h2o-pysparkling-3.3

v3.46.0.6.post1

Sparkling Water integrates H2O's Fast Scalable Machine Learning with Spark For more information about how to use this package see README

Latest version published 7 days ago

License: Apache-2.0

PyPI

GitHub

Package Health Score

85 / 100

security
No known security issues
popularity
Popular
maintenance
Healthy
community
Active

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Popularity

Popular

GitHub Stars: 968
Forks: 360
Contributors: 50

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package h2o-pysparkling-3.3, we found that it has been starred 968 times.

Security

No known security issues

Security and license risk for latest version

Release Date: Nov 19, 2024
Direct Vulnerabilities: 0
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Indirect Vulnerabilities: 0
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License Risk: 0
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All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

Apache-2.0

Security Policy

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Maintenance

Healthy

Commit Frequency

Open Issues: 29
Open PR: 12
Last Release: 7 days ago
Last Commit: 8 days ago

Further analysis of the maintenance status of h2o-pysparkling-3.3 based on released PyPI versions cadence, the repository activity, and other data points determined that its maintenance is Healthy.

We found that h2o-pysparkling-3.3 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: No
Code of Conduct: Yes
Contributors: 50
Funding: No

With more than 10 contributors for the h2o-pysparkling-3.3 repository, this is possibly a sign for a growing and inviting community.

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Package

Python Versions Compatibility: ==3.10.*, ==3.7.*, ==3.8.*, ==3.9.*

Age: 2 years
Latest Release: 7 days ago
Dependencies: N/A
Versions: 25
Maintainers: 1
Wheels: No

Readme

PySparkling

This package contains complete functionality for training and scoring Sparkling Water/H2O-3 MOJO models. It's also possible to use this package for scoring with Driverless AI MOJO models.

PySparkling Documentation is hosted at our documentation page:

For Spark 3.5 -
For Spark 3.4 -
For Spark 3.3 -
For Spark 3.2 -
For Spark 3.1 -
For Spark 3.0 -
For Spark 2.4 -
For Spark 2.3 -

FAQs

What is h2o-pysparkling-3.3?

Sparkling Water integrates H2O's Fast Scalable Machine Learning with Spark. Visit Snyk Advisor to see a full health score report for h2o-pysparkling-3.3, including popularity, security, maintenance & community analysis.

Is h2o-pysparkling-3.3 popular?

The python package h2o-pysparkling-3.3 receives a total of 15,583 weekly downloads. As such, h2o-pysparkling-3.3 popularity was classified as a popular. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is h2o-pysparkling-3.3 well maintained?

We found that h2o-pysparkling-3.3 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 h2o-pysparkling-3.3 safe to use?

The python package h2o-pysparkling-3.3 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 22 November-2024, at 14:40 (UTC).

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