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Generators in Python

 


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Generators in Python

Generators are a special type of iterator in Python that allow you to iterate over a sequence of items without storing them all in memory at once. They are useful for generating large sequences of data on-the-fly, or for processing data in a memory-efficient manner.

Creating Generators

In Python, generators are created using generator functions or generator expressions:


# Generator function
def my_generator(n):
    for i in range(n):
        yield i

# Generator expression
my_generator = (i for i in range(10))

A generator function uses the yield keyword to yield values one at a time, while a generator expression creates an anonymous generator.

Iterating Over Generators

You can iterate over the values produced by a generator using a for loop:


for value in my_generator(5):
    print(value)

This will print the values generated by the generator function.

Generator Expressions

Generator expressions are similar to list comprehensions, but they produce values lazily as they are needed:


# Generator expression
squares = (x**2 for x in range(10))

# Iterate over the generator expression
for square in squares:
    print(square)

This will print the squares of numbers from 0 to 9.

Benefits of Generators
  • Memory Efficiency: Generators produce values one at a time, so they can be more memory efficient than storing all values in memory at once.
  • Lazy Evaluation: Generator expressions are evaluated lazily, meaning values are generated as they are needed, rather than all at once.
  • Efficient Pipelines: Generators can be used to create efficient data processing pipelines, where each stage of processing produces values as needed.

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