PyScaffold helps you setup a new Python project. Just install it with:
pip install pyscaffold
or if you want to also install all extensions with:
pip install pyscaffold[all]
If you prefer conda over pip, just install PyScaffold with:
conda install -c conda-forge pyscaffold
This will give you a new
putup command and you can just type:
This will create a new folder called
my_project containing a perfect project
template with everything you need for some serious coding. After the usual:
python setup.py develop
you are all set and ready to go.
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 in
my_project 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
In order to build a source, binary or wheel distribution, just run
python setup.py sdist,
python setup.py bdist or
python setup.py bdist_wheel (recommended).
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
include_package_data = True in
It is not necessary to have a
MANIFEST.in file for this to work.
Versioning and Git Integration
Your project is an already initialised Git repository and
the information of tags to infer the version of your project with the help of
To use this feature, you need to tag with the format
python setup.py --version to retrieve the current PEP440-compliant
version. This version
will be used when building a package and is also accessible through
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
.gitignore file is also provided; it is
well adjusted for Python projects and the most common tools.
Build the documentation with
python setup.py docs and run doctests with
python setup.py doctest after you have Sphinx installed.
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. Just make sure Sphinx 1.3 or above is installed.
Unittest & Coverage
python setup.py test to run all unittests defined in the subfolder
tests with the help of py.test and pytest-runner. Some sane
default flags for py.test are already defined in the
[tool:pytest] section of
setup.cfg. The py.test 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:
python setup.py test --addopts -h
to show the help of py.test.
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
--travis to generate
templates of the Travis configuration files
tests/travis_install.sh which even features the
coverage and stats system Coveralls.
In order to use the virtualenv management and test tool Tox the flag
--tox can be specified.
Management of Requirements & Licenses
Installation requirements of your project can be defined inside
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, or maximum versions, e.g.
pandas<0.12, are used sometimes.
More specific installation requirements should go into
This file can also be managed with the help of
pip compile from pip-tools
that basically pins packages to the current version, e.g.
The packages defined in
requirements.txt can be easily installed with:
pip install -r requirements.txt
All licenses from choosealicense.com can be easily selected with the help
PyScaffold comes with several extensions:
- If you want a project setup for a Data Science task, just use
--dsprojectafter having installed pyscaffoldext-dsproject.
- Create a Django project with the flag
--djangowhich is equivalent to
django-admin.py startproject my_projectenhanced by PyScaffold's features.
- Create a template for your own PyScaffold extension with
--custom-extensionafter having installed pyscaffoldext-custom-extension with
- Have a
README.mdbased on MarkDown instead of
--markdownafter having installed pyscaffoldext-markdown with
- Add a
pyproject.tomlfile according to PEP 518 to your template by using
--pyprojectafter having installed pyscaffoldext-pyproject with
- With the help of Cookiecutter it is possible to further customize your project
setup with a template tailored for PyScaffold. Just use the flag
--cookiecutter TEMPLATEto use a cookiecutter template which will be refined by PyScaffold afterwards.
- ... and many more like
--gitlabto create the necessary files for GitLab.
Find more extensions within the PyScaffold organisation and consider contributing your own.
All extensions can easily be installed with
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
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!