How to write a Python module/package?
Kick-off a Python package by creating a directory that contains an __init__.py
file. This turns a regular folder into a recognizable Python package and is where you can import methods for external use. Your Python code should be neatly tucked into .py
files:
mymodule/
├── __init__.py
└── core.py
Fill core.py
with your functions or classes:
Within __init__.py
, pull in your code:
Now you can use your package like this:
Use setup.py
to make your package shareable! It contains all the metadata about your package. Use setuptools and twine to package your module for distribution.
Proper file structure
Choose short, all-lowercase filenames for your modules. House related functions together to keep it straightforward. Keep everything tidy with docstrings that clarify what each module, class, or function does. If you're creating a larger package, use namespaces for better organization.
Dependencies and virtual environments
Before distributing your package, test it within an isolated virtual environment to pinpoint any undisclosed dependencies. Only after this should you place dependencies in setup.py
.
Community best practices
Maintain a GitHub repository with a sensible .gitignore
that can duck stuff you don't need in your repo. Include a LICENSE.txt
file to set usage boundaries and create a README
file to clue users in on what your module does.
Keep your code in check (unit testing)
Test your package in the local environment and on PyPI's test repository before uploading. Introduce unit testing with pytest to ensure that your functions are rock stars that perform well under pressure.
For the user
Ensure your package installs with just pip install
. This way, getting up and running with your package is a breeze! For this to happen, manage dependencies thoughtfully and keep setup.py
in top shape.
Best practices
Following PEP 8 naming conventions, your code will be as readable as a children's book, making it easier for others to understand.
Continuous Integration/Deployment (CI/CD)
Set up CI/CD pipelines, like GitHub Actions, to keep your pacakge in top shape without breaking a sweat.
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