List of videos

Magnus Hagander - Enhancing your Python database experience with PostgreSQL

Keynote of the first day of PyCon SE 2015

Robin Linderborg Target audience: Beginners A gentle introduction to data analysis and visualization in Python using the Pandas library. We will explore how to clean, restructure, analyze and visualize data sets.

Belhorma Bendebiche Target audience: Advanced users Docker is a tool that helps containerize, package and run applications in their own isolated environment, greatly simplifying the deployment process.This talk is about how we containerized some of our Python services at Spotify, the challenges faced and how we solved them.

Roelof Pieters Target audience: Advanced users Deep Learning, anyone who has followed machine learning over the past years has heard it. In this talk I will go past the hype and show what deep learning actually means and how one goes about solving complex machine learning task with a minimum amount of code, with the help of theano, an amazing python library for deep learning. I will show examples from my own research in language and vision, and hope to show that Deep Learning is not only fun, but also not as difficult as one might expect.

Hendrik Heuer Target audience: Advanced users If you convert words into numbers, you can do interesting things with them. You can compare the topics in a book, make better translations and tell if a sentence is positive or negative. Python libraries like gensim and spaCy make it easy to play with this for fun, profit or social science.

Spring I/O 2024 - 30-31 May, Barcelona Slides: https://2024.springio.net/slides/its-all-in-the-mix-producing-production-ready-apps-with-spring-boot-springio24.pdf Repo: https://github.com/jkuipers/in-the-mix-demos You already know how to develop Spring Boot applications: implement web controllers, work with databases, integrate security and so on. But just like releasing a song doesn’t end with recording the individual instruments, there’s more to getting an application production-ready than implementing functional requirements. In this tips & tricks talk Joris will explain various aspects of “mixing and mastering” your applications for release. He’ll cover configuring metrics, tuning container image layers, supporting HTTP response caching headers, securing actuator endpoints incl. masking of exposed secrets, integrating custom auto-configuration with Boot’s own and many other topics. If you want to become a bootiful producer as well, then don’t miss out on this demo-packed presentation and let your application become a nr. 1 hit!

Spring I/O 2024 - 30-31 May, Barcelona Slides: https://speakerdeck.com/jonatan_ivanov/2024-05-31-spring-io-micrometer-mastery-unleash-advanced-observability-in-your-jvm-apps Repo: https://github.com/jonatan-ivanov/teahouse/tree/2024-springio Is your application a black box? Is your current observability instrumentation not good enough? Do you want to add more to your metrics and distributed tracing? Join us and unlock the full potential of Micrometer and its cutting-edge observability features! Dive into: Micrometer Observation API: Instrument once and have multiple benefits out of it. Observation Conventions: Instrumentation with standardized naming and tagging. Automated Documentation: Effortlessly generate rich observability descriptions from your code. We’ll showcase: Practical code examples for instrumenting real-world applications. Advanced techniques to extract deeper insights and troubleshoot issues faster. Real-world use cases demonstrating the power of Micrometer’s observability toolkit. Ready to elevate your observability game using the industry’s golden standard? This talk is your one-stop shop for Micrometer mastery!

Spring I/O 2024 - 30-31 May, Barcelona Speaker: Nele Lea Uhlemann Slides: https://www.slideshare.net/slideshow/spring-i-o-deep-and-brief-dive-into-causality/269620850 How to bring causality to the forefront in Spring services and systems? When building and running complex systems, we encounter multiple options, and various tools address causality concerning service-to-service invocation. Traces, Workflows and Service Meshes provide insights into causal relationships. They make dependencies between different services, events, and transactions visible. Let’s dive into the technical choices available to make causality visible in our systems and see how they integrate with Spring services. The session includes examples of Dapr workflows, displaying collected traces in Jaeger, Istio’s call graphs with Kiali. We delve into the purpose of causality in each tool, discussing their differences and similarities. Discovering how operators and application engineers perceive causal relationships differently is not just insightful—it’s a key factor that drives better collaboration and communication among engineering teams. This, in turn, leads to more effective system design, debugging, and troubleshooting.