Python dictionaries are like fancy spreadsheets that can handle all sorts of weird stuff without breaking a sweat! They’re made up of keys and values, where each row has a label (called a “key”) and a value associated with it. To access a value in the dictionary, you use its key. If the key doesn’t exist, Python will throw an error unless you use the `get()` method instead. Dictionaries can handle any type of value as a key or a value (including other dictionaries!). This makes them super useful for organizing data in your code.
Did you know that Python also has function annotations and decorators? Function annotations allow us to add extra information about the arguments and return values of functions. Decorators are a way to modify how a function or method works without changing its original definition. They can be used for all sorts of things, like adding pre- and postconditions, tracing, synchronization, and even improving other decorators!
Function annotations look like this: `def my_function(arg1: int, arg2: str) -> float:` The syntax is similar to Java’s annotation system. Decorators are a bit more complex they involve wrapping the original function with another function that modifies its behavior. For example, we can create a decorator called `viking_chorus` that runs a function 8 times for each time it’s called:
# Define a decorator function called "viking_chorus" that takes in a function as its argument
def viking_chorus(myfunc):
# Define an inner function that takes in any number of arguments and keyword arguments
def inner_func(*args, **kwargs):
# Use a for loop to run the original function 8 times
for i in range(8):
# Call the original function with the given arguments and keyword arguments
myfunc(*args, **kwargs)
# Return the inner function, which will be used to modify the behavior of the original function
return inner_func
To use this decorator, we simply add the `@viking_chorus` syntax before our function definition:
# This is a decorator function that takes in a function as an argument
def viking_chorus(func):
# This is the wrapper function that will be returned and used as the new function
def wrapper():
# This is the code that will be executed before the original function is called
print("Spam, spam, spam, spam, spam, spam, spam, spam, lovely spam, wonderful spam")
# This calls the original function and stores the result in a variable
result = func()
# This is the code that will be executed after the original function is called
print("Spam, spam, spam, spam, spam, spam, spam, spam, lovely spam, wonderful spam")
# This returns the result of the original function
return result
# This returns the wrapper function to be used as the new function
return wrapper
# This is the original function that will be decorated
def menu_item():
print("spam")
# This is how we use the decorator by adding the @viking_chorus syntax before the function definition
@viking_chorus
def menu_item():
print("spam")
# This calls the decorated function, which will now include the additional code from the decorator
menu_item()
Or, if you prefer chaining decorators, you can do this instead:
# The original script:
python
# The invincible decorator makes the black_knight function invincible
# The favourite_colour decorator sets the favourite colour of the black_knight to "Blue"
@invincible
@favourite_colour("Blue")
def black_knight():
pass
# The corrected script:
python
# The invincible decorator makes the black_knight function invincible
# The favourite_colour decorator sets the favourite colour of the black_knight to "Blue"
@invincible
@favourite_colour("Blue")
def black_knight():
# The pass statement is used as a placeholder for future code
pass
# Explanation:
The original script is missing a pass statement within the black_knight function, which is necessary for the function to have a valid body. The pass statement acts as a placeholder for future code and ensures that the function does not throw an error.
This is equivalent to the previous example with intermediate variables.