proglearn

v0.0.7

A package to implement and extend the methods desribed in 'Omnidirectional Transfer for Quasilinear Lifelong Learning' For more information about how to use this package see README

Latest version published 3 years ago

License: MIT

PyPI

GitHub

Package Health Score

45 / 100

security
Security review needed
popularity
Limited
maintenance
Inactive
community
Sustainable

Popularity

Limited

GitHub Stars: 35
Forks: 42
Contributors: 40

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package proglearn, we found that it has been starred 35 times.

Security

Security review needed

Security and license risk for latest version

Release Date: Mar 17, 2022
Direct Vulnerabilities: 0
C
0
H
0
M
0
L
Indirect Vulnerabilities: 0
C
0
H
0
M
0
L
License Risk: 0
H
2
M
0
L

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

License

MIT

Security Policy

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Maintenance

Inactive

Commit Frequency

Open Issues: 45
Open PR: 10
Last Release: 3 years ago
Last Commit: 8 months ago

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

An important project maintenance signal to consider for proglearn is that it hasn't seen any new versions released to PyPI in the past 12 months, and could be considered as a discontinued project, or that which receives low attention from its maintainers.

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

Sustainable

Readme: Yes
Contributing.md: Yes
Code of Conduct: No
Contributors: 40
Funding: No

With more than 10 contributors for the proglearn 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 proglearn is missing a Code of Conduct.

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Package

Python Versions Compatibility: ==3.6.*, ==3.7.*, ==3.8.*, ==3.9.*

Age: 4 years
Latest Release: 3 years ago
Dependencies: 5 Direct / 47 Total
Versions: 8
Maintainers: 3
Wheels: OS Independent

Readme

ProgLearn

ProgLearn (Progressive Learning) is a package for exploring and using progressive learning algorithms developed by the neurodata group.

Installation Guide: http://proglearn.neurodata.io/install.html
Documentation: http://proglearn.neurodata.io
Tutorials: http://proglearn.neurodata.io/tutorials.html
Source Code: http://proglearn.neurodata.io/reference/index.html
Issues: https://github.com/neurodata/proglearn/issues
Contribution Guide: http://proglearn.neurodata.io/contributing.html

Some system/package requirements:

Python: 3.6+
OS: All major platforms (Linux, macOS, Windows)
Dependencies: tensorflow, scikit-learn, scipy, numpy, joblib

proglearn dependencies

joblib numpy scikit-learn scipy tensorflow

FAQs

What is proglearn?

A package to implement and extend the methods desribed in 'Omnidirectional Transfer for Quasilinear Lifelong Learning'. Visit Snyk Advisor to see a full health score report for proglearn, including popularity, security, maintenance & community analysis.

Is proglearn popular?

The python package proglearn receives a total of 76 weekly downloads. As such, proglearn popularity was classified as limited. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is proglearn well maintained?

We found indications that proglearn is an Inactive project. See the full package health analysis to learn more about the package maintenance status.

Is proglearn safe to use?

While scanning the latest version of proglearn, 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 29 November-2024, at 11:38 (UTC).

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