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A Gentle Introduction to Programming Using Python

Code Like a Pythonista: Idiomatic Python In this interactive tutorial, we'll cover many essential Python idioms and techniques in depth, adding immediately useful tools to your belt. There are 3 versions of this presentation: ©2006-2008, licensed under a Creative Commons Attribution/Share-Alike (BY-SA) license. My credentials: I am a resident of Montreal,father of two great kids, husband of one special woman,a full-time Python programmer,author of the Docutils project and reStructuredText,an editor of the Python Enhancement Proposals (or PEPs),an organizer of PyCon 2007, and chair of PyCon 2008,a member of the Python Software Foundation,a Director of the Foundation for the past year, and its Secretary. In the tutorial I presented at PyCon 2006 (called Text & Data Processing), I was surprised at the reaction to some techniques I used that I had thought were common knowledge. Many of you will have seen some of these techniques and idioms before. These are the guiding principles of Python, but are open to interpretation. import this

FreeComputerBooks.com Building Skills in Python — Building Skills in Python A Programmer’s Introduction to Python Legal Notice This work is licensed under a Creative Commons License. You are free to copy, distribute, display, and perform the work under the following conditions: Attribution. For any reuse or distribution, you must make clear to others the license terms of this work. Language Basics The Processing View A programming language involves two closely interleaved topics. This part describes the most commonly-used Python statements, sticking with basic numeric data types. Some of the examples in this part refer to the rules of various common casino games. We’ll provide a little background on Python in Background and History. In Simple Numeric Expressions and Output we’ll introduce the print statement (and print() function); we’ll use this to see the results of arithmetic expressions including the numeric data types, operators, conversions, and some built-in functions. Data Structures The Data View Expression Statement. The Other Side of the Coin. Sequences.

Using natural language as a metaphoric base for object-oriented modeling and programming - AC Alistair A.R. Cockburn Originally printed as IBM Technical Report TR-36.00021 May 1, 1992 ABSTRACT: This paper proposes natural language as a strong and intuitive metaphor to extend object oriented’s metaphor of interacting objects. Nouns and verbs are already found in the object model, but adjectives and adverbs are not. 0. Object-oriented programming began with a strong and intuitive metaphorical base for a rather abstract activity, programming, but has become enmeshed in ad hoc technological proposals trying to fulfill and extend that base. The object-oriented model takes advantage of our natural cognitive skills, anthropomorphizing the world into a model of communicating, even self-motivated objects. Why metaphorical only, why not natural language as the programming language itself? Figure 1. A chart of some current concerns in the object-oriented (OO) domain might look like Figure I. Figure 2. The topics in the paper crisscross each other just as Figure 2 does. 1. 2. 2.1. 2.2. 2.3.

Think Complexity by Allen B. Downey Buy this book from Amazon.com. Download this book in PDF. Read this book online. Description This book is about complexity science, data structures and algorithms, intermediate programming in Python, and the philosophy of science: Data structures and algorithms: A data structure is a collection that contains data elements organized in a way that supports particular operations. This book focuses on discrete models, which include graphs, cellular automata, and agent-based models. Complexity science is an interdisciplinary field---at the intersection of mathematics, computer science and physics---that focuses on these kinds of models. Free books! This book is under the Creative Commons Attribution-NonCommercial 3.0 Unported License, which means that you are free to copy, distribute, and modify it, as long as you attribute the work and don't use it for commercial purposes. Download the LaTeX source code (with figures and a Makefile) in a zip file.

CSS Tutorials - Photoshop Tutorials - PHP Tutorials Think Python: How to Think Like a Computer Scientist How to Think Like a Computer Scientist by Allen B. Downey This is the first edition of Think Python. It uses Python 2, with notes on differences in Python 3. Buy this book at Amazon.com Download Think Python in PDF. Read Think Python in HTML. Example programs and solutions to some problems are here (links to specific examples are in the book). Description Think Python is an introduction to Python programming for beginners. Some examples and exercises are based on Swampy, a Python package written by the author to demonstrate aspects of software design, and to give readers a chance to experiment with simple graphics and animation. Think Python is a Free Book. If you have comments, corrections or suggestions, please send me email at feedback{at}thinkpython{dot}com. Other Free Books by Allen Downey are available from Green Tea Press. Download Precompiled copies of the book are available in PDF. Python 3.0 Most of the book works for Python 2.x and 3.0. Michael Kart at St. Earlier Versions

120 Tips, Tricks, and Tuts from 2009 Worth your Time | Nettuts+ Now that we're down to the end of 2009, what were some of the best web development and design tutorials and articles from the year? We'll take a look at 120 of them! Jump to a Month January How to Build a Login System for a Simple Website In today's video tutorial, we'll be building a login system with PHP and MYSQL. Run Your Own TinyURL Service With Phurl Jan 13th, 2009 in Other by Thord Hedengren URL shortening services are a must if microblogging services like Twitter are to work. Slice and Dice that PSD In today's video tutorial, we'll be slicing up a PSD, dicing it for the web, and serving it on a warm hot plate. The Definitive Guide to Creating a Practical jQuery Plugin In this article weíre going to be building our very own jQuery plugin step-by-step from scratch; jQuery makes this task exceptionally easy for us, giving us a simple method of packaging up our scripts and exposing their functionality, and encouraging the use of scalable and reusable object-oriented techniques. February

Non-Programmer's Tutorial for Python 2.6 Non-Programmer's Tutorial for Python 2.6 From Wikibooks, open books for an open world Jump to: navigation, search For Python 3, see Non-Programmer's Tutorial for Python 3. Contents[edit] Authors Contributors to this book Front matter Initial remarks Intro Installing and using Python – where to get help Hello, World The famous first program – screen output – numbers and calculations Who Goes There? Interactive input – strings Count to 10 while loops Decisions if statements Debugging Finding out what goes wrong Defining Functions Structuring programs with the use of functions Advanced Functions Example (Almost) mind-blowing example of how programmers can think Lists Variables containing more than one value For Loops A second kind of loop Boolean Expressions Computer logic – true and false – and and or – not Dictionaries Variables containing key/value pairs Using Modules Extensions to the standard set of functionality More on Lists Using elements or parts of lists Revenge of the Strings Advanced text manipulation File IO Views

Text Processing in Python (a book) A couple of you make donations each month (out of about a thousand of you reading the text each week). Tragedy of the commons and all that... but if some more of you would donate a few bucks, that would be great support of the author. In a community spirit (and with permission of my publisher), I am making my book available to the Python community. Minor corrections can be made to later printings, and at the least errata noted on this website. Email me at <mertz@gnosis.cx> . A few caveats: (1) This stuff is copyrighted by AW (except the code samples which are released to the public domain).

The Python Tutorial Python is an easy to learn, powerful programming language. It has efficient high-level data structures and a simple but effective approach to object-oriented programming. Python’s elegant syntax and dynamic typing, together with its interpreted nature, make it an ideal language for scripting and rapid application development in many areas on most platforms. The Python interpreter and the extensive standard library are freely available in source or binary form for all major platforms from the Python Web site, and may be freely distributed. The Python interpreter is easily extended with new functions and data types implemented in C or C++ (or other languages callable from C). This tutorial introduces the reader informally to the basic concepts and features of the Python language and system. For a description of standard objects and modules, see The Python Standard Library. The Glossary is also worth going through.

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