Python Programming Python Datatypes Python If Else Python If Else Examples Python Loops Python For Loops Examples Python List Tuple and Set Python List Example Python Dictionary Python Dictionary Example Python Functions Python Functions Example Python Classes and Objects Python Classes and Objects Example Inheritance and Polymorphism Python Exception Python Exception Example Python Iterator and Generator File Handling Python Regular Expression Python Quiz

Python Iterators and Generators

In Python, iterators and generators are both mechanisms for iterating over a sequence of values, but they have different implementations and use cases.

Iterator

An iterator is an object that implements the iterator protocol, which consists of the __iter__() and __next__() methods. It allows you to iterate over a collection of items one at a time, fetching the next item when requested.

Here's an example of an iterator that generates a sequence of numbers up to a given limit:




Generators

Generators are a simpler and more concise way to create iterators. They are defined using a special type of function called a generator function, which uses the yield keyword to return values one at a time.

Each time the yield statement is encountered, the generator function's state is saved, and the value is returned.

The next time the generator is called, it resumes from where it left off. Here's an example of a generator function that generates a sequence of numbers up to a given limit:


Generators are memory-efficient because they generate values on-the-fly instead of storing them in memory.

They are particularly useful when dealing with large sequences or when you only need to access a portion of the sequence.

In summary, iterators and generators provide ways to iterate over sequences, but generators offer a simpler and more concise syntax and are often more memory-efficient.

Enroll Now

  • Python Programming
  • Machine Learning