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recordclass

Mutable variant of namedtuple -- recordclass, which support assignments, compact dataclasses and other memory saving variants.

With conditionsPyPI Python ModulesReleased Jan 2026126.4K downloads / mopermissive licenseSource build

Decision gist · record as of 2026-08-14

sdist only — recordclass-0.24.tar.gz · builds from source
v0.24 · released 2026-01-05 · Python >=3.8

Yes, if you are building memory-sensitive applications with many small objects and can guarantee no circular references. The active maintenance, permissive license, and support for modern Python versions (3.8–3.14) make it reliable. However, the high install friction (source compilation required) and narrow use case (only beneficial when memory overhead of PyGC_Head is a real bottleneck) mean it is not a general-purpose replacement for dataclass or namedtuple—install only when profiling shows memory is a constraint.AI-flagged interpretation of the facts on this page — verify before relying

Before you install

  • Requires a C compiler and Python development headers to build from source; pre-built wheels may not be available for all platforms.
  • Installation requires compilation from source (high friction).
  • The package is actively maintained with recent commits and supports modern Python versions (3.8–3.14), but the build dependency may complicate deployment in restricted environments.

License · maintenance · safety

permissive license (permissive) — MIT License permits unrestricted use, modification, and distribution with minimal restrictions—suitable for both open-source and proprietary projects.

last release 2026-01-05 (221 days) · last repo commit 2026-07-20 · 37 stars

0 known vulnerabilities (OSV.dev, 2026-08-14) · 126,365 downloads/mo, #11,778 on PyPI

Verify before relying

from recordclass import recordclass, dataobject, astuple, asdict

# Factory function
Point = recordclass('Point', 'x y')
p = Point(1, 2)
p.y = -1
print(astuple(p))  # (1, -1)
print(asdict(p))   # {'x': 1, 'y': -1}

# Class-based
class Coord(dataobject):
    x: int
    y: int

c = Coord(3, 4)
print(c.x, c.y)
  • Whether pre-built wheels are available for common platforms or if source compilation is always required.
  • Actual memory savings in real-world applications compared to dataclass or __slots__ with typical field counts.
  • Whether the reference-cycle avoidance guarantee holds under all documented use patterns.
Same gist for agents: .md · .json

What it is and what it does

Recordclass is a library for creating lightweight, mutable record types in Python that avoid the memory overhead of standard dataclasses and namedtuples by opting out of cyclic garbage collection. It provides three main interfaces: a `recordclass` factory (namedtuple-like), a `dataobject` base class (dataclass-like), and lightweight container types (`litetuple`, `mutabletuple`) designed for scenarios where you are certain your objects will never participate in reference cycles.

The library is built on a custom metaclass that skips the `PyGC_Head` prefix normally added to Python objects, reducing per-instance memory by 16–32 bytes depending on Python version. This is most useful for applications that create many small, short-lived objects with simple field types (int, float, str, date/time), such as coordinate records, scientific data points, or compact data structures in memory-constrained environments. The trade-off is that you must manually ensure no circular references are created; the library does not enforce this at runtime.

Use it for

  • Store millions of coordinate or vector records (x, y, z) in memory-intensive scientific or graphics applications.
  • Build compact data structures for machine learning feature vectors where memory footprint directly impacts cache performance.
  • Replace namedtuple in high-throughput data pipelines where object creation speed and size matter.
  • Create immutable or mutable tuple-like containers (litetuple, mutabletuple) for collections that will never form cycles.
  • Define strongly-typed record classes with type hints that consume less memory than standard dataclass instances.

Worth the install?

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

With conditions

Yes, if you are building memory-sensitive applications with many small objects and can guarantee no circular references.

The active maintenance, permissive license, and support for modern Python versions (3.8–3.14) make it reliable. However, the high install friction (source compilation required) and narrow use case (only beneficial when memory overhead of PyGC_Head is a real bottleneck) mean it is not a general-purpose replacement for dataclass or namedtuple—install only when profiling shows memory is a constraint.

Install

recordclass on PyPI

Before you install

Installation requires compilation from source (high friction). The package is actively maintained with recent commits and supports modern Python versions (3.8–3.14), but the build dependency may complicate deployment in restricted environments.

Requires a C compiler and Python development headers to build from source; pre-built wheels may not be available for all platforms.

License in practice

MIT License permits unrestricted use, modification, and distribution with minimal restrictions—suitable for both open-source and proprietary projects.

Quickstart

from recordclass import recordclass, dataobject, astuple, asdict

# Factory function
Point = recordclass('Point', 'x y')
p = Point(1, 2)
p.y = -1
print(astuple(p))  # (1, -1)
print(asdict(p))   # {'x': 1, 'y': -1}

# Class-based
class Coord(dataobject):
    x: int
    y: int

c = Coord(3, 4)
print(c.x, c.y)

Verify before relying

  • Whether pre-built wheels are available for common platforms or if source compilation is always required.
  • Actual memory savings in real-world applications compared to dataclass or __slots__ with typical field counts.
  • Whether the reference-cycle avoidance guarantee holds under all documented use patterns.

Package facts

Licensepermissive license permissive
Python supportSupports the current Python release >=3.8
Install frictionHigh. Source build required
Runtime dependenciesNone
MaintenanceActively maintained 221 days since the last release
Last repo commit
First released
Downloads126,365 / month, #11,778 on PyPI 30-day window, as of 2026-08-14
Known vulnerabilitiesNone known OSV.dev, checked 2026-08-14
Classifiers
Development Status :: 4 - BetaIntended Audience :: DevelopersIntended Audience :: Science/ResearchLicense :: OSI Approved :: BSD LicenseOperating System :: OS IndependentProgramming Language :: CythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Topic :: Software Development :: Libraries :: Python Modules

Evidence: recordclass-0.24.tar.gz

Tags

Capabilities
mutable namedtuplememory-efficient dataclasslightweight record typescompact data structuresgc-free python objectsnamedtuple alternativeslot-like classes
Topics
memory-optimizationdata-structuresperformance-tuning
PyPI keywords
dataclassnamedtuplerecordclassdataobject

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See also namedlist · recordtype · dataclass-csv · tinsel · dataclass-factory · HeapDict · ordered-set · itemadapter · fields · dataclasses