Package Health Score

74 / 100

security
No known security issues
popularity
Limited
maintenance
Sustainable
community
Active

Popularity

Limited

GitHub Stars: 137
Forks: 64
Contributors: 20

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package mlos-viz, we found that it has been starred 137 times.

Security

No known security issues

Security and license risk for latest version

Release Date: Aug 16, 2024
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

Yes

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Maintenance

Sustainable

Commit Frequency

Open Issues: 78
Open PR: 15
Last Release: 3 months ago
Last Commit: 1 month ago

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

We found that mlos-viz 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

Active

Readme: Yes
Contributing.md: Yes
Code of Conduct: Yes
Contributors: 20
Funding: No

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

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Package

Python Versions Compatibility: >=3.8

Age: 10 months
Latest Release: 3 months ago
Dependencies: 1 Direct
Versions: 5
Maintainers: 1
Wheels: OS Independent

Readme

mlos_viz

The mlos_viz module is an aid to visualizing experiment benchmarking and optimization results generated and stored by mlos_bench.

Its core API is mlos_viz.plot(experiment), initially implemented as a wrapper around dabl to provide a basic visual overview of the results, where experiment is an ExperimentData objected returned from the mlos_bench.storage layer APIs.

In the future, we plan to add more automatic visualizations, interactive visualizations, feedback to the mlos_bench experiment trial scheduler, etc.

It's available for pip install via the pypi repository at mlos-viz.

mlos-viz dependencies

matplotlib

FAQs

What is mlos-viz?

Visualization Python interface for benchmark automation and optimization results. Visit Snyk Advisor to see a full health score report for mlos-viz, including popularity, security, maintenance & community analysis.

Is mlos-viz popular?

The python package mlos-viz receives a total of 82 weekly downloads. As such, mlos-viz popularity was classified as limited. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is mlos-viz well maintained?

We found indications that mlos-viz maintenance is sustainable demonstrating some project activity. We saw a total of 20 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is mlos-viz safe to use?

The python package mlos-viz 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 25 November-2024, at 00:22 (UTC).

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mlos-viz

Visualization Python interface for benchmark automation and optimization results. 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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Readme

mlos_viz

mlos-viz dependencies

FAQs

What is mlos-viz?

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Is mlos-viz well maintained?

Is mlos-viz safe to use?

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Package Health Score

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Commit Frequency

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Readme

mlos_viz

mlos-viz dependencies

FAQs

What is mlos-viz?

Is mlos-viz popular?

Is mlos-viz well maintained?

Is mlos-viz safe to use?

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Source Code

Open Source

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Config

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