memoiz 2.0.2

Memoiz is a memoization decorator that makes reasonable assumptions about how and if to cache the return value of a function or method based on the arguments passed to it. The decorator can be used on both free and bound functions.

Memoiz

A thread-safe memoization decorator for functions and methods.

Introduction

Memoiz provides a function decorator that adds memoization to a function or method. It makes reasonable assumptions about how and if to cache the return value of a function or method based on the arguments passed to it.

Features

• Use the Memoiz decorator on functions and methods
• Thread-safe cache
• Support for any number of arguments or keyword arguments
• Support for parameter and return type hints
• Selective cache entry removal

Table of Contents

• Installation
• Usage
  • Apply Memoization to Class Methods
  • Apply Memoization to Functions
• Memoization Strategy
  • Type Transformations
• API
• Test

Installation

pip install memoiz

Usage

Apply Memoization to Class Methods

In this example you will use Memoiz to memoize the return value of the greeter.greet method and print the greeting.

from memoiz import Memoiz

# `cache` is a Python decorator and a callable.
cache = Memoiz()


class Greeter:

    def __init__(self):
        self.adv = "Very"

    @cache # The `cache` decorator adds memoization capabilities to the `greet` method.
    def greet(self, adj: str) -> str:
        return f"Hello, {self.adv} {adj} World!"


greeter = Greeter()

print("1:", cache._cache)

greeting = greeter.greet("Happy")

print("2:", greeting)

1: {}
2: Hello, Very Happy World!

As a continuation of the example, you will selectively clear cached articles using the cache.clear method.

greeter = Greeter()

print("1:", cache._cache)

greeting = greeter.greet("Happy")

print("2:", greeting)

greeting = greeter.greet("Cautious")

print("3:", greeting)

# The cache has memoized the two method calls.
print("4:", cache._cache)

# Clear the call to `greeter.greet` with the "Happy" argument.
#                          ⮶ args
cache.clear(greeter.greet, "Happy")
#                   ⮴ method

print("5:", cache._cache)

# Clear the call to `greeter.greet` with the `Cautious` argument.
cache.clear(greeter.greet, "Cautious")

# The cache is empty.
print("6:", cache._cache)

1: {}
2: Hello, Very Happy World!
3: Hello, Very Cautious World!
4: {<bound method Greeter.greet of <__main__.Greeter object at 0x7f486842fbe0>>: {(('Happy',), ()): 'Hello, Very Happy World!', (('Cautious',), ()): 'Hello, Very Cautious World!'}}
5: {<bound method Greeter.greet of <__main__.Greeter object at 0x7f486842fbe0>>: {(('Cautious',), ()): 'Hello, Very Cautious World!'}}
6: {}

Apply Memoization to Functions

In this example you will use Memoiz to memoize the return value of the greet function and print the greeting.

from memoiz import Memoiz

cache = Memoiz()


@cache
def greet(adj: str) -> str:
    return f"Hello, {adj} World!"


print("1:", cache._cache)

greeting = greet("Happy")

print("2:", greeting)

1: {}
2: Hello, Happy World!

As a continuation of the example, you will selectively clear cached articles using the cache.clear method.

print("1:", cache._cache)

greeting = greet("Happy")

print("2:", greeting)

greeting = greet("Cautious")

print("3:", greeting)

print("4:", cache._cache)

#                  ⮶ args
cache.clear(greet, "Happy")
#           ⮴ function

# The cached call using the "Happy" argument is deleted; however, the call using the "Cautious" is still present.
print("5:", cache._cache)

#                  ⮶ args
cache.clear(greet, "Cautious")
#           ⮴ function

# The cache is now empty.
print("6:", cache._cache)

1: {}
2: Hello, Happy World!
3: Hello, Cautious World!
4: {<function greet at 0x7f486842bd00>: {(('Happy',), ()): 'Hello, Happy World!', (('Cautious',), ()): 'Hello, Cautious World!'}}
5: {<function greet at 0x7f486842bd00>: {(('Cautious',), ()): 'Hello, Cautious World!'}}
6: {}

Memoization Strategy

Memoiz will attempt to recursively transform a callable's arguments into a hashable key. The key is used in order to index and look up the callable's return value. The strategy that Memoiz employs for key generation depends on the type of the argument(s) passed to the callable. The Type Transformations table provides examples of how Memoiz transforms arguments of common types.

Type Transformations

Type	Example	Hashable Type	Hashable Representation
dict	{'b':42, 'c': 57, 'a': 23}	tuple of tuples	(('a', 23), ('b', 42), ('c', 57))
list	[23, 42, 57]	tuple	(23, 42, 57)
tuple	(23, 42, 57)	tuple	(23, 42, 57)
set	{23, 42, 57}	tuple	(23, 42, 57)
hashable types	hash(...)	tuple	(Ellipsis,)

NB Dictionaries are sorted by their keys prior to indexing the callable's return value.

API

The Memoiz Class

memoiz.Memoiz(sequentials, mapables, deep_copy)

• sequentials Tuple[type, ...] An optional tuple of types that are assumed to be sequence-like. Default (list, tuple, set)
• mapables Tuple[type, ...] An optional tuple of types that are assumed to be dict-like. Default (dict,)
• deep_copy bool Optionally return the cached return value using Python's copy.deepcopy. This can help prevent mutations of the cached return value. Default: True.

memoiz.__call__(callable)

• callable typing.Callable The function or method for which you want to add memoization.

A Memoiz instance (see above) is a callable. This is the @cache decorator that is used in order to add memoization to a callable. Please see the above usage for how to use this decorator.

memoiz.clear(callable, *args, **kwargs)

• callable typing.Callable The callable.
• args Any The arguments passed to the callable.
• kwargs Any The keyword arguments passed to the callable.

Clears the cache for the specified callable and arguments. See the usage for for how to clear the cache.

memoiz.clear_all()

Resets the cache making items in the old cache potentially eligible for garbage collection.

Test

Clone the repository.

git clone https://github.com/faranalytics/memoiz.git

Change directory into the root of the repository.

cd memoiz

Run the tests.

python tests/test.py -v