lru_cache annotation doesn't work as a property

So I originally reported it in typeshed/#2659 but was told this can't be fixed there and it is mypy limitation so repporting it here.

I have following code:

#! /usr/bin/env python

import time
from functools import lru_cache

class MyClass:
	@property
	@lru_cache(1)
	def expensive_operation(self) -> int:
		time.sleep(2)
		return 42

	def another_operation(self) -> int:
		return self.expensive_operation + 1

if __name__ == '__main__':
	o = MyClass()
	print(o.expensive_operation)
	print(o.expensive_operation)
	print(o.another_operation())

It works as expected:

$ ./test.py
42
42
43

Yet, mypy is showing errors:

$ mypy test.py
test.py:7: error: Decorated property not supported
test.py:14: error: Unsupported operand types for + ("_lru_cache_wrapper[int]" and "int")

The lru_cache works just fine when decorated as property, and the returned type should be int and not _lru_cache_wrapper[int].

This is on python 3.7.0 and mypy 0.641.

Duplicates #1362 and #1608

@probablyodd

@probablyodd well its a bit different. If you set # type: ignore to @property in this case,
mypy will completely ignore existence of this decorator and treat such methods as common callable methods. Mypy will just say somethingh like "lru_cache" has no attribute "..." if complex object such as dict returned from property method.

from functools import lru_cache

class Foo:
    @property  # type: ignore
    @lru_cache
    def bar(self) -> dict:
        return dict(key='value')

Foo().bar.get('key')

test.py:11: error: "lru_cache" has no attribute "get"

Edit:

Possible adhoc solution:

T = TypeVar('T')

def cache(func: Callable[..., T]) -> T:
    return functools.lru_cache()(func)  # type: ignore

...
    @property  # type: ignore
    @cache
    def foo(self) -> dict:
        return {}

@sashgorokhov

Besides @sashgorokhov awesome workaround (that adds some complexity to code) - is there any plan to support this ?

@sashgorokhov

Taking a look at the actual implementation of lru_cache and mypy's excellent documentation on decorator factories, here is another workaround for having type annotations work properly with functool's lru_cache:

import functools
from typing import Any, Callable, TypeVar, Union, no_type_check, overload


RT = TypeVar("RT", bound=Callable[..., Any])


@overload
def lru_cache(
    max_size: Callable[..., RT], typed: bool = False
) -> Callable[..., RT]:
    ...


@overload
def lru_cache(max_size: int, typed: bool = False) -> Callable[[RT], RT]:
    ...


@overload
def lru_cache(
    max_size: Union[Callable[..., RT], int], typed: bool = False
) -> Union[Callable[..., RT], Callable[[RT], RT]]:
    ...


@no_type_check
def lru_cache(*args, **kwargs):
    return functools.lru_cache(*args, **kwargs)

This maintains the signature of whatever callable you are decorating, and you should get proper type annotation checks. Credits goes to @sashgorokhov for inspiring to get this solution with his solution above.

@malthunayan

Is this something that should be adjusted in mypy or is it technically the fault of lru_cache?

Also @malthunayan I can't seem to get your workaround to work with @lru_cache(maxsize=None).

Here's my modified workaround - not sure where your max_size is coming from, could have worked in previous Python versions? I'm on 3.8.

import functools
from typing import Any, Callable, TypeVar, Union, no_type_check, overload, Optional

RT = TypeVar("RT", bound=Callable[..., Any])


@overload
def lru_cache(
        maxsize: Callable[..., RT], typed: bool = False
) -> Callable[..., RT]:
    ...


@overload
def lru_cache(maxsize: Optional[int], typed: bool = False) -> Callable[[RT], RT]:
    ...


@overload
def lru_cache(
        maxsize: Union[Callable[..., RT], Optional[int]], typed: bool = False
) -> Union[Callable[..., RT], Callable[[RT], RT]]:
    ...


@no_type_check
def lru_cache(*args, **kwargs):
    return functools.lru_cache(*args, **kwargs)

If there is no plan to fix this soon, then can this be documented properly? This error is implicated by the recommendation in the standard library docs for functools.cached_property for caching properties in classes without proper __dict__s, but there's no hint that such recommendation would frustrate Mypy:

# test_5858.py
import statistics
from functools import cache

class DataSet:
    __slots__ = ("_data",)

    def __init__(self, sequence_of_numbers):
        self._data = sequence_of_numbers

    @property  # <- error: Decorated property not supported  [misc]
    @cache  # <- results in downstream errors involving type "_lru_cache_wrapper[…]"
    def stdev(self):
        return statistics.stdev(self._data)

f: float = statistics.stdev(range(10))
f = DataSet(range(10)).stdev

% python --version
Python 3.9.10
% mypy --version
mypy 0.941
% mypy --config-file=/dev/null test_5858.py
/dev/null: No [mypy] section in config file
test_5858.py:11: error: Decorated property not supported
test_5858.py:17: error: Incompatible types in assignment (expression has type "_lru_cache_wrapper[Any]", variable has type "float")
Found 2 errors in 1 file (checked 1 source file)

Fix inference for properties with __call__ (#15926)

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lru_cache annotation doesn't work as a property #5858

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probablyodd commented on Dec 1, 2018

sashgorokhov commented on Jan 14, 2019

pgilad commented on Jun 21, 2020

malthunayan commented on Apr 29, 2021

Doggie52 commented on Oct 2, 2021

Doggie52 commented on Oct 2, 2021

posita commented on Mar 19, 2022

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