PyCon 2010: New *and* Improved: Coming changes to unittest, the standard library test framework (#52)
Presented by Michael J Foord
In Python 2.7 and 3.2 a whole bunch of improvements to unittest will arrive. unittest is the Python standard library testing framework and for several years it has languished whilst other Python testing frameworks have innovated. Some of the best innovations have made their way into unittest which has had quite a renovation.
This talk will go through the major changes, like the new assert methods, test discovery and the load_tests protocol, and also explain how they can be used with earlier versions of Python.
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PyCon 2010: Introduction to Traits
Introduction to Traits Presented by Corran Webster The Traits project allows you to simply add validation, initialization, delegation, notification and a graphical user interface to Python object attributes. In this tutorial we will explore the Traits toolset and learn how to dramatically reduce the amount of boilerplate code you write, do rapid GUI application development, and understand the ideas which underly other parts of the Enthought Tool Suite (such as MayaVi and Chaco plotting toolkits). Traits and the Enthought Tool Suite are open source projects licensed under a BSD-style license. Intended Audience Intermediate to advanced Python programmers Class Outline Introduction to ETS and Traits Basic Traits + Trait types + Property Traits + Trait Validation Traits UI + Basic Traits UI + Tour of the Trait editors + Advanced Trait editors Notification in Traits + Static notification + Dynamic notification Advanced Traits UI + Customizing Views, Groups and Items + Traits UI Handlers + Buttons, Menus and Toolbars + Drag and Drop Q&A Requirements Laptop recommended (any major OS is fine), with the following software installed: Python 2.5 or 2.6 (www.python.org) Either wxPython (http://www.wxpython.org/) or PyQt (http://www.riverbankcomputing.co.uk/software/pyqt/intro) Numpy and Scipy (http://www.scipy.org) Enthought Tool Suite 3.2 or higher (http://code.enthought.com/projects) All required software can be obtained by installing the free trial version of the Enthought Python Distribution v5 or later (http://www.enthought.com/products/epd.php).
PyCon 2010: Django Deployment Workshop
Django Deployment Workshop Presented by Jacob Kaplan-Moss So you've written a Django site... now what? Writing the application is just the beginning; now you've got to put it into production! In this hands-on workshop we'll walk through the creation of a full Django deployment environment running on a cluster of (virtual) machines. This class will introduce students to a wide variety of technologies, including Amazon's EC2 and S3, Fabric, Varnish, nginx, mod_wsgi, memcached, PostgreSQL, pgpool, pg_standby, and more. By the end of the class, each student will have created an environment featuring: Multiple levels of caching and load balancing. Multiple web application servers. Shared media servers. Redundant replicated database servers. Separate caching servers. We'll create this whole stack on Amazon EC2 virtual machines, so students will be able to take home a complete copy of all the deployment configuration for future review at their leisure. Note: the example application used in this class with be a Django site, and the class assumes at least a moderate comfort level with Django. However, the tools and techniques apply just as well to other Python web frameworks, so users of other tools will likely be able to follow along fairly easily. Intended Audience Intermediate to advanced Django users with sites nearing or in production. Python developers using other web frameworks will likely be able to follow along -- see the note in the summary, above. Class Outline Introduction: the deployment question Application server: mod_wsgi Database server: PostgreSQL Automated deployment with Fabric Multiple web servers; load balancing with nginx Adding memcached Database connection middleware: pgpool Database redundancy: warm standby Upstream caching: Varnish Final load testing: how'd we do? Requirements Students will need a computer and Amazon EC2 and S3 accounts, and will be asked to familiarize themselves with the process of starting and stopping EC2 virtual machines before the class. http://us.pycon.org/2010/tutorials/kaplanmoss_django/
PyCon 2010: Introduction to unittest (a.k.a. PyUnit) (#96)
Introduction to Unittest (a.k.a. PyUnit) Presented by Chander K Ganesan Presented by The PyUnit (unittest) unit testing framework provides an easy-to-use set of tools and techniques to add robust unit testing to your Python code. By integrating unit testing in their code, developers allow for a robust set of tools to quickly and easily identify "broken" code. In this session we'll explore the unittest module and demonstrate how to leverage PyUnit for unit testing.
PyCon 2010: Modern version control: Mercurial internals (#113)
Modern version control: Mercurial internals Presented by Dirkjan Ochtman In this talk, I'd like to talk a bit about Mercurial. This will not be a beginner-level talk on DVCS or hg; it aims to be a higher-level discussion of the concepts employed in Mercurial. After having discussed these, I'd also like to compare Mercurial and git based on UI, performance and underlying concepts.
PyCon 2010: Hg and Git : Can't we all just get along? (#154)
Hg and Git: Can't we all just get along? Presented by Scott Chacon There is a fair amount of unnecessary animosity between developers about version control systems, especially between Mercurial and Git users. In reality, these two systems are very similar and can actually cooperate pretty well. In this talk we will show just how similar Git and Mercurial are, look at some of their technical differences, and see how they can work together by looking at hg-git, the bidirectional Git/Mercurial bridge, implemented in Python.
PyCon 2010: Remixing Music Pythonically (#157)
Remixing Music Pythonically Presented by Adam T. Lindsay The Echo Nest Remix API (http://code.google.com/p/echo-nest-remix/) was made open source by The Echo Nest, a "music intelligence" company based in the Boston area in the autumn of 2008. This talk will offer details on the concise expressivity offered when editing multimedia driven by content-based features, and some insights on what Pythonic magic did and didn't work in the development of the modules. Audio and video examples of the fun-yet-odd outputs that are possible will be shown.
PyCon 2010: Teaching compilers with python (#87)
Teaching compilers with python Presented by Dr. Matthieu Amiguet Why choose Python to teach compilers? In the University of Applied Sciences ARC, compilers are taught in a relatively short amount of time. Focus is put on the main conceptual ideas, letting aside many technical details. Still, the students are expected to write a full compiler within a few weeks' time. After trying the traditional C/Lex/Yacc based approach, and a more education-oriented Java/Jaccie solution, we settled on Python and PLY, plus a few enhancements (syntax tree graphical representation, decorator to achieve better code separation). As a result, the students get a better understanding of the compiler concepts and produce more interesting and creative projects.
PyCon 2010: Dealing with unsightly data in the real world. (#156)
Dealing with unsightly data in the real world Presented by Alexander Dutton Drawing on experiences writing http://m.ox.ac.uk/, we'll explore the art of getting data out of unhelpful systems. We'll start with working out how to interact with a system, move on to techniques for parsing the data it gives you, and round off by implementing a shinier interface over the top.
PyCon 2010: rapid multi-purpose testing (#81)
Rapid multi-purpose testing Presented by Holger Krekel Want to rapidly test code, javascript or documents on different Python Interpreters and versions? This talk gives an overview on new py.test features of the last year. I'll discuss the minimal-boilerplate testing and new plugin model and give an overview on which testing needs are covered so far, for example: run tests written for nose or unittest ad-hoc distribute tests to local or remote Python environments test compatibility with Python3 run javascript unit-tests in real browsers coverage testing django-specific testing I'll conclude with upcoming features regarding testing-in-the-cloud and plans on more test tool convergence. (URL: http://pytest.org) [VIDEO HAS ISSUES: first 47 seconds or so are really quiet]
