NP_Complete_Approximation | Approximation algorithms to find a close to optional

by philipp-kurz Python Version: Current License: No License

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kandi X-RAY | NP_Complete_Approximation Summary

NP_Complete_Approximation is a Python library. NP_Complete_Approximation has no bugs, it has no vulnerabilities and it has low support. However NP_Complete_Approximation build file is not available. You can download it from GitHub.

Approximation algorithms to find a close to optional solution for 1000 inputs to an NP Complete problem. Final project for CS170 - "Efficient Algorithms and Intractable Problems" at UC Berkeley during the Spring 2020 semester.

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Support

NP_Complete_Approximation 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.

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

It has a neutral sentiment in the developer community.

The latest version of NP_Complete_Approximation is current.

Quality

NP_Complete_Approximation has no bugs reported.

Security

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

License

NP_Complete_Approximation does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

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

NP_Complete_Approximation has no build file. You will be need to create the build yourself to build the component from source.

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NP_Complete_Approximation Key Features

No Key Features are available at this moment for NP_Complete_Approximation.

NP_Complete_Approximation Examples and Code Snippets

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Community Discussions

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Vulnerabilities

No vulnerabilities reported

Install NP_Complete_Approximation

You can download it from GitHub.
You can use NP_Complete_Approximation 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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