Pyckage-Cookiecutter 1.0.2

This projects consist of a cookiecutter template that generates a full structure for a creating a PyPi standard package.

Introduction

This projects consist of a cookiecutter template that generates a full structure for a creating a PyPi standard package.

While using this project, you will be asked to provide some inputs such as the author, the name of the project, etc. As result you will obtain the complete file and folder structure to quickly start to code your package.

How to Use

Tutorial

Let’s pretend you want to create a project called “feddit”. By using this template based on cookiecutter, you will be able to quickly setup a buildable PyPi package.

First, get cookiecutter. Trust me, it’s awesome:

$ pip install cookiecutter

or with poetry:

$ poetry self add cookiecutter

Now run it against this repo:

$ cookiecutter https://github.com/zhiwei2017/pyckage-cookiecutter

or:

$ poetry run cookiecutter https://github.com/zhiwei2017/pyckage-cookiecutter

You’ll be prompted for some values. Provide them, then a project will be created for you.

Warning: After this point, change ‘My Awesome Project’, ‘John Doe’, etc to your own information.

Answer the prompts with your own desired Prompts. For example:

Cloning into 'pyckage-cookiecutter'...
remote: Enumerating objects: 219, done.
remote: Counting objects: 100% (219/219), done.
remote: Compressing objects: 100% (123/123), done.
remote: Total 219 (delta 83), reused 181 (delta 69), pack-reused 0
Receiving objects: 100% (219/219), 41.09 KiB | 1.71 MiB/s, done.
Resolving deltas: 100% (83/83), done.
  [1/8] Select your project name (My Awesome Project):
  [2/8] Project URL for hosting the source code. (https://repository-hosting.com/example_project): https://github.com/zhiwei2017/feddit
  [3/8] Author full name. (John Doe): John Doe
  [4/8] Author email address. ([e-mail]): [e-mail]
  [5/8] Short description. (Behold My Awesome Project!): A fake reddit API.
  [6/8] Semantic version to use for release. (0.1.0): 0.1.0
  [7/8] Which license do you want to use for your project?
    1 - None
    2 - MIT
    3 - APACHE
    4 - 2-Clause BSD
    5 - 3-Clause BSD
    6 - GPL
    Choose from [1/2/3/4/5/6] (1): 2
  [8/8] Which CI/CD pipelines do you plan to use?
    1 - None
    2 - GitHub
    3 - GitLab
    4 - Bitbucket
    Choose from [1/2/3/4] (1): 2
**Please read the comments from README.rst in your project to get to know how to setup the CI/CD pipeline and use commands from Makefile.**

Enter the project and take a look around:

$ cd feddit/
$ ls

Your repo should have the following structure:

feddit
├── .github                         - github actions configurations
│   └── workflows
│       ├── test.yml                - pipelines for linting checks and testing
│       ├── release.yml             - pipelines for releases with tags
│       └── sphinx.yml              - pipelines for publishing github pages
├── docs                            - sphinx documentation
│   ├── Makefile                    - Makefile defines terminal commands for sphinx documentation
│   └── source                      - documentation source folder
│       ├── 01_about.rst
│       ├── 02_source.rst
│       ├── 03_authors.rst
│       ├── 04_contributing.rst
│       ├── conf.py                 - sphinx configuration file
│       └── index.rst
├── feddit
│   └── __init__.py
├── tests                           - tests
│   ├── resources                   - resources used in tests
│   ├── conftest.py                 - fixtures in tests
│   └── test_version.py             - test version information.
├── .gitignore
├── CONTRIBUTING.rst                - contributing guidelines
├── LICENSE
├── Makefile                        - predefined terminal commands
├── MANIFEST.in                     - commands, one per line, instructing setuptools to add or remove some set of files from the sdis
├── README.rst                      - package information
├── setup.cfg                       - configurations for flake8, since it doesn't support pyproject.toml.
└── pyproject.toml                  - package configuration file

If you want to use CI/CD pipeline for uploading your package to PyPi, please check the section CI/CD configuration.

Note:

• This repo is built as a wheel package and uploaded to PyPi. You can install it through pip:

  $ pip install pyckage-cookiecutter

  or through poetry:

  $ poetry self add pyckage-cookiecutter

  And start generating a new project by call:

  $ pyckage_cookiecutter

  or:

  $ poetry run pyckage_cookiecutter

  The rest is the same as the Tutorial introduced.

CI/CD Pipelines

The CI/CD pipelines are predefined in the generated project. Please check following sections for which steps are included and how to configure them in different platforms.

GitHub Actions

You can find all the configuration files of GitHub Actions in .github/workflows folder.

Content

Config File	Steps	Trigger Rules	Requisite CI/CD Variables	CI/CD Variables description
test.yml	mypy check	Pushes to master/develop branches Pull Requests to master/develop branches
	flake8 check
	bandit check
	test with python 3.8 (Ubuntu/Mac OS/Windows)
	test with python 3.9 (Ubuntu/Mac OS/Windows)
	test with python 3.10 (Ubuntu/Mac OS/Windows)
	test with python 3.11 (Ubuntu/Mac OS/Windows)
	test with python 3.12 (Ubuntu/Mac OS/Windows)
	twine check the built package
release.yml	deploy to PyPi	Pushes to tags matching vXX.XX.XX	POETRY_PYPI_TOKEN_PYPI	Token for uploading package to official PyPi. If you’re using a private artifactory, please use the variables PACKAGE_INDEX_REPOSITORY_URL, PACKAGE_INDEX_USERNAME, and PACKAGE_INDEX_PASSWORD instead.
			PACKAGE_INDEX_REPOSITORY_URL	URL of Private package index.
			PACKAGE_INDEX_USERNAME	Username of Private package index.
			PACKAGE_INDEX_PASSWORD	Password of Private package index.
sphinx.yml	deploy GitHub pages	Pushes to master branch

Note:

• Before publishing the GitHub pages of your project for the first time, please manually create the branch gh-pages via:

  $ git checkout master
  $ git checkout -b gh-pages
  $ git push origin gh-pages

Setup Steps

1. Go to Settings.

2. Click Secrets section.

3. Click New repository secret button.

4. Input the name and value of a CI/CD variable.

GitLab CI

The file .gitlab-ci.yml contains all the configurations for GitLab CI.

Content

Stages	Steps	Trigger Rules	Requisite CI/CD Variables	CI/CD Variables description
linting	mypy check	Pushes to master/develop branches Any Merge Requests
	flake8 check
	bandit check
test	test with python 3.8
	test with python 3.9
	test with python 3.10
	test with python 3.11
	test with python 3.12
build	twine check the built package
deploy	deploy to PyPi	Pushes to tags matching vXX.XX.XX	POETRY_PYPI_TOKEN_PYPI	Token for uploading package to official PyPi. If you’re using a private artifactory, please use the variables PACKAGE_INDEX_REPOSITORY_URL, PACKAGE_INDEX_USERNAME, and PACKAGE_INDEX_PASSWORD instead.
			PACKAGE_INDEX_REPOSITORY_URL	URL of Private package index.
			PACKAGE_INDEX_USERNAME	Username of Private package index.
			PACKAGE_INDEX_PASSWORD	Password of Private package index.

Setup Steps

1. Go to Settings.

2. Click CI/CD section.

3. Go to Variables section.

4. Click Add variable button.

5. Input the name and value of a CI/CD variable.

   By default, the flag protected is checked, which means the added variable can only be used for protected branches/tags. If you want to keep your variable protected, please add wildcards v* as protected tags in Settings -> Repository -> Protected tags.

   Or you can uncheck the box to use the variable for all branches and tags.

Bitbucket Pipelines

The file bitbucket-pipelines.yml contains all the configurations of Bitbucket Pipelines.

Content

Steps	Trigger Rules	Requisite CI/CD Variables	CI/CD Variables description
mypy check	Pushes to master/develop branches Any Pull Requests
flake8 check
bandit check
test with python 3.8
test with python 3.9
test with python 3.10
test with python 3.11
test with python 3.12
twine check the built package
deploy to PyPi	Pushes to tags matching vXX.XX.XX	POETRY_PYPI_TOKEN_PYPI	Token for uploading package to official PyPi. If you’re using a private artifactory, please use the variables PACKAGE_INDEX_REPOSITORY_URL, PACKAGE_INDEX_USERNAME, and PACKAGE_INDEX_PASSWORD instead.
		PACKAGE_INDEX_REPOSITORY_URL	URL of Private package index.
		PACKAGE_INDEX_USERNAME	Username of Private package index.
		PACKAGE_INDEX_PASSWORD	Password of Private package index.

Setup Steps

1. Go to Repository settings.

2. Click Repository variables.

3. Click add button.

4. Input the name and value of a CI/CD variable.

   You need to enable pipelines before adding a new variable for the first time.

Makefile

Command	Description
clean	Remove autogenerated folders and artifacts.
clean-pyc	Remove python artifacts.
clean-build	Remove build artifacts.
bandit	Run bandit security analysis.
mypy	Run mypy type checking.
flake8	Run flake8 linting.
install	Install all the dependencies and the package itself.
test	Run tests and generate coverage report.
build	Build wheel package.
publish	Publish the built wheel package.

Acknowledgements

Special thanks to the project cookiecutter-pypackage for the nice CONTRIBUTING.rst template.

Author

• Zhiwei Zhang - Author / Maintainer - [e-mail]