List of videos

EuroPython 2022 - When gRPC met Python - presented by Sanket Singh [Wicklow Hall 1 on 2022-07-14] gRPC is one of the most new breakthroughs in the world of client server interaction. Using gRPC our client can directly make a call to a server on a different machine as if it were a local object. gRPC has low latency, high scalability and supports multiple use cases for distributed system. We can even build mobile clients which can communicate to a cloud server. gRPC uses Protocol Buffers which is an open source mechanism for serializing structured data, which makes payloads faster, smaller and simpler. In this talk we will try to understand how can we get started with gRPC in Python. grpcio package of python will be used for the demonstration of the examples and we will cover basics of gRPC as well. We will build a basic gRPC service and define protocol buffers for it. Demonstration of how a client and a server can be made through gRPC and how can they communicate. This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License http://creativecommons.org/licenses/by-nc-sa/4.0/

EuroPython 2022 - Async Django - presented by Ivaylo Donchev [Wicklow Hall 1 on 2022-07-14] This talk will cover: 1. What is the difference between asynchrony and concurrency? 2. Python and Django tools for asynchronous programming. 3. Examples of efficient and inefficient "async" Django views. 4. How does Django handle requests asynchronously - the path from `NGINX` to the database 5. How should we handle thread-blocking operations? 6. A brief history and roadmap of Django's async support This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License http://creativecommons.org/licenses/by-nc-sa/4.0/

EuroPython 2022 - Maps with Django - presented by Paolo Melchiorre [Wicklow Hall 1 on 2022-07-14] A _map_ in a website is the best way to make geographic data easily accessible to users because it represents, in a simple way, the information relating to a specific geographical area and is in fact used by many online services. Implementing a web _map_ can be complex and many adopt the strategy of using external services, but in most cases this strategy turns out to be a major data and cost management problem. In this talk we'll see how to create a web _map_ with the *Python* based web framework *Django* using its *GeoDjango* module, storing geographic data in your local database on which to run geospatial queries. Through this intervention you can learn how to add a _map_ on your website, starting from a simple _map_ based on Spatialite/SQLite up to a more complex and interactive _map_ based on PostGIS/PostgreSQL. Slides: https://www.paulox.net/2022/07/14/europython-2022/ This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License http://creativecommons.org/licenses/by-nc-sa/4.0/

EuroPython 2022 - Walk-through of Django internals - presented by Hitul Mistry [Wicklow Hall 1 on 2022-07-14] ⭐ Talk will start with the introduction of how does end to end web request works internally in Django. ⭐ The talk will introduce users to the internals of ORM, database backend, middleware, etc. ⭐ The talk will also cover, all processes Django does internally to start a server. ⭐ At the end of the talk attendees will be able to understand the internal code structure of Django, how does Django server start, how does Django serves the requests, etc. This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License http://creativecommons.org/licenses/by-nc-sa/4.0/

EuroPython 2022 - Thursday's Lightning Talks - presented by [The Auditorium on 2022-07-14] Signing up is on a first-come-first-served basis. The queue is reset every day in the morning. You may talk about / present (almost) everything with certain boundaries: - no promotion for products of companies, no call for 'we are hiring' (but you may name your employer). - conference announcements are limited to one minute only - one LT per person per conference policy: everyone who has not given an LT at this year's conference, yet, is ahead of you in the queue - keep it short, the shorter the presentations, the more people can give a talk See you there and have fun! This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License http://creativecommons.org/licenses/by-nc-sa/4.0/

The Myth of Neutrality: How AI is widening social divides [EuroPython 2021 - Talk - 2021-07-30 - Optiver] [Online] By Stefanie Stoppel Imagine you're a Black woman having your face not recognized by a government photo booth, no matter how you position yourself in front of the camera. Imagine you're a woman getting your loan request rejected, while your partner - who has a similar income and credit history - gets his approved. Imagine you're an African American man arrested by the police because your face was mistakenly matched to a guy involved in an armed robbery. In these real-world examples, the people affected might not know that they are being treated unfairly by Artificial Intelligence (AI). And even if they did, they would not be able to do anything about it. While they may be used to handling discrimination by humans, algorithmic discrimination is a different story: you cannot argue with the algorithms and, due to their inherent scalability, you might be confronted with them wherever you go. We often expect AI technology to be neutral, but it's far from it. The reason is that - especially when we are not aware of it - we transfer existing stereotypes into these systems through our current data collection practices, our development processes and by how we apply these technologies within our societies. My talk will shed light on how algorithms become discriminatory, how difficult it is to build "fair and responsible" AI, and what we should do to prevent the systems we build from cementing existing injustices. License: This video is licensed under the CC BY-NC-SA 4.0 license: https://creativecommons.org/licenses/by-nc-sa/4.0/ Please see our speaker release agreement for details: https://ep2021.europython.eu/events/speaker-release-agreement/

Pointers? In my Python? It's more likely than you think [EuroPython 2021 - Talk - 2021-07-30 - Optiver] [Online] By Eli Holderness Ever wondered about the difference between is and ==, or why you might need to use deepcopy? Maybe you’ve been stumped by an interview question about object lifetimes, or overriding the __eq__ method. Or, perhaps, you just really want to see some tuples behaving badly. Join me for a tour of some of CPython’s dark memory magic and unintuitive behaviours, where we’ll find out: What pointers are and where you’ll see them in your code; What the id of a Python object is, and why it matters; How CPython can tell when you’re done using an object, and what happens next. Python is a wonderful thing that takes all the complication of memory management away from us. We don’t have to worry about pre-allocating memory for our objects, or remember to free it once we’re done. So, given that we’re not doing it manually, how do these things happen? Do we have to care? Well, sometimes. Maybe. In this talk, we’ll discuss what a pointer is, where they crop in in Python, and what you need to know in order to avoid getting tripped up by them. We’ll also cover the id of an object, why it's implemented the way it is, and why 'equal' is different from 'identical'. Finally, we’ll talk about garbage collection, what reference counting is, and how CPython knows when it’s time to get rid of unused objects. Whether you just want to understand what’s going on under the hood without having to dive into the implementation, or you’re on the hunt for some new diabolical things to do with code (self-referential lists are only the beginning!), come along to this talk and learn about the pointers in your Python. This talk is aimed at anyone with an interest in how Python handles objects in memory, or who’s ever been confused by side-effects popping up in their code. Absolutely no knowledge of C is required, and Python beginners are extremely welcome. License: This video is licensed under the CC BY-NC-SA 4.0 license: https://creativecommons.org/licenses/by-nc-sa/4.0/ Please see our speaker release agreement for details: https://ep2021.europython.eu/events/speaker-release-agreement/

Sliding into Causal Inference, with Python! [EuroPython 2021 - Talk - 2021-07-30 - Parrot [Data Science]] [Online] By Alon Nir What would the world look like if Russia won the cold war? If the Boston Tea Party never happened? And where would we be if Guido van Rossum had decided to go to music school? Unfortunately we don't have the technology to slide into parallel worlds and explore alternative histories. However it turns out we do have the tools to simulate parallel realities and give decent answers to intriguing 'what if' questions. This talk will provide a gentle introduction to these tools, professionally known as Causal Inference. The talk is aimed at data practitioners, preferably with basic knowledge of Python and statistics. That said, the focus of the talk is to nurture an intuitive understanding of the subject first, and implementation second. By the end of the talk I hope audience members could identify causal inference problems, have an intuitive understanding of the different tools they can apply to these problems, and have the appetite to further their learning! The talk will cover the problem of answering causal questions (The Fundamental Problem of Causal Inference) and the main tools to address it. The emphasis will be on intuitive understanding how the different tools work, rather than pesky underlying assumptions, complex notation or convoluted literature. Just enough theory and lines of code to get the message across. Outline: - Introduction to parallel universes and "what if?" questions? - The golden standard for causal inference. We'll discuss randomised controlled experiments and also set the scene for cases these aren't possible. [6 mins] Three key tools: - Differences-in-Differences - Propensity score methods - Synthetic Controls (or: creating an alternate universe on your machine) What's next: A wrap up that includes: - What we didn't cover (a few words about other techniques, DAGs, etc.) - Quick overview of Python tools for causal inference - Where do we go from here - resources, curriculums, readings and communities. Slides and code: https://github.com/alonnir/EuroPython-2021-Talk License: This video is licensed under the CC BY-NC-SA 4.0 license: https://creativecommons.org/licenses/by-nc-sa/4.0/ Please see our speaker release agreement for details: https://ep2021.europython.eu/events/speaker-release-agreement/

The spec you never knew you needed [EuroPython 2021 - Talk - 2021-07-30 - Brian] [Online] By Andy Fundinger Many of the systems we build fail to account for performance, error rates, data correctness, or other customer reliability needs. This talk discusses the basics of service level objectives by comparing them to ordinary functional specifications. It also serves as an introduction to System Reliability Engineering (SRE). License: This video is licensed under the CC BY-NC-SA 3.0 license: https://creativecommons.org/licenses/by-nc-sa/3.0/ Please see our speaker release agreement for details: https://ep2021.europython.eu/events/speaker-release-agreement/