"""
This module exposes decorators for in-memory caching of functional results.
This is particularly useful when prototyping dynamic programming algorithms.
Either :func:`memoize`, :func:`memoize_method`, and :func:`memoize_property`
should be used depending on what type of function is being wrapped. The
following example demonstrates this.
In Python 3.8+ :func:`memoize` works similarly to the standard library
:func:`functools.cache`, but the ubelt version makes use of
:func:`ubelt.util_hash.hash_data`, which is slower, but handles inputs
containing mutable containers.
Example:
>>> import ubelt as ub
>>> # Memoize a function, the args are hashed
>>> @ub.memoize
>>> def func(a, b):
>>> return a + b
>>> #
>>> class MyClass:
>>> # Memoize a class method, the args are hashed
>>> @ub.memoize_method
>>> def my_method(self, a, b):
>>> return a + b
>>> #
>>> # Memoize a property: there can be no args,
>>> @ub.memoize_property
>>> @property
>>> def my_property1(self):
>>> return 4
>>> #
>>> # The property decorator is optional
>>> def my_property2(self):
>>> return 5
>>> #
>>> func(1, 2)
>>> func(1, 2)
>>> self = MyClass()
>>> self.my_method(1, 2)
>>> self.my_method(1, 2)
>>> self.my_property1
>>> self.my_property1
>>> self.my_property2
>>> self.my_property2
"""
import functools
import sys
from ubelt import util_hash
__all__ = ['memoize', 'memoize_method', 'memoize_property']
def _hashable(item):
"""
Returns the item if it is naturally hashable, otherwise it tries to use
ubelt.util_hash.hash_data to make it hashable. Errors if it cannot.
"""
try:
hash(item)
except TypeError:
return util_hash.hash_data(item)
else:
return item
def _make_signature_key(args, kwargs):
"""
Transforms function args into a key that can be used by the cache
Example:
>>> from ubelt.util_memoize import _make_signature_key
>>> args = (4, [1, 2])
>>> kwargs = {'a': 'b'}
>>> key = _make_signature_key(args, kwargs)
>>> print('key = {!r}'.format(key))
>>> # Some mutable types cannot be handled by ub.hash_data
>>> import pytest
>>> from collections import abc
>>> # This used to error, in ubelt versions < 0.9.5
>>> _make_signature_key((4, [1, 2], {1: 2, 'a': 'b'}), kwargs={})
>>> class Dummy(abc.MutableSet):
>>> def __contains__(self, item): return None
>>> def __iter__(self): return iter([])
>>> def __len__(self): return 0
>>> def add(self, item, loc): return None
>>> def discard(self, item): return None
>>> with pytest.raises(TypeError):
>>> _make_signature_key((Dummy(),), kwargs={})
"""
kwitems = kwargs.items()
# TODO: we should check if Python is at least 3.7 and sort by kwargs
# keys otherwise. Should we use hash_data for key generation
if (sys.version_info.major, sys.version_info.minor) < (3, 7): # nocover
# We can sort because they keys are guaranteed to be strings
kwitems = sorted(kwitems)
kwitems = tuple(kwitems)
try:
key = _hashable(args), _hashable(kwitems)
except TypeError:
msg = ('Signature is not hashable: '
'args={} kwargs{}'.format(args, kwargs))
raise TypeError(msg)
return key
[docs]
def memoize(func):
"""
memoization decorator that respects args and kwargs
In Python 3.9. The :mod:`functools` introduces the `cache` method, which is
currently faster than memoize for simple functions [FunctoolsCache]_.
However, memoize can handle more general non-natively hashable inputs.
Args:
func (Callable): live python function
Returns:
Callable: memoized wrapper
References:
.. [WikiMemoize] https://wiki.python.org/moin/PythonDecoratorLibrary#Memoize
.. [FunctoolsCache] https://docs.python.org/3/library/functools.html
Example:
>>> import ubelt as ub
>>> closure = {'a': 'b', 'c': 'd'}
>>> incr = [0]
>>> def foo(key):
>>> value = closure[key]
>>> incr[0] += 1
>>> return value
>>> foo_memo = ub.memoize(foo)
>>> assert foo('a') == 'b' and foo('c') == 'd'
>>> assert incr[0] == 2
>>> print('Call memoized version')
>>> assert foo_memo('a') == 'b' and foo_memo('c') == 'd'
>>> assert incr[0] == 4
>>> assert foo_memo('a') == 'b' and foo_memo('c') == 'd'
>>> print('Counter should no longer increase')
>>> assert incr[0] == 4
>>> print('Closure changes result without memoization')
>>> closure = {'a': 0, 'c': 1}
>>> assert foo('a') == 0 and foo('c') == 1
>>> assert incr[0] == 6
>>> assert foo_memo('a') == 'b' and foo_memo('c') == 'd'
"""
cache = {}
@functools.wraps(func)
def memoizer(*args, **kwargs):
key = _make_signature_key(args, kwargs)
if key not in cache:
cache[key] = func(*args, **kwargs)
return cache[key]
memoizer.cache = cache
return memoizer
[docs]
class memoize_method(object):
"""
memoization decorator for a method that respects args and kwargs
References:
.. [ActiveState_Miller_2010] http://code.activestate.com/recipes/577452-a-memoize-decorator-for-instance-methods
Attributes:
__func__ (Callable): the wrapped function
Example:
>>> import ubelt as ub
>>> closure = {'a': 'b', 'c': 'd'}
>>> incr = [0]
>>> class Foo(object):
>>> @ub.memoize_method
>>> def foo_memo(self, key):
>>> "Wrapped foo_memo docstr"
>>> value = closure[key]
>>> incr[0] += 1
>>> return value
>>> def foo(self, key):
>>> value = closure[key]
>>> incr[0] += 1
>>> return value
>>> self = Foo()
>>> assert self.foo('a') == 'b' and self.foo('c') == 'd'
>>> assert incr[0] == 2
>>> print('Call memoized version')
>>> assert self.foo_memo('a') == 'b' and self.foo_memo('c') == 'd'
>>> assert incr[0] == 4
>>> assert self.foo_memo('a') == 'b' and self.foo_memo('c') == 'd'
>>> print('Counter should no longer increase')
>>> assert incr[0] == 4
>>> print('Closure changes result without memoization')
>>> closure = {'a': 0, 'c': 1}
>>> assert self.foo('a') == 0 and self.foo('c') == 1
>>> assert incr[0] == 6
>>> assert self.foo_memo('a') == 'b' and self.foo_memo('c') == 'd'
>>> print('Constructing a new object should get a new cache')
>>> self2 = Foo()
>>> self2.foo_memo('a')
>>> assert incr[0] == 7
>>> self2.foo_memo('a')
>>> assert incr[0] == 7
>>> assert self.foo_memo.__doc__ == 'Wrapped foo_memo docstr'
>>> assert self.foo_memo.__name__ == 'foo_memo'
"""
def __init__(self, func):
"""
Args:
func (Callable): method to wrap
"""
self._func = func
self._cache_name = '_cache__' + func.__name__
# Mimic attributes of a bound method
self.__func__ = func
functools.update_wrapper(self, func)
def __get__(self, instance, cls=None):
"""
Descriptor get method. Called when the decorated method is accessed
from an object instance.
Args:
instance (object): the instance of the class with the memoized method
cls (type | None): the type of the instance
"""
self._instance = instance
return self
def __call__(self, *args, **kwargs):
"""
The wrapped function call
"""
cache = self._instance.__dict__.setdefault(self._cache_name, {})
key = _make_signature_key(args, kwargs)
if key in cache:
return cache[key]
else:
value = cache[key] = self._func(self._instance, *args, **kwargs)
return value
[docs]
def memoize_property(fget):
"""
Return a property attribute for new-style classes that only calls its
getter on the first access. The result is stored and on subsequent accesses
is returned, preventing the need to call the getter any more.
This decorator can either be used by itself or by decorating another
property. In either case the method will always become a property.
Note:
implementation is a modified version of [estebistec_memoize]_.
References:
.. [estebistec_memoize] https://github.com/estebistec/python-memoized-property
Args:
fget (property | Callable): A property or a method.
Example:
>>> import ubelt as ub
>>> class C(object):
... load_name_count = 0
... @ub.memoize_property
... def name(self):
... "name's docstring"
... self.load_name_count += 1
... return "the name"
... @ub.memoize_property
... @property
... def another_name(self):
... "name's docstring"
... self.load_name_count += 1
... return "the name"
>>> c = C()
>>> c.load_name_count
0
>>> c.name
'the name'
>>> c.load_name_count
1
>>> c.name
'the name'
>>> c.load_name_count
1
>>> c.another_name
"""
# Unwrap any existing property decorator
while hasattr(fget, 'fget'):
fget = fget.fget
attr_name = '_' + fget.__name__
@functools.wraps(fget)
def fget_memoized(self):
if not hasattr(self, attr_name):
setattr(self, attr_name, fget(self))
return getattr(self, attr_name)
return property(fget_memoized)