Controleren op een closure

Je leert je nichtje programmeren in Python, en zij is bezig met het retourneren van geneste functies. Ze denkt dat ze de code goed heeft geschreven, maar is bang dat de geretourneerde functie bij het aanroepen niet over de benodigde informatie zal beschikken. Laat haar zien dat alle nonlocal-variabelen die ze nodig heeft in de closure van de nieuwe functie zitten.

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Functies schrijven in Python

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def return_a_func(arg1, arg2):
  def new_func():
    print('arg1 was {}'.format(arg1))
    print('arg2 was {}'.format(arg2))
  return new_func
    
my_func = return_a_func(2, 17)

# Show that my_func()'s closure is not None
print(my_func.____ is not None)

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Deze oefening maakt deel uit van de cursus

Functies schrijven in Python

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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: Using context managers Exercise 2: The number of cats Exercise 3: The speed of cats Exercise 4: Writing context managers Exercise 5: The timer() context manager Exercise 6: A read-only open() context manager Exercise 7: Advanced topics Exercise 8: Context manager use cases Exercise 9: Scraping the NASDAQ Exercise 10: Changing the working directory

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: Functies zijn objecten Exercise 2: Een data-app voor de command line bouwen Exercise 3: De code van je collega reviewen Exercise 4: Functies retourneren voor een rekenspel Exercise 5: Scope Exercise 6: Scope begrijpen Exercise 7: Variabelen buiten de lokale scope aanpassen Exercise 8: Closures Exercise 9: Controleren op een closure

Huidige oefening

Exercise 10: Closures houden je waarden veilig Exercise 11: Decorators Exercise 12: Decorator-syntaxis gebruiken Exercise 13: Een decorator definiëren

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!