Python Generators and Iterators

Iterators and Generators

Generators produce values lazily, one at a time, instead of building a whole list in memory. Perfect for huge or infinite sequences.

A Generator with yield

def countdown(n):
    while n > 0:
        yield n
        n -= 1

for num in countdown(3):
    print(num)  # 3, 2, 1

Why It Saves Memory

# List — stores ALL 10 million numbers in RAM
nums = [n for n in range(10_000_000)]

# Generator — stores ONE number at a time
nums = (n for n in range(10_000_000))

Infinite Generators

def infinite_ids():
    i = 1
    while True:
        yield i
        i += 1

Reading a Huge File Lazily

def read_lines(path):
    with open(path) as f:
        for line in f:
            yield line.strip()
# Processes a 50GB file with tiny memory

FAQs

Generator vs list — when to use which?

Use a list when you need random access or to reuse data. Use a generator for one-pass, large, or streaming data.

Can I reuse a generator?

No — once exhausted it's done. Create a new one. More in our Python section.