Python Generators: Difference between revisions
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* [[Python_Language#Generators|Python Language]] | * [[Python_Language#Generators|Python Language]] | ||
* <tt>[[Python_Language_Functions#reversed|reversed()]]</tt> | * <tt>[[Python_Language_Functions#reversed|reversed()]]</tt> | ||
* [[Python_Iterators#Overview|Python Iterators]] | |||
=TODO= | =TODO= |
Latest revision as of 19:11, 17 May 2024
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.