOXENV environment set to py3, e.g.:

TOXENV=py3 ./make test-ext

All pull requests are run through the Travis CI process specified in .travis.yml and must pass all unit and doc tests in Python 2 and Python 3 before being accepted.

Deployment

Deployment of tagged commits happens to PyPI automatically via Travis CI. To bump and deploy a new version directly, you must have access to write to the master branch. Run make bump/[foo]-ext, where [foo] is major, minor, or patch. Then git push origin --tags master. If you do not have access to the master branch, do the same thing, but in a separate branch, and make a pull request.

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Source Distribution

pychemy-0.4.6.tar.gz (601.6 kB view hashes)

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Built Distribution

pychemy-0.4.6-py2.py3-none-any.whl (639.8 kB view hashes)

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