OopsieData Tools
Oopsie Data is an initative to build a large-scale dataset of real robot manipulation failures (along with other mixed-quality behaviors and successes). Oopsie Data Tools helps labs record, annotate, and contribute those rollouts instead of throwing them away.
Ready to contribute? Start with the Quickstart Guide.
For documentation, contribution instructions, and tooling guides, visit our website.
This repository currently provides tools for:
- HDF5 episode recording (
EpisodeRecorder) - Web annotation workflows
- In-the-loop annotation during policy rollout
as well as all the necessary utilities to validate, inspect, and upload Oopsie-Data to the official repositories.
Need help integrating?
Open an issue if you need help adding Oopsie Tools recording to your eval pipeline. Include your robot platform, policy stack, and a pointer to your evaluation/inference code.
Metadata
Release files for oopsie-data-tools 0.9.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| oopsie_data_tools-0.9.3.tar.gz | 2.4 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| oopsie_data_tools-0.9.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 2.6 MB
Release files / oopsie_data_tools-0.9.3.tar.gz
| Download URL | oopsie_data_tools-0.9.3.tar.gz |
|---|---|
| Size | 2.4 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
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Transparency logRelease files / oopsie_data_tools-0.9.3-py3-none-any.whl
| Download URL | oopsie_data_tools-0.9.3-py3-none-any.whl |
|---|---|
| Size | 210.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
7e5c31b66b18f151602757a5fd8665e3f6c35db19d11ce557c3c73a9c9975d65
|
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BLAKE2b-256 checksum How to use checksums |
66f6d273fbb403f8bed65985387961f1c5722d2a54c83c23ed8a181934324386
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Aug 20, 2026.
Transparency log