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Python Tips | Your daily dose of bite sized python tips. Full Stack Python. Blog | Armin Ronacher's Thoughts and Writings. Life is short - you need Python! Home — Doug Hellmann. Coder Who Says Py. Effbot.org. The Mouse Vs. The Python. The Python Challenge. Popular Python recipes. Welcome, guest | Sign In | My Account | Store | Cart ActiveState Code » Recipes Languages Tags Authors Sets NOTE: Recipes have moved! Please visit GitHub.com/activestate/code for the current versions. Popular Python recipes Tags: Recipe 1 to 20 of 4591 « Prev 1 2 3 ... 230 Next » View popular, latest, top-rated or most viewed Feed of the popular Python recipes Python Versions Top-rated recipes Python tags more… algorithms database debugging files graphics linux math mathematics network oop programs python shortcuts sysadmin text threads tkinter web windows xml Accounts Code Recipes Feedback & Information ActiveState Privacy Policy | Contact Us | Support © 2018 ActiveState Software Inc.

Python Tutorials, more than 300, updated March 2, 2009 and carefully sorted by topic and category. Python Course: Modular Programming and Modules. Modular Programming If you want to develop programs which are readable, reliable and maintainable without too much effort, you have use some kind of modular software design. Especially if your application has a certain size. There exists a variety of concepts to design software in modular form. Modular programming is a software design technique to split your code into separate parts. These parts are called modules. The focus for this separation should be to have modules with no or just few dependencies upon other modules. But how do we create modules in Python? Def fib(n): if n == 0: return 0 elif n == 1: return 1 else: return fib(n-1) + fib(n-2) def ifib(n): a, b = 0, 1 for i in range(n): a, b = b, a + b return a We can import this module in the interactive python shell and call the functions by prefixing them with "fibonacci A local name can be assigned to a module function to get shorter names: >>> fib = fibonacci.ifib >>> fib(10) 55 >>> More on Modules Executing Modules as Scripts.

Dive Into Python. 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). Scientific Python Lectures. 10 Resources to Learn Python Programming Language. Python beginner's mistakes. Every Python programmer had to learn the language at one time, and started out as a beginner. Beginners make mistakes. This article highlights a few common mistakes, including some I made myself. Beginner's mistakes are not Python's fault, nor the beginner's. They're merely a result of misunderstanding the language. However, there is a difference between misunderstanding (often subtle) language features, vs misunderstanding the language as a whole, and what can (and cannot) be done with it.

The pitfalls article focused on the former; this article deals with the latter. To put it another way, the mistakes in this article are often cases of "the wrong tool for the job", rather than coding errors or sneaky language traps. Mistake 1: trying to do low-level operations Python is sometimes described as a VHLL, a Very High-Level Language. This doesn't mean that it isn't possible to do these things with Python; but it's probably just not the right language for these jobs.

Some advice. PythonMonk - Interactive Python tutorials. Invent Your Own Computer Games with Python - Learn how to program with a free ebook programming tutorial. Hands-On Python A Tutorial Introduction for Beginners. Hands-On Python A Tutorial Introduction for Beginners Contents Chapter 1Beginning With Python 1.1. Context You have probably used computers to do all sorts of useful and interesting things. In each application, the computer responds in different ways to your input, from the keyboard, mouse or a file. 1.1.1.

First let us place Python programming in the context of the computer hardware. Z = x+y is an instruction in many high-level languages that means something like: Access the value stored at a location labeled x Calculate the sum of this value and the value stored at a location labeled y Store the result in a location labeled z. No computer understands the high-level instruction directly; it is not in machine language. Obviously high-level languages were a great advance in clarity! If you follow a broad introduction to computing, you will learn more about the layers that connect low-level digital computer circuits to high-level languages. 1.1.2. There are many high-level languages. 1.1.3. Learn Python Through Public Data Hacking. How to Think Like a Computer Scientist — How to Think like a Computer Scientist: Interactive Edition.

This interactive book is a product of the Runestone Interactive Project at Luther College, led by Brad Miller and David Ranum. There have been many contributors to the project. Our thanks especially to the following: This book is based on the Original work by: Jeffrey Elkner, Allen B. Downey, and Chris MeyersActivecode based on SkulptCodelens based on Online Python TutorMany contributions from the CSLearning4U research group at Georgia Tech.ACM-SIGCSE for the special projects grant that funded our student Isaac Dontje Lindell for the summer of 2013.NSF The Runestone Interactive tools are open source and we encourage you to contact us, or grab a copy from GitHub if you would like to use them to write your own resources.

An Introduction to Interactive Programming in Python. How not to write Python code. Lately I’ve been reading some rather unclean Python code. Maybe this is mainly because the author(s) of the code had no in-depth knowledge of the Python language itself, the ‘platform’ delivered with cPython,… Here’s a list of some of the mistakes you should really try to avoid when writing Python code: Some days ago RealNitro pointed me at this list of essential Python readings. “Idiomatic Python” is a must-read, even for experienced Python developers. That’s about it for now, maybe I’ll add some more items to this list later on. If you have some other hints, comments! Posted in Development, Technology. Tagged with Development, python.

By Nicolas – February 8, 2008. Pythonista. Python Programming Language – Official Website.