Package Health Score

60 / 100

security
Security review needed
popularity
Small
maintenance
Inactive
community
Active

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Popularity

Small

GitHub Stars: 7.85K
Forks: 1.35K
Contributors: 390

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package predictably, we found that it has been starred 7,853 times.

Security

Security review needed

Security and license risk for latest version

Release Date: Jul 15, 2020
Direct Vulnerabilities: 0
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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

BSD-3-Clause

Security Policy

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Maintenance

Inactive

Commit Frequency

Open Issues: 958
Open PR: 232
Last Release: 4 years ago
Last Commit: 1 month ago

Further analysis of the maintenance status of predictably 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 predictably 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

Active

Readme: Yes
Contributing.md: Yes
Code of Conduct: Yes
Contributors: 390
Funding: Yes

A good and healthy external contribution signal for predictably project, which invites more than one hundred open source maintainers to collaborate on the repository.

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Package

Python Versions Compatibility: ==3.*

Age: 4 years
Latest Release: 4 years ago
Dependencies: 4 Direct / 12 Total
Versions: 5
Maintainers: 1
Wheels: OS Independent

Readme

predict-ably

A Python module for time-series forecasting that seeks to provide high-level functionality similar to R's fable and forecast packages

Where functionality already exists in Python the goal is to provide a consistent API wrapper that fits with scikit-learn and standard forecasting practice.

To that extent, the project will leverage some of the code used in Alan-Turing Institute's sktime (https://github.com/alan-turing-institute/sktime).

Plan to add hierarchical reconciliation along the lines of:

predictably dependencies

numpy scikit-learn scipy statsmodels

FAQs

What is predictably?

Scikit-learn compatible Python forecasting module. Visit Snyk Advisor to see a full health score report for predictably, including popularity, security, maintenance & community analysis.

Is predictably popular?

The python package predictably receives a total of 56 weekly downloads. As such, predictably popularity was classified as small. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is predictably well maintained?

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

Is predictably safe to use?

While scanning the latest version of predictably, 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 18 November-2024, at 17:31 (UTC).

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predictably

Scikit-learn compatible Python forecasting module For more information about how to use this package see README

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predict-ably

predictably dependencies

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Readme

predict-ably

predictably dependencies

FAQs

What is predictably?

Is predictably popular?

Is predictably well maintained?

Is predictably safe to use?

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Source Code

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