Poetry

Python dependency management and packaging made easy.

Description

Poetry helps you declare, manage and install dependencies of Python projects, ensuring you have the right stack everywhere.

It supports Python 2.7 and 3.4+.

Programming language: Python

License: MIT License

Tags: Environment Management     Package Management     Build Tools     Command-line Tools     CLI    

Latest version: v1.2.0.b2

README

Poetry: Dependency Management for Python

Poetry helps you declare, manage and install dependencies of Python projects, ensuring you have the right stack everywhere.

It supports Python 3.7+.

The complete documentation is available on the official website.

Installation

Instructions on how to install poetry can be found here. You can also refer here for information on how to enable tab completion in your environment.

Introduction

poetry is a tool to handle dependency installation as well as building and packaging of Python packages. It only needs one file to do all of that: the new, standardized pyproject.toml.

In other words, poetry uses pyproject.toml to replace setup.py, requirements.txt, setup.cfg, MANIFEST.in and the newly added Pipfile.

[tool.poetry]
name = "my-package"
version = "0.1.0"
description = "The description of the package"

license = "MIT"

authors = [
    "Sébastien Eustace <[email protected]>"
]

readme = "README.md"  # Markdown files are supported

repository = "https://github.com/python-poetry/poetry"
homepage = "https://github.com/python-poetry/poetry"

keywords = ["packaging", "poetry"]

[tool.poetry.dependencies]
python = "~2.7 || ^3.2"  # Compatible python versions must be declared here
toml = "^0.9"
# Dependencies with extras
requests = { version = "^2.13", extras = [ "security" ] }
# Python specific dependencies with prereleases allowed
pathlib2 = { version = "^2.2", python = "~2.7", allow-prereleases = true }
# Git dependencies
cleo = { git = "https://github.com/sdispater/cleo.git", branch = "master" }

# Optional dependencies (extras)
pendulum = { version = "^1.4", optional = true }

[tool.poetry.dev-dependencies]
pytest = "^3.0"
pytest-cov = "^2.4"

[tool.poetry.scripts]
my-script = "my_package:main"

There are some things we can notice here:

• It will try to enforce semantic versioning as the best practice in version naming.
• You can specify the readme, included and excluded files: no more MANIFEST.in. poetry will also use VCS ignore files (like .gitignore) to populate the exclude section.
• Keywords can be specified and will act as tags on the packaging site.
• The dependencies sections support caret, tilde, wildcard, inequality and multiple requirements.
• You must specify the python versions for which your package is compatible.

poetry will also detect if you are inside a virtualenv and install the packages accordingly. So, poetry can be installed globally and used everywhere.

poetry also comes with a full fledged dependency resolution library.

Why?

Packaging systems and dependency management in Python are rather convoluted and hard to understand for newcomers. Even for seasoned developers it might be cumbersome at times to create all files needed in a Python project: setup.py, requirements.txt, setup.cfg, MANIFEST.in and the newly added Pipfile.

So I wanted a tool that would limit everything to a single configuration file to do: dependency management, packaging and publishing.

It takes inspiration in tools that exist in other languages, like composer (PHP) or cargo (Rust).

And, finally, I started poetry to bring another exhaustive dependency resolver to the Python community apart from Conda's.

Resources

• Official Website
• Issue Tracker
• Discord