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.. image:: https://pyscaffold.org/en/latest/_images/logo.png :height: 512px :width: 512px :scale: 60 % :alt: PyScaffold logo :align: center

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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).

.. image:: https://pyscaffold.org/en/latest/_images/demo.gif :alt: Creating a simple package with PyScaffold :target: https://asciinema.org/a/qzh5ZYKl1q5xYEnM4CHT04HdW?autoplay=1

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).

.. rubric:: 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.

.. rubric:: 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