Python Generators

Internal

• Python Language
• reversed()

TODO

• PROCESS IPy Generators Page 101.
• PROCESS PyOOP "Generator expressions"
• PROCESS PyOOP "Generators" + "Yield items from another iterable"

Overview

A generator is a way to construct a new iterable object. Whereas normal functions execute and return a single result at a time, generators can return a sequence of multiple values by pausing and resuming execution each time the generator is used. To create a generator, use the yield keyword instead of return in a function.

def squares(n=10):
  for i in range(1, n+1):
    yield i ** 2

When the generator is called no code is immediately executed:

gen = squares()

It is not until you request elements from the generator that it begins executing code:

for x in gen:
  print(x)

Generator Comprehensions

A generator expression is the generator analogues to list, dictionary and set comprehensions. To create one, enclose what would be otherwise a list comprehension within parentheses instead of brackets. Depending on the number of elements produced by the comprehension expression, the generator expression can sometimes be meaningfully faster.

• PROCESS IPy Comprehensions Page 88.

Use Cases

Create a list with a generator.