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Learn Python Programming

You're reading from   Learn Python Programming A comprehensive, up-to-date, and definitive guide to learning Python

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Product type Paperback
Published in Nov 2024
Publisher Packt
ISBN-13 9781835882948
Length 616 pages
Edition 4th Edition
Languages
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Authors (2):
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Heinrich Kruger Heinrich Kruger
Author Profile Icon Heinrich Kruger
Heinrich Kruger
Fabrizio Romano Fabrizio Romano
Author Profile Icon Fabrizio Romano
Fabrizio Romano
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Toc

Table of Contents (20) Chapters Close

Preface A Gentle Introduction to Python FREE CHAPTER Built-In Data Types Conditionals and Iteration Functions, the Building Blocks of Code Comprehensions and Generators OOP, Decorators, and Iterators Exceptions and Context Managers Files and Data Persistence Cryptography and Tokens Testing Debugging and Profiling Introduction to Type Hinting Data Science in Brief Introduction to API Development CLI Applications Packaging Python Applications Programming Challenges Other Books You May Enjoy
Index

Generators

Generators are based on the concept of iteration, as we said before, and they allow coding patterns that combine elegance with efficiency.

Generators are of two types:

  • Generator functions: These are similar to regular functions, but instead of returning results through return statements, they use yield, which allows them to suspend and resume their state between each call.
  • Generator expressions: These are similar to the list comprehensions we have seen in this chapter, but instead of returning a list, they return an object that produces results one by one.

Generator functions

Generator functions behave like regular functions in all respects, except for one difference: instead of collecting results and returning them at once, they are automatically turned into iterators that yield results one at a time.

Suppose we asked you to count from 1 to 1,000,000. You start, and at some point, we ask you to stop. After some time, we ask you to...

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