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Designing interfaces so that other code can interact with ours (whether our code is a library, framework, application, website...) is a very common and clearly crucial activity, but it's fraught with dangers -- there's a lot stuff we all keep doing wrong time after time. This talk shows some common categories of API design errors encountered in the wild, with tips on how to avoid them when you design your next API.
Goals: to show you how to focus resources and attention to help avoid mistakes in API design. Prereqs: experience designing and developing software, esp. software which needs to interact w/other existing software.
In a world of many programming languages, the popularity of Python continues to grow without bound. We examine what makes it special and how it influences the way we program:
by Jon Åslund
This is a story about how Spotify started, how we evolved, where we are today and how Python has always been a big part of our success. Where do we use it? Where do we not use it? Learn about the Unix way and the Debian way of maintaining a healthy love for Python, while two-timing with other languages such as Java and C++.
by Péter Szabó
Stackless Python and the greenlet package for CPython are two different implementations of coroutine support for Python. (Coroutines are fundamental building blocks of I/O frameworks like gevent, Eventlet, Concurrence and Syncless to conveniently handle thousands of socket connections at a time without creating threads.) Stackless and greenlet implement a different interface. However, each is powerful enough so that it can be used to emulate the other one. In this talk we explore the differences and discuss design decisions and testing strategies of the emulations we have implemented.
by Yann Le Du
In Electron Paramagnetic Resonance Imaging, we are faced with a deconvolution problem that has a strong impact on the image actually reconstructed. Faced with the need of mapping the distribution of organic matter in Terrestrial and Martian rock samples for applications in exobiology, we needed to see how to extract a maximum amount of information from our data : our approach uses reservoir computing artificial neural networks coupled to a particle swarm algorithm that evolves the reservoirs’ weights.
The code runs on the Hybrid Processing Units for Science (HPU4Science) cluster located at the Laboratoire de Chimie de la Matière Condensée de Paris (LCMCP). The cluster is composed of a central data storage machine and a heterogeneous ensemble of 6 decentralized nodes. Each node is equipped with a Core2 Quad or i7 CPU and 3-7 NVIDIA Graphical Processing Units (GPUs) including the GF110 series. Each of the 28 GPUs independently explores a different parameter space sphere of the same problem. Our application shows a sustained real performance of 15.6 TFLOPS. The HPU4Science cluster cost $36,090 resulting in a 432.3 MFLOPS/$ cost performance.
That talk is meant to demonstrate on a practical case how consumer grade computer hardware coupled to a very popular computer language can be used to tackle a difficult yet very elementary scientific problem : how do you go from formulating the problem, to choosing the right hardware and software, and all the way to programming the algorithms using the appropriate development tools and methodologies (notably Literate Programming). On the math side, the talk requires a basic understanding of matrix algebra and of the discretization process involved when computing integrals.
Gevent (http://gevent.org) is a coroutine-based library that enables you to write highly-concurrent network and web applications. Learn in detail what Gevent is, what it does and how it does it.
I will introduce a coroutine-based approach to network programming, explain it benefits and pitfalls.We will walk through the Gevent API, including the most recent additions, and understand how it is implemented. I will make a quick overview of the most interesting 3rd party add-on and applications after that.
Django is an excellent web development platform with an extensive developers community. It may be the most popular Python web framework nowadays. However, the exisiting django based CMS products are not as feature complete as other comparable solutions (Drupal, Plone, Alfresco, ModX, etc.).
The Merengue project tries to fill this gap. It is financed by the University of Málaga (Spain) and takes advantage of existing code and knowledge from other projects (Plone, Drupal, Pinax, django-cms, feincms, LFC, etc.)
What was my motivation for working with Python after two years of PHP? There is so much you can do. Functions are objects you can pass around, you can decompile functions to see how they work internally, you can alias a bound method to a global function and it will just work. You can change import semantics, override the method resolution order, you can write metaclasses, you can hook into the CPython interpreter API and much more.
Five years later I came to the conclusion that this is really not what Python is about and that a lot of what I did was interesting but not necessarily a good idea. This talk is a 45 minute recompilation of things I really shouldn't have done in the first place. Expect a bunch of neat and interesting hacks that showcase the possibilities of the language.
At ep.io we built a Python hosting platform from the ground up, designed to run large numbers of web applications on a small number of physical machines both securely and in a reasonably scalable way. This talk will show you how we built our infrastructure - using Redis, eventlet, PostgreSQL and more - and what lessons we learnt from our first few thousand deploys.
See how we split services into multiple processes and greenthreads; the pains of building a cooperatively-multitasking PTY module; how Redis isn't the answer to everything, but is still very useful; how to persuade third-party software to work securely in a shared environment; and how important it is to have good logging, especially when you have more than five servers.
by Wesley Chun
All of us are familiar with using open source tools to develop software applications with, but instead of writing code, it is also possible to create the manuscript of a book in very much the same way. These days, authors have many choices in terms of the tools which are available to aid them in writing a book. Gone are the times when the only option is using a proprietary word processor, so why not try it using open source tools? It's especially attractive to those who develop software using open source tools as well those who are writing books about open source tools. Both code and the written word are created in plain text files. These files are easily archived using some version control system. They can be shared easily via e-mail and can also be backed up in the same manner. In the end, the final product is shipped to the customer: in the case of software, it's distribution via CD or DVD, or perhaps a release for installation on a server, and for a book, it's delivering a manuscript to the publisher, perhaps in a format such as HTML or PDF®.
Upon some reflection, writing a book is, in many ways, similar to writing an application: you create text or code which is saved to a file (or files--typically one but could be more) file in some format, proprietary or otherwise. Additions, changes, or deletions are made to the file(s), which is then updated when the file is (re)saved. Backups need to be made, some versioning may be required to keep track of multiple files during the course of development, and finally, the resulting file(s) have to be delivered, as described above. Because of all the similarities described, we assert that it is possible to use a development environment utilizing Python and other open source tools to not only write application with, but also be able to create the entire manuscript for a book as well! While this entire concept should not really be mind-blowing, it does represent a trend seemingly growing in popularity in the open source world.
In particular, we highlight the following requirements that are necessary when creating a manuscript, especially with co-authors:
In this talk, we highlight one particular case study, the development of Addison Wesley's 2009 publication, "Python Web Development with Django", as well as provide some insight into other projects created using similar tools. Open source software has radically affected how applications are built today, and this phenomenon has the ability to affect the book publishing world in the same way.
by Claudio Desideri
In this talk I'm going to explain the main features and possibility that Panda3D gives us when we want to create a game from scratch. Then, I'll explain how the engine is structured and how it works conceptually going also through code examples and some practical operations.
It's meant for beginners who have also never worked with realtime graphics and the only prerequisite is a bit of python knoweledge including how to write a simple program and how to run it. The goal is to create a simple realtime application that take care of user input and reacts depending on it.
PostgreSQL (or “Postgres”) is an immensely powerful, incredibly extensible relational database, released under a permissive open source licence that is similar to that of CPython. PL/Python is one of PostgreSQL's standard server-side procedural languages, through which Python stored functions can be defined that can be called directly from SQL, quite seamlessly.
Play to the strengths of Postgres, by writing application business logic within the database in either Python 2 or Python 3. Enforce advanced business rules using Python, including constraints on both tables and database level datatypes (“domains”). By pushing the logic tier into the database, you can potentially greatly increasing your application's scalability by minimising the number of database roundtrips.
Includes case studies and topical coverage of PL/Python related enhancements in upcoming 9.1 release, and recent 9.0 release. The talk only assumes a very basic understanding of databases.
by Armin Rigo and Antonio Cuni
A teaser for the full tutorial on Tuesday: http://lanyrd.com/2011/europytho...
A teaser for the full tutorial on Tuesday: http://lanyrd.com/2011/europytho...
The PSF recently adopted a diversity statement. While some argue that we should do this just because it's "the right thing to do", others question why we, as a technical community, should even worry about diversity. This talk addresses the diversity question, not in moralistic or ethical terms, but in pragmatic ones. Studies on creativity and productivity demonstrate the potential benefits of diversity for the Python community. Making Python the best language it can be is not merely helped by increasing diversity, but may be dependent on diversity.
Share the lessons learned from a decade of core Python development, what worked and what didn't. Look at the development process and thinking behind some of Python's successful APIs and ones that leave something to be desired. Learn general principles for designing a good API for public consumption.
by Claudio Desideri
In questo talk spiegherò quali opportunità ci offre il game-engine Panda3D nel momento in cui vogliamo creare un videogioco da zero. Spiegherò com'è strutturato al suo interno e i concetti di base per capire come funziona, ma mostrerò anche prove pratiche e pezzi di codice.
Può partecipare chiunque abbia una conoscenza di base di Python, anche se non ha mai lavorato con applicazioni realtime 3D. L'obiettivo è mostrare come creare un semplice videogioco che risponda agli input immessi dall'utente e come utilizzare al meglio questo potente engine.
The talk will give an introduction to the concepts used in the Python Database API and relational databases in general. Connection, cursors and transactions are discussed, and their use in a typical Python database application are demonstrated. The talk will also touch upon some advanced database programming techniques and discuss best practices.
Messaging is a well established domain in information technology and can greatly improve the scalability and throughput of a system when employed appropriately. Message queues can be used to achieve
There is a huge number of messaging patterns identified in the industry  and a small selection of these will be presented to whet your appetite :-)
AMQP  is a fairly new and open messaging standard with a number of freely available open source message brokers (RabbitMQ , ZeroMQ , qpid  etc.) with different features and performance trade-offs.
In the course of the presentation you will be
* introduced to AMQP concepts and jargon
* introduced to available Python AMQP bindings (focussing on an asynchronous (txAMQP ) and a synchronous variant (most likely kombu ))
* shown code examples demonstrating how to use these Python bindings
The presentation (45 minutes in total) is structured as follows:
* 7.5 minutes for messaging concepts and patterns
* 7.5 minutes for AMQP concepts
* 5 minutes for an overview of the Python bindings for AMQP
* 10 minutes for txAMQP examples (asynchronous bindings)
* 10 minutes for kombu examples (synchronous bindings)
* 5 minutes for questions
by Wesley Chun
Python is currently at a crossroads: Python 2 has taken it from a quiet word-of-mouth language to primetime, with many companies around the world using it and an ever-increasing global marketshare of the programming world. But now comes Python 3, the first version of the language that is not backwards compatible with previous releases.
What does this mean? Are all my Python programs going to break? Will I have to rewrite everything? How much time do I have? When is Python 2 going to be EOL'd? Is the language undergoing a complete rewrite and will I even recognize it? What are the changes between Python 2 and 3 anyway? Also, the next generation is already here, as Python 3 is over two years old now. What has been ported so far, and what is its current status? Are migration plans or transition tools available? If I want to start learning Python, should I do Python 2 or Python 3? Are all Python 2 books obsolete?
We will attempt to answer all of these questions and more. Join us!
rdflib is a python library implementing a database with various triples back-end, parser, data serializers, SPARQL is a Python interface to extract/insert triples. We integrated it in Django reusing the database connection and exposing an ORM interface, along with full-text search on literals. This presentation shows a django-rdflib case study with a PostgreSQL backend in Brain Architecture Management System (http://brancusi1.usc.edu) - a neuroscientific project for the University of Southern California. Benefits of the flexible RDF structure will be shown, allowing researchers to insert free format data, making data public with a customizable serialization and use the powerful full-text search integrated in PostgreSQL.
Objective: show attendees an effective combination of RDF, PostgreSQL full-text search and Django ORM via django-rdflib.
Requirements: Django familiarity.
by Cesare Di Mauro
A partire da Python 3 il vecchio tipo intero ("int") è stato abbandonato, lasciando il posto al "long", che l'ha rimpiazzato mettendo a disposizione un unico, uniforme tipo per lavorare con gli interi.
Tuttavia, i long richiedono una struttura più complessa che ha ridotto un po' le prestazioni di Python 3.x.
Un'idea è si è fatta strada dando un'occhiata alla loro implementazione, che può aiutare a migliorare la situazione in scenari comuni (usando interi "corti").
Verrà presentata una struttura leggermente modificata, e confrontata col vecchio PyIntObject e l'attuale PyLongObject di Python 3.2, assieme ad alcune ottimizzazioni, pensieri, e problemi che si sono presentati, che mostreranno lo sforzo richiesto da un simile cambiamento a un elemento del "cuore" di Python.
This talk is the updated and especially enhanced of the "Python and PostgreSQL - a match made in heaven" talk of EP 2006, CERN, Switzerland.
PostgreSQL and Python share more then the first letter: their communities have great similiarities; their development processes are really comparable; their licenses and their openness to academics AND business (on a technical and communitie perspective) are big pluses.
We will have a look at those similiarities and learn why PostgreSQL is really the database sister to Python. There will be an overview of PostgreSQL, information of how to connect PostgreSQL and Python; how PostgreSQL streaming replication works and what it can do for you, how PL/Python helps to have Web 2.5 JSON storage and handling right inside PostgreSQL. We will show that YESQL is also a valid answer to many data storage qeuestions.
To Relate or Not to Relate, that is the question raised by the NoSQL movement. There is a lot of buzz about Couch, Casandra, MongoDB, and other non relational databases, and at the same time there are decades of hard work that's gone into optimizing databases built around the relational model.
I would actually argue that there is no such thing as a NoSQL database -- there are a variety of compelling options to relational database -- each of which have different features and different performance characteristics. So no one-sized fits all comparison will do. So, I'll try to outline a general taxonomy for persistence mechanisms, and then proceed to comparing relational DB's to their new friends in practice.
The talk will contain quite a few stories from the trenches with CouchDB, MongoDB, MySQL, Postgres, Tokyo Cabinet, ZODB, and other databases, and will help you think about the data storage needs of your applications in new ways.
by David Cramer
Building scalable web applications may seem like a distant problem, but the problem is not thinking about it before it's too late. This talk will focus on designing a scalable web application before it needs to be (and avoiding the premature optimization dilemma). It will cover topics such as efficient usage of your database, appropriate caching (and invalidation!), and what the speaker considers as best practices.
Clojure is a modern Lisp dialect symbiotic with the Java Virtual Machine and designed for concurrency. Clojure is compiled to byte-code and yet is fully dynamic. It is very oriented towards functional programming and manages state change in a controlled environment with software transactional memory (STM). Since Clojure is a Lisp dialect, it retains the code-as-data philosophy and has a powerful macro system
Using the Jython, an implementation of the Python programming language written in Java, it is possible to call Clojure from Python and call Python from Clojure, using the JVM as an interoperability platform.
After a brief introduction of the main Clojure features, the presentation will show how Jython and Clojure can be used together.
No previous knowledge of Clojure (or Lisp) is assumed nor required.
by Bruno Renié
GeoDjango is the "world-class geographic web framework" everyone has probably heard of. The purpose of this talk, targeted at people familiar with Django itself, is to introduce in more details the capabilities of this framework.
After learning the basics of Geographic Information Systems, we will see:
During this talk we will be building a simple GeoDjango application to illustrate the different concepts introduced.
La prima parte del talk introdurra' la storia di uWSGI, dall'idea iniziale alla messa in produzione dei primi lavori, fino alla sua inclusione nei progetti Cherokee e Nginx.
Seguira' una serie di esempi di deploy in ambienti ostili (a livello di sicurezza, non faremo deploy nella jungla) o con risorse fortemente limitate fino all'utilizzo delle funzionalita' integrate per il clustering.
Il talk si rivolge a tutti gli sviluppatori di applicazioni web che sono alla ricerca di un ambiente robusto e veloce per i propri lavori, o a chi gia' utilizza uWSGI e vuole
conoscere qualcuna delle nuove funzionalita' introdotte nel ramo di sviluppo.
Django benefits from a thriving third-party ecosystem. This talk will take a deep look at three of the components I have found most useful in my own projects: Haystack for full-text search, Celery for offline processing and Fabric for automated deployments. I'll discuss how we use them for Lanyrd.com, and demonstrate why they deserve a permanent place in your toolbox.
by Pavlos Christoforou
Point Nine provides operations outsourcing and support to large and complex financial institutions.
As part of our day to day responsibilities we are required to process our client's trading activity which generally involves receiving data in various formats and through various protocols, apply transformations, validations and enrichment processes and distribute the resulting data to various third parties, in short Data Plumbing.
The goal of this talk is to introduce the audience to the (vast) field of financial data processing which we believe presents a tremendous opportunity for python and it's community and provide a brief overview of Point Nine's deployment of Python as the main framework for all data plumbing activities.
20th–26th June 2011