All 15 Iterators & the Iterator Protocol questions
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What does the built-in next() function's optional default argument do? How do you manually exhaust and inspect an iterator without a for-loop? How do you implement a custom iterator by defining __iter__ and __next__? How does Python's iter() function work with a sentinel value as a second argument? How does Python know whether to treat a for-in target as iterable, and what error occurs if it isn't? What is the relationship between generators and the iterator protocol? What is the difference between iter(obj) and using obj directly in a for-loop, in terms of what Python calls internally? What is the difference between __iter__ returning self versus returning a separate iterator object? How would you implement a lazy, chainable iterator pipeline (like filter-then-map) from scratch? How does itertools.tee let you iterate over the same iterator multiple times independently?
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How does the itertools module complement the iterator protocol?

Intermediate

Answer

itertools provides fast, memory-efficient building blocks that operate on the iterator protocol: infinite iterators (count, cycle, repeat), combinatoric generators (product, permutations, combinations), and terminating iterators (chain, islice, groupby, takewhile). They let you compose complex lazy pipelines without materializing intermediate lists.
import itertools

for combo in itertools.combinations([1,2,3], 2):
    print(combo)  # (1,2) (1,3) (2,3)

for x in itertools.islice(itertools.count(10), 3):
    print(x)  # 10 11 12
Real-world example A test suite uses itertools.product to generate every combination of browser, OS, and screen resolution for cross-browser test cases without nested loops.

Common follow-ups: What's the memory advantage of itertools over building lists?;How does groupby require sorted input?

functools & Functional Programming Tools;Comprehensions & Generators
All 15 Iterators & the Iterator Protocol questions