cached_method
The equivalent of cached_property for methods
Decision gist · record as of 2026-08-14
Yes, if you need per-instance method caching for non-hashable classes or resource-intensive objects. The code is simple and stable, but be aware the package is unmaintained since 2021-10-31—verify compatibility with your Python version before relying on it in production. For small hashable objects where global caching is acceptable, the standard functools approach may be preferable.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python >= 3.6.
- Low install friction with no runtime dependencies.
- However, the package is abandoned—last release was 2021-10-31 with no updates since, though the repository remains public and the code is stable.
License · maintenance · safety
permissive license (permissive) — Licensed under MIT (permissive), so you may use, modify, and distribute freely with minimal restrictions.
last release 2021-10-31 (1748 days) · last repo commit 2021-10-31 · 11 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 77,437 downloads/mo, #14,524 on PyPI
Alternatives
Verify before relying
from cached_method import cached_method
class Example:
@cached_method(maxsize=2)
def expensive_method(self, arg):
return arg * 2
obj = Example()
result = obj.expensive_method(arg)- Whether the package works correctly with modern Python versions despite being unmaintained since 2021.
- Performance characteristics compared to functools.lru_cache in typical use cases.
- Thread-safety guarantees when methods are called concurrently with identical arguments.
What it is and what it does
cached_method is a decorator that caches method results on a per-instance basis, similar to functools.cached_property but for methods with arguments. Unlike functools.lru_cache applied directly to methods, it does not require the containing class to be hashable, and it does not maintain a global cache that extends object lifetimes. This is particularly useful for classes managing scarce resources like GPU memory, where you want objects and their caches to be garbage-collected together.
The decorator closely mirrors functools.cached_property's implementation but omits internal locking, accepting the possibility of redundant method calls in multi-threaded contexts when equivalent arguments are used simultaneously. It also supports caching expensive operations like __hash__ without requiring the object itself to be hashable for cache lookups.
Use it for
- Cache expensive GPU operations in tensor-based classes where immediate garbage collection matters.
- Memoize method results for non-hashable objects without polluting a global cache.
- Cache __hash__ computations for objects that perform costly transfers between devices.
- Reduce redundant computation in methods called repeatedly with the same arguments within an instance.
- Manage memory-intensive resources that should be freed when their owning object is deleted.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need per-instance method caching for non-hashable classes or resource-intensive objects.
The code is simple and stable, but be aware the package is unmaintained since 2021-10-31—verify compatibility with your Python version before relying on it in production. For small hashable objects where global caching is acceptable, the standard functools approach may be preferable.
Install
cached-method on PyPI
Before you install
Low install friction with no runtime dependencies. However, the package is abandoned—last release was 2021-10-31 with no updates since, though the repository remains public and the code is stable.
Requires Python >= 3.6.
License in practice
Licensed under MIT (permissive), so you may use, modify, and distribute freely with minimal restrictions.
Quickstart
from cached_method import cached_method
class Example:
@cached_method(maxsize=2)
def expensive_method(self, arg):
return arg * 2
obj = Example()
result = obj.expensive_method(arg)Verify before relying
- Whether the package works correctly with modern Python versions despite being unmaintained since 2021.
- Performance characteristics compared to functools.lru_cache in typical use cases.
- Thread-safety guarantees when methods are called concurrently with identical arguments.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >= 3.6 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | None |
| Maintenance | Abandoned 1,748 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 77,437 / month, #14,524 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: Python |
Evidence: cached_method-0.1.0-py3-none-any.whl
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See also propcache · methodtools · memoization · backports.cached-property · django-memoize · cachier · django-cache-memoize · cache-to-disk · klepto · weakrefmethod