Compute cumulative sums or apply a binary function cumulatively over an iterable.

Express the idea of cumulatively applying a binary function over a sequence, typically for running totals.

When you need running totals, prefix sums, or cumulative application of a function over a sequence (e.g., cumulative sums, products).

Data processing, numerical algorithms, streaming data processing, algorithmic challenges requiring prefix sums.

itertools.accumulate(iterable, func=operator.add)

itertools.accumulate(iterable, func=operator.add)

iterable, func

• list
• range
• operator.add
• operator.mul
• lambda

• operator.mul
• lambda x
• y: x+y
• operator.sub

Forgetting to import itertools or operator; expecting a list instead of an iterator; using a non-associative function leading to unexpected results.

itertools.accumulate with custom function; numpy.cumsum for numeric arrays.

Confusing with built-in sum(); confusing with itertools.accumulate vs itertools.accumulate with default addition vs custom function.

• itertools.accumulate
• itertools.accumulate custom func
• itertools.accumulate numeric

The default function operator.add yields cumulative sums; any binary function works, but non-associative functions may produce unintuitive results.

Expresses a concise functional pattern for computing running totals.

Think of a running total while iterating.

Commonly used with operator module functions or lambda for cumulative operations.

itertools.accumulate with custom functions; numpy.cumsum for numeric arrays