Pyglet. Panda3D - Free 3D Game Engine. Gensim: Topic modelling for humans. Marisa-trie 0.6. Static memory-efficient & fast Trie-like structures for Python (based on marisa-trie C++ library) Static memory-efficient Trie-like structures for Python (2.x and 3.x).
String data in a MARISA-trie may take up to 50x-100x less memory than in a standard Python dict; the raw lookup speed is comparable; trie also provides fast advanced methods like prefix search. Based on marisa-trie C++ library. Note. Context Managers in Python. What are we going to talk about What is a Context Manager.How to use a Context Manager.How to write your own Context Manager.Few words about contextlib. 1.
Setting up Django with Nginx, Gunicorn, virtualenv, supervisor and PostgreSQL - Michał Karzyński. Django is an efficient, versatile and dynamically evolving web application development framework.
When Django initially gained popularity, the recommended setup for running Django applications was based around Apache with mod_wsgi. The art of running Django advanced and these days the recommended configuration is more efficient and resilient, but also more complex and includes such tools as: Nginx, Gunicorn, virtualenv, supervisord and PostgreSQL. In this text I will explain how to combine all of these components into a Django server running on Linux. Frameworks, microframeworks, too many choices. SampleApps - google-api-python-client - Google APIs Client Library for Python. Ad Exchange Buyer API Lets you manage your Ad Exchange Buyer account. Documentation for the Ad Exchange Buyer API in PyDoc AdSense Management API Gives AdSense publishers access to their inventory and the ability to generate reports Documentation for the AdSense Management API in PyDoc Google Analytics API View and manage your Google Analytics data Documentation for the Google Analytics API in PyDoc Enterprise Audit API Lets you access user activities in your enterprise made through various applications.
Documentation for the Enterprise Audit API in PyDoc Blogger API API for access to the data within Blogger. Documentation for the Blogger API in PyDoc Google Maps Coordinate API Lets you view and manage jobs in a Coordinate team. Documentation for the Google Maps Coordinate API in PyDoc CustomSearch API Lets you search over a website or collection of websites Documentation for the CustomSearch API in PyDoc APIs Discovery Service Documentation for the APIs Discovery Service in PyDoc. Creating a Development Environment with pip and virtualenv · zookeepr/zookeepr Wiki.
Creating a development environment using virtualenv(wrapper) and pip See also Development-Environment-in-5-minutes (using vagrant) Tested on Ubuntu 10.10 Steps.
Green Unicorn - Welcome. Mnot/thor at spdy. Web2py Web Framework. PyPy. CoderBuddy - Create and Publish Apps and Free Web Sites to Google App Engine Easily. Machine Vision made Easy - SimpleCV. 1. Kay tutorial — Kay v1.1.0 documentation. 1.1.
Preparation Install following stuff: Python-2.7.xApp Engine SDK/Python 1.6+Kay Frameworkipython (recommended) If you retreive Kay from the repository, you need to install also: mercurial You can retreive source code of Kay as follows. $ hg clone kay If you use released stable version, you can download the latest released tarball from and unpack it as follows: $ tar zxvf kay-VERSION.tar.gz If you have installed a zip version of appengine SDK, please create a symbolic link as follows: $ sudo ln -s /some/where/google_appengine /usr/local/google_appengine If you have used an installer of appengine SDK, you don’t need to create the symlink.
Kay-framework - A web framework made specifically for Google App Engine. Kay is a web framework made specifically for Google App Engin The basic design of Kay is based on the Django framework, like middleware, settings and pluggable application, etc.
Kay uses Werkzeug as lower level framework, Jinja2 as template engine, and babel for handling language translations. This software is distributed under BSD license. Welcome to Flask — Flask v0.8-dev documentation. Welcome to Flask’s documentation.
This documentation is divided into different parts. I recommend that you get started with Installation and then head over to the Quickstart. Besides the quickstart, there is also a more detailed Tutorial that shows how to create a complete (albeit small) application with Flask. If you’d rather dive into the internals of Flask, check out the API documentation. Common patterns are described in the Patterns for Flask section.
This is the Cython-based libfreenect Python wrappers. Python Kinect Webserver. Overview — PyGraphviz v1.1 documentation. 19.5. xml.parsers.expat — Fast XML parsing using Expat — Python v2.7.1 documentation. Warning The pyexpat module is not secure against maliciously constructed data.
If you need to parse untrusted or unauthenticated data see XML vulnerabilities. New in version 2.0. The xml.parsers.expat module is a Python interface to the Expat non-validating XML parser. Python and XML Processing: Other Software. Python API Tutorial for AllegroGraph 4.0. This is an introduction to the Python client API to AllegroGraph RDFStore™ version 4.2 from Franz Inc.
The Python Sesame API offers convenient and efficient access to an AllegroGraph server from a Python-based application. This API provides methods for creating, querying and maintaining RDF data, and for managing the stored triples. The Python Sesame API deliberately emulates the Aduna Sesame API to make it easier to migrate from Sesame to AllegroGraph.
The Python Sesame API has also been extended in ways that make it easier and more intuitive than the Sesame API. Contents. Graph. Graph Description In mathematics and computer science, graph theory studies networks of connected nodes and their properties. RDFLib. PyAIML (a.k.a. Program Y) - A Python AIML Interpreter. City in a Bottle. Category:Programming language:Python. Pydev. Trendrr/whirlwind - GitHub. Overview — Official Grok v1.2.1 documentation. Jaikuengine - Project Hosting on Google Code. JaikuEngine is a social microblogging platform that runs on AppEngine. JaikuEngine powers Jaiku.com. For the mobile client source, see: Jaiku Mobile client Dependencies Python 2.4 or 2.5 Docutils: Mox: version 0.5.1 Everything else should be included in the checkout via svn:externals.
If you're using Ubuntu you will need to install the pstats library which is in the python-profilers package. Quickstart Check out the repository (it's somewhat large due to image binaries): svn checkout jaikuengine Copy local_settings.example.py to local_settings.py Run the server with some test data pre-loaded: python manage.py testserver common/fixtures/*.json Browse to localhost:8080 and log in with popular/password Getting Running Jaiku uses the Django framework as well as most of its development process, so most actions go through manage.py. To run the development server: Visualization-python - Project Hosting on Google Code. Pebl-project - Project Hosting on Google Code. Update 11/15/2011 Pebl source code and issues are now hosted at This site is only for historical purposes.
Pebl is a python library and command line application for learning the structure of a Bayesian network given prior knowledge and observations. Pebl includes the following features: Can learn with observational and interventional data Handles missing values and hidden variables using exact and heuristic methods Provides several learning algorithms; makes creating new ones simple Has facilities for transparent parallel execution using several cluster/grid resources Calculates edge marginals and consensus networks Presents results in a variety of formats Pebl Documentation includes installation instructions, tutorial and API reference. Pebl has been developed at the Systems Biology Lab at the University of Michigan and is available with a permissive MIT-style license.
Update 3/6/2009. Shah09a. Pbnt.berlios. Bayesian-inference - Project Hosting on Google Code. This package is a collection of useful classes for basic Bayesian inference. Currently, its main goal is to be a tool for learning and exploration of Bayesian probabilistic calculations. Currently it also includes subpackages for stochastic simulation tools which are not strictly related to Bayesian inference, but are currently being developed within BIP. One such package is the BIP.SDE which contains a parallelized solver for stochastic differential equations, an implementation of the Gillespie direct algorithm. The Subpackage Bayes also offers a tool for parameter estimation of Deterministic and Stochastic Dynamical Models.
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