QueueSim | Python package for discrete event stochastic simulation

by A-Herzog Jupyter Notebook Version: 1.2 License: Apache-2.0

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

kandi X-RAY | QueueSim Summary

QueueSim is a Jupyter Notebook library. QueueSim has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

QueueSim is a Python package for discrete event stochastic simulation of queueing networks. For Kendall models the performance indicators can also be computed using Erlang and Allen Cunneen approximation formulas.

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Quality

Security

License

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Support

QueueSim has a low active ecosystem.

It has 2 star(s) with 1 fork(s). There are 1 watchers for this library.

It had no major release in the last 12 months.

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

It has a neutral sentiment in the developer community.

The latest version of QueueSim is 1.2

Quality

QueueSim has no bugs reported.

Security

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

License

QueueSim is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

QueueSim releases are available to install and integrate.

Installation instructions, examples and code snippets are available.

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QueueSim Key Features

No Key Features are available at this moment for QueueSim.

QueueSim Examples and Code Snippets

No Code Snippets are available at this moment for QueueSim.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install QueueSim

A PyPI package is not yet available. Just download and extract the zip package offered here. The zip package also includes some example files (as plain Python files and as Jupyter notebooks) describing the base functions.
If you are using a Python environment which can show Jupyter notebooks, open and run any from the example_*.ipynb files in this directory.
If you are using plain Python, open and run any from the example_*.py files in this directory.

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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