Python Generators
Internal
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.