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backports.cached-property

cached_property() - computed once per instance, cached as attribute

With conditionsPyPI Python ModulesReleased Jun 2022509.4K downloads / moMIT LicensePure Python

Decision gist · record as of 2026-08-14

pure-Python wheel — backports.cached_property-1.0.2-py3-none-any.whl
v1.0.2 · released 2022-06-14 · Python >=3.6.0 · 1 runtime deps: typing

Yes, if you need cached_property on Python 3.6 or 3.7. The package is stable, permissively licensed, and has no known vulnerabilities. Dormant maintenance is acceptable here because the backport targets a fixed API from Python 3.8—there is little reason for it to change. If you are already on Python 3.8+, use the standard library instead.AI-flagged interpretation of the facts on this page — verify before relying

Before you install

  • Requires Python 3.6 or later.
  • Does not work with classes using __slots__ without __dict__, or with metaclasses.
  • Low install friction with a single wheel dependency.

License · maintenance · safety

MIT License (permissive) — MIT License (permissive) places no restrictions on use, modification, or distribution in proprietary or open-source projects.

last release 2022-06-14 (1522 days) · last repo commit 2023-11-22 · 15 stars

0 known vulnerabilities (OSV.dev, 2026-08-14) · 509,434 downloads/mo, #6,271 on PyPI

Verify before relying

pip install backports.cached-property

from backports.cached_property import cached_property

class DataSet:
    @cached_property
    def stdev(self):
        return statistics.stdev(self._data)
  • Whether dormant maintenance (last commit 2023-11-22) poses a risk for future Python versions beyond 3.9.
  • Real-world performance impact of caching overhead versus computation savings in typical use cases.
Same gist for agents: .md · .json

What it is and what it does

This package backports Python 3.8's cached_property descriptor to Python 3.6 and 3.7. It lets you decorate a method so its result is computed once and then stored as a regular instance attribute, avoiding recomputation on subsequent accesses. The decorator is useful for expensive computed properties that don't change during an instance's lifetime.

The implementation is minimal and closely follows Python 3.8's standard library version. It depends only on the typing module and installs as a single wheel with low friction. However, it has a known limitation: it requires instances to have a mutable __dict__ attribute, so it won't work with classes that define __slots__ without including __dict__, or with metaclasses.

Use it for

  • Add caching to expensive statistical computations in data analysis classes.
  • Backport cached_property to legacy codebases still running Python 3.6 or 3.7.
  • Cache derived attributes in immutable-like objects where recomputation is wasteful.
  • Simplify property definitions when you need both lazy evaluation and memoization.

Worth the install?

AI-flagged interpretation of the facts on this page. Verify before relying on it.

With conditions

Yes, if you need cached_property on Python 3.6 or 3.7.

The package is stable, permissively licensed, and has no known vulnerabilities. Dormant maintenance is acceptable here because the backport targets a fixed API from Python 3.8—there is little reason for it to change. If you are already on Python 3.8+, use the standard library instead.

Install

backports-cached-property on PyPI

Before you install

Low install friction with a single wheel dependency. Maintenance is dormant—last release was 2022-06-14 and no commits since 2023-11-22—but the package is marked Production/Stable and addresses a narrow, stable backport use case.

Requires Python 3.6 or later. Does not work with classes using __slots__ without __dict__, or with metaclasses.

License in practice

MIT License (permissive) places no restrictions on use, modification, or distribution in proprietary or open-source projects.

Quickstart

pip install backports.cached-property

from backports.cached_property import cached_property

class DataSet:
    @cached_property
    def stdev(self):
        return statistics.stdev(self._data)

Verify before relying

  • Whether dormant maintenance (last commit 2023-11-22) poses a risk for future Python versions beyond 3.9.
  • Real-world performance impact of caching overhead versus computation savings in typical use cases.

Package facts

LicenseMIT License permissive
Python supportSupports the current Python release >=3.6.0
Install frictionLow. Pure-Python wheel
Runtime dependencies
1 package
typing
MaintenanceDormant 1,522 days since the last release
Last repo commit
First released
Downloads509,434 / month, #6,271 on PyPI 30-day window, as of 2026-08-14
Known vulnerabilitiesNone known OSV.dev, checked 2026-08-14
Classifiers
Development Status :: 5 - Production/StableIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 3Programming Language :: Python :: 3.6Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Programming Language :: Python :: Implementation :: CPythonProgramming Language :: Python :: Implementation :: PyPyTopic :: Software Development :: Libraries :: Python Modules

Evidence: backports.cached_property-1.0.2-py3-none-any.whl

Tags

Capabilities
cached property decoratorproperty caching pythoncomputed property memoizationbackport cached_propertyinstance attribute cachingexpensive computation caching
Topics
backportperformance-optimization
PyPI keywords
cachingdevelopment

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See also lazy · property-manager · zope.cachedescriptors · propcache · cached_method · async-property · backports.functools-lru-cache · django-cache-memoize