A recommender system (recsys) is a no-brainer investment for any service that offers users a wide choice of items. This talk will teach you how to design and build one yourself, informed by lessons learnt shipping a recsys to 5 million MAUs. We'll start with the simplest heuristics and ML models that do the trick, focusing significantly on system design. We'll discuss how to compute, store, and serve recommendations - and also how to build a robust data system with long-term value. We can also nerd out about machine learning and idea jam at the end.

I write at bakerwho.github.io and tweet at @bakerwhodata sometimes. HMU

Have you experienced issues with your Python code while wrangling new data sets and crunching big numbers? Have you wondered what are the places where you could make your Python scripts run faster? Let's talk! Today, I will cover a few options to speed up your data processing operations. This talk can be especially valuable for those who are just starting out in Data Science and Python 
development. Nonetheless, everyone interested in efficient Python is welcome!

The MicroPython part of Evezor Modular Automation System.

or how to link an input device to a liniar actuator over CAN Bus.

I will maybe spend 5 min talking about my anser to  "What is / Teach me programming?" 

For sure I will spend a few moments talking about Python on FPGAs like Fomu and have a few to give out.

https://micropython.org

https://github.com/adafruit/circuitpython

https://github.com/evezor/Edge_Boards

https://github.com/CarlFK/px/blob/master/For_Teachers.md

https://tomu.im/fomu.html

Prefect is air traffic control for the modern data stack. Monitor, coordinate, and orchestrate dataflows between and across your applications. Build pipelines, deploy them anywhere, and configure them remotely. You might just love your workflows again.

Learn how to get up and running with Prefect!

This talk explores the relationship between Kubernetes/cloud infrastructure and the most common Python ASGI app deployment topology (Gunicorn with Uvicorn workers). We'll look at the issues that you'll encounter with this deployment strategy and how you can solve them and make your code simpler and more robust by ditching Gunicorn and taking control of your application.

A walkthrough of the Asynchronous Gateway Server Interface, the API that powers Uvicorn, Starlette and FastAPI.

We'll go through some history, the spec itself, how to write an app and how to write middleware.

By the end of this talk you should have a good idea of what is going on under the hood in your ASGI web server and framework.

This presentation focuses on an exploration of common software development design patterns, best development practices, and a discussion of anti-patterns.

Introduction to processing and serving Geospatial Data using Python. The talk will introduce relevant background information, common data formats, and how to create, modify and serve geospatial data. 

Xpresso is an extensible and composable ASGI web framework, inspired by FastAPI.

It improves on FastAPI by decoupling the dependency injection from the request/response paradigm and decoupling the framework from Pydantic, using PEP 593 annotations. This enables many nice features, like a more flexible dependency injection system, concurrent execution of dependencies and much more customizable processing of request parameters and bodies.

The Observer Pattern enables us to design event-driven systems using loosely coupled components. In this talk, we will learn how, when, and why to use this pattern; we will explore how popular PyPI packages use the pattern; and, we will design a decorator-based Observer to process GitHub events.