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10 Reasons Python Rocks for Research — Hoyt Koepke

10 Reasons Python Rocks for Research — Hoyt Koepke
The following is an account of my own experience with Python. Because that experience has been so positive, it is an unabashed attempt to promote the use of Python for general scientific research and development. About four years ago, I dropped MATLAB in favor of Python as my primary language for coding research projects. This article is a personal account of how rewarding I have found that experience. As I describe in the next sections, the variety and quality of Python’s features has spoiled me. Even in small scripts, I now rely on Python’s numerous data structures, classes, nested functions, iterators, the flexible function calling syntax, an extensive kitchen-sink-included standard library, great scientific libraries, and outstanding documentation. Given these libraries, many features in MATLAB that enable one to quickly write code for machine learning and artificial intelligence – my primary area of research – are essentially a small subset of those found in Python. Readability gives

http://www.stat.washington.edu/~hoytak/blog/whypython.html

Introduction to Pyjamas, Part 1: Exploit the synergy of GWT and Python Introduction Google's Web Toolkit (GWT) lets you develop a Rich Internet Application (RIA) with Ajax, entirely in Java™ code. You can use the rich Java toolset (IDEs, refactoring, code completion, debuggers, and so on) to develop applications that can be deployed on all major Web browsers. With GWT you can write applications that behave like desktop applications but run in the browser.

Package Index : Theano 0.3.0 Optimizing compiler for evaluating mathematical expressions on CPUs and GPUs. Latest Version: 0.6.0 Theano is a Python library that allows you to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays. It is built on top of NumPy.

UC BerkeleyX: CS188.1x: Artificial Intelligence *Note - This is an Archived course* This is a past/archived course. At this time, you can only explore this course in a self-paced fashion. Certain features of this course may not be active, but many people enjoy watching the videos and working with the materials. Make sure to check for reruns of this course. CS188.1x is a new online adaptation of the first half of UC Berkeley's CS188: Introduction to Artificial Intelligence.

BeginnersGuide - PythonInfo Wiki New to programming? Python is free and easy to learn if you know where to start! This guide will help you to get started quickly. Rich Internet Applications (RIA) » Blog Archive » Slimmed Down Software- A Lean, Groovy Approach Part 5- Deliver Fast This article originally appeared in the August 2010 edition of GroovyMag, the Groovy and Grails magazine. Parts 6 and 7 are currently available for download from the magazine’s site, and more will come each month. Previous articles in this series are on the Canoo website: Part 1: Eliminate Waste, Part 2: Build Quality In, Part 3: Create Knowledge, and Part 4: Defer Commitment. Lastly, if you like this, you may want to check out some of my older blog posts from my personal site under the ‘craft’ category. Enjoy!

1. An Introduction to Distutils — Python v2.7 documentation This document covers using the Distutils to distribute your Python modules, concentrating on the role of developer/distributor: if you’re looking for information on installing Python modules, you should refer to the Installing Python Modules chapter. 1.1. Concepts & Terminology Using the Distutils is quite simple, both for module developers and for users/administrators installing third-party modules.

Google's Python Class - Educational Materials Welcome to Google's Python Class -- this is a free class for people with a little bit of programming experience who want to learn Python. The class includes written materials, lecture videos, and lots of code exercises to practice Python coding. These materials are used within Google to introduce Python to people who have just a little programming experience. The first exercises work on basic Python concepts like strings and lists, building up to the later exercises which are full programs dealing with text files, processes, and http connections. The class is geared for people who have a little bit of programming experience in some language, enough to know what a "variable" or "if statement" is.

Viewing Python 3.2 as the successor to Python 2.7 Over on python-dev a discussion kicked up over what to do about backward-incompatible changes against Python 2.7 in the name of fixing consistency. The suggestion seemed to be for a Python 2.8, but that is simply not going to happen. I think the reason the idea of Python 2.8 even came up is because I don't think people in general realize how python-dev views the latest and upcoming releases of Python, so I just wanted to clarify this point for the general community. For as long as I have been involved in Python's development (joined python-dev in June 2002), there has always been a maintenance version and an in-development version. When a version of Python is released it immediately becomes the maintenance version.

10 Reasons Python Rocks for Research — Hoyt Koepke The following is an account of my own experience with Python. Because that experience has been so positive, it is an unabashed attempt to promote the use of Python for general scientific research and development. About four years ago, I dropped MATLAB in favor of Python as my primary language for coding research projects. This article is a personal account of how rewarding I have found that experience. As I describe in the next sections, the variety and quality of Python’s features has spoiled me. Even in small scripts, I now rely on Python’s numerous data structures, classes, nested functions, iterators, the flexible function calling syntax, an extensive kitchen-sink-included standard library, great scientific libraries, and outstanding documentation.

6 Things You Need to Learn To Build Your Own Prototype This is the fourth part of a series on becoming your own technical co-founder. In 2008, we couldn’t find a technical co-founder for Yipit. I’m writing about how I became our technical co-founder. Hopefully, I’ll encourage other entrepreneurs with a dream but no technical co-founder options to take their destiny into their own hands. Disclaimer: If you know a great technical co-founder that wants to work with you, join them.

Using the Cython Compiler to write fast Python code Passionate Python developer since 2002after Basic, Logo, Pascal, Prolog, Scheme, Java, C, ...CS studies in Germany, Ireland, FrancePhD in distributed systems in 2007Language design for self-organising systemsDarmstadt University of Technologies, GermanyCurrent occupations:Employed by Senacor Technologies AG, GermanyIT transformations, SOA design, Java-Development, ...»lxml« OpenSource XML toolkit for Part 1: Intro to CythonPart 2: Building Cython modulesPart 3: Writing fast codePart 4: Talking to other extensions Cython is the missing linkbetween the simplicity of Pythonand the speed of C / C++ / Fortran. Cython is the missing linkbetween the simplicity of Pythonand the speed of C / C++ / Fortran. Cython is an Open-Source projecta Python compiler (almost)an enhanced, optimising fork of Pyrexan extended Python language forwriting fast Python extension modulesinterfacing Python with C libraries

John Anderson ( sontek ) - Debugging Python with pdb Being a great debugger is almost as important as being great at writing the software. I think I spend just as much time debugging programs as I do writing them. pdb (python debugger) is a very powerful tool for interactively debugging the state of your application and inspecting portions of your code. For the rest of this post we are going to be debugging a file called fib.py with the following code: # fib.pydef main(): low = 0 high = 1 for i in range(10): print high new_high = get_new_high(low, high) low = high high = new_high def get_new_high(low, high): return low + high if __name__ == '__main__': main() There are many ways to get your application to drop into pdb, the first way is to import pdb in the file you want to debug and put pdb.set_trace() on any lines you want to debug. So we are going to change our file to look like this:

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