SEF_lab

by dKosarevsky Python Version: Current License: Non-SPDX

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | SEF_lab Summary

SEF_lab is a Python library. SEF_lab has no bugs, it has no vulnerabilities, it has build file available and it has low support. However SEF_lab has a Non-SPDX License. You can download it from GitHub.

SEF_lab

Support

Quality

Security

License

Reuse

Support

SEF_lab has a low active ecosystem.

It has 0 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

SEF_lab has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of SEF_lab is current.

Quality

SEF_lab has no bugs reported.

Security

SEF_lab has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

SEF_lab has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

SEF_lab releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

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SEF_lab Key Features

No Key Features are available at this moment for SEF_lab.

SEF_lab Examples and Code Snippets

No Code Snippets are available at this moment for SEF_lab.

Community Discussions

No Community Discussions are available at this moment for SEF_lab.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install SEF_lab

You can download it from GitHub.
You can use SEF_lab like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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