List of videos

Jameson Rollins - LIGO: The Dawn of Gravitational Wave Astronomy [EuroPython 2016] [20 July 2016] [Bilbao, Euskadi, Spain] (https://ep2016.europython.eu//conference/talks/keynote-ligo) Scientists have been searching for the elusive gravitational wave for more than half a century. Hear how they finally found them, and the role that Python played in the discovery. ----- Scientists have been searching for the elusive gravitational wave for more than half a century. On September 14, 2015, the Laser Interferometer Gravitational-wave Observatory (LIGO) finally observed the gravitational wave signature from the merger of two black holes. This detection marks the dawn of a new age of _gravitational wave astronomy_, where we routinely hear the sounds emanating from deep within the most energetic events in the Universe. This talk will cover the events leading up to one of the most important discoveries of the last century, and the myriad of ways in which Python enabled the effort.

Alexys Jacob - Using Service Discovery to build dynamic python applications [EuroPython 2016] [20 July 2016] [Bilbao, Euskadi, Spain] (https://ep2016.europython.eu//conference/talks/service-discovery-for-dynamic-python-applications) Let's compare the usage of three major **service discovery** technologies to build a dynamic and distributed python application ! This talk will be about **consul**, **etcd** and **zookeeper** and their python bindings and will feature code along with a live demo. ----- This talk will **showcase and compare** three Service Discovery technologies and their usage to **build a dynamic and distributed python application** : - consul - etcd - zookeeper After a short introduction to service discovery, we will **iterate and compare** how we can address the concrete and somewhat complex design of our python application using each technology. We'll then be able to discuss their strengths, weaknesses and python bindings and finally showcase the application in a demo. All the source code will of course be made available for the audience to benefit and start from for their own use !

Victor Stinner - FAT Python: a new static optimizer for Python 3.6 [EuroPython 2016] [20 July 2016] [Bilbao, Euskadi, Spain] (https://ep2016.europython.eu//conference/talks/fat-python-a-new-static-optimizer-for-python-36) The Python language is hard to optimize. Let's see how guards checked at runtime allows to implement new optimizations without breaking the Python semantic. ----- (Almost) everything in Python is mutable which makes Python a language very difficult to optimize. Most optimizations rely on assumptions, for example that builtin functions are not replaced. Optimizing Python requires a trigger to disable optimization when an assumption is no more true. FAT Python exactly does that with guards checked at runtime. For example, an optimization relying on the builtin len() function is disabled when the function is replaced. Guards allows to implement various optimizations. Examples: loop unrolling (duplicate the loop body), constant folding (propagates constants), copy builtins to constants, remove unused local variables, etc. FAT Python implements guards and an optimizer rewriting the Abstract Syntax Tree (AST). The optimizer is implemented in Python so it's easy to enhance it and implement new optimizations. FAT Python uses a static optimizer, it is less powerful than a JIT compiler like PyPy with tracing, but it was written to be integrated into CPython. I wrote 3 PEP (509, 510, 511) targeting Python 3.6. Some changes to support FAT Python have already been merged into Python 3.6. We will also see other pending patches to optimize CPython core, and the bytecode project which allows to modify bytecode, it also includes a peephole optimizer written in pure Python. Links: * http://faster-cpython.readthedocs.org/fat_python.html * http://fatoptimizer.readthedocs.org/ * http://bytecode.readthedocs.org/

Alessandro Molina - Moving away from NodeJS to a pure python solution for assets [EuroPython 2016] [20 July 2016] [Bilbao, Euskadi, Spain] (https://ep2016.europython.eu//conference/talks/moving-away-from-nodejs-to-a-pure-python-solution-for-assets) The talk covers the complexity of managing an asset transformation pipeline through tools like Grunt and NodeJS, especially during deploy, test suites or when a new development environment has to be configured from scratch, and showcase how this complexity can be dodged by using tools like WebAssets and DukPy. No more need to keep around two languages, two package management systems and manage your dependencies between them by youself. Just pip install your app and have it working. ----- When working with WebApplications it is common to rely on an asset management pipeline to compile scripts, minify css or preprocess images. Most of the tools available today rely on JavaScript to perform those steps and always forced Python developers to rely on NodeJS to have grunt perform the pipeline tasks, coffee-script to compile their CoffeeScript or lessc to build their css. This causes longer setup times for projects newcomers, complex development environment, working with two package managers and dependencies that you use once a week but still need to be there. The talk will showcase the DukPy project and focus on how it is possible to build a pure python asset pipeline relying on DukPy to run javascript tools and WebAssets framework to perform the most common tasks that usually Nodejs and tools like Grunt handle for us, greatly reducing the development environment complexity and making its setup as simple as ‘pip install’. The talk aims at explaining the complexity of managing an asset transformation pipeline through tools like Grunt, especially during deploy, test suites or when a new development environment has to be created, and showcase how this complexity can be dodged by using tools like WebAssets and DukPy. No more need to keep around two languages, two package management systems and manage your dependencies between them by youself. Just pip install your app and have it working.

Miguel Reguero/Rodrigo Núñez - Cybersecurity in the financial sector with Python [EuroPython 2016] [21 July 2016] [Bilbao, Euskadi, Spain] (https://ep2016.europython.eu//conference/talks/ciberseguridad-en-el-sector-financiero-con-python) When people talk about cybersecurity they often think about ethical hacking and exploits, that is but a fraction of what cybersecurity is about, today we are going to talk about another aspect, which is often deemed as not too important.

Fabio Pliger/Marc-André Lemburg - EuroPython 2017: Help us build the next edition! [EuroPython 2016] [21 July 2016] [Bilbao, Euskadi, Spain] (https://ep2016.europython.eu//conference/talks/europython-2017-help-us-build-the-next-edition) We need help with organizing and running EuroPython 2017. In this session, we will explain how the EuroPython workgroup model works and where you could help. ----- We need help with organizing and running EuroPython 2017 In this session, we will explain how the EuroPython workgroup model works and where you could help.

Fabio Pliger/Marc-André Lemburg - EPS General Assembly [EuroPython 2016] [21 July 2016] [Bilbao, Euskadi, Spain] (https://ep2016.europython.eu//conference/talks/eps-general-assembly) This is where the EuroPython Society (EPS) board gives its reports, resolutions are passed and the EPS members can vote in a new EPS board.

Helen Sherwood-Taylor - Managing Mocks [EuroPython 2016] [21 July 2016] [Bilbao, Euskadi, Spain] (https://ep2016.europython.eu//conference/talks/managing-mocks) Mocking is a valuable technique for writing tests but mocking effectively is often a stumbling block for many developers and can raise questions about its overall value as a technique. There will be a brief introduction to mocking, then a look at features and techniques of Python’s unittest.mock library and cover some useful tips and common scenarios, so this will be useful to those who have some experience mocking but would like to do so more effectively. ----- Mocking is a valuable technique for writing tests but mocking effectively is often a stumbling block for many developers and can raise questions about its overall value as a technique. The audience will have some familiarity with unit testing and may have tried mocking before, but some introduction will be provided for those who haven’t. We will look at some features and techniques of Python’s unittest.mock library and cover some useful tips and common scenarios, so this will be useful to those who have some experience mocking but would like to do so more effectively. Summary of proposed content: 1. A short introduction to what mocking is and why it is useful. 2. Tour of Python’s mock library and how to make the most of it * Creating and manipulating Mock objects * Setting up return values and side effects to control test environment * Inspecting mocks - different ways to examine a mock object and find out what happened during the test * How and where to patch 3. Common mocking situations - scenarios where mocking is particularly useful and/or tricky to get right. For example - date/time, filesystem, read only properties 4. Some discussion of when mocking is and isn't helpful. Focus will be mainly on Python's unittest.mock module but we will also have a brief look at some other useful libraries.

Mihai Iachimovschi - Real virtual environments without virtualenv [EuroPython 2016] [21 July 2016] [Bilbao, Euskadi, Spain] (https://ep2016.europython.eu//conference/talks/real-virtual-environments-without-virtualenv) Virtualenv is a great tool for the development environment but it's definitely not suitable for every use case. Also, Docker is great for running the application in production, but not everyone that use it in production tried to use it in the development environment. Why not use the same tool from the beginning of the project and until it hits the production in a uniform stack of tooling? This talk will show use cases of using Docker in the process of development as well. ----- The process of developing using Python is very straightforward and easy. Still, each and every developer has his own style of developing and building his entire dev environment. Most of us use virtualenvs which are reliable and comfortable to use. But there are some issues. For instance, the repeatability and immutability of the built environment are not guaranteed. Virtualenv does a lot of work that targets the direction of somehow isolated and independent environments. They are *almost* *fully* repeatable. In any team, we can hear the notorious expression "It works for me!". For some time now, I am using Docker instead of virtualenv for building custom and really-virtual environments that are entirely isolated. The containers are immutable and consistent, so this workflow guarantees repeatability. Using such technique, not only enables the user to have unique and immutable environments, it also allows de developer to create full app architecture that can then be tested and deployed as is. So the production version will be in identical conditions as the one from the development environment. These features are not provided by virtualenv at all. The goal of this exercise is to try to use totally different tooling for building the application from its first line of code until the production.