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Test-Driven Development with Python

Test-Driven Development with Python
Test-Driven Development with Python Test-Driven Development with Python Harry Percival Gillian McGarvey Rebecca Demarest Wendy Catalano Randy Comer David Futato Copyright © 2014 Harry Percival Printed in the United States of America. O’Reilly books may be purchased for educational, business, or sales promotional use. Nutshell Handbook, the Nutshell Handbook logo, and the O’Reilly logo are registered trademarks of O’Reilly Media, Inc. Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. While every precaution has been taken in the preparation of this book, the publisher and authors assume no responsibility for errors or omissions, or for damages resulting from the use of the information contained herein. Praise for Test-Driven Development with Python Table of Contents © 2013, O’Reilly Media, Inc. Related:  DevOps

PyQt4 tutorial This is PyQt4 tutorial. The tutorial is suited for beginners and intermediate programmers. After reading this tutorial, you will be able to program non trivial PyQt4 applications. PyQt5 tutorial is the successor of this tutorial. Table of contents E-book A unique e-book covering advanced features of the PyQt4 library: Advanced PyQt4 tutorial. Related tutorials To refresh your knowledge of the Python language there is a Python tutorial on ZetCode. wxPython tutorial, PyGTK tutorial and Tkinter tutorial are tutorials for other popular Python GUI bindings. So You’d Like To Make a Map Using Python Making thematic maps has traditionally been the preserve of a ‘proper’ GIS, such as ArcGIS or QGIS. While these tools make it easy to work with shapefiles, and expose a range of common everyday GIS operations, they aren’t particularly well-suited to exploratory data analysis. In short, if you need to obtain, reshape, and otherwise wrangle data before you use it to make a map, it’s easier to use a data analysis tool (such as Pandas), and couple it to a plotting library. This tutorial will be demonstrating the use of: PandasMatplotlibThe matplotlib Basemap toolkit, for plotting 2D data on mapsFiona, a Python interface to OGRShapely, for analyzing and manipulating planar geometric objectsDescartes, which turns said geometric objects into matplotlib “patches”PySAL, a spatial analysis library Package installation This tutorial uses Python 2.7.x, and the following non-stdlib packages are required: IPythonPandasNumpyMatplotlibBasemapShapelyFionaDescartesPySAL Running the Code Obtaining a basemap

1.3. A Quick Tour — Buildbot 0.9.12 documentation 1.3.1. Goal This tutorial will expand on the First Run tutorial by taking a quick tour around some of the features of buildbot that are hinted at in the comments in the sample configuration. As a part of this tutorial, we will make buildbot do a few actual builds. This section will teach you how to: make simple configuration changes and activate themdeal with configuration errorsforce buildsenable and control the IRC botenable ssh debuggingadd a ‘try’ scheduler 1.3.2. Let’s start simple by looking at where you would customize the buildbot’s project name and URL. We continue where we left off in the First Run tutorial. Open a new terminal, and first enter the same sandbox you created before (where $EDITOR is your editor of choice like vim, gedit, or emacs): cd ~/tmp/bb-master source sandbox/bin/activate $EDITOR master/master.cfg Now, look for the section marked PROJECT IDENTITY which reads: After making a change go into the terminal and type: 1.3.3. This creates a Python SyntaxError. 1.3.4. Note

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).

Changing Between Spaces and Tabs in Sublime Text Sublime Text is pretty dang good at making it easy to switch between using tabs and spaces to indent your code. More importantly, it makes it easy to adjust the indentation of code that doesn't match your preference. I thought I'd put this together for reference, as there is a particular sequence of steps for some of the transitions that needs to be followed. The first step is making sure your User Preferences are how you like them. I prefer spaces, so my settings are like this: Adjust to your liking there. You can override these settings on any given file, from the bottom right. This is also headquarters for fixing up a document that isn't how you like it. Changing from Tabs to Spaces (Same Level of Indentation) Here's a document that is in tabs right now. You can see that those Tabs are 2 spaces wide. And I'm good to go for that case. Changing from Tabs to Spaces (Different Level of Indentation) Let's say a straight conversion from tabs to spaces isn't going to do it for me. .editorconfig

Python Programming Python Programming From Wikibooks, open books for an open world Jump to: navigation, search This book describes Python, an open-source general-purpose interpreted programming language available for a broad range of operating systems. There are currently three major implementations: the standard implementation written in C, Jython written in Java, and IronPython written in C# for the .NET environment. There are two common versions currently in use: 2.x and 3.x. Contents[edit] Intro[edit] Overview Getting Python Setting it up Interactive mode Self Help Basics[edit] Creating Python programs Variables and Strings Basic syntax Sequences (Strings, Lists, Tuples, Dictionaries, Sets) Data types Numbers Strings Lists Tuples Dictionaries Sets Basic Math -- redundant to "Operators" Operators Control Flow Decision Control Conditional Statements Loops Functions Scoping Input and output Files Text Modules Classes Exceptions Errors Source Documentation and Comments Idioms Advanced[edit] Decorators Context Managers Reflection Metaclasses Email Qt4

How to Tango with Django: A Python Django Tutorial Continuous Integration - Full Stack Python Continuous integration automates the building, testing and deploying of applications. Software projects, whether created by a single individual or entire teams, typically use continuous integration as a hub to ensure important steps such as unit testing are automated rather than manual processes. Why is continuous integration important? When continuous integration (CI) is established as a step in a software project's development process it can dramatically reduce deployment times by minimizing steps that require human intervention. Automated testing Another major advantage with CI is that testing can be an automated step in the deployment process. The automated testing on checked in source code can be thought of like the bumper guards in bowling that prevent code quality from going too far off track. Continuous integration example The following picture represents a high level perspective on how continuous integration and deployment can work. Open source CI projects Jenkins CI resources

introduction to python - Random stream This is the material which I use for teaching python to beginners. tld;dr: Very minimal explanation more code. Python? Interpreted languageMultiparadigm Introduction hasgeek@hasgeek-MacBook:~/codes/python/hacknight$ python Python 2.7.3 (default, Aug 1 2012, 05:14:39) [GCC 4.6.3] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> >>> print "Let's learn Python" Let's learn Python Numbers Expressions >>> 3 < 2 False >>> 3 > 2 True >>> 3 > 2 < 1 False >>> (3 > 2) and (2 < 1) False >>> 3 > 2 > 1 > 0 True >>> (3 > 2) and (2 > 1) and (1 > 0) True >>> 1 or 2 1 >>> 2 or 1 2 >>> 1 + 2 + 3 * 4 + 5 20 1 + 2 + 3 * 4 + 5 ↓ 3 + 3 * 4 + 5 ↓ 3 + 12 + 5 ↓ 15 + 5 ↓ 20 >>> "python" > "perl" True >>> "python" > "java" True Variables >>> a = 23 >>> print a 23 >>> a = "Python" >>> print a Python Guess the output True = False False = True print True, False print 2 > 3 Parallel Assignment z, y = 23, z + 23 a, b = 23, 12, 20 a = 1, 2 Swap Variable String Guess output Condition Data Structure List

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