Features
The resulting project uses
rituals
and invoke
for task automation, and
setuptools
for building and distributing the project.
A provided autoenv script takes care
of creating a fully boot-strapped virtualenv – it can also be used manually
if you don't want to install autoenv.
The setup.py script follows the DRY principle and tries to
minimize repetition of project metadata by loading it from other
places (like the package's __init__.py). Incidently, this makes
the script almost identical between different projects, and thus
provides an easy update experience later on. Usually, the only specific
thing in it is the docstring with the project's name and license notice.
This relies on conventions, specially check out
__init__.py
and
__main__.py
in the src folder, for their double-underscore meta variables.
It is also importable (by using the usual if __name__ == '__main__'
idiom), and exposes the project's setup data in a project dict.
This allows other tools to exploit the contained data assembling code,
and again supports the DRY principle. The rituals package
uses that to provide Invoke tasks that work for any project, based on
its project metadata.
Other integrated tools are pylint for code quality checking,
pytest for testing support, and a Travis CI configuration.
Using the Template
Preparations
In case you don't have the cookiecutter command line tool yet, here's
how to install it.
 |
For py-generic-project v1.2 and upwards, you need at least cookiecutter v1.0 – for pipsi installs, just issue a pipsi upgrade cookiecutter command and you're done. |
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Project Creation
Creating a new Python project based on this template goes like this (make sure you're in the directory you want your project added to):
cookiecutter "https://github.com/Springerle/py-generic-project.git"It's advisable to git add the created directory directly afterwards, before any
generated files are added, that you don't want to have in your repository.
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To get your defaults for common template values cookiecutter will ask you for when you use a template, it makes sense to have a ~/.cookiecutterrc in your home directory. Follow the link to see an example. |
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You should at least check these files regarding their content and adapt them according to your needs:
-
classifiers.txt– Add the correct categories (a/k/a Trove classifiers) for your project. -
requirements.txt– Add any Python packages you need for your project at runtime.
To bootstrap the project (as mentioned, best after git add), use these commands from within its directory:
. .env --yes --develop
inv ci | less -R
"$(basename $(pwd))" --help