Python Start Project with Cookiecutter

This template allows you to easily setup new Python projects with the most important libraries and configuration files for managing dependencies and virtualenv, code formatting, debugging, testing, static code analysis and creating command-line interfaces.

This project is based on python-new-project, with a heavy amount of changes

What is included in the template

The template will:

• install Pytest and Pytest-sugar for tests
• install pydantic for data validation
• install Black and Flake8 for standardization
• install pre-commit to run Black, Flake8, etc before every commit
• install sphinx and sphinx-autobuild for documentation
• create pyproject.toml configuration file for managing project dependencies and virtual environments using Poetry
• create README.md README file
• create .gitignore file
• initialize new Git repository

How to use the template

This is a cookiecutter template.

To use it, make sure you have at least Python 3.7 and git installed.

Then install cookiecutter and poetry via pip:

pip install poetry --user
pip install cookiecutter --user

You can now create a new Python project by running:

cookiecutter <git-url>

This will take you to a project setup asking for:

• package_display_name - The name that will be used in README, documentation, etc
• package_name - The Python package name and name of the project folder (will generate automatically)
• package_description - The Python package description
• package_command - This will configure poetry to allow calling the package, package_name/console:entry_point, via this command. Generally, this would be the same value as package_name
• author_name - The author of the package
• author_email - The email for the author
• git_branch - The branch to utilize when performing git init -b <branch>
• github_repo_name - For documentation, such as URLs to the issue tracker
• github_user_name - For documentation, such as URLs to the issue tracker
• python_version- The Python version that should be defined in pyproject.toml

The generated structure looks like this:

└── package_name/
    ├── docs
    │   ├── build
    │   ├── make.bat
    │   ├── Makefile
    │   └── source
    │       ├── conf.py
    │       ├── dev
    │       │   └── index.rst
    │       ├── index.rst
    │       └── user
    │           └── index.rst
    ├── poetry.lock
    ├── pyproject.toml
    ├── README.md
    ├── src
    │   └── package_name
    │       ├── console.py
    │       ├── __init__.py
    │       └── logger.py
    └── tests/
        ├── __init__.py
        └── test_project.py

From here, you can install the current dependencies, if needed running poetry install from within package_name. We can run poetry shell and package_name to run the script.

Default Configs

The project includes pydantic to help with configuration and settings for projects.

The provided example console.py allows for the following object:

>>> from package_name.console import Config
>>> config = Config()
>>> config
Config(api_key='EXAMPLEKEY', more_settings=SubModel(foo='bar'))
>>> config.more_settings.foo
'bar'

The config settings can be defined either through environment variables, such as the following:

API_KEY='MY_ACTUAL_KEY'
MORE_SETTINGS__FOO='OTHER'