Fresher · Language concepts

Generators vs. Lists

Compare a list comprehension with a generator when processing a large file. Explain iteration, laziness, and resource lifetime.

Examples

Compare approaches

Baseline approach

Begin by explaining the core mechanism, stating assumptions, and walking through one concrete example.

Time: Depends on design · Space: Depends on design

def squares(values):
    for value in values:
        yield value * value

Strong answer

A generator evaluates lazily and holds its current state. A list eagerly materializes results. Both perform O(n) total work; the generator needs O(1) auxiliary state for this example.

Time: O(n) total · Space: O(1) auxiliary

def squares(values):
    for value in values:
        yield value * value

Common traps

Generators are consumed; a second pass does not restart them.
State assumptions and justify trade-offs rather than memorizing a single answer.

Practise in the workspace →