Package Health Score

50 / 100

security
Security review needed
popularity
Limited
maintenance
Sustainable
community
Limited

Popularity

Limited

GitHub Stars: 46
Forks: 10
Contributors: 2

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package nextorch, we found that it has been starred 46 times.

Security

Security review needed

Security and license risk for latest version

Release Date: Dec 12, 2023
Direct Vulnerabilities: 0
C
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

Sustainable

Commit Frequency

Open Issues: 4
Open PR: 0
Last Release: 12 months ago
Last Commit: 12 months ago

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

We found that nextorch demonstrates a positive version release cadence with at least one new version released in the past 12 months.

In the past month we didn't find any pull request activity or change in issues status has been detected for the GitHub repository.

Community

Limited

Readme: Yes
Contributing.md: No
Code of Conduct: No
Contributors: 2
Funding: No

This project has seen only 10 or less contributors.

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Package

Python Versions Compatibility: >=3.7

Age: 4 years
Latest Release: 12 months ago
Dependencies: N/A
Versions: 11
Maintainers: 2
Wheels: No

Readme

NEXTorch

NEXTorch is an open-source software package in Python/PyTorch to faciliate experimental design using Bayesian Optimization (BO).

NEXTorch stands for Next EXperiment toolkit in PyTorch/BoTorch. It is also a library for learning the theory and implementation of Bayesian Optimization.

Documentation

See our documentation page for examples, equations used, and docstrings.

Developers

Yifan Wang ()
Tai-Ying (Chris) Chen

Dependencies

Python >= 3.7
PyTorch <= 1.8: Used for tensor operations with GPU and autograd support
GPyTorch <= 1.4: Used for training Gaussian Processes
BoTorch <= 0.4.0: Used for providing Bayesian Optimization framework
Matplotlib: Used for generating plots
PyDOE2: Used for constructing experimental designs
Numpy: Used for vector and matrix operations
Scipy: Used for curve fitting
Pandas: Used to import data from Excel or CSV files
openpyxl: Used by Pandas to import Excel files
pytest: Used for unit tests

Getting Started

Install using pip (see documentation for full instructions):
```
pip install nextorch
```
Run the unit tests.
Read the documentation for tutorials and examples.

License

This project is licensed under the MIT License - see the LICENSE.md. file for details.

Contributing

If you have a suggestion or find a bug, please post to our Issues page on GitHub.

Questions

If you are having issues, please post to our Issues page on GitHub.

Funding

This material is based upon work supported by the Department of Energy's Office of Energy Efficient and Renewable Energy's Advanced Manufacturing Office under Award Number DE-EE0007888-9.5.

Acknowledgements

Jaynell Keely (Logo design)

Publications

Y. Wang, T.-Y. Chen, and D.G. Vlachos, NEXTorch: A Design and Bayesian Optimization Toolkit for Chemical Sciences and Engineering, J. Chem. Inf. Model. 2021, 61, 11, 5312–5319.

FAQs

What is nextorch?

Experimental design and Bayesian optimization library in Python/PyTorch. Visit Snyk Advisor to see a full health score report for nextorch, including popularity, security, maintenance & community analysis.

Is nextorch popular?

The python package nextorch receives a total of 79 weekly downloads. As such, nextorch popularity was classified as limited. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is nextorch well maintained?

We found indications that nextorch maintenance is sustainable demonstrating some project activity. We saw a total of 2 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is nextorch safe to use?

While scanning the latest version of nextorch, we found that a security review is needed. A total of 0 vulnerabilities or license issues were detected. See the full security scan results.

Last updated on 11 November-2024, at 17:33 (UTC).

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nextorch

Experimental design and Bayesian optimization library in Python/PyTorch For more information about how to use this package see README

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Package Health Score

Popularity

Direct Usage Popularity

Security

Security and license risk for latest version

Maintenance

Commit Frequency

Community

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Package

Readme

NEXTorch

Documentation

Developers

Dependencies

Getting Started

License

Contributing

Questions

Funding

Acknowledgements

Publications

FAQs

What is nextorch?

Is nextorch popular?

Is nextorch well maintained?

Is nextorch safe to use?

Build a secure application checklist

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Package Health Score

Direct Usage Popularity

Security and license risk for latest version

Commit Frequency

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Readme

NEXTorch

Documentation

Developers

Dependencies

Getting Started

License

Contributing

Questions

Funding

Acknowledgements

Publications

FAQs

What is nextorch?

Is nextorch popular?

Is nextorch well maintained?

Is nextorch safe to use?

Build a secure application checklist

Select a recommended open source package

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Source Code

Open Source

Container

Config

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