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.

Docstrings

Crafting a docstring

Retrieving docstrings

Docstrings to the rescue!

DRY and "Do One Thing"

Extract a function

Split up a function

Pass by assignment

Mutable or immutable?

Best practice for default arguments

Best Practices

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.

Context Manager verwenden

Katzen zählen

Katzen schnell erkennen

Context Manager schreiben

Der Context Manager timer()

Ein schreibgeschützter open()-Kontextmanager

Fortgeschrittene Themen

Anwendungsfälle für Context Manager

NASDAQ-Analyse

Das Arbeitsverzeichnis ändern

Context Managers

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.

Functions are objects

Building a command line data app

Reviewing your co-worker's code

Returning functions for a math game

Scope

Understanding scope

Modifying variables outside local scope

Closures

Checking for closure

Closures keep your values safe

Decorators

Using decorator syntax

Defining a decorator

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.

Real-world examples

Print the return type

Counter

Decorators and metadata

Preserving docstrings when decorating functions

Measuring decorator overhead

Decorators that take arguments

Run_n_times()

HTML Generator

Timeout(): a real world example

Tag your functions

Check the return type

Great job!

More on Decorators

Du hast deine Analyse durchgeführt, den Bericht erstellt und ein Modell trainiert. Und jetzt? Wenn du dein Modell in Produktion bringen willst, muss dein Code verlässlicher sein als explorative Skripte in einem Jupyter-Notebook. Dieser Kurs gibt dir ein solides Fundament, um komplexe und elegante Funktionen zu entwickeln – so trägst du Forschungs- und Engineering-Kompetenz zu deinem Team bei. Du lernst praktische Tricks wie das Schreiben von Context Managern und Decorators. Außerdem lernst du Best Practices kennen für wartbare und wiederverwendbare Funktionen mit guter Dokumentation. Es heißt, wer gute Forschung betreibt und hochwertigen Code schreibt, sei ein Einhorn. Absolviere diesen Kurs und erlebe, was dahintersteckt!

Python Toolbox

Lernen Sie, wartbare, wiederverwendbare Funktionen mit guter Dokumentation zu schreiben.

Funktionen in Python schreiben

Lerne empfohlene Vorgehensweisen für das Schreiben von Code für komplexe, aber dennoch klare und wiederverwendbare Funktionen.

Associate Data Scientist  in Python

Python for Software Engineering

Anwendungsfälle für Context Manager

Interaktive praktische Übung