The Hacker's Guide to Scaling Python/

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Memoization

Memoization

Learn about memoization in Python.

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Memoization is a technique used to speed up function calls by caching their results. The results can be cached only if the function is pure, meaning that it has no side effects or outputs and that it does not depend on any global state.

Memoizing sin function

A trivial function that can be memoized is the sine function sin.

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import math
_SIN_MEMOIZED_VALUES = {}
def memoized_sin(x):
  if x not in _SIN_MEMOIZED_VALUES:
    _SIN_MEMOIZED_VALUES[x] = math.sin(x)
  return _SIN_MEMOIZED_VALUES[x]
print('memoized_sin(1): ', memoized_sin(1))
print('_SIN_MEMOIZED_VALUES:', _SIN_MEMOIZED_VALUES)
print('memoized_sin(2):', memoized_sin(2))
print('memoized_sin(2):', memoized_sin(2))
print('_SIN_MEMOIZED_VALUES:', _SIN_MEMOIZED_VALUES)
print('memoized_sin(1):', memoized_sin(1))
print('_SIN_MEMOIZED_VALUES:', _SIN_MEMOIZED_VALUES)

The first time that memoized_sin is called with an argument that is not stored in ...