Update rerun requirement from 0.31 to 0.32

[dependabot]

Updates the requirements on rerun to permit the latest version.

Release notes

Sourced from rerun's releases.

0.32.1

Rerun is an easy-to-use database and visualization toolbox for multimodal and temporal data. Try it live at https://rerun.io/viewer.

• Python: pip install -U rerun-sdk
• Rust: cargo add rerun and cargo install rerun-cli --locked
• Online demo: https://rerun.io/viewer
• C++ FetchContent: https://github.com/rerun-io/rerun/releases/download/0.31.1/rerun_cpp_sdk.zip

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🔎 Details

🪵 Log API

• Fix problem of intermixing different store messages in one rrd 5620f47

Changelog

Sourced from rerun's changelog.

0.32.1 - 2026-05-15

🔎 Details

🪵 Log API

• Fix problem of intermixing different store messages in one rrd 5620f47

0.32.0 - 2026-05-13 - Chunk Processing, Pytorch dataloader, Dataset Review

🧳 Migration guide: https://rerun.io/docs/reference/migration/migration-0-32

✨ Overview & highlights

Python chunk processing API

This release introduces a chunk processing API designed for systematic and efficient wrangling of robotics data. It includes:

• A Chunk object for inspecting, creating, and manipulating chunks.
• Readers for common file formats (RRD, MCAP, Parquet, URDF, and more to come) which output streams of chunks.
• A composable LazyChunkStream class to define memory-bounded chunk-based filtering and transformation pipelines.
• Lenses: an expressive and performant API to manipulate component data in chunks.
• A multithreaded, GIL-free, native engine for pipeline execution that is designed for distributed execution in the future.
• Interoperability with a catalog server and the Rerun SDK logging API.

In addition to enabling powerful data wrangling pipelines, the chunk processing API is significant for offering read/write chunk-level control of RRD files down to the raw Arrow data.

Note: this API is experimental and subject to breaking changes as we continue to improve it.

Experimental dataset review

You can now build tables of recording previews configured with arbitrary blueprints!

59636c2a3c79f0f4f543e353a87315ec416bdad8_datasetpreview.new.mp4

Clickable flags let you curate data directly from the table: toggles update a boolean flag column and are written back to the server.

To try it out, enable the experimental options in the Viewer's settings and try the two Python examples: table_grid_with_flags for basic grids with clickable flags, and table_blueprints for the full preview experience.

Limitations, or why this is still experimental:

• previews don't yet work directly on raw datasets; you have to send a special table to the server instead (see examples)
• table blueprints are currently text-encoded in table metadata, this is subject to change
• depending on the number and content of previews, overall runtime performance can be poor, especially in the browser
• many UX details are still unfinished

Experimental state timeline view

A new experimental view for visualizing discrete state transitions over time as horizontal colored lanes, useful for state machines, mode transitions, and similar discrete signals. Log state changes with the new StateChange archetype; configure their display on the UI or using StateConfiguration in the blueprint API.

... (truncated)

Commits

• a106a51 Use newer export from sim
• 02d694f Bump versions to 0.32.1
• 4ca331f Fix parsing griffe output for classes that are empty so have no members
• 96097e1 Bump versions to 0.32.1-rc.1
• 54e060a Fix links in Chunk docs, part 2
• 728f0d8 Updates the changelog
• 5620f47 Fix problem of intermixing different store messages in one rrd
• 296e486 Adding overview to Getting Started
• c7494b7 Fix links in Chunk docs
• aa72dad Fix code formating in d2 diagram
• Additional commits viewable in compare view

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