Package Health Score

66 / 100

security
No known security issues
popularity
Limited
maintenance
Healthy
community
Limited

Popularity

Limited

GitHub Stars: 42
Forks: 2
Contributors: 6

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package liesel, we found that it has been starred 42 times.

Security

No known security issues

Security and license risk for latest version

Release Date: Dec 10, 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

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Maintenance

Healthy

Commit Frequency

Open Issues: 44
Open PR: 6
Last Release: 11 days ago
Last Commit: 11 days ago

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

We found that liesel 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: 6
Funding: No

This project has seen only 10 or less contributors.

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Package

Python Versions Compatibility: >=3.10

Age: 3 years
Latest Release: 11 days ago
Dependencies: 0 Direct
Versions: 17
Maintainers: 0
Wheels: OS Independent

Readme

Liesel: A Probabilistic Programming Framework

Liesel is a probabilistic programming framework with a focus on semi-parametric regression. It includes:

Liesel, a library to express statistical models as Probabilistic Graphical Models (PGMs). Through the PGM representation, the user can build and update models in a natural way.
Goose, a library to build custom MCMC algorithms with several parameter blocks and MCMC kernels such as the No U-Turn Sampler (NUTS), the Iteratively Weighted Least Squares (IWLS) sampler, or different Gibbs samplers. Goose also takes care of the MCMC bookkeeping and the chain post-processing.
RLiesel, an R interface for Liesel which assists the user with the configuration of semi-parametric regression models such as Generalized Additive Models for Location, Scale and Shape (GAMLSS) with different response distributions, spline-based smooth terms and shrinkage priors.

The name "Liesel" is an homage to the Gänseliesel fountain, landmark of Liesel's birth city Göttingen.

Resources

FAQs

What is liesel?

A probabilistic programming framework with a focus on semi-parametric regression. Visit Snyk Advisor to see a full health score report for liesel, including popularity, security, maintenance & community analysis.

Is liesel popular?

The python package liesel receives a total of 268 weekly downloads. As such, liesel popularity was classified as limited. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is liesel well maintained?

We found that liesel demonstrated a healthy version release cadence and project activity. It has a community of 6 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is liesel safe to use?

The python package liesel 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 21 December-2024, at 22:23 (UTC).

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liesel

A probabilistic programming framework with a focus on semi-parametric regression For more information about how to use this package see README

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Package Health Score

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Readme

Liesel: A Probabilistic Programming Framework

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Is liesel well maintained?

Is liesel safe to use?

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Package Health Score

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Readme

Liesel: A Probabilistic Programming Framework

Resources

FAQs

What is liesel?

Is liesel popular?

Is liesel well maintained?

Is liesel safe to use?

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Source Code

Open Source

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Config

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