❗	This is a mirror repository of Galactipy, which is currently being developed on GitLab. Take a look at our CONTRIBUTING.md to get more familiar with the project and understand how to contribute!

Galactipy

Expand your project structure from atoms of code to galactic dimensions. 🌌

TL;DR

cookiecutter gl:galactipy/galactipy --checkout v1.1.0

All you need is the latest version of Cookiecutter! 😉

✨ Features

In this Cookiecutter 🍪 template we combine state-of-the-art libraries and best development practices for Python.

:race_car: Start Developing Your App out of the Box

• Supports Python 3.10 and higher;
• Provides minimal boilerplate code for CLI/TUI applications with Typer and Textual (or no code at all, you choose)! With it, you have:
  • Batteries-included configuration setup and management with Orbittings;
  • Both beautiful logging on the terminal and easy-to-parse log files thanks to Nebulog;
  • Preconfigured Noctis themes to make your application shine on the terminal;
• Uses Poetry as the dependency manager and extends functionality with dynamic versioning, virtual environment bundling, dependency export and update resolution; see configuration in pyproject.toml;
• Automatic code formatting with Ruff, with ready-to-use pre-commit hooks and several rules already selected for linting;
• Type checks with mypy, security checks with Bandit;
• Testing with Pytest and an option to use behaviour-driven development for managing scenarios; more details in How to Handle the Development Cycle with BDD;
• Code quality integrations with either Coveralls for more basic test coverage or Codacy for full code analysis, both integrated into your project's workflow via CI/CD;
• Everything is already set up for security checks, codestyle checks, code formatting, testing, linting, docker builds etc. with Invoke; more details in Invoke Usage;
• Predefined VS Code settings.json with quality-of-life configuration for editor, workbench, debugging and more;
• Ready-to-use .editorconfig, .dockerignore and .gitignore files; you don't have to worry about those things.

🪄 We Assemble the Tools to Ship, You Bring Your Code to Life

• The boilerplate code provided with the template is already 100% covered by unit tests; you can dive in directly into your project's implementation without the hassle of handling test cases;
• Predefined CI/CD build workflow with GitLab CI and Github Actions;
• Automatic package uploads to PyPI test and production repositories;
• A Dockerfile for your package, with CI/CD workflows to publish your image to a container registry;
• Intended Effort Versioning with GitLab Changelog or Release Drafter.

:man_golfing: Manage Your Project like a Walk in the Park

• Ready-to-use Merge Request templates and several Issue templates for easy integration with GitLab and GitHub;
• Workflows to mark and close abandoned issues after a period of inactivity for both GitLab with Triage Policies and GitHub with Stale Bot;
• Option to choose between Gitmoji, Conventional Commits or a mix of both to standardise your commit titles.

🪢 Nurture the Community around Your Project from Day One

• With Galactipy templates, you get more than a CONTRIBUTING.md file; you have a comprehensive development philosophy, drawing inspiration from some of the most distinguished open source projects; we provide extensive yet user-friendly guidelines, enabling your project to onboard new contributors and scale effortlessly with minimal adjustments;
• Files such as LICENCE, CODE_OF_CONDUCT.md, CITATION.cff, ROADMAP.md and SECURITY.md are generated automatically;
• Loads of predefined badges to make your project stand out; you can either keep them, remove as you wish or be welcome to add even more.

GitLab vs. GitHub feature comparison chart

You are free to choose whichever platform works best for you and your project. The original template by TezRomacH was created with GitHub in mind, which prompted the creation of a similarly fully-featured template for GitLab users as well.

However, not everything that is available for GitHub users is available to GitLab users, and vice-versa. Please mind the differences between both options.

Below is a comparison between the features available in this package depending on which platform you choose to host your project:

Feature	GitLab	GitHub	Observations
Issue templates	✅	✅	Both options feature automatic labels, but GitHub has an extra configuration to prevent the creation of empty issues.
Merge/pull requests templates	✅	⚠️	For GitHub, templates can only be accessed by applying custom query parameters during PR creation.
Project conditions checks	✅	✅	A basic workflow to install the package and run tests, check codestyle and safety.
Publication to TestPyPI	✅	✅	For GitHub, the workflow uses the official PyPI Publish action, while GitLab CI uses the PyPI API.
Publication to PyPI	✅	✅	For GitHub, trusted publishing is used with the PyPI Publish action, while GitLab CI uses the PyPI API.
Image publication	✅	✅	For GitHub, images are pushed to Docker Hub, while GitLab CI pushes images to the repository's Container Registry by default (and can be reconfigured).
Snapshot images	✅	❌	For GitLab, the Docker CI/CD component is used and allows for pushing snapshot images for testing when a Merge Request is open.
Dockerfile linting	✅	❌	The Docker GitLab CI/CD component includes a job for linting the Dockerfile with Hadolint.
Image vulnerability analysis	✅	❌	The Docker GitLab CI/CD component uses Trivy to scan the image for vulnerabilities.
SBOM files	✅	❌	The Docker GitLab CI/CD component generates a bill of materials with CycloneDX.
Stale issues	✅	✅	GitLab rules are more flexible, marking stale issues only for those not opened by project members.
Greetings workflow	❌	✅	GitHub provides workflows to automatically reply to issues and merge requests with the First Interaction action.
Dependabot	❌	✅	Dependabot is a feature now incorporated into GitHub Security. See here how to enable it.
Release drafter	❌	✅	Release Drafter is a custom workflow available on GitHub Marketplace. You may see the list of labels in release-drafter.yml. Works perfectly with EffVer or any SemVer-compatible specification.
Changelog configuration	✅	❌	GitLab provides automatic changelog updates through their API. You may modify the template in changelog_config.yml.
Test Reports	✅	❌	JUnit XML reports are supported by GitLab to allow test reports to be displayed in pipelines and merge requests.
CI control over pushed tags	✅	⚠️	GitLab provides full control for tags pushed to the repository using regex, while GitHub Actions is more restricted in how it filters workflows to run, and can only apply these filters at the top level, limiting workflow customization.

🃏 How to Use It

Installation

To begin using the template consider updating Cookiecutter:

pipx upgrade cookiecutter

then go to a directory where you want to create your project and run:

cookiecutter gl:galactipy/galactipy --checkout v1.1.0

Input variables

Cookiecutter will ask you to fill some variables in order to generate the files with everything you need already set up.

The input variables, with their default values, are as follows:

Parameter	Default value	Description
project_name	Python Project	A suitable name by which people will refer to, you are free to name it however you wish to.
repo_name	based on project_name	Name of the repository to develop the project on. Check the availability of possible names before creating the project.
package_name	based on project_name	PyPI-compliant Python package name. Check the availability of possible names before creating the project.
project_description	based on project_name	A brief one-line description of your project.
copyright	The Galactipy Contributors	Name of the author or organisation which will hold the project's copyright. Used to specify code ownership in LICENCE.
maintainer	Manoel Pereira de Queiroz	Name of the primary maintainer of the project. Used to specify author data in pyproject.toml and CITATION.cff.
scm_platform	GitLab Free	One of GitLab Free, GitLab Premium/Ultimate and GitHub. Depending on the choice you will have different features to work with.
scm_namespace	galactipy	GitHub or GitLab namespace for hosting. Also used to set up README.md, pyproject.toml and template files for either platform.
email	based on scm_namespace	Email for CODE_OF_CONDUCT.md, SECURITY.md files and to specify author data in pyproject.toml and CITATION.cff.
licence	MIT	One of MIT, BSD-3, GNU GPL v3.0, GNU AGLP v3.0, GNU LGPL v3.0, Mozilla Public License 2.0 and Apache Software License 2.0, or Not open source.
minimal_python_version	3.10	Minimal Python version. All versions since 3.10 are available to choose. It is used for builds, pipelines and formatters.
line_length	88	The max length per line. NOTE: This value must be between 50 and 300.
docstring_style	numpy	One of numpy, google, sphinx or other. This latter option will only render the docstring short summaries, while the former ones will detail arguments and returns for public methods and functions.
docstring_length	based on line_lenght	The max length for docstrings. NOTE: This value must be between 50 and 300 and lower of equal to line_lenght.
commit_convention	gitmoji	One of Gitmoji, Conventional Commits and Conventional Commits with Gitmoji for the commit standard to follow.
use_bdd	True	🔺 Option to use behaviour-driven development for managing tests.
coverage_service	Coveralls	One of Coveralls for code coverage and Codacy for code quality and static analysis.
create_docker	True	🔺 Option to create a Dockerfile to build an image for your project.
app_type	Integrated CLI+TUI	One of Integrated CLI+TUI for a straight TUI application, Hybrid CLI/TUI for a CLI application with a preset TUI command, CLI-only application with minimal app configuration and Bare repository for no sample files at all. Employs Typer and Textual as libraries.

Note

Input variables marked with 🔺 are boolean variables, you can dismiss those by typing either 0, false, f, no, n or off.

All input values will be saved in the cookiecutter-config-file.yml file so that you won't lose them. 😉

Initial set up

You must have Poetry installed to leverage the features provided with the Galactipy template.

After creating a project, ensure you have Invoke installed and run the following command to install dependencies and pre-commit hooks:

invoke install

If you don't have Invoke available in your system, run this instead:

poetry install
invoke hooks

Want to know more about Poetry? Check its documentation. Poetry's commands are very intuitive and easy to learn, streamlining your development process.

Sample Application

Galactipy is best used for terminal applications, either a TUI or a simple CLI interface. If you choose any of the options for app_type excluding Bare repository, your project will embed Typer as a dependency, and Textual will be provided for the Integrated CLI+TUI and Hybrid CLI/TUI options.

For any of the options providing an interface, you can call the application after setting up the virtual environment via invoke install or poetry install:

poetry run <repo_name> --help

poetry run <repo_name> --version

Then you can use the structure provided with Galactipy to build your application upon the barebones codebase. 😄

Building and releasing your package

To release a new version of the application, you must first have a PyPI account and generate an API token.

Then, add the registry to the Poetry configuration with

invoke config <API_token>

You'll be all set to build and publish your package in one go!

invoke publish

You should also push a tag to GitLab or GitHub and create a Release for your application, enabling users to download, track and inspect the changes made to the API.

Of course, you can also rely solely on the CI tools provided by Galactipy to handle building, publishing and releasing automatically, with minimal configuration required! 🥳

Note

To allow releasing directly via CI/CD workflows, besides setting up a canonical PyPI token, you must also generate a API toke for the TestPyPI repository.

If you have generated your project with the Docker option enabled, pushing a tag to your repository will also set up the automated workflows to build and publish your image to a container registry.

Invoke Usage

invoke is a library that enables easy configuration of shell-oriented subprocesses as Python functions, essentially organising a collection of aliases for all project developers to use.

Below is a list with the main task groups and details when relevant. Available tasks can be viewed at anytime with the invoke --list command.

Environment Setup

Command	Details
invoke install	🔺 Sets up the Poetry virtual environment, installs the dependencies, pre-commit hooks and runs a mypy check.
invoke pyproject	Checks pyproject.toml integrity.
invoke update	Updates dependencies to their latest compatible release requirements, with an option to update to the latest versions overall.

Warning

🔺 Invoke must be installed and callable. Otherwise, it is recommended to run poetry install to set up the repository.

Quality Assurance Tasks

Command	Details
invoke codestyle	Format files with Ruff, with an option to check files only.
invoke lint	Check compliance with linting rules, with an option to correct those considered fixable by Ruff.
invoke mypy	Run mypy to check for static typing.
invoke test	Run the test suite with Pytest.
invoke report	Run the test and mypy tasks and open their HTML coverage reports.
invoke security	Run security checks with Bandit and check pyproject.toml integrity.

The invoke sweep task groups all tasks except for report into a single command. invoke ruff can be used to run the Ruff formatter and linter with a single command.

Project Building & Publishing

Command	Details
invoke build	Build the project wheels.
invoke config	🔺 Configure PyPI repositories, requiring at least an API token, with optional repository name and URL arguments.
invoke publish	Publish the project to a registry, defaulting to the canonical PyPI repository, with an option to build the project wheels.

Note

🔺 When provided with no --repo option, Invoke will configure the connection to the canonical PyPI repository, with only the API token being required. When provided with the --repo testpypi option instead, it will configure the connection to TestPyPI and no URL is needed. Other --repo values must also receive a --url argument pointing to the desired custom registry.

Docker Operations

Command	Details
invoke login	Log in to a container registry. For GitHub users, points to Docker Hub. For GitLab users, points to the repository's integrated container registry.
invoke container	Build local container images, with the option to set multiple tags and an alternate repository to point.
invoke push	Push all project images to a container registry, with the option to set an alternate repository to push.
invoke prune	Remove all local images built for the project, with the option to set an alternate repository to point.

Cleanup Tasks

Command	Details
invoke remove-cache	Remove __pycache__ files from the local repository.
invoke remove-dsstore	Remove the .DS_Store directory from the local repository.
invoke remove-mypy	Remove the .mypy_cache directory from the local repository.
invoke remove-ipynb	Remove the .ipynb_checkpoints directory from the local repository.
invoke remove-pytest	Remove the .pytest_cache directory and the .coverage and test_report.xml files from the local repository.
invoke remove-ruff	Remove the .ruff_cache directory from the local repository.
invoke remove-build	Remove wheels built locally.

The invoke cleanup task groups all tasks except for remove-build into a single command.

How to Handle the Development Cycle with BDD

Behaviour-driven development is a software development paradigm in which domain language is used to describe the behaviour of the code. It emerged as a sophisticated evolution of test-driven development.

If you choose to use BDD for your project, a features directory will be created under tests and pytest-bdd will be added as a dependency. You should place .feature files inside this folder to describe real-life usage scenarios using the Gherkin language:

# tests/features/root_command.feature
Feature: Command-line interface

  Scenario: Check program version
    When the root program receives the `--version` option
    Then the terminal displays the program's version
    And the program exits without errors

You would then use pytest-bdd to wrap each scenario referred in the feature file as a step-by-step validation:

from typer.testing import CliRunner
from pytest_bdd import scenario, when, then, parsers
from python_project.cli.commands.root_command import app

runner = CliRunner()

@scenario("root_command.feature", "Check program version")
def test_cli_with_version_arg():
    pass

@when("the root program receives the `--version` option", target_fixture="cli_run")
def invoke_version_arg():
    return runner.invoke(app, args=["--version"])

@then("the terminal displays the program's version")
def version_display(cli_run, version_string):
    assert cli_run.stdout == version_string

@then("the program exits without errors")
def successful_termination(cli_run):
    assert cli_run.exit_code == 0

Once the tests are defined, you can simply use Pytest as you normally would to run the test suite and check the results.

For more information on behaviour-driven development and tools to handle more complex conditions, please check out the Cucumber documentation.

🛣️ What's next

Well, that's up to you. 💪

For further setting up your project:

• Look for files and sections marked with special inline comment tags:
  • TODO comments must be addressed in order for your project to run properly from end-to-end;
  • UPDATEME comments point to additional settings or content you can provide, but are not necessary to enable development;
  • DEFINE comments mark sections in policy files for concepts and content specifically tailored to your project's context;
  • If you use VS Code, install the Todo Tree extension to easily locate and jump to these marks, they are already configured in the settings.json file;
• Make sure to create your desired Issue labels (and GitLab statuses, if you're using GitLab Premium) on your repository before you start tracking issues;
• Make changes to your CI configuration to better suit your needs.

Important

In order to reduce user prompts and keep things effective, the template generates files with a few assumptions:

• It assumes your main Git branch is master; if you wish to use another branch name for development, be aware of changes you will have to make in Markdown files so links won't break when you push them to your repo;
• It defines the name setting in pyproject.toml assuming you will be able to publish your project to PyPI under repo_name, change it otherwise;
• It specifies the DEFAULT_DOCKER_REPOSITORY constant in tasks.py assuming you also use scm_namespace for Docker Hub and you will push your image under repo_name, change it otherwise.

If you want to put your project on steroids, here are a few Python tools which can help you depending on what you want to achieve with your application:

• If you chose to generate a TUI or CLI example during the Cookiecutter setup, these libraries will already be among your dependencies:
  • Rich makes it easy to add beautiful formatting in the terminal;
  • Typer builds great Command-Line Interfaces (CLI) applications with an easy-to-code API based on type hints;
  • Textual is a rapid application development framework to create Terminal User Interfaces (TUIs), made to be fun to build with;
  • Orbittings is Galactipy's own utility to manage configuration files and settings for these CLI/TUI applications; 😎
  • Nebulog makes logging stupidly simple (and beautiful), brought to you by The Galactipy Contributors; 🕺
• attrs and cattrs work together to make data structuring and validation your application's powerhouse, not its Achilles's heel;
• Trio is a friendly library for async concurrency and I/O;
• FastAPI is a web framework for high performance and easy learning;
• textX allows you to build your own Domain-Specific Languages (DSL) in plain Python;
• Returns makes you function's output meaningful, typed and safe;
• Hydra is a framework for elegantly configuring complex applications;
• Locust allows you to write scalable load tests in plain Python;
• orjson is an ultra fast JSON parsing library.

For taking development and exposition of your project to the next level:

• Experiment with additional badges; not only they enhance your project's appearance but also visually communicate key aspects, helping visitors quickly grasp important details about your work:
  • You can look at dynamic badges available at Shields.io;
  • There is a myriad of static badges for brands and services in general at Simple Badges;
  • awesome-badges provides a lot of useful resources on this topic;
• Add your project to the OpenSSF Best Practices and OSSRank indexes; if you have ambitious goals or expect significant growth, these indexes provide valuable visibility;
  • There are already badges for them in your README.md file, just waiting for you to update their URLs with your project's index; 😀
• Create a sponsorship page enabling users and organisations to help fund your project's growth and development; popular plaforms include:
  • Liberapay;
  • Open Collective;
  • Ko-fi;
  • If you host your project on GitHub, you can set a Sponsors account directly integrated into the platform;
• If you are unsure about which versioning logic to use, check this list with a plethora of options to choose from.

And here are a few articles which may help you:

• Open Source Guides;
• A handy guide to financial support for open source;
• GitLab CI Documentation;
• GitHub Actions Documentation;
• A Comprehensive Look at Testing in Software Development;
• Robust Exception Handling;
• Why Your Mock Doesn't Work;
• Managing TODOs in a codebase;
• The importance of layered thinking in data engineering.

📈 Galactipy Releases

You can see the list of available releases on the GitLab Releases page.

We follow the Romantic Versioning specification, details can be found in our CONTRIBUTING guide.

:map: Roadmap

Galactipy's roadmap is managed through our Milestones page, which lays out the current development streams mapped for delivery. All official details on development, timeline and deliverables are found there. The project's milestones are also presented in the ROADMAP file purely for informational purposes.

🛡️ Licence

This project is licenced under the terms of the MIT licence. See LICENCE for more details.

:sports_medal: Acknowledgements

Firstly, there is no way this template would exist without the previous phenomenal work by Roman Tezikov and his rich python-package-template. If there is anyone more deserving of a 🌟 and acknowledgement, it's him! Please give a shoutout and support if possible.

The original template was inspired by several articles that might be helpful if you are starting out managing projects:

• Hypermodern Python;
• Ultimate Setup for Your Next Python Project;
• Nine simple steps for better-looking python code;
• Modern Python developer's toolkit.

Additionally, we would like to thank the teams of the following projects for either aiding us directly during our research of best practices and tools for Python development or whose documentation have inspired parts of the project:

• Pelican;
• Spark;
• React;
• Chai;
• Harbor.

Give them your ⭐, these resources are amazing! 😉

Galactipy Bot avatar created by Smashicons.

📃 Citation

We provide a CITATION.cff file to make it easier to cite this project in your paper.

📣 Spread the Word

Add the badge to your project! It would be really appreciated to spread the word of this template.

Here is the Markdown source for it:

[![Expand your project structure from atoms of code to galactic dimensions.](https://img.shields.io/badge/made%20with-galactipy%20%F0%9F%8C%8C-179287?style=for-the-badge&labelColor=193A3E)](https://kutt.it/7fYqQl)

We would be equally grateful if you could also do any of the following:

• Set the notification level to "Watch" to receive our latest updates; 🔔
• Star the project! 🌟
• Share the project with colleagues; 🗣️
• Write a short article on how you are using Galactipy on your projects; ✏️
• Share best practices, references and tools for project management with us! 🍻