Skip to main content

MAGMA Scenarios

Official robotic task scenarios and the shared scenario registry for MAGMA-GEN and MAGMA-BENCH. The package provides simulation environments, task definitions, presets, skills, and functions for discovering and loading scenarios from installed Python packages.

You can add your own scenarios in a separate package without modifying this repository or the generation pipeline.

Installation

Python 3.12 is required. Simulation installation has been checked on Linux x86_64.

python -m pip install "magma_scenarios==2.1.1"

This installs magma_core[simulation] and the simulation dependencies, including ManiSkill, SAPIEN, and PyTorch. Version 2.1.1 is a stable release of this package; it accepts MAGMA Core starting at 2.0.0b1, including subsequent stable v2 releases. GPU rendering requires suitable system drivers.

To install the release directly from GitHub:

python -m pip install "magma_scenarios @ git+https://github.com/MAGMA-rob/magma-scenarios.git@v2.1.1"

This installs the scenario code from GitHub and resolves dependencies from PyPI. For development, clone this repository and run python -m pip install -e ..

Discover and load scenarios

magma-scenarios list
magma-scenarios show press_button

The same registry is available in Python:

from magma_scenarios import get_scenario, list_scenarios, load_definition, load_preset

print(list_scenarios())
manifest = get_scenario("press_button")
definition_type = load_definition("press_button.Definition")
preset_type = load_preset("press_button.ButtonPressOrdered")

Listing scenarios and reading manifests do not start a simulator or register simulation environments. Loading a definition, preset, or skill registers its scenario's environments and returns the component class; it does not create an environment. Benchmarks can register an environment by ID with register_environment("PressButtonBasic-v1").

Included scenarios cover button pressing, sorting, delivery, table cleaning, laundry, coffee preparation, and packaging. Use magma-scenarios list to see all installed scenario providers.

Add your own scenarios

Please refer to the official documentation site

Development and support

Use magma-scenarios --help for all commands. test-tools and test-requests provide interactive checks for scenario implementations; see their --help for configuration options.

Report bugs through GitHub Issues or contact Loan Bernat.

Authors and license

Loan Bernat, with contributions from Abdelbasset Houdass (internship). Licensed under the BSD 2-Clause License.

Metadata

Release files for magma-scenarios 2.1.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for magma-scenarios 2.1.1
File Size Uploaded
magma_scenarios-2.1.1.tar.gz 22.8 MB Details

Built distribution (wheel)

Table of built distributions (wheels) for magma-scenarios 2.1.1
File Interpreter ABI Platform
magma_scenarios-2.1.1-py3-none-any.whl Python 3 none any Details

Total release size: 46.2 MB

Release files / magma_scenarios-2.1.1.tar.gz

Download URL magma_scenarios-2.1.1.tar.gz
Size 22.8 MB
Tags Source
SHA-256 checksum
How to use checksums
80c65a19cc3b046231295a14855ca76d92c71bf0e1434c0b5506dc7cd597a6b6
BLAKE2b-256 checksum
How to use checksums
ec93424a524bb043371bf13d0254eaab028c973292fe7d8585ad378e2df8b8bf
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 Oct 10, 2026.

Transparency log

Release files / magma_scenarios-2.1.1-py3-none-any.whl

Download URL magma_scenarios-2.1.1-py3-none-any.whl
Size 23.4 MB
Tags Python 3
SHA-256 checksum
How to use checksums
7a08b6158e8f3cd2891b1649f68c324215d5d3d3e3430dbd1d347fb705436494
BLAKE2b-256 checksum
How to use checksums
b066b07581bc8908fcf62fa8de8d0f7181952e6942debe4c515a14fe1211b13d
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 Oct 10, 2026.

Transparency log

Release history Release notifications | RSS feed

This release

2.1.1 This release

2 release files

2.1.0

2 release files

2.0.2

2 release files

2.0.1

2 release files

2.0.0

2 release 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