Chapter 6: Iterators and Generators

In this chapter, we delve into the world of iterators and generators, essential tools for efficient data processing in Python. 📚

Key Concepts

• Iterator Protocol: Objects that implement __iter__() and __next__() methods.
• Generator Functions: Use yield to produce a sequence of values lazily.
• Generator Expressions: Compact way to create generators using parentheses.

Example: Generator Function

def count_up_to(n):
    count = 1
    while count <= n:
        yield count
        count += 1

Practical Applications

• Memory-efficient handling of large datasets.
• Infinite sequences (e.g., yield from for recursive generation).
• Pipelines for data transformation.

For deeper insights, explore our Python Essentials Guide. 🌐

📌 Summary

Generators and iterators are powerful for managing data flow. Use them to optimize performance and simplify complex operations!