Welcome to issue 55 of Python Weekly. This week's issue is packed with lot of great content. Enjoy it!
Articles, Tutorials and Talks
In this video, Guido Van Rossum talks about tips and tricks, the state of Python, and its bright future.
Skip list is a probabilistic data structure that allows efficient search, insertion and removal operations. This post shows you how to implement a simple version of the skip list in python.
In the latest exciting episode of From Python Import Podcast, we had the pleasure of sitting down with James Tauber (Pinax, Eldarion), Kenneth Reitz (Requests, The Hitchhiker's Guide to Python, Tablib), and Chad Whitacre (Gittip, Aspen) for an end-of-conference chat at PyOhio 2012.
Development of scientific software involves tradeoffs between ease of use, generality, and performance. This paper describe the design of a general hyperbolic PDE solver that can be operated with the convenience of MATLAB yet achieves efficiency near that of hand-coded Fortran and scales to the largest supercomputers. This is achieved by using Python for most of the code while employing automatically-wrapped Fortran kernels for computationally intensive routines, and using Python bindings to interface with a parallel computing library and other numerical packages.
A Python 3 tutorial series, which attempts to guide the prospective student through the development of "minimem" - a small memory match game.
Latent Semantic Analysis (LSA), also known as Latent Semantic Indexing (LSI) literally means analyzing documents to find the underlying meaning or concepts of those documents. If each word only meant one concept, and each concept was only described by one word, then LSA would be easy since there is a simple mapping from words to concepts.
Petri nets are a simple model of computation with a range of modelling applications that include chemical reaction networks, manufacturing processes, and population biology dynamics. They are graphs through which entities flow and have their types transformed. They also have far-reaching mathematical properties which are the subject of an extensive literature. This article introduces Petri nets and gives an expository presentation of a program to simulate them.
The goal of this article is to share simple coding patterns for effectively performing multiprocessing for geoprocessing. The article will cover relevant considerations and limitations, which are important when attempting to implement this approach.
If you're looking to get your feet wet when it comes to working with open U.S. government data, I can think of no better place to start than with the Sunlight Laps APIs. They're not kidding when they say that using their APIs is absurdly easy.
If you are an experienced Rails developer this article will help you get started with building Django apps and help map Rails concepts to Django.
Interesting Projects, Tools and Libraries
Xpresser is a GUI automation tool written in Python, used to automate anything and everything.
A simple BDD testing framework for Python.
A small utility for easily switching multiple virtual environments and python installations
Compress, encrypt (symmetric encryption) and upload files directly to Amazon S3 in a single command. Can also be used as a python module.
Coverage.py measures code coverage, typically during test execution. It uses the code analysis tools and tracing hooks provided in the Python standard library to determine which lines are executable, and which have been executed.
Selfspy is a daemon for Unix/X11 that continuously monitors and stores what you are doing on your computer. This way, you can get all sorts of nifty statistics and reminders on what you have been up to.
facebewk is a clever little Python wrapper for the facebook Graph API.
Mmstats is a way to expose and read diagnostic values and metrics for applications. Think of mmstats as /proc for your application and the readers as procps utilities.
pyscale is a general purpose Python framework for writing highly scalable applications
New Releases
Python 3.3 includes a range of improvements of the 3.x series, as well as easier porting between 2.x and 3.x.
Upcoming Events and Webinars
In this hands-on webcast presented by Wes McKinney, author of "Python for Data Analysis", he will showcase a number of examples and you will receive an introduction to some of the most important tools in the Python language for:
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Data preparation
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Data analysis
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Data visualization
Join us at SunGard on October 9 for Heroku 101: a crash course on deploying Python applications to Heroku by special guest Kenneth Reitz. The feature talk will be followed by a round of lightning talks, including one about Requests, Kenneth's popular HTTP library.
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