Package Health Score

78 / 100

security
No known security issues
popularity
Small
maintenance
Healthy
community
Active

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Popularity

Small

GitHub Stars: 418
Forks: 44
Contributors: 50

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package nimblephysics, we found that it has been starred 418 times.

Security

No known security issues

Security and license risk for latest version

Release Date: Dec 2, 2024
Direct Vulnerabilities: 0
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0
H
0
M
0
L
Indirect Vulnerabilities: 0
C
0
H
0
M
0
L
License Risk: 0
H
0
M
0
L

All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

MIT

Security Policy

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Maintenance

Healthy

Commit Frequency

Open Issues: 53
Open PR: 15
Last Release: 19 days ago
Last Commit: 19 days ago

Further analysis of the maintenance status of nimblephysics based on released PyPI versions cadence, the repository activity, and other data points determined that its maintenance is Healthy.

We found that nimblephysics demonstrates a positive version release cadence with at least one new version released in the past 3 months.

As a healthy sign for on-going project maintenance, we found that the GitHub repository had at least 1 pull request or issue interacted with by the community.

Community

Active

Readme: Yes
Contributing.md: Yes
Code of Conduct: No
Contributors: 50
Funding: No

With more than 10 contributors for the nimblephysics repository, this is possibly a sign for a growing and inviting community.

We found a way for you to contribute to the project! Looks like nimblephysics is missing a Code of Conduct.

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Package

Python Versions Compatibility: Unspecified

Age: 1 year
Latest Release: 19 days ago
Dependencies: 2 Direct
Versions: 25
Maintainers: 0
Wheels: macOS

Readme

Stanford Nimble Logo

Stanford Nimble

pip3 install nimblephysics

** BETA SOFTWARE **

Read our docs and the paper.

Use physics as a non-linearity in your neural network. A single timestep, nimble.timestep(state, controls), is a valid PyTorch function.

Forward pass illustration

We support an analytical backwards pass, that works even through contact and friction.

Backpropagation illustration

It's as easy as:

from nimble import timestep

# Everything is a PyTorch Tensor, and this is differentiable!!
next_state = timestep(world, current_state, control_forces)

Nimble started life as a fork of the popular DART physics engine, with analytical gradients and a PyTorch binding. We've worked hard to maintain as much backwards compatability as we can, so many simulations that worked in DART should translate directly to Nimble.

Check out our website for more information.

Installing on Arm64 Macs (M1, M2, etc)

We don't yet publish Arm64 binaries to PyPI from our CI system, so you may not be able to pip3 install nimblephysics from a new Arm64 Mac. We will endeavor to manually push binaries occassionally, but until GitHub Actions supports using Arm64 Mac runners, that may run a bit behind.

Currently, the pre-built Arm64 binaries are ONLY AVAILABLE ON PYTHON 3.9. So if you create a virtual environment with Python 3.9, and then pip3 install nimblephysics, that should work.

If you really need another Python version for some reason, the solution is to clone this repo, then run

ci/mac/install_dependencies.sh
ci/mac/manually_build_arm64_wheels.sh That will install the dependencies you need, and then build and install the Python package. Please create Issues if you run into problems, and we'll do our best to fix them.

nimblephysics dependencies

numpy torch

FAQs

What is nimblephysics?

A differentiable fully featured physics engine. Visit Snyk Advisor to see a full health score report for nimblephysics, including popularity, security, maintenance & community analysis.

Is nimblephysics popular?

The python package nimblephysics receives a total of 2,883 weekly downloads. As such, nimblephysics popularity was classified as small. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is nimblephysics well maintained?

We found that nimblephysics demonstrated a healthy version release cadence and project activity. It has a community of 50 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is nimblephysics safe to use?

The python package nimblephysics was scanned for known vulnerabilities and missing license, and no issues were found. Thus the package was deemed as safe to use. See the full health analysis review.

Last updated on 20 December-2024, at 13:54 (UTC).

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nimblephysics

A differentiable fully featured physics engine For more information about how to use this package see README

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Readme

Stanford Nimble

Installing on Arm64 Macs (M1, M2, etc)

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Readme

Stanford Nimble

Installing on Arm64 Macs (M1, M2, etc)

nimblephysics dependencies

FAQs

What is nimblephysics?

Is nimblephysics popular?

Is nimblephysics well maintained?

Is nimblephysics safe to use?

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