propcache
Accelerated property cache
Decision gist · record as of 2026-08-14
Yes. propcache is actively maintained, has no security vulnerabilities, zero runtime dependencies, low install friction, and is in the top 100 PyPI packages by download volume. The Apache-2.0 license is permissive. Install it if you need faster cached properties than functools.cached_property or require the under_cached_property variant for specific architectural reasons. The C extension is optional; pure-Python fallback works everywhere.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- C compiler and Python headers needed only if building from source on unsupported platforms; binary wheels available for Linux, Windows, and macOS.
- Low friction: pure wheel distribution with binary wheels for Linux, Windows, and macOS.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows use in proprietary and open-source projects without copyleft obligations or attribution requirements beyond license inclusion.
last release 2026-05-08 (98 days) · last repo commit 2026-08-10 · 37 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 587,094,457 downloads/mo, #61 on PyPI
Alternatives
Verify before relying
pip install propcache
from propcache import cached_property
class MyClass:
@cached_property
def expensive_value(self):
return compute_something()
obj = MyClass()
result = obj.expensive_value # computed once, cached thereafter- Performance improvement magnitude compared to functools.cached_property in typical workloads
- Whether under_cached_property's self._cache approach provides meaningful isolation benefits in practice
- Compatibility with property subclassing or descriptor protocol edge cases
What it is and what it does
propcache is a Python library that provides optimized cached-property decorators backed by a C extension. It offers two main decorators: cached_property, which mirrors the standard library's functools.cached_property, and under_cached_property, which stores cached values in self._cache instead of self.__dict__ and prevents __set__ from being called. The library is designed for Python 3.10 and later, with binary wheels available for Linux, Windows, and macOS.
The package solves the problem of expensive property computations that need to be cached efficiently. Instead of recomputing a property on every access, propcache caches the result after the first call. The C-extension implementation is significantly faster than pure Python, though a pure-Python fallback is available via environment variable or build configuration for platforms without prebuilt wheels. It has no runtime dependencies and integrates directly into class definitions as a decorator.
Use it for
- Cache expensive database queries or API calls in ORM models or data classes
- Optimize repeated calculations on object properties without manual cache management
- Use under_cached_property in frameworks where __dict__ pollution must be avoided
- Speed-critical applications where property access is a hot path in the call graph
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
propcache is actively maintained, has no security vulnerabilities, zero runtime dependencies, low install friction, and is in the top 100 PyPI packages by download volume. The Apache-2.0 license is permissive. Install it if you need faster cached properties than functools.cached_property or require the under_cached_property variant for specific architectural reasons. The C extension is optional; pure-Python fallback works everywhere.
Install
propcache on PyPI
Before you install
Low friction: pure wheel distribution with binary wheels for Linux, Windows, and macOS. Active maintenance with recent release. No runtime dependencies. Optional pure-Python fallback available via environment variable or PEP 517 config, though slower than compiled version.
Requires Python 3.10 or later. C compiler and Python headers needed only if building from source on unsupported platforms; binary wheels available for Linux, Windows, and macOS.
License in practice
Apache-2.0 permissive license allows use in proprietary and open-source projects without copyleft obligations or attribution requirements beyond license inclusion.
Quickstart
pip install propcache
from propcache import cached_property
class MyClass:
@cached_property
def expensive_value(self):
return compute_something()
obj = MyClass()
result = obj.expensive_value # computed once, cached thereafterVerify before relying
- Performance improvement magnitude compared to functools.cached_property in typical workloads
- Whether under_cached_property's self._cache approach provides meaningful isolation benefits in practice
- Compatibility with property subclassing or descriptor protocol edge cases
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | None |
| Maintenance | Actively maintained 98 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 587,094,457 / month, #61 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersLicense :: OSI Approved :: Apache Software LicenseProgramming Language :: CythonProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Internet :: WWW/HTTPTopic :: Software Development :: Libraries :: Python Modules |
Evidence: propcache-0.5.2-py3-none-any.whl
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See also backports.cached-property · cached_method · memoization · asyncache · async-property · django-cache-memoize · django-memoize · cachier