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functools for caching, partial application, and more

functools contains several small tools with big practical payoff. The most useful ones in everyday code are lru_cache, partial, and cached_property.

Why it is useful​

These tools help you avoid boilerplate:

  • lru_cache memoizes repeated function calls
  • partial pre-fills some function arguments
  • cached_property computes a value once per instance

A few high-value patterns​

Caching repeated pure work:

from functools import lru_cache


@lru_cache
def fibonacci(n: int) -> int:
    if n < 2:
        return n
    return fibonacci(n - 1) + fibonacci(n - 2)

Pre-filling arguments:

from functools import partial

int_base_2 = partial(int, base=2)
print(int_base_2("101"))

When to be careful​

Caching only helps when repeated calls use the same inputs and the function behaves like a pure function. partial is handy, but not if it makes call sites more mysterious.

Rules of thumb​

  • Use lru_cache for repeated pure computations.
  • Use partial when a configured function is clearer than a wrapper.
  • Use cached_property for expensive per-instance values.