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PyScaffold 4.5
PyScaffold is a project generator for bootstrapping high quality Python
packages, ready to be shared on PyPI and installable via pip.
It is easy to use and encourages the adoption of the best tools and
practices of the Python ecosystem, helping you and your team
to stay sane, happy and productive. The best part? It is stable and has been used
by thousands of developers for over half a decade!
Checkout out this demo project, which was set up using PyScaffold and
if you are still not convinced yet, also have a look at these reasons to use PyScaffold.
NOTE - This document refers to the latest version of PyScaffold (v4).
Please refer to v3.3 for the previous stable version.
Quickstart
Just pick your favourite installation method:
## Good old pip
# (make sure it is up-to-date: pip install -U pip setuptools)
pip install pyscaffold
## Conda for the datascience fans
conda install -c conda-forge pyscaffold
## Or even pipx for the virtualenv aficionados
pipx install pyscaffold
If you want to install all PyScaffold’s extensions you can even:
pip install pyscaffold[all]
(More details of each method are available in the installation docs)
After the installation, a new putup command will be available and you can just type:
putup my_project
This will create a new folder called my_project containing a perfect project
template with everything you need for some serious coding.
After cd-ing into your new project and creating (or activating) an isolated
development environment (with virtualenv, conda or your preferred tool),
you can do the usual editable install:
pip install -e .
… all set and ready to go!
We also recommend using tox, so you can take advantage of the automation tasks
we have setup for you, like:
tox -e build # to build your package distribution
tox -e publish # to test your project uploads correctly in test.pypi.org
tox -e publish -- --repository pypi # to release your package to PyPI
tox -av # to list all the tasks available
The following figure demonstrates the usage of putup with the new experimental
interactive mode for setting up a simple project.
It uses the –cirrus flag to add CI support (via Cirrus CI), and
tox to run automated project tasks like building a package file for
distribution (or publishing).
Type putup -h to learn about more configuration options. PyScaffold assumes
that you have Git installed and set up on your PC,
meaning at least your name and email are configured.
The project template provides you with following features:
Configuration & Packaging
All configuration can be done in setup.cfg like changing the description,
URL, classifiers, installation requirements and so on as defined by setuptools.
That means in most cases it is not necessary to tamper with setup.py.
In order to build a source or wheel distribution, just run tox -e build
(if you don’t use tox, you can also install build and run python -m build).
Package and Files Data
Additional data, e.g. images and text files, that reside within your package and
are tracked by Git will automatically be included
if include_package_data = True in setup.cfg.
It is not necessary to have a MANIFEST.in file for this to work.
Note that the include_package_data option in setup.cfg is only
guaranteed to be read when creating a wheels distribution. Other distribution methods might
behave unexpectedly (e.g. always including data files even when
include_package_data = False). Therefore, the best option if you want to have
data files in your repository but not as part of the pip installable package
is to add them somewhere outside the src directory (e.g. a files
directory in the root of the project, or inside tests if you use them for
checks). Additionally you can exclude them explicitly via the
[options.packages.find] exclude option in setup.cfg.
Versioning and Git Integration
Your project is an already initialised Git repository and uses
the information of tags to infer the version of your project with the help of
setuptools_scm.
To use this feature, you need to tag with the format MAJOR.MINOR[.PATCH]
, e.g. 0.0.1 or 0.1.
This version will be used when building a package and is also accessible
through my_project.__version__.
Unleash the power of Git by using its pre-commit hooks. This feature is
available through the --pre-commit flag. After your project’s scaffold
was generated, make sure pre-commit is installed, e.g. pip install pre-commit,
then just run pre-commit install.
A default .gitignore file is also provided; it is
well adjusted for Python projects and the most common tools.
Sphinx Documentation
PyScaffold will prepare a docs directory with all you need to start writing
your documentation.
Start editing the file docs/index.rst to extend the documentation.
The documentation also works with Read the Docs.
The Numpy and Google style docstrings are activated by default.
If you have tox in your system, simply run tox -e docs or tox -e doctests to compile the docs or run the doctests.
Alternatively, if you have make and Sphinx installed in your computer, build the
documentation with make -C docs html and run doctests with
make -C docs doctest. Just make sure Sphinx 1.3 or above is installed.
Automation, Tests & Coverage
PyScaffold relies on pytest to run all automated tests defined in the subfolder
tests. Some sane default flags for pytest are already defined in the
[tool:pytest] section of setup.cfg. The pytest plugin pytest-cov is used
to automatically generate a coverage report. It is also possible to provide
additional parameters and flags on the commandline, e.g., type:
pytest -h
to show the help of pytest (requires pytest to be installed in your system
or virtualenv).
Projects generated with PyScaffold by default support running tests via tox,
a virtualenv management and test tool, which is very handy. If you run:
tox
in the root of your project, tox will download its dependencies, build the
package, install it in a virtualenv and run the tests using pytest, so you
are sure everything is properly tested.
JUnit and Coverage HTML/XML
For usage with a continuous integration software JUnit and Coverage XML output
can be activated in setup.cfg. Use the flag --cirrus to generate
templates of the Cirrus CI configuration file .cirrus.yml which even
features the coverage and stats system Coveralls.
Management of Requirements & Licenses
Installation requirements of your project can be defined inside setup.cfg,
e.g. install_requires = numpy; scipy. To avoid package dependency problems
it is common to not pin installation requirements to any specific version,
although minimum versions, e.g. sphinx>=1.3, and/or maximum versions, e.g.
pandas<0.12, are used frequently in accordance with semantic versioning.
All licenses from choosealicense.com can be easily selected with the help
of the --license flag.
Extensions
PyScaffold comes with several extensions:
If you want a project setup for a Data Science task, just use --dsproject
after having installed pyscaffoldext-dsproject.
Have a README.md based on Markdown instead of README.rst by using
--markdown after having installed pyscaffoldext-markdown.
Create a Django project with the flag --django which is equivalent to
django-admin startproject my_project enhanced by PyScaffold’s features
(requires pyscaffoldext-django).
… and many more like --gitlab to create the necessary files for GitLab,
--travis for Travis CI (see pyscaffoldext-travis), or
--cookiecutter for Cookiecutter integration (see pyscaffoldext-cookiecutter).
Find more extensions within the PyScaffold organisation and consider contributing your own,
it is very easy! You can quickly generate a template for your extension with the
--custom-extension option after having installed pyscaffoldext-custom-extension.
All extensions can easily be installed with pip install pyscaffoldext-NAME.
Easy Updating
Keep your project’s scaffold up-to-date by applying
putup --update my_project when a new version of PyScaffold was released.
An update will only overwrite files that are not often altered by users like
setup.py. To update all files use --update --force.
An existing project that was not setup with PyScaffold can be converted with
putup --force existing_project. The force option is completely safe to use
since the git repository of the existing project is not touched!
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
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