February 24-26, 2016
Montreal, Canada
Python Conference
Python
Kubernetes de Google est une plateforme d'orchestration pour des conteneurs Docker sur systèmes Linux. Afin d'automatiser son utilisation avec nos différents outils internes, nous avons écrit un module Python et un module Ansible pour procéder vers du déploiement continu. Nous aborderons les différents composants de Kubernetes, un survol de son intégration avec Mesos et une démonstration d'intégration avec Ansible.
Python
With the high demand of data analytics, this presentation will focus on how to build an analytics dashboard with Flask and the HighCharts API. First, we will look at how to set up a basic Flask app with an elegant UI using Bootstrap. Then, we will look at how to use the HighCharts API and integrate some graphs. Finally, well deploy the app to Heroku and discuss advanced topics such as database for dynamic chart update, security, and other APIs!
Python
Si à la sortie de Python 3.0, avoir du code compatible à la fois avec Python 2 et Python 3 était assez difficile, ce n'est plus le cas actuellement. Des librairies comme "python-modernize" ou "future" vous simplifie grandement la vie. Nous verrons comment ces librairies fonctionnent et quelles sont les erreurs à éviter.
Python
Django is an “all-in-one” web development platform. Built-in features include full templating technology, routing and object-relational mapping. Using Django’s ORM capabilities, frees you from having to write your own database access code, so you can focus the application you wish to build. The Django ORM can even create and manage the database for you! Learn how to create objects for ORM, and map properties to columns in your database.
Python
Data is everywhere, and much of our work as developers is to present it in a way that is useful, usable, and desirable. In this talk, I will walk through some practical examples of using Python's superb data processing capabilities to churn through datasets, and use D3 in your presentation layer to display interactive, beautiful infographics.
Python
From 'Space Oddity' to 'Blackstar', Bowie inspired us with his diverse personas. What can IBM Watson reveal about those iconic characters through natural language analysis? That's the mission of 'Ziggy' a little Python app that builds a database of songs, and digs into the style and tone of writing within them. This session explores the findings, and shows how it works. We'll consider real world use cases, and future iterations.
Python
You are growing your e-commerce business, so what’s the next move that will get you your next sale? Exploratory data analysis to identify opportunities is key. We’ll start small, using Python to illustrate some effective and simple data explorations. Then we’ll talk about how we scaled that at Shopify to automatically give data-driven advices to our 175k+ merchants using PySpark. You'll be able to apply those tricks in your favorite language too.
Python
Django, Flask ou Falcon ? REST ou GraphQL ? Comment rendre une API Web compréhensible par les (ré)utilisateurs et par les futurs mainteneurs ? Quels sacrifices (performances, sémantique, utilisabilité, etc) sont possibles ? Quelle stratégie d'évolutivité mettre en place ? Quelles statistiques pour quelles décisions ?
Python
We'll examine the "Meta" inner-class pattern used in popular python libraries such as Django, Factory Boy and Django REST Framework. The use of inner classes is part of a technique that allows for library creators to place constraints on provided customization points at class definition time. This talk will span the Python type hierarchy, how to define new types and review magic methods related to class construction.
Python
Depending on who you ask, PEP 484's Type Hints are either the next big thing in Python, or the harbinger of doom upon our entire community. Which is it? Let's find out by looking at a language that isn't Python in any way at all!
Python
This is a story about the unit tests suite at the National Film Board of Canada. An analysis and presentation was done on September 2013. The suite was too long so we were not always running our tests locally.
During the presentation, a summary of the analysis will be given and you will be told a series of tricks that helped us accelerate the performance of these mysterious tests.
During the presentation, a summary of the analysis will be given and you will be told a series of tricks that helped us accelerate the performance of these mysterious tests.
Python
Python 3.5 est sortie le 13 septembre 2015 et apporte comme à chaque version son lot de nouveautés : langage normalisée pour le typage optionnel, un opérateur pour le calcul de matrices, de nouvelles expressions pour la programmation asynchrone ou une nouvelle fonction beaucoup plus rapide pour le scan de répertoire. Nous ferons un tour des nouveautés et nous nous attarderons sur les plus importantes, notamment et surtout le type hinting.
Python
Test-driven development's great, but what happens when you find yourself working on code where automated testing took a back seat to being shipped? This talk looks at techniques for automated testing of late-stage or even production code, and how to use this to fix bugs in your code. Testing late in life isn't a lost cause any more!
Montreal 2016
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