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Template tool for putting up the scaffold of a Python project

Project description

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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:

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 the usual:

python develop

you are all set and ready to go.

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 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 sdist, python bdist or python 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 setup.cfg). It is not necessary to have a file for this to work.

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. Run python --version to retrieve the current PEP440-compliant version. 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

Build the documentation with python docs and run doctests with python 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

Run python 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 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 .travis.yml and tests/ 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 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, or maximum versions, e.g. pandas<0.12, are used sometimes.

More specific installation requirements should go into requirements.txt. 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. numpy==1.13.1. The packages defined in requirements.txt can be easily installed with:

pip install -r requirements.txt

All licenses from can be easily selected with the help of the --license flag.


PyScaffold comes with several extensions:

  • If you want a project setup for a Data Science task, just use --dsproject after having installed pyscaffoldext-dsproject.
  • Create a Django project with the flag --django which is equivalent to startproject my_project enhanced by PyScaffold’s features.
  • Create a template for your own PyScaffold extension with --custom-extension after having installed pyscaffoldext-custom-extension with pip.
  • Have a based on MarkDown instead of README.rst by using --markdown after having installed pyscaffoldext-markdown with pip.
  • Add a pyproject.toml file according to PEP 518 to your template by using --pyproject after having installed pyscaffoldext-pyproject with pip.
  • 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 TEMPLATE to use a cookiecutter template which will be refined by PyScaffold afterwards.
  • … and many more like --gitlab to 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 pip 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 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!

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Files for PyScaffold, version 3.2.3
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