{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/10"}],"enrichment":{"capability":"Provides a JAX-compatible wrapper around Python dataclasses that automatically registers them as pytrees and enables serialization, while supporting static fields and nested mutations.","skillfed_tags":["jax-integration","pytree-registration","immutable-dataclass"],"use_cases":["Define model parameters and state as frozen dataclasses in JAX neural network code, automatically compatible with jit and vmap.","Mark configuration fields as static to prevent JAX from recompiling when only non-array metadata changes.","Serialize and deserialize JAX model checkpoints via flax.serialization without manual pytree registration.","Modify deeply nested dataclass structures in a readable way using copy_and_mutate instead of chained dataclasses.replace() calls.","Use standard type checkers and IDE autocomplete on JAX dataclasses since the decorator matches the standard library API."],"what_it_does":"jax_dataclasses is a thin wrapper around Python's standard dataclasses that integrates them seamlessly into JAX's pytree system. It automatically registers decorated classes as pytree nodes, making them usable at JAX API boundaries (e.g., as function arguments to jitted code). The package adds support for marking fields as static\u2014meaning they are constant at compile time and won't be traced\u2014and enables serialization through flax.serialization.\n\nThe main value proposition is ergonomic: unlike hand-registering pytrees, you write normal dataclass syntax and get pytree behavior automatically. The package also provides copy_and_mutate(), a context manager that temporarily unfreezes nested dataclass structures for easier in-place modifications, addressing a common pain point when working with deeply nested immutable objects in JAX.","worth_installing":"Yes, if you are building JAX applications with structured state or model parameters. The package solves a real integration gap between Python dataclasses and JAX's pytree system with minimal overhead. Install friction is low and the MIT license is unrestrictive. The aging maintenance status (238 days since last release) is a minor concern but not a blocker\u2014the package is stable, unarchived, and has no known vulnerabilities."},"id":"jax-dataclasses","links":{"html":"https://skillfed.io/packages/jax-dataclasses","md":"https://skillfed.io/packages/jax-dataclasses.md","pypi":"https://pypi.org/project/jax-dataclasses/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2025-12-19","license_spdx":null,"license_treatment":"permissive","name":"jax-dataclasses","python_support":"supports_current","summary":"Dataclasses + JAX"},"popularity":{"monthly_downloads":103209,"position":12821,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.6.3"}