March 8-10, 2017
Montreal, Canada

Python Conference

Python Neural networks have seen renewed interest from data scientists and machine learning experts for their ability to accurately classify high-dimensional data like images and sound. In this session we will discuss the fundamental algorithms behind neural networks, and develop an intuition for how to train a deep neural network. We will then use the algorithms we have learned to train a simple handwritten digit recognizer using TensorFlow.
Python Async I/O is fashionable with good reason: its low per-connection overhead lets you scale an I/O-intensive workflow better than threads or processes. But there are drawbacks. I'll explain the pros and cons, show how they bit in a real-world project, and help you to weigh the options for your next project.
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 Come learn how to better communicate between Python services. We'll use simple-to-follow examples and go from a service with undocumented endpoints to one which has full docs and validation on requests. Learn how to use Swagger tooling for python, including the bravado (client) and pyramid_swagger (server) libraries. In the end, you'll (hopefully!) find nirvana and make the machines do all the hard work for you.
Python Je travaille avec le gouvernement français à l’ouverture des données à l’échelle nationale. J’ai eu l’occasion de travailler à deux reprise sur des données brutes qu’il fallait (re)construire en données avec un historique facilement exploitable. Cette session sera l’occasion de décrire les enjeux de l’opendata et les outils Python qui ont été développés pour mener à bien ces projets.
Python Object-Relational mappers are nothing new. The popular Django web framework's ORM has been around for more than ten years now.

Historically, ORMs have only really been good for simple queries and make upgrading models difficult. Not any more!

These days, Django features support for some very complex queries, and a migration platform that's actually enjoyable to use. I've forgotten how to code SQL: find out if you can too!
Python Data never sleeps, so this talk will provide you strong foundations on libraries, frameworks, and utilities to build pipelines, analyze data, and help you make better predictions. We will start by looking at Python libraries (Pandas, Numpy, Theanos) and then we will integrate them with powerful APIs (Google Webmaster Tools, Google Adwords, and Google Analytics). Then, we will
shift our focus to e-Commerce and Data Warehousing applications.
Python Python is one of the most popular programming languages, and one of the most flexible. You can create basically any type of code you need: object oriented, procedural, functional... It can be used to create any type of application, and is used in many big data scenarios. You can also get up and running in a short period of time if you’re experienced with another programming language. The goal of this session is to get you up and running in 60min.
Python While its name may seem to imply that it's Python-only, uWSGI is a combination application server, proxy, process manager/monitor, async queue, cross-language RPC framework, and more.

We'll take a look at the broad features that make uWSGI an interesting option as an application server, and then show you how to concurrently serve Python, PHP, Ruby, Perl, Go, Lua, and Clojure applications, and use the built-in RPC, queue and in-memory cache.
Python Writing tests is tedious. Rather than writing your own tests, you should get your computer to do it for you! Hypothesis is a Python testing library that lets you specify properties of your code that should hold, and it generates the data for you. This means that you get literally thousands of test cases with minimal effort. See how you can get better tests by writing fewer test cases!
Python The CPython interpreter have seen a fair share of security incidents. As a core contributor and member of the security team I have been involved in fixing security bugs and hardening Python. You will learn about past vulnerabilities in Python's dict implementation and standard library modules, how to avoid common mistakes and recent improvements of ssl, hashlib and random number generator.

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Montreal 2017 sponsored by