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Iterators & Generators

7 Topics
1

Iterators

The iterator protocol — understanding __iter__ and __next__ methods, how for loops work internally, and building custom iterable sequences.

Common interview topic — understanding iterators demonstrates deep knowledge of Python internals and lazy evaluation.
2

Iterables

Understanding iterables vs iterators — objects that can produce iterators, the iter() function, and building custom iterable collections.

Interviewers frequently ask the difference between iterables and iterators — a key Python concept.
3

Generators

Generator functions using yield — lazy evaluation, memory efficiency, sending values into generators, and generator lifecycle management.

Generators are a top interview topic — they demonstrate understanding of lazy evaluation, memory efficiency, and Pythonic design.
4

Generator Expressions

Memory-efficient lazy evaluation using generator expressions — the parenthesized form of list comprehensions that produces values on demand.

Performance optimization question — know when to use generator expressions vs list comprehensions.
5

itertools Module

The itertools standard library — efficient iteration tools including infinite iterators, combinatoric functions, grouping, and chaining utilities.

Shows advanced Python knowledge — interviewers value candidates who use itertools instead of hand-rolled loops.
6

yield from

Delegating to sub-generators with yield from — simplifying nested iteration, bidirectional communication, and building recursive generators.

Advanced generator pattern — shows deep understanding of Python generator mechanics.
7

Infinite Iterators

Creating and managing infinite sequences — generators and itertools functions that produce values forever, with strategies for safe consumption.

Tests understanding of lazy evaluation and how to safely work with unbounded data streams.
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