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Python packaging and dependency management made easy
Official project repository for the Setuptools build system
Python Development Workflow for Humans.
Modern, extensible Python project management
Quick Overview
Flit is a simple way to distribute Python packages. It is a lightweight alternative to tools like setuptools
and pip
for creating and publishing Python packages. Flit aims to make the process of packaging and distributing Python code easier and more streamlined.
Pros
- Simple and Intuitive: Flit has a straightforward and user-friendly interface, making it easy for developers to create and publish Python packages.
- Dependency Management: Flit automatically handles dependency management, ensuring that all required packages are installed when a user installs your package.
- No Build Step: Flit eliminates the need for a separate build step, as it generates the necessary distribution files directly from your source code.
- Reproducible Builds: Flit ensures that your package can be reliably built and installed on different systems, promoting reproducibility.
Cons
- Limited Ecosystem: Flit is a relatively new tool, and it may not have the same level of community support and integration as more established packaging tools like
setuptools
. - Lack of Advanced Features: Flit is designed to be a lightweight and simple tool, which means it may not offer the same level of customization and advanced features as other packaging tools.
- Compatibility Concerns: While Flit aims to be compatible with existing packaging tools, there may be some compatibility issues or limitations when working with certain projects or environments.
- Learning Curve: Although Flit is relatively simple to use, developers who are accustomed to other packaging tools may need to invest some time in learning the Flit workflow.
Code Examples
Flit is a packaging tool, so it does not provide any code examples for its own functionality. However, you can use Flit to package and distribute your own Python code. Here's an example of how you might use Flit to create a simple Python package:
# my_package/my_module.py
def greet(name):
return f"Hello, {name}!"
# my_package/__init__.py
from .my_module import greet
# pyproject.toml
[build-system]
requires = ["flit_core >=3.2,<4"]
build-backend = "flit_core.buildapi"
[project]
name = "my-package"
version = "0.1.0"
description = "A simple Python package"
authors = [
{name = "Your Name", email = "your.email@example.com"},
]
license = {file = "LICENSE"}
classifiers = [
"Programming Language :: Python :: 3",
"License :: OSI Approved :: MIT License",
"Operating System :: OS Independent",
]
dependencies = [
"requests>=2.25.1",
]
requires-python = ">=3.7"
Getting Started
To get started with Flit, follow these steps:
-
Install Flit:
pip install flit
-
Create a
pyproject.toml
file in the root directory of your Python package, which will contain the package metadata and build configuration. Here's an example:[build-system] requires = ["flit_core >=3.2,<4"] build-backend = "flit_core.buildapi" [project] name = "my-package" version = "0.1.0" description = "A simple Python package" authors = [ {name = "Your Name", email = "your.email@example.com"}, ] license = {file = "LICENSE"} classifiers = [ "Programming Language :: Python :: 3", "License :: OSI Approved :: MIT License", "Operating System :: OS Independent", ] dependencies = [ "requests>=2.25.1", ] requires-python = ">=3.7"
-
Create your Python module(s) in the appropriate directory (e.g.,
my_package/my_module.py
). -
To build and install your package locally, run:
flit install --symlink
The
--symlink
option creates a symbolic link to your
Competitor Comparisons
Python packaging and dependency management made easy
Pros of Poetry
- More comprehensive dependency management with lock files
- Built-in virtual environment handling
- Intuitive CLI with commands for common tasks
Cons of Poetry
- Steeper learning curve for beginners
- Larger footprint and slower installation
- Less flexible for non-standard project structures
Code Comparison
Poetry (pyproject.toml
):
[tool.poetry]
name = "my-package"
version = "0.1.0"
description = "A sample package"
authors = ["Author Name <author@example.com>"]
[tool.poetry.dependencies]
python = "^3.7"
requests = "^2.25.1"
Flit (pyproject.toml
):
[build-system]
requires = ["flit_core >=3.2,<4"]
build-backend = "flit_core.buildapi"
[project]
name = "my-package"
authors = [{name = "Author Name", email = "author@example.com"}]
dynamic = ["version", "description"]
Poetry offers a more detailed configuration but requires more setup, while Flit provides a simpler approach with less boilerplate. Poetry's dependency management is more robust, but Flit's simplicity can be advantageous for smaller projects or quick prototypes.
Official project repository for the Setuptools build system
Pros of setuptools
- More mature and widely adopted in the Python ecosystem
- Offers extensive customization options for complex packaging needs
- Supports a broader range of Python versions and package types
Cons of setuptools
- Configuration can be complex and verbose, especially for simple projects
- Requires more boilerplate code and setup files
- Steeper learning curve for beginners
Code comparison
setuptools:
from setuptools import setup, find_packages
setup(
name="mypackage",
version="0.1",
packages=find_packages(),
install_requires=["dependency1", "dependency2"],
)
flit:
[build-system]
requires = ["flit_core >=3.2,<4"]
build-backend = "flit_core.buildapi"
[project]
name = "mypackage"
version = "0.1"
dependencies = ["dependency1", "dependency2"]
flit uses a simpler, more declarative approach with a pyproject.toml
file, while setuptools typically uses a setup.py
script. flit's configuration is more concise and easier to read, especially for straightforward projects. However, setuptools offers more flexibility for complex packaging scenarios and has been the de facto standard for Python packaging for many years.
Python Development Workflow for Humans.
Pros of Pipenv
- Manages both dependencies and virtual environments in a single tool
- Provides a lockfile for deterministic builds
- Offers advanced dependency resolution and management features
Cons of Pipenv
- Can be slower than simpler tools like Flit
- Has a steeper learning curve for beginners
- May be overkill for small projects or simple package management needs
Code Comparison
Pipenv:
# Pipfile
[packages]
requests = "*"
flask = "==1.1.2"
# Install dependencies
$ pipenv install
Flit:
# pyproject.toml
[tool.flit.metadata]
requires = [
"requests",
"flask==1.1.2",
]
# Install package
$ flit install
Both tools use configuration files to manage dependencies, but Pipenv uses a separate Pipfile, while Flit integrates with pyproject.toml. Pipenv offers more granular control over virtual environments and dependency resolution, while Flit focuses on simplicity and ease of use for package building and publishing.
Modern, extensible Python project management
Pros of Hatch
- More comprehensive project management tool, offering features beyond just building and publishing
- Supports multiple build backends and provides environment management
- Offers a plugin system for extensibility
Cons of Hatch
- Steeper learning curve due to more features and complexity
- Potentially slower for simple projects that don't need advanced features
- Larger dependency footprint
Code Comparison
Flit:
[build-system]
requires = ["flit_core >=3.2,<4"]
build-backend = "flit_core.buildapi"
[project]
name = "example"
version = "0.1.0"
Hatch:
[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "example"
version = "0.1.0"
Both Flit and Hatch use pyproject.toml for configuration, but Hatch offers more extensive options for project management and build customization. Flit is simpler and more straightforward for basic Python packages, while Hatch provides a more feature-rich environment for complex projects and workflows. The choice between them depends on the specific needs of your project and your preferred level of control over the development process.
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Flit is a simple way to put Python packages and modules on PyPI.
It tries to require less thought about packaging and help you avoid common
mistakes.
See Why use Flit? <https://flit.readthedocs.io/en/latest/rationale.html>
_ for
more about how it compares to other Python packaging tools.
Install
::
$ python3 -m pip install flit
Flit requires Python 3 and therefore needs to be installed using the Python 3 version of pip.
Python 2 modules can be distributed using Flit, but need to be importable on Python 3 without errors.
Usage
Say you're writing a module foobar
â either as a single file foobar.py
,
or as a directory â and you want to distribute it.
-
Make sure that foobar's docstring starts with a one-line summary of what the module is, and that it has a
__version__
:.. code-block:: python
"""An amazing sample package!""" __version__ = "0.1"
-
Install flit if you don't already have it::
python3 -m pip install flit
-
Run
flit init
in the directory containing the module to create apyproject.toml
file. It will look something like this:.. code-block:: ini
[build-system] requires = ["flit_core >=3.2,<4"] build-backend = "flit_core.buildapi" [project] name = "foobar" authors = [{name = "Sir Robin", email = "robin@camelot.uk"}] dynamic = ["version", "description"] [project.urls] Home = "https://github.com/sirrobin/foobar"
You can edit this file to add other metadata, for example to set up command line scripts. See the
pyproject.toml page <https://flit.readthedocs.io/en/latest/pyproject_toml.html#scripts-section>
_ of the documentation.If you have already got a
flit.ini
file to use with older versions of Flit, convert it topyproject.toml
by runningpython3 -m flit.tomlify
. -
Run this command to upload your code to PyPI::
flit publish
Once your package is published, people can install it using pip just like any other package. In most cases, pip will download a 'wheel' package, a standard format it knows how to install. If you specifically ask pip to install an 'sdist' package, it will install and use Flit in a temporary environment.
To install a package locally for development, run::
flit install [--symlink] [--python path/to/python]
Flit packages a single importable module or package at a time, using the import name as the name on PyPI. All subpackages and data files within a package are included automatically.
Top Related Projects
Python packaging and dependency management made easy
Official project repository for the Setuptools build system
Python Development Workflow for Humans.
Modern, extensible Python project management
Convert
designs to code with AI
Introducing Visual Copilot: A new AI model to turn Figma designs to high quality code using your components.
Try Visual Copilot