Library for structured information processing: parsing, interpreting, converting, etc.
Readme
Graph-talk is a library for structured data processing to solve tasks like parsing, interpreting, or converting in a simple and comprehensible manner.
The library uses 3 key concepts to achieve the goal: a graph-like representation of information and its processing; a dialog-like communication between the model and the process; and a handler-event approach to recognize the input messages.
.. contents:: Table of Contents
Check the docs_ for the documentation and examples_ folder for examples of lexing, interpreting, and converting using Graph-talk.
From pypi_::
$ pip install graph-talk
Easy_install::
$ easy_install graph-talk
Clone from github_::
$ git clone git://github.com/krvss/graph-talk.git
Setuptools::
$ cd graph-talk
$ sudo python setup.py install
Testing::
$ python setup.py test
Documentation with sphinx_::
$ sphinx-build -b html docs docs/html
If you're having problems using the project, make the issue_ at GitHub.
graph-talk is protected by Apache Software License. Check the LICENSE_ file for
details.
.. _LICENSE: https://github.com/krvss/graph-talk/blob/master/LICENSE .. _docs: https://pythonhosted.org/graph-talk/ .. _examples: https://github.com/krvss/graph-talk/tree/master/examples .. _github: https://github.com .. _pypi: http://pypi.python.org/pypi/graph-talk .. _issue: https://github.com/krvss/graph-talk/issues .. _sphinx: http://sphinx-doc.org/ .. _DOT: http://en.wikipedia.org/wiki/DOT_(graph_description_language)
FAQs
Library for structured information processing: parsing, interpreting, converting, etc.
We found that graph-talk demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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