List Comprehensions

In order to keep your code elegant and readable, it’s recommended that you use Python’s comprehension features List comprehension is a powerful and concise method for creating lists in Python

• List comprehension methods are an elegant way to create and manage lists.
• more compact way of creating lists.
• More flexible than for loops and faster

  syntax

  my_new_list = [ expression for item in list ]

  • item is the object that the expression will work on.
  • list iterable list of objects to build our new list from. example :

    digits = [x for x in range(10)]
    print(digits)
    

    Output [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

Decorators

decorators wrap a function, modifying its behavior. Python allows you to use decorators in a simpler way with the @

• They can be reused.
• They can decorate functions with arguments and return values.
• They can use @functools.wraps to look more like the decorated function. ex : ``` def my_decorator(func): def wrapper(): print(“Something is happening before the function is called.”) func() print(“Something is happening after the function is called.”) return wrapper

@my_decorator def say_whee(): print(“Whee!”) ```

Registering Plugins

Decorators don’t have to wrap the function they’re decorating. They can also simply register that a function exists and return it unwrapped. This can be used, for instance, to create a light-weight plug-in architecture

• The @register decorator simply stores a reference to the decorated function in the global PLUGINS dict

Is the User Logged In

Flask to set up a /secret web page that should only be visible to users that are logged in or otherwise authenticated