4. Generators

See ref video at: https://www.youtube.com/watch?v=bD05uGo_sVI

4.1. Generator via a for-loop

Python generators use the yield keyword.
The code below uses a generator for square numbers.
The generator object does not hold all the values it generates in memory, whereas a list does.

# I want to yield 'n * n' for each 'n' in nums
nums = [1, 2, 3, 4, 5]


def gen_squares(nums):
    for n in nums:
        yield n * n


my_gen_squares = gen_squares(nums)

for num in my_gen_squares:
    print(num, end=" ")

The printout is: 1 4 9 16 25

4.2. Generator comprehension

Generator comprehension looks just like list comprehension but uses parentheses () rather than square brackets [].

Syntax:

new_generator = (expression for item in iterable)

Parameters:

expression – the item variable only (e.g. x) or any expression such as one that uses the item variable (e.g. x * x).
item – a variable.
iterable – iterable objects like strings, lists, dictionaries, range function and others.

The code below is a generator for square numbers.

# I want to yield 'n * n' for each 'n' in nums
nums = [1, 2, 3, 4, 5]

my_gen_squares = (x * x for x in nums)

for num in my_gen_squares:
    print(num, end=" ")

The printout is: 1 4 9 16 25

4.2.1. Practice Questions

Tasks

Use a generator comprehension to produce the first 5 cubic numbers.
Use a generator comprehension to get the value of (x ** 2 + 2 * x + 1) for each x from 1 to 5.