How to Create Generator in Python: Simple Guide with Examples

In Python, you create a generator by defining a function that uses the yield keyword instead of return. This makes the function return an iterator that produces values one at a time, saving memory and allowing lazy evaluation.

Syntax

A generator function looks like a normal function but uses yield to produce a sequence of values. Each time yield is called, the function pauses and returns a value, resuming from there on the next call.

• def: defines the generator function.
• yield: pauses and sends a value back to the caller.
• Function returns a generator object, which is an iterator.

python

def generator_function():
    value = 1  # example value
    yield value  # produces a value and pauses
    # more code or yields can follow

Example

This example shows a generator that yields numbers from 1 to 3. It demonstrates how the generator pauses after each yield and resumes when next value is requested.

python

def count_up_to_three():
    yield 1
    yield 2
    yield 3

for number in count_up_to_three():
    print(number)

Output

1
2
3

Common Pitfalls

Common mistakes include using return instead of yield, which ends the function and does not create a generator. Another is forgetting that generators can only be iterated once.

Also, trying to access generator values by index like a list will not work because generators produce values on demand.

python

def wrong_generator():
    return 1  # This ends the function immediately, no generator created

def correct_generator():
    yield 1  # This creates a generator

# Using the generators
print(type(wrong_generator()))  # <class 'int'>
print(type(correct_generator()))  # <class 'generator'>

Output

<class 'int'>
<class 'generator'>

Quick Reference

• Use yield inside a function to create a generator.
• Generators produce values lazily, saving memory.
• Use for loops or next() to get values from generators.
• Generators can only be iterated once.

Key Takeaways

Use yield in a function to create a generator that produces values one at a time.

Generators save memory by generating values lazily instead of storing them all at once.

You can iterate over generators with for loops or next() calls.

Generators can only be used once; after exhaustion, they do not reset.

Avoid using return when you want to create a generator; use yield instead.