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Welcome to Pythonect’s documentation. This documentation is divided into different parts. I recommend that you get started with Installation and then head over to the Tutorial. If you’d rather dive into the internals of Pythonect, check out the API Reference documentation.
Pythonect is dependent on one external library: the NetworkX graph library. This library is not documented here. If you want to dive into its documentation, check out the following link: NetworkX Documentation
Note
This is the main documentation for the Pythonect project. The contents of this site are automatically generated via Sphinx based on the Python docstrings throughout the code and the reStructuredText documents in the doc/ directory of the git repository. If you find an error in the documentation, please report it in the bug tracker here, or even better, submit a pull request!
This part of the documentation, which is mostly prose, begins with some background information about Pythonect, then focuses on step-by-step instructions for building applications with Pythonect.
If you are looking for information on a specific function, class or method, this part of the documentation is for you.
Design notes, legal information and changelog are here for the interested.
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Read this before you get started with Pythonect. This hopefully answers some questions about the purpose and goals of the project, and when you should or should not be using it.
Pythonect is a new, experimental, general-purpose dataflow programming language based on Python. It provides both a visual programming language and a text-based scripting language. The text-based scripting language aims to combine the quick and intuitive feel of shell scripting, with the power of Python. The visual programming language is based on the idea of a diagram with “boxes and arrows”.
The Pythonect interpreter (and reference implementation) is a free and open source software written completely in Python, and is available under the BSD license.
Pythonect, being a dataflow programming language, treats data as something that originates from a source, flows through a number of processing components, and arrives at some final destination. As such, it is most suitable for creating applications that are themselves focused on the “flow” of data. Perhaps the most readily available example of a dataflow-oriented applications comes from the realm of real-time signal processing, e.g. a video signal processor which perhaps starts with a video input, modifies it through a number of processing components (video filters), and finally outputs it to a video display.
As with video, other domain problems (e.g. image processing, data analysis, rapid prototyping, and etc.) can be expressed as a network of different components that are connected by a number of communication channels. The benefits, and perhaps the greatest incentives, of expressing a domain problem this way is scalability and parallelism. The different components in the network can be maneuvered to create entirely unique dataflows without necessarily requiring the relationship to be hardcoded. Also, the design and concept of components make it easier to run on distributed systems and parallel processors.
Continue to Installation or Tutorial
Pythonect works with Python version 2.6 and greater, but it will not work (yet) with Python 3. Dependencies are listed in setup.py and will be installed automatically as part of any of the techniques listed below.
Easiest way to install Pythonect is to use pip:
pip install Pythonect
And second to easiest is with easy_install:
easy_install Pythonect
Note
Using easy_install is discouraged. Why? Read here.
Regular development happens at our GitHub repository. Grabbing the cutting edge version might give you some extra features or fix some newly discovered bugs. We recommend not installing from the git repo unless you are actively developing Pythonect. To clone the git repository and install it locally:
git clone git://github.com/ikotler/pythonect.git
cd pythonect
python setup.py install
Alternatively, if you use pip, you can install directly from the git repository:
pip install \
git+git://github.com/ikotler/pythonect.git@master#egg=pythonect \
-r https://github.com/ikotler/pythonect/raw/master/doc/requirements.txt
Here you can see the full list of changes between each Pythonect release.
Ticket numbers in this file can be looked up by visiting http://github.com/ikotler/pythonect/issues/<number>
Release date: 22-Jul-2013
Release date: 24-Apr-2013
Release date: 16-Feb-2013
Release date: 03-Sep-2012
Release date: 09-Aug-2012
Release date: 14-Jul-2012
Release date: 20-Jun-2012
Release date: 27-May-2012
Release date: 30-Apr-2012
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This Python module provides the capability to parse and evaluate a string as Pythonect code
Parse the source into a directed graph (i.e. networkx.DiGraph)
Evaluate Pythonect code in the context of globals and locals.
globals: A dictionary. locals: Any mapping.