Package Health Score

77 / 100

security
Security review needed
popularity
Popular
maintenance
Sustainable
community
Active

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Popularity

Popular

GitHub Stars: 3.35K
Forks: 240
Contributors: 50

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package deepchecks, we found that it has been starred 3,350 times.

Security

Security review needed

Security and license risk for latest version

Release Date: Jan 31, 2024
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: 1
H
1
M
0
L

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

License

AGPL-3.0

Non-Permissive License

We noticed that this project uses a license which requires less permissive conditions such as disclosing the source code, stating changes or redistributing the source under the same license. It is advised to further consult the license terms before use.

Security Policy

We found a way for you to contribute to the project! Looks like deepchecks is missing a security policy.

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Maintenance

Sustainable

Commit Frequency

Open Issues: 247
Open PR: 43
Last Release: 3 months ago
Last Commit: 2 months ago

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

We found that deepchecks 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: Yes
Code of Conduct: Yes
Contributors: 50
Funding: No

With more than 10 contributors for the deepchecks repository, this is possibly a sign for a growing and inviting community.

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Package

Python Versions Compatibility: ==3.10.*, ==3.6.*, ==3.7.*, ==3.8.*, ==3.9.*

Age: 3 years
Latest Release: 3 months ago
Dependencies: 23 Direct / 96 Total
Versions: 56
Maintainers: 1
Wheels: OS Independent

Readme

build pkgVersion pyVersions

Deepchecks is a Python package for comprehensively validating your machine learning models and data with minimal effort. This includes checks related to various types of issues, such as model performance, data integrity, distribution mismatches, and more.

What Do You Need in Order to Start Validating?

Depending on your phase and what you wise to validate, you'll need a subset of the following:

Raw data (before pre-processing such as OHE, string processing, etc.), with optional labels
The model's training data with labels
Test data (which the model isn't exposed to) with labels
A model compatible with scikit-learn API that you wish to validate (e.g. RandomForest, XGBoost)

Deepchecks validation accompanies you from the initial phase when you have only raw data, through the data splits, and to the final stage of having a trained model that you wish to evaluate. Accordingly, each phase requires different assets for the validation. See more about typical usage scenarios and the built-in suites in the docs.

Installation

Using pip

pip install deepchecks #--upgrade --user

Using conda

conda install -c deepchecks deepchecks

FAQs

What is deepchecks?

Package for validating your machine learning model and data. Visit Snyk Advisor to see a full health score report for deepchecks, including popularity, security, maintenance & community analysis.

Is deepchecks popular?

The python package deepchecks receives a total of 20,394 weekly downloads. As such, deepchecks popularity was classified as a popular. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is deepchecks well maintained?

We found indications that deepchecks maintenance is sustainable demonstrating some project activity. We saw a total of 50 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is deepchecks safe to use?

While scanning the latest version of deepchecks, 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 1 May-2024, at 03:02 (UTC).

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deepchecks

Package for validating your machine learning model and data For more information about how to use this package see README

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Package Health Score

Explore Similar Packages

Popularity

Direct Usage Popularity

Security

Security and license risk for latest version

Non-Permissive License

Maintenance

Commit Frequency

Community

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Snyk Vulnerability Scanner

Package

Readme

What Do You Need in Order to Start Validating?

Installation

Using pip

Using conda

deepchecks dependencies

FAQs

What is deepchecks?

Is deepchecks popular?

Is deepchecks well maintained?

Is deepchecks safe to use?

Build a secure application checklist

Select a recommended open source package

Scan your app for vulnerabilities

Fix identified vulnerabilities

Monitor for new issues

Package Health Score

Explore Similar Packages

Direct Usage Popularity

Security and license risk for latest version

Commit Frequency

Embed Package Health Score Badge

Keep your project healthy

Check your requirements.txt

Snyk Vulnerability Scanner

Readme

What Do You Need in Order to Start Validating?

Installation

Using pip

Using conda

deepchecks dependencies

FAQs

What is deepchecks?

Is deepchecks popular?

Is deepchecks well maintained?

Is deepchecks safe to use?

Build a secure application checklist

Select a recommended open source package

Scan your app for vulnerabilities

Source Code

Open Source

Container

Config

Fix identified vulnerabilities

Monitor for new issues