List of videos

The coding conventions that makes our lives easier — Çağıl Uluşahin Sönmez
[EuroPython 2023 — South Hall 2B on 2023-07-20] https://ep2023.europython.eu/session/the-coding-conventions-that-makes-our-lives-easier Discover how coding conventions can enhance code quality, readability, maintainability, and reduce errors. Join us as we discuss the creation and implementation of coding conventions, and how to use linters for maintenance. This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License http://creativecommons.org/licenses/by-nc-sa/4.0/
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Site Unseen: hidden python customization — Jeremiah Paige
[EuroPython 2023 — North Hall on 2023-07-21] https://ep2023.europython.eu/session/site-unseen-hidden-python-customization Python offers us the ability to customize how it starts up. In some cases arbitrary python code can get executed before the first line of your module is reached. This is necessary for some of its dynamic nature, like virtualenvs but can also be harnessed to make the interpreter experience truly personal. This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License http://creativecommons.org/licenses/by-nc-sa/4.0/
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What polars does for you — Ritchie Vink
[EuroPython 2023 — North Hall on 2023-07-20] https://ep2023.europython.eu/session/what-polars-does-for-you Ritchie Vink is the Author of the new Polars DataFrame library. The library that is built for modern hardware. Polars is a query engine written in Rust that focusses on the DataFrame front-end. It is written from scratch in Rust designed to be fast, parallel and memory efficient. This talk we'll go through in the design of Polars and some of its design decisions. This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License http://creativecommons.org/licenses/by-nc-sa/4.0/
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Caching in microservices — Michał Lowas-Rzechonek
[EuroPython 2023 — North Hall on 2023-07-21] https://ep2023.europython.eu/session/caching-in-microservices There are two hard problems in programming: naming things and cache invalidation. I'll cover the latter, in a microservice-based system. Given a fairly standard setup with API Gateway and a backend service with its own database, I'll show how to implement cache that allows us to avoid database queries without modifying API client. The whole talk is based on live coding. This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License http://creativecommons.org/licenses/by-nc-sa/4.0/
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Whisper AI: Live English Subtitles for 96 Languages — Mathias Arens
[EuroPython 2023 — Terrace 2B on 2023-07-20] https://ep2023.europython.eu/session/whisper-ai-live-english-subtitles-for-96-languages Whisper AI, a model from OpenAI, has been largely overlooked despite its impressive ability to accurately transcribe and translate human speech from audio. In this talk I will explore the architecture of the model and explain why it works so well. Additionally, I will live demo the model's capabilities in three languages, showing how you can use it on your own computer to generate English subtitles for a wide range of content. This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License http://creativecommons.org/licenses/by-nc-sa/4.0/
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Python, Visual Studio Code, Copilot - Revolutionizing the way you do data science — Steve Dower
[EuroPython 2023 — Terrace 2A on 2023-07-20] https://ep2023.europython.eu/session/python-visual-studio-code-copilot-revolutionizing-the-way-you-do-data-science Come join this session to check out how Visual Studio Code along with GitHub, Codespaces, and Copilot can significantly improve the data science workflow and take your productivity to the next level. In this talk we will walk through several common Python data science scenarios, showcasing all the productive tooling VS Code has to offer along the way. As a sneak peek, we will be demoing a best-in-class Jupyter Notebooks experience with VS Code Notebooks, a revolutionary new data cleaning / preparation experience with Data Wrangler in VS Code, Copilot that helps you write code and fix issues faster, and more! This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License http://creativecommons.org/licenses/by-nc-sa/4.0/
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Story Generation using Stable Diffusion in Python — Nilesh Jain
[EuroPython 2023 — South Hall 2B on 2023-07-20] https://ep2023.europython.eu/session/story-generation-using-stable-diffusion-in-python Recently, most works focus on synthesizing independent images, while for real-world applications, it is common and necessary to generate a series of coherent images for story-telling. In this work, we mainly focus on story visualization and continuation tasks and propose AR-LDM, a latent diffusion model auto-regressively conditioned on history captions and generated images. To my best knowledge, this is the first work successfully leveraging diffusion models for coherent visual story synthesizing. This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License http://creativecommons.org/licenses/by-nc-sa/4.0/
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The challenges of doing Infra-As-Code without "the cloud" — Nicolas Demarchi
[EuroPython 2023 — Terrace 2A on 2023-07-20] https://ep2023.europython.eu/session/the-challenges-of-doing-infra-as-code-without-the-cloud How do you implement Infrastructure-as-Code (IaC) in a non-cloud environment? This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License http://creativecommons.org/licenses/by-nc-sa/4.0/
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Poisoned pickles make you ill — Adrian Gonzalez-Martin
[EuroPython 2023 — South Hall 2A on 2023-07-20] https://ep2023.europython.eu/session/poisoned-pickles-make-you-ill Don’t you love pickles? In the data science space, the pickle module has become one of the most popular ways to serialise and distribute machine learning models - yet, pickles introduce a wide range of problems. For starters, it is incredibly easy to poison a pickle. Once this happens, a poisoned pickle can be used by an attacker to inject any arbitrary code into your ML pipelines. And what’s even worse: it’s incredibly hard to detect if a pickle has been poisoned! Good news? Help is on the way! You now have access to an increasing number of tools to help you generate higher-quality pickles. And when those are not enough, you can always draw inspiration from the DevOps movement and their trust-or-discard processes. This talk will show you how widespread pickles are and how easy it is to poison models serialised with pickle, but also how easy it is to start protecting them from attacks. This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License http://creativecommons.org/licenses/by-nc-sa/4.0/
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