Simulator for queueing networks written in Python
Python
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Failed to load latest commit information.
docs
examples
queueing_tool
tests
.coveragerc
.gitignore
.travis.yml
LICENSE.txt
MANIFEST.in
README.rst
VERSION
requirements.txt
setup.cfg
setup.py

README.rst

Queueing-tool

Build Status Coverage Status Supported Python versions. MIT License

Queueing-tool is a package for simulating and analyzing networks. It is an event based simulator that uses queues to simulate congestion and waiting on the network that includes tools for visualizing network dynamics.

Documentation

The package documentation can be found at http://queueing-tool.readthedocs.org/.

Features

  • Fast simulation. Queueing-tool is designed to run very quickly; the core algorithms were written in cython.
  • Visualizations. There are several tools that allow you to easily view congestion and movement within your network. This includes ready made functions for animating network dynamics, while your simulations take place.
  • Full documentation. Every function and class is fully documented both online and in the docstrings.
  • Fast setup. The network is represented as a networkx graph. Queueing-tool networks allow for probabilistic routing, finite capacity queues, and different blocking protocols for analyzing loss networks.

Installation

Prerequisites: Queueing-tool runs on Python 2.7 and 3.3-3.5 and it requires networkx and numpy. If you want to plot, you will need to install matplotlib as well.

Installation: To install from PyPI use:

pip install queueing-tool

The above will automatically install networkx and numpy. If you want to install all optional packages, use:

pip install numpy matplotlib pygraphviz
pip install queueing-tool

After installation, import with something like:

import queueing_tool as qt

Bugs and issues

The issue tracker is at https://github.com/djordon/queueing-tool/issues. Please report any bugs or issue that you find there. Of course, pull requests are always welcome.

Copyright and license

Code and documentation Copyright 2014-2016 Daniel Jordon. Code released under the MIT license.