Python Boilerplate contains all the boilerplate you need to create a Python package.
Project description
Python Boilerplate (python_boilerplate)
This is a test repo.
Documentation
For more detailed instructions, see our documentation.
Installation
To install python_boilerplate (indexed online as bryn_python_boilerplate), we recommend using the mamba package manager:
As a user
mamba create -n python_boilerplate -c conda-forge -c brynpickering bryn_python_boilerplate
mamba activate python_boilerplate
As a developer
git clone git@github.com:brynpickering/python_boilerplate.git
cd python_boilerplate
mamba create -n python_boilerplate -c conda-forge --file requirements/base.txt --file requirements/dev.txt
mamba activate python_boilerplate
pip install --no-deps -e .
For more detailed instructions, see our documentation.
Contributing
There are many ways to contribute to python_boilerplate. Before making contributions to the python_boilerplate source code, see our contribution guidelines and follow the development install instructions.
If you plan to make changes to the code then please make regular use of the following tools to verify the codebase while you work:
pre-commit
: runpre-commit install
in your command line to load inbuilt checks that will run every time you commit your changes. The checks are: 1. check no large files have been staged, 2. lint python files for major errors, 3. format python files to conform with the pep8 standard. You can also run these checks yourself at any time to ensure staged changes are clean by simple callingpre-commit
.pytest
- run the unit test suite and check test coverage.pytest -p memray -m "high_mem" --no-cov
(not available on Windows) - after installing memray (mamba install memray pytest-memray
), test that memory and time performance does not exceed benchmarks.
For more information, see our documentation.
Building the documentation
If you are unable to access the online documentation, you can build the documentation locally. First, install a development environment of python_boilerplate, then deploy the documentation using mike:
mike deploy develop
mike serve
Then you can view the documentation in a browser at http://localhost:8000/.
Credits
This package was created with Cookiecutter and the arup-group/cookiecutter-pypackage project template.
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