---
id: einops
version: "0.8.2"
license: MIT
license_treatment: permissive
maintenance: active
---

# einops — A new flavour of deep learning operations

License: permissive · Maintenance: active · Popularity: top 1,000 on PyPI

## Install

pip install einops
uv add einops
poetry add einops

## Description

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# einops 
[![Run tests](https://github.com/arogozhnikov/einops/actions/workflows/run_tests.yml/badge.svg)](https://github.com/arogozhnikov/einops/actions/workflows/run_tests.yml)
[![PyPI version](https://badge.fury.io/py/einops.svg)](https://badge.fury.io/py/einops)
[![Documentation](https://img.shields.io/badge/documentation-link-blue.svg)](https://einops.rocks/)
![Supported python versions](https://raw.githubusercontent.com/arogozhnikov/einops/main/docs/resources/python_badge.svg)


Flexible and powerful tensor operations for readable and reliable code. <br />
Supports numpy, pytorch, tensorflow, jax, and...

## AI interpretation — verify before relying

Einops provides readable tensor operations (rearrange, reduce, repeat, pack, unpack, einsum) that work across numpy, PyTorch, TensorFlow, JAX, and other frameworks, making multidimensional array manipulation explicit and maintainable.

Verdict: Einops is a mature, well-maintained library with zero security vulnerabilities and permissive MIT licensing. Its zero runtime dependencies and low install friction make it a low-risk addition to any project. Active development and broad framework support make it a reliable choice for readable tensor operations.

[View on SkillFed](https://skillfed.io/packages/einops) · [View on PyPI](https://pypi.org/project/einops/)