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Python for Informatics: Exploring Information

Python for Informatics: Exploring Information

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. 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 Translations and adaptations

Python for Fun This collection is a presentation of several small Python programs. They are aimed at intermediate programmers; people who have studied Python and are fairly comfortable with basic recursion and object oriented techniques. Each program is very short, never more than a couple of pages and accompanied with a write-up. I have found Python to be an excellent language to express algorithms clearly. Some of the ideas here originated in other programs in other languages. From many years of programming these are some of my favorite programs. Many thanks to Paul Carduner and Jeff Elkner for their work on this page, especially for Paul's graphic of Psyltherin (apologies to Harry Potter) and to the teams behind reStructured text and Sphinx to which the web pages in this collection have been adapted. Chris Meyers

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. A few caveats: (1) This stuff is copyrighted by AW (except the code samples which are released to the public domain).

Book Natural Language Processing with Python – Analyzing Text with the Natural Language Toolkit Steven Bird, Ewan Klein, and Edward Loper This version of the NLTK book is updated for Python 3 and NLTK 3. 0. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. Bibliography Term Index This book is made available under the terms of the Creative Commons Attribution Noncommercial No-Derivative-Works 3.0 US License. NPR Puzzle: Finding Synonyms with Python and WordNet | Data Dork This week’s puzzle asks: From Alan Meyer of Newberg, Ore.: Think of a common word that’s six letters long and includes a Q. Change the Q to an N, and rearrange the result to form a new word that’s a synonym of the first one. What are the words? This puzzle is a good opportunity to play with some very cool computational language tools available through the Natural Langauge Toolik (NLTK). NLTK is a group of libraries and functions that contain powerful tools for symbolic and statistical natural language processing (NLP). Before we get to using the NLTK, let’s break down this puzzle into multiple steps. 1. Approach: 1. 2. 3. This is best demonstrated through example and the use of one our language’s most versatile words – shit. So what I’ve done here is started Python in the terminal, and then installed the wordnet module from nltk.corpus. Back to the puzzle at hand, we need to see if any of the words from step 1 and step 2 are synonyms. Full code available here at github here. Like this:

Invent Your Own Computer Games with Python - Chapters Chapter 1 Read online: Chapter 1 - Installing Python Videos: Chapter 2 Read online: Chapter 2 - The Interactive Shell Chapter 3 Read online: Chapter 3 - Strings Download source: hello.py Copy source to clipboard: Use the online diff tool to find typos in your code: hello.py Chapter 4 Read online: Chapter 4 - Guess the Number Download source: guess.py Use the online diff tool to find typos in your code: guess.py Chapter 5 Read online: Chapter 5 - Jokes Download source: jokes.py Use the online diff tool to find typos in your code: jokes.py Chapter 6 Read online: Chapter 6 - Dragon Realm Download source: dragon.py Use the online diff tool to find typos in your code: dragon.py Chapter 7 Read online: Chapter 7 - Using the Debugger Chapter 8 Read online: Chapter 8 - Flow Charts Chapter 9 Read online: Chapter 9 - Hangman Download source: hangman.py Use the online diff tool to find typos in your code: hangman.py Chapter 10 Read online: Chapter 10 - Tic Tac Toe Download source: tictactoe.py Chapter 11 Download source: bagels.py

Understanding Python's "with" statement Fredrik Lundh | October 2006 | Originally posted to online.effbot.org Judging from comp.lang.python and other forums, Python 2.5’s new with statement (dead link) seems to be a bit confusing even for experienced Python programmers. As most other things in Python, the with statement is actually very simple, once you understand the problem it’s trying to solve. Consider this piece of code: set things up try: do something finally: tear things down Here, “set things up” could be opening a file, or acquiring some sort of external resource, and “tear things down” would then be closing the file, or releasing or removing the resource. If you do this a lot, it would be quite convenient if you could put the “set things up” and “tear things down” code in a library function, to make it easy to reuse. def controlled_execution(callback): set things up try: callback(thing) finally: tear things down def my_function(thing): do something controlled_execution(my_function) This wasn’t very difficult, was it?

How to Think Like a Computer Scientist Learning with Python by Allen Downey, Jeff Elkner and Chris Meyers. This book is now available for sale at Lulu.com. How to Think... is an introduction to programming using Python, one of the best languages for beginners. How to Think... is a Free Book available under the GNU Free Documentation License. Please send suggestions, corrections and comments about the book to feedback{at}thinkpython{dot}com. Download The book is available in a variety of electronic formats: Precompiled copies of the book are available in PDF and Postscript . Translations Here are some translations of the book into other (natural) languages: Spanish translation by Gregorio Inda. Other Free Books by Allen Downey are available from Green Tea Press. If you are using this book and would like to make a contribution to support my work, please consider making a donation toward my web hosting bill by clicking on the icon below.

The Python “with” Statement by Example Python’s with statement was first introduced five years ago, in Python 2.5. It’s handy when you have two related operations which you’d like to execute as a pair, with a block of code in between. The classic example is opening a file, manipulating the file, then closing it: with open('output.txt', 'w') as f: f.write('Hi there!') The above with statement will automatically close the file after the nested block of code. Here’s another example. This code sample uses a Context object (“cairo context”) to draw six rectangles, each with a different rotation. cr.translate(68, 68) for i in xrange(6): cr.save() cr.rotate(2 * math.pi * i / 6) cr.rectangle(-25, -60, 50, 40) cr.stroke() cr.restore() That’s a fairly simple example, but for larger scripts, it can become cumbersome to keep track of which save goes with which restore, and to keep them correctly matched. By themselves, pycairo’s save and restore methods do not support the with statement, so we’ll have to add the support on our own.

Hacking Secret Ciphers with Python - Chapters Chapter 1 Read online: Chapter 1 - Making Paper Cryptography Tools PDF of the Caesar Cipher WheelInteractive Virtual Cipher Wheel Chapter 2 Read online: Chapter 2 - Downloading and Installing Python Download Python 3Download pyperclip.py Chapter 3 Read online: Chapter 3 - The Interactive Shell Chapter 4 Read online: Chapter 4 - String and Writing Programs Download source: hello.py Copy source to clipboard: Use the online diff tool to find typos in your code: hello.py Chapter 5 Read online: Chapter 5 - The Reverse Cipher Download source: reverseCipher.py Use the online diff tool to find typos in your code: reverseCipher.py Chapter 6 Read online: Chapter 6 - The Caesar Cipher Download source: caesarCipher.py Use the online diff tool to find typos in your code: caesarCipher.py Download source: caesarCipher2.py Use the online diff tool to find typos in your code: caesarCipher2.py Download source: password.py Use the online diff tool to find typos in your code: password.py Download source: password2.py Chapter 7

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