Le nombre de chats

Vous travaillez sur un projet de traitement du langage naturel visant à déterminer ce qui rend les grands écrivains si exceptionnels. Votre hypothèse actuelle est que les grands écrivains évoquent fréquemment les chats. Pour le démontrer, vous souhaitez compter le nombre d'occurrences du mot « chat » dans « Alice au pays des merveilles » de Lewis Carroll. Vous avez déjà téléchargé un fichier texte, alice.txt, contenant l'intégralité de cet excellent ouvrage.

Cet exercice fait partie du cours

<cours>Écrire des fonctions en Python</cours>

Instructions de l’exercice

Utilisez le gestionnaire de contexte open() pour ouvrir alice.txt et attribuer le fichier à la variable file.

Exercice interactif pratique

Essayez cet exercice en complétant ce code d’exemple.

# Open "alice.txt" and assign the file to "file"
____ ____('alice.txt') ____ file:
  text = file.read()

n = 0
for word in text.split():
  if word.lower() in ['cat', 'cats']:
    n += 1

print('Lewis Carroll uses the word "cat" {} times'.format(n))

Modifier et exécuter le code

Cet exercice fait partie du cours

<cours>Écrire des fonctions en Python</cours>

IntermédiaireNiveau de compétence

4.8+

Commencer le cours gratuitement

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.

Exercise 1: Docstrings Exercise 2: Crafting a docstring Exercise 3: Retrieving docstrings Exercise 4: Docstrings to the rescue!Exercise 5: DRY and "Do One Thing"Exercise 6: Extract a function Exercise 7: Split up a function Exercise 8: Pass by assignment Exercise 9: Mutable or immutable?Exercise 10: Best practice for default arguments

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.

Exercise 1: Utilisation des gestionnaires de contexte Exercise 2: Le nombre de chats

Exercice actuel

Exercise 3: La rapidité des chats Exercise 4: Rédaction des gestionnaires de contexte Exercise 5: Le gestionnaire de contexte timer()Exercise 6: Un gestionnaire de contexte open() en lecture seule Exercise 7: Sujets avancés Exercise 8: Cas d'utilisation du gestionnaire de contexte Exercise 9: Récupération des données du NASDAQ Exercise 10: Modification du répertoire de travail

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.

Exercise 1: Functions are objects Exercise 2: Building a command line data app Exercise 3: Reviewing your co-worker's code Exercise 4: Returning functions for a math game Exercise 5: Scope Exercise 6: Understanding scope Exercise 7: Modifying variables outside local scope Exercise 8: Closures Exercise 9: Checking for closure Exercise 10: Closures keep your values safe Exercise 11: Decorators Exercise 12: Using decorator syntax Exercise 13: 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.

Exercise 1: Real-world examples Exercise 2: Print the return type Exercise 3: Counter Exercise 4: Decorators and metadata Exercise 5: Preserving docstrings when decorating functions Exercise 6: Measuring decorator overhead Exercise 7: Decorators that take arguments Exercise 8: Run_n_times()Exercise 9: HTML Generator Exercise 10: Timeout(): a real world example Exercise 11: Tag your functions Exercise 12: Check the return type Exercise 13: Great job!