Developing Python Packages

Learn to create your own Python packages to make your code easier to use and share with others.
Start Course for Free
4 Hours14 Videos47 Exercises
3900 XP

Create Your Free Account

GoogleLinkedInFacebook
or
By continuing you accept the Terms of Use and Privacy Policy. You also accept that you are aware that your data will be stored outside of the EU and that you are above the age of 16.

Loved by learners at thousands of companies


Course Description

Do you find yourself copying and pasting the same code between files, wishing it was easier to reuse and share your awesome snippets? Wrapping your code into Python packages can help! In this course, you’ll learn about package structure and the extra files needed to turn loose code into convenient packages. You'll also learn about import structure, documentation, and how to maintain code style using flake8. You’ll then speed up your package development by building templates, using cookiecutter to create package skeletons. Finally, you'll learn how to use setuptools and twine to build and publish your packages to PyPI—the world stage for Python packages.

  1. 1

    From Loose Code to Local Package

    Free
    Get your package started by converting scripts you have already written. You'll create a simple package which you can use on your own computer.
    Play Chapter Now
  2. 2

    Install Your Package from Anywhere

    Make your package installable for yourself and others. In this chapter, you'll learn to deal with dependencies, write READMEs, and include licenses. You'll also complete all the steps to publish your package on PyPI—the main home of Python packages.
    Play Chapter Now
  3. 3

    Increasing Your Package Quality

    Bring your package up to a professional standard. Discover how to use pytest to guard against errors, tox to test if your package functions with multiple versions of Python, and flake8 to maintain great code style.
    Play Chapter Now
  4. 4

    Rapid Package Development

    Create your packages more quickly. In this final chapter, you’ll learn how to use cookiecutter to generate all the supporting files your package needs, Makefiles to simplify releasing new versions, and be introduced to the last few files your package needs to attract users and contributors.
    Play Chapter Now
Collaborators
Maggie MatsuiAmy Peterson
Prerequisites
Introduction to ShellWriting Functions in Python
James Fulton Headshot

James Fulton

Climate Informatics Researcher
James is a PhD researcher at the University of Edinburgh, where he tutors computing, machine learning, data analysis, and statistical physics. His research involves using and developing machine learning algorithms to extract space-time patterns from climate records and climate models. He has held visiting researcher roles, working on planet-scale data analysis and modeling, at the University of Oxford and Queen's University Belfast and has a masters in physics where he specialized in quantum simulation. In a previous life, he was employed as a data scientist in the insurance sector. When not several indents deep in Python, he performs improvised comedy.
See More

What do other learners have to say?

I've used other sites—Coursera, Udacity, things like that—but DataCamp's been the one that I've stuck with.

Devon Edwards Joseph
Lloyds Banking Group

DataCamp is the top resource I recommend for learning data science.

Louis Maiden
Harvard Business School

DataCamp is by far my favorite website to learn from.

Ronald Bowers
Decision Science Analytics, USAA