jax-jumpy
Common backend for Jax or Numpy.
Decision gist · record as of 2026-08-14
Yes, if you are building libraries or environments that need to support both NumPy and JAX users without code duplication. The low install friction, active maintenance, permissive license, and zero known vulnerabilities make it a safe choice. Not necessary if you are already committed to a single backend or do not need optional acceleration.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- JAX is optional; without it, jax-jumpy falls back to NumPy.
- To use JAX acceleration, install with `pip install jax-jumpy[jax]`.
- Low friction install with only numpy as a required dependency; jax is optional.
License · maintenance · safety
permissive license (permissive) — Apache 2.0 permissive license allows commercial and private use with minimal restrictions; you must include a copy of the license and document any modifications you make.
last release 2023-03-17 (1246 days) · last repo commit 2026-08-03 · 56 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 96,724 downloads/mo, #13,197 on PyPI
Alternatives
Verify before relying
pip install jax-jumpy
import jax_jumpy as jp
import numpy as np
arr = jp.array([1, 2, 3])
result = jp.sum(arr)- Coverage of NumPy and JAX function implementations—documentation does not specify which functions are currently supported versus missing.
What it is and what it does
Jax-jumpy is a compatibility layer that lets you write code once and run it on either NumPy or JAX depending on what is installed and how the code is called. The core idea is to enable framework-agnostic libraries—particularly reinforcement learning environments like Gymnasium and PettingZoo—to work seamlessly with both standard NumPy arrays and JAX-accelerated versions without code duplication.
When you call a jax-jumpy function, it checks whether JAX is available and whether the inputs are JAX arrays or the function is JIT-compiled; if so, it runs the JAX version for acceleration. Otherwise it falls back to NumPy. This design lets you debug with plain NumPy (which is easier to inspect and step through) and deploy with JAX (for hardware acceleration) using the same codebase. The package currently supports a subset of NumPy and JAX functions, with some advanced features like `vmap` and `scan` available only when JAX is installed.
Use it for
- Write RL environment wrappers that work with both NumPy and JAX backends without duplicating logic.
- Debug numerical code in plain NumPy, then run it accelerated on GPU/TPU via JAX without code changes.
- Build libraries that optionally use JAX acceleration when available, falling back gracefully to NumPy.
- Implement array operations that automatically dispatch to the fastest available backend at runtime.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building libraries or environments that need to support both NumPy and JAX users without code duplication.
The low install friction, active maintenance, permissive license, and zero known vulnerabilities make it a safe choice. Not necessary if you are already committed to a single backend or do not need optional acceleration.
Install
jax-jumpy on PyPI
Before you install
Low friction install with only numpy as a required dependency; jax is optional. Repository is actively maintained with recent commits and no archived status, though the latest release was over a year ago.
JAX is optional; without it, jax-jumpy falls back to NumPy. To use JAX acceleration, install with `pip install jax-jumpy[jax]`.
License in practice
Apache 2.0 permissive license allows commercial and private use with minimal restrictions; you must include a copy of the license and document any modifications you make.
Quickstart
pip install jax-jumpy
import jax_jumpy as jp
import numpy as np
arr = jp.array([1, 2, 3])
result = jp.sum(arr)Verify before relying
- Coverage of NumPy and JAX function implementations—documentation does not specify which functions are currently supported versus missing.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.7 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagenumpy |
| Maintenance | Actively maintained 1,246 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 96,724 / month, #13,197 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 :: DevelopersIntended Audience :: Science/ResearchLicense :: OSI Approved :: Apache Software LicenseProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Topic :: Scientific/Engineering :: Artificial Intelligence |
Evidence: jax_jumpy-1.0.0-py3-none-any.whl
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See also jax · jaxlib · jax-cuda12-pjrt · jax-cuda12-plugin · jax-cuda13-pjrt · jax-cuda13-plugin · jaxellip · chex · torchax · numpyro