Numpy_Numexpr_benchmark | without Numexpr

by cayetanobv Python Version: Current License: GPL-2.0

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kandi X-RAY | Numpy_Numexpr_benchmark Summary

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

#Benchmark: Numpy with Numexpr and without Numexpr (and with/without multiprocessing). This a litle benchmark between Numpy with Numexpr and without Numexpr (and with/without multiprocessing). Numexpr is a fast numerical array expression evaluator for Python, NumPy, PyTables, pandas, bcolz and more: ##About author Developed by Cayetano Benavent. GIS Analyst at Geographica. ##License This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.

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Numpy_Numexpr_benchmark 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.

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

It has a neutral sentiment in the developer community.

The latest version of Numpy_Numexpr_benchmark is current.

Quality

Numpy_Numexpr_benchmark has 0 bugs and 0 code smells.

Security

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

Numpy_Numexpr_benchmark code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Numpy_Numexpr_benchmark is licensed under the GPL-2.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

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

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

It has 125 lines of code, 12 functions and 7 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

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Numpy_Numexpr_benchmark Key Features

No Key Features are available at this moment for Numpy_Numexpr_benchmark.

Numpy_Numexpr_benchmark Examples and Code Snippets

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Community Discussions

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Vulnerabilities

No vulnerabilities reported

Install Numpy_Numexpr_benchmark

You can download it from GitHub.
You can use Numpy_Numexpr_benchmark 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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