Skip to main content

Rerun

The data layer for physical AI

The data primitives to build, understand, and improve your data loop. Designed for multi-rate, multimodal data, from the first recording to massive scale.

The open source Rerun Python SDK provides a single toolchain to log, transform, query, view, and train on multi-rate, multimodal data.

Install

pip install rerun-sdk

The Python module is called rerun, while the package published on PyPI is rerun-sdk.

See Install Rerun for the Viewer and other SDK languages.

We also provide a Jupyter widget for interactive data visualization in Jupyter notebooks:

pip install rerun-sdk[notebook]

Example

import numpy as np
import rerun as rr

rr.init("rerun_example_app", spawn=True)

positions = np.vstack([xyz.ravel() for xyz in np.mgrid[3 * [slice(-5, 5, 10j)]]]).T
colors = np.vstack([rgb.ravel() for rgb in np.mgrid[3 * [slice(0, 255, 10j)]]]).astype(np.uint8).T

rr.log("points3d", rr.Points3D(positions, colors=colors))

Resources

Logging and viewing in different processes

The Viewer and Python logger can run in separate processes. Start the Viewer in one terminal:

python3 -m rerun

In a second terminal, run the example with the --connect option:

python3 examples/python/plots/plots.py --connect

Note that SDK and Viewer can run on different machines! See SDK operating modes for connection options.

Building Rerun from source

Rerun uses pixi for development tools and tasks. Install pixi, clone the repository, and run these commands from its rerun/ directory.

Build and install a development version of the Python SDK:

pixi run py-build

For an optimized build, use:

pixi run py-build-release

Run an example in the development environment:

pixi run uvpy examples/python/minimal/minimal.py

Build a wheel for manual installation:

pixi run py-build-wheel

See BUILD.md for all Viewer and SDK build options.

Installing a pre-release

Development wheels built from the latest main branch are available from the prerelease release. The main branch can be unstable, so use these wheels at your own risk.

Running Python unit tests

Run the full Python test suite:

pixi run py-test

Build the SDK and run one test file:

pixi run py-build && pixi run uvpy -m pytest rerun_py/tests/unit/test_tensor.py

Profiling the Python SDK

Install puffin_viewer, then set RERUN_PUFFIN=1 when you start a Python program:

cargo install puffin_viewer
RERUN_PUFFIN=1 pixi run uvpy your_script.py

Save a recording from the viewer for offline analysis (use the investigate-puffin skill in .claude/skills/).

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

rerun_sdk-0.37.1-cp310-abi3-win_amd64.whl (140.6 MB view details)

Uploaded CPython 3.10+Windows x86-64

rerun_sdk-0.37.1-cp310-abi3-manylinux_2_28_x86_64.whl (163.1 MB view details)

Uploaded CPython 3.10+manylinux: glibc 2.28+ x86-64

rerun_sdk-0.37.1-cp310-abi3-manylinux_2_28_aarch64.whl (157.8 MB view details)

Uploaded CPython 3.10+manylinux: glibc 2.28+ ARM64

rerun_sdk-0.37.1-cp310-abi3-macosx_11_0_arm64.whl (147.5 MB view details)

Uploaded CPython 3.10+macOS 11.0+ ARM64

File details

Details for the file rerun_sdk-0.37.1-cp310-abi3-win_amd64.whl.

File metadata

File hashes

Hashes for rerun_sdk-0.37.1-cp310-abi3-win_amd64.whl
Algorithm Hash digest
SHA256 ca21e1c105c3fb8eeb4c8170c836c8f3c005576bb912b204c8d737025dd882f4
MD5 16da46315baeacdca5b8d485ef6989a1
BLAKE2b-256 0de71e23613080a4a30d0a5a7ee35f47f93ff7740571c2100d9865830dfea576

See more details on using hashes here.

File details

Details for the file rerun_sdk-0.37.1-cp310-abi3-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for rerun_sdk-0.37.1-cp310-abi3-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 2a9cdd8172090b967103b855e9c210e56d151fe345980a3771c0087e2450c8eb
MD5 338e8f59f8b97a1d0f0e8d3e2847ef3b
BLAKE2b-256 ae461c14e5bf09a99f5737449df11f79b8a52893b7e4f1d2c131719bd24e4787

See more details on using hashes here.

File details

Details for the file rerun_sdk-0.37.1-cp310-abi3-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for rerun_sdk-0.37.1-cp310-abi3-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 07a72ec98f930316efb5c6197c2c815c6336c8a53e86119717014dcb00eeabc4
MD5 a5dc5257635987d412a138232767670c
BLAKE2b-256 fec640894ec15c0f0aba254c89ff47b10c26b62cbb9d9f58d275624ddc310ca7

See more details on using hashes here.

File details

Details for the file rerun_sdk-0.37.1-cp310-abi3-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for rerun_sdk-0.37.1-cp310-abi3-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 ebf84ded4a9e0883e5c206cba12c985d72a1fa07d21f17ce8d1b03a2394a10b7
MD5 b2f2d7d9059aa4ae9d2dcdab44e792e6
BLAKE2b-256 3d5c27f04c7c4de0de32ca847627c01f03a450d6ba9fd1a3f16c8e2bbb5a059d

See more details on using hashes here.

Release history Release notifications | RSS feed

This release

0.37.1 This release

4 files

0.37.0

4 files

0.36.3

4 files

0.36.2

4 files

0.36.1

4 files

0.36.0

4 files

0.35.0

4 files

0.34.1

4 files

0.34.0

4 files

0.33.1

4 files

0.33.0

4 files

0.32.2

4 files

0.32.1

4 files

0.32.0

4 files

0.31.4

4 files

0.31.3

4 files

0.31.2

4 files

0.31.1

4 files

0.31.0

4 files

0.30.2

4 files

0.30.1

4 files

0.30.0

4 files

0.29.2

4 files

0.29.1

4 files

0.29.0

4 files

0.28.2

4 files

0.28.1

4 files

0.28.0

4 files

0.27.3

4 files

0.27.2

4 files

0.27.1

4 files

0.27.0

4 files

0.26.2

5 files

0.26.1

5 files

0.26.0

5 files

0.25.1

5 files

0.25.0

5 files

0.24.1

5 files

0.24.0

5 files

0.23.4

5 files

0.23.3

5 files

0.23.2

5 files

0.23.1

5 files

0.23.0

5 files

0.22.1

5 files

0.22.0

5 files

0.21.0

5 files

0.20.3

5 files

0.20.2

5 files

0.20.1

5 files

0.20.0

5 files

0.19.1

5 files

0.19.0

5 files

0.18.2

5 files

0.18.1

5 files

0.18.0

5 files

0.17.0

5 files

0.16.1

5 files

0.16.0

5 files

0.15.1

5 files

0.15.0

5 files

0.14.1

4 files

0.14.0

4 files

0.13.0

4 files

0.12.1

4 files

0.12.0

4 files

0.11.0

4 files

0.10.1

4 files

0.10.0

4 files

0.9.1

4 files

0.9.0

4 files

0.8.2

4 files

0.8.1

4 files

0.8.0

4 files

0.7.0

4 files

0.6.0

4 files

0.5.1

4 files

0.5.0

4 files

0.4.0

4 files

0.3.1

4 files

0.3.0

4 files

0.2.0

3 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page