List of videos

[EuroPython 2024 — South Hall 2B on 2024-07-11] Open Source Sustainability Panel by Armin Ronacher, Çağıl Uluşahin Sönmez, Artur Czepiel, Deb Nicholson, Anwesha Das, Samuel Colvin https://ep2024.europython.eu/session/open-source-sustainability-panel The motivation behind this panel is to provide insights to the audience with regards to funding open source projects, manage the community interaction, and options people might find attractive in order to be paid while doing Open source. We can also observe the sustainability of a project by the amount of contributors, even if it’s code or activities around it like conferences, communities, and NGOs that support the ecosystem. --- This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License: https://creativecommons.org/licenses/by-nc-sa/4.0/

[EuroPython 2024 — South Hall 2B on 2024-07-11] Many ways to be a Python contributor by Paolo Melchiorre https://ep2024.europython.eu/session/many-ways-to-be-a-python-contributor **Python** is an increasingly used language and the number of potential contributors is growing increasingly. **Newcomers** to the community have a lot of documentation to guide them to transform from mere users to contributors. There are many ways to **contribute** to Python or one of its packages or frameworks, and we will try to see some of them together. In this talk, new Python developers will discover new ways to get involved in the community, and **community members** will get ideas for getting new people involved. More info on my website 👇 https://www.paulox.net/2024/07/11/europython-2024/ --- This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License: https://creativecommons.org/licenses/by-nc-sa/4.0/

[EuroPython 2024 — South Hall 2B on 2024-07-11] Python Unplugged: Mining for Hidden 'Batteries by Torsten Zielke https://ep2024.europython.eu/session/python-unplugged-mining-for-hidden-batteries Python prides itself on its 'batteries included' philosophy, but beyond the well-trodden modules lie hidden gems awaiting discovery. This talk ventures into the depths of the Python standard library to unearth lesser-known features from itertools, collections, functools, typing and more. All of these tools are already built into every standard python installation and no "(uv) pip install" is necessary. Many if not all of those are likely already known to old fashioned pythonistas, but for beginners (1-2years) there will be something new to learn, while for intermediate python developers there might be at least a few more gems to discover. By delving into these underutilized modules, attendees will gain a richer understanding of Python's built-in capabilities and learn how to write more pythonic code. 00:00 Introduction 05:30 Chapter 1: Fetching data 05:42 urllib 06:48 TypedDict 09:02 Batching 09:44 islice 11:10 batched 11:50 DictWriter 15:32 Chapter 2: Cleaning data 17:22 pairwise 19:16 chain 22:20 ChainMap¹ 23:36 Multiple Context Managers 25:54 Doctest 27:44 yield from 29:44 misusing return value in generators 33:03 NamedTuple² 33:06 Chapter 3: Processing data 34:51 defaultdict 36:28 Counter 39:55 groupby 43:10 reduce / tee Corrections 22:21 ¹itertools.ChainMap is wrong: collections.ChainMap is right 33:06 ²We also need to yield one more time at the end for the case, where the last books are lost books. Maybe even yield namedtuple(book: Book, lost: bool) --- This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License: https://creativecommons.org/licenses/by-nc-sa/4.0/

[EuroPython 2024 — Terrace 2A on 2024-07-11] Profile, Optimize, Repeat: One Core Is All You Need™ by Valentin Nieper, Jonathan Striebel https://ep2024.europython.eu/session/profile-optimize-repeat-one-core-is-all-you-needtm Your data analysis pipeline works. Nice! Could it be faster? Probably. Do you need to parallelize? Not yet. Discover optimization steps that boost the performance of your data analysis pipeline on a single core, reducing time & costs. This walkthrough shows tools to identify bottlenecks via profiling, and strategies to mitigate those, demonstrating them in an example. To improve our memory and runtime performance we will use numpy, numba jit-ing and pybind11 extensions. --- This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License: https://creativecommons.org/licenses/by-nc-sa/4.0/

[EuroPython 2024 — Terrace 2A on 2024-07-11] Forecasting the future with EarthPT by Mike Smith https://ep2024.europython.eu/session/forecasting-the-future-with-earthpt We introduce EarthPT -- an open source Earth Observation (EO) pretrained transformer written in Python and PyTorch. EarthPT is a 700 million parameter decoding transformer foundation model trained in an autoregressive self-supervised manner and developed specifically with EO use-cases in mind. EarthPT is trained on time series derived from satellite imagery, and can accurately predict future pixel-level surface reflectances across the 400-2300 nm range well into the future. For example, forecasts of the evolution of the Normalised Difference Vegetation Index (NDVI) have a typical error of approximately 0.05 (over a natural range of -1 - 1) at the pixel level over a five month test set horizon, out-performing simple phase-folded models based on historical averaging. We also demonstrate that embeddings learnt by EarthPT hold semantically meaningful information and could be exploited for downstream tasks such as highly granular, dynamic land use classification, crop yield, and drought prediction. Excitingly, we note that the abundance of EO data provides us with -- in theory -- quadrillions of training tokens. Therefore, if we assume that EarthPT follows neural scaling laws akin to those derived for Large Language Models (LLMs), there is currently no data-imposed limit to scaling EarthPT and other similar ‘Large Observation Models.’ EarthPT is released under the MIT licence here: https://github.com/aspiaspace/EarthPT. --- This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License: https://creativecommons.org/licenses/by-nc-sa/4.0/

[EuroPython 2024 — Terrace 2A on 2024-07-11] NLP Application in Cases of Violence Against Women by Deborah Foroni https://ep2024.europython.eu/session/nlp-application-in-cases-of-violence-against-women Domestic violence is a widespread problem, one which demands attention and policy fixes. But available data is largely unstructured, making analysis difficult for both researchers and policy makers. In this talk, I'll show you how Python helped me to retrieve, structure, and classify violence victims' testimony. I'll show which APIs and libraries allowed me to retrieve the woman's testimony from YouTube, turn their speech into text, and then analyze the text itself. You'll come away knowing not just some new Python techniques, but also how those techniques can be used to improve our society. --- This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License: https://creativecommons.org/licenses/by-nc-sa/4.0/

[EuroPython 2024 — Terrace 2A on 2024-07-11] How to destroy the world using Python and a synthetic virus by Helena Gómez Pozo, Marina Moro López https://ep2024.europython.eu/session/how-to-destroy-the-world-using-python-and-a-synthetic-virus Would you believe us if we told you that we could create a potentially dangerous virus using Python? This is theoretically possible thanks to synthetic biology, the field of biotechnology that studies how to create and modify organisms. This discipline is used, for example, to genetically modify bacteria to produce the insulin that diabetics will later use. Obviously, such a powerful tool has its possible evil side, which is what we will explore in this talk. After a little biology and genetics class, we will explain a practical example of how to use synthetic biology through a Python script to modify an existing virus and turn it into a deadly one. Thus, you as an attendee will be able to see the potential of this field and how Python can make it easier, not only in the example of the evil virus, but also in other healthcare applications. --- This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License: https://creativecommons.org/licenses/by-nc-sa/4.0/

[EuroPython 2024 — Terrace 2A on 2024-07-11] Python on the Rocks: Crafting a Smooth Blend with RocksDB by Ria Bhatia https://ep2024.europython.eu/session/python-on-the-rocks-crafting-a-smooth-blend-with-rocksdb When it comes to selecting a high-performance database for your application, RocksDB emerges as a top contender, offering a lightweight and efficient solution. RocksDB brings a robust set of features to the table, but what lies beneath its surface? Let's dive into the world of RocksDB with Python, uncovering the mysteries of its internal workings and exploring the principles that make data storage and retrieval seamlessly efficient. Get ready to equip yourself with the knowledge to harness the full potential of RocksDB and elevate your applications to new heights. --- This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License: https://creativecommons.org/licenses/by-nc-sa/4.0/

[EuroPython 2024 — Terrace 2A on 2024-07-11] Mastering Design Patterns: Crafting Elegant Solutions with a Confidence by Petr Balogh https://ep2024.europython.eu/session/mastering-design-patterns-crafting-elegant-solutions-with-a-confidence Join us for an illuminating 30-minute journey into the world of design patterns at EuroPython 2024. Design patterns aren't just abstract concepts; they are the architectural blueprints that empower developers to create elegant and maintainable software solutions. In this session, we bridge the gap between theory and practice, offering practical insights for developers of all levels. We'll delve into a curated selection of design patterns, from foundational creational patterns to advanced behavioral patterns, showcasing their real-world applications and transformative impact on Python development. Through a blend of theory and practice, attendees will gain a comprehensive understanding of how to identify common design problems and apply appropriate patterns to solve them efficiently. Using engaging examples and hands-on exercises, we'll equip attendees with the knowledge and skills needed to architect cleaner, more maintainable codebases. Whether you're a seasoned veteran or a curious novice, this presentation offers a comprehensive roadmap for mastering Python design patterns and architecting software solutions with grace. --- This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License: https://creativecommons.org/licenses/by-nc-sa/4.0/