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Writing Functions in Python

55 reviews

Learn to use best practices to write maintainable, reusable, complex functions with good documentation.

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4 Hours15 Videos46 Exercises
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Course Description

You've done your analysis, built your report, and trained a model. What's next? Well, if you want to deploy your model into production, your code will need to be more reliable than exploratory scripts in a Jupyter notebook. Writing Functions in Python will give you a strong foundation in writing complex and beautiful functions so that you can contribute research and engineering skills to your team. You'll learn useful tricks, like how to write context managers and decorators. You'll also learn best practices around how to write maintainable reusable functions with good documentation. They say that people who can do good research and write high-quality code are unicorns. Take this course and discover the magic!
  1. 1

    Best Practices


    The goal of this course is to transform you into a Python expert, and so the first chapter starts off with best practices when writing functions. You'll cover docstrings and why they matter and how to know when you need to turn a chunk of code into a function. You will also learn the details of how Python passes arguments to functions, as well as some common gotchas that can cause debugging headaches when calling functions.

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    50 xp
    Crafting a docstring
    100 xp
    Retrieving docstrings
    100 xp
    Docstrings to the rescue!
    50 xp
    DRY and "Do One Thing"
    50 xp
    Extract a function
    100 xp
    Split up a function
    100 xp
    Pass by assignment
    50 xp
    Mutable or immutable?
    50 xp
    Best practice for default arguments
    100 xp
  2. 2

    Context Managers

    If you've ever seen the "with" keyword in Python and wondered what its deal was, then this is the chapter for you! Context managers are a convenient way to provide connections in Python and guarantee that those connections get cleaned up when you are done using them. This chapter will show you how to use context managers, as well as how to write your own.

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  3. 3


    Decorators are an extremely powerful concept in Python. They allow you to modify the behavior of a function without changing the code of the function itself. This chapter will lay the foundational concepts needed to thoroughly understand decorators (functions as objects, scope, and closures), and give you a good introduction into how decorators are used and defined. This deep dive into Python internals will set you up to be a superstar Pythonista.

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  4. 4

    More on Decorators

    Now that you understand how decorators work under the hood, this chapter gives you a bunch of real-world examples of when and how you would write decorators in your own code. You will also learn advanced decorator concepts like how to preserve the metadata of your decorated functions and how to write decorators that take arguments.

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In the following tracks

Data Scientist with PythonData Scientist Professional with PythonPython DeveloperPython Programming


Collaborator's avatar
Hillary Green-Lerman
Collaborator's avatar
Becca Robins
Shayne Miel HeadshotShayne Miel

Director of Software Engineering @ American Efficient

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Don’t just take our word for it

from 55 reviews
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  • Josue U.
    5 months

    Excellent, but by far the best was the topic about decorators.

  • Juan S.
    7 months

    Terrific course. Same for all courses in the track on Data Science.

  • Aboutaleb P.
    7 months

    I love Data Camp's beginner friendly way of teaching

  • P S.
    8 months

    A very good unit, which enabled me to understand closures and decorators.

  • Emmanuel H.
    8 months

    It was challenging and very interesting. I enjoy the lesson.

"Excellent, but by far the best was the topic about decorators."

Josue U.

"Terrific course. Same for all courses in the track on Data Science."

Juan S.

"I love Data Camp's beginner friendly way of teaching"

Aboutaleb P.

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