View dataheroes on Snyk Open Source Advisor

Package Health Score

66 / 100

security
No known security issues
popularity
Small
maintenance
Sustainable
community
Limited

Popularity

Small

GitHub Stars: 22
Forks: 7
Contributors: 9

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package dataheroes, we found that it has been starred 22 times.

Security

No known security issues

Security and license risk for latest version

Release Date: Dec 5, 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

Other/Proprietary License (Proprietary)

Security Policy

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Maintenance

Sustainable

Commit Frequency

Open Issues: 2
Open PR: 0
Last Release: 22 days ago
Last Commit: 1 month ago

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

We found that dataheroes 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

Limited

Readme: Yes
Contributing.md: No
Code of Conduct: No
Contributors: 9
Funding: No

This project has seen only 10 or less contributors.

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Package

Python Versions Compatibility: >=3.8

Age: 2 years
Latest Release: 22 days ago
Dependencies: 0 Direct
Versions: 24
Maintainers: 0
Wheels: Linux, macOS, Windows

Readme

DataHeroes

DataHeroes is a Python library that solves some of today’s biggest machine learning challenges: reducing the time, effort and resources required to develop and maintain high-quality machine learning models.

DataHeroes uses a unique methodology called Coresets, originating in computational geometry, to reduce the size of the dataset to a small subset that maintains the statistical properties and corner cases of the full dataset, such that solving a problem on the Coreset will yield the same result as solving it on the full dataset (to learn more about Coresets, visit our Introduction to Coresets page).

Website: https://dataheroes.ai
Getting started: https://dataheroes.ai/getting-started
Documentation: https://data-heroes.github.io/dh-library/
Tutorials: https://dataheroes.ai/tutorials/

FAQs

What is dataheroes?

DataHeroes - Build Better ML Models 10x Faster. Visit Snyk Advisor to see a full health score report for dataheroes, including popularity, security, maintenance & community analysis.

Is dataheroes popular?

The python package dataheroes receives a total of 6,008 weekly downloads. As such, dataheroes popularity was classified as small. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is dataheroes well maintained?

We found indications that dataheroes maintenance is sustainable demonstrating some project activity. We saw a total of 9 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is dataheroes safe to use?

The python package dataheroes 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 December-2024, at 03:40 (UTC).

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dataheroes

DataHeroes - Build Better ML Models 10x Faster For more information about how to use this package see README

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Readme

FAQs

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Source Code

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