PyCon Session List
5 Things about fastAPI I wish we had known beforehand
Alexander CS Hendorf
5 Things about fastAPI I wish we had known beforehand - An opinionated talk about fastAPI in practice.
Accelerating Python Code
Jens Nie
Struggling to get your Python simulation prototype to production because you think it's too slow? Let's speed it up using #PyPy, #numpy, #numba and friends.
An unbiased evaluation of environment management and packaging tools
Anna-Lena Popkes
Python packaging is quickly evolving and new tools pop up on a regular basis. Lots of talks and posts on packaging exist but none of them give a structured, unbiased overview of the available tools. Let's change this!
Aspect-oriented Programming - Diving deep into Decorators
Mike Müller
Effectively programming cross-cutting task with decorators - Code re-use via the @ symbol
Behind the Scenes of tox: The Journey of Rewriting a Python Tool with more than 10 Million Monthly Downloads
Jürgen Gmach
Behind the Scenes of tox: The Journey of Rewriting a Python Tool with Over 10 Million Monthly Downloads
BLE and Python: How to build a simple BLE project on Linux with Python
Bruno Vollmer
Learn what BLE is and how to use it with Python. @bvollmer5 shows in this talk how you can easily build a Linux-based BLE server for your next project.
Bringing NLP to Production (an end to end story about some multi-language NLP services)
Larissa Haas, Jonathan Brandt
How to bring NLP models to production? Following a use case that runs for over 1 year in 10 different languages, this talk will enable you to ask the right questions before starting to deploy NLP services.
Building Hexagonal Python Services
Shahriyar Rzayev
Building Hexagonal Python Services from scratch using Repository, Unit of Work and Use Cases patterns
Code Cleanup: A Data Scientist's Guide to Sparkling Code
Corrie Bartelheimer
Does your production code look like it’s been copied from Untitled12.ipynb? Are your engineers complaining about the code but nobody got time to clean things up? Check out this talk to learn some of the basics of clean coding and how to implement them in a data science team.
Data Kata: Ensemble programming with Pydantic #1
Lev Konstantinovskiy, Gregor Riegler, Nitsan Avni
Write code as an ensemble to solve a data validation problem using P. Working together is not just about code - we will see what it is like to listen to colleagues, make typos in front of everyone, become a supportive team member, defend our ideas and maybe even accept criticism.
Data Kata: Ensemble programming with Pydantic #2
Lev Konstantinovskiy, Gregor Riegler, Nitsan Avni
Write code as an ensemble to solve a data validation problem with Py. Working together is not just about code - we will see what it is like to listen to colleagues, make typos in front of everyone, become a supportive team member, defend our ideas and maybe even accept criticism.
Data-driven design for the Dask scheduler
Guido Imperiale
Historically, changes in the scheduling algorithm of Dask have often been based on theory, single use cases, or even gut feeling. Coiled has now moved to using hard, comprehensive performance metrics for all changes - and it's been a turning point!
FastAPI and Celery: Building Reliable Web Applications with TDD
Avanindra Kumar Pandeya
Build reliable and maintainable APIs with FastAPI and Celery using test-driven development (TDD)! Learn how to set up a testing environment, write unit and integration tests, and use mocks and fixtures to isolate and control the tests.
Fear the mutants. Love the mutants.
Max Kahan
Developers often use code coverage as a target, which makes it a bad measure of test quality. Mutation testing changes the game: use your code to create mutants that break your tests, and you'll quickly start to write better tests! Come and learn to use it in your CI/CD process.
From notebook to pipeline in no time with LineaPy
Thomas Fraunholz
The nightmare before data science production: You found a working prototype for your problem using a Jupyter notebook and now it's time to build a production grade solution from that notebook. The good news is, there's finally a cure: The open-source python package LineaPy!
Giving and Receiving Great Feedback through PRs
David Andersson
Do you struggle with PRs? Have you ever had to change code even though you disagreed with the change? Have you ever given feedback only to get into a comment war? We'll discuss how to give and receive feedback optimally without the communication problems
Great Security Is One Question Away
Wiktoria Dalach
Security doesn't have to be a nightmare. The 3rd hack will surprise you.
How to connect your application to the world (and avoid sleepless nights)
Luis Fernando Alvarez
Come and explore some of the common techniques to help you build reliable distributed systems in Python
Introducing FastKafka
Tvrtko Sternak
"Don't miss our talk on FastKafka, a Python library for easy Kafka communication! #PyCon #Kafka #FastKafka"
Introduction to Async programming
Dishant Sethi
Asynchronous programming has been gaining a lot of attention in the past few years, and for good reason. This session is going to be an intro to async programming in python.
Machine Learning Lifecycle for NLP Classification in E-Commerce
Gunar Maiwald, Tobias Senst
idealo.de presents its MLOps solution and ML lifecycle for product classification
Maps with Django
Paolo Melchiorre
"Maps with Django" Keeping in mind the Pythonic principle that simple is better than complex 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.
Maximizing Efficiency and Scalability in Open-Source MLOps: A Step-by-Step Approach
Paul Elvers
Novel approach to #MLOps combines open-source tech with cloud computing to build scalable, maintainable ML system accessible to ML Engineers & Data Scientists.
MLOps in practice: our journey from batch to real-time inference
Theodore Meynard
I will present the challenges we encountered while migrating an ML model from batch to real-time predictions and how we handled them.
Modern typed python: dive into a mature ecosystem from web dev to machine learning
samsja
Typing is at the center of „modern Python“, and tools (mypy, beartype) and libraries (FastAPI, SQLModel, Pydantic, DocArray) based on it are slowly eating the Python world. This talks explores the benefits of Python type hints, and shows how they are infiltrating the next big do
Monorepos with Python
AbdealiLoKo
Monorepos have been successful in other communities - how does it work in Python ?
Practical Session: Learning on Heterogeneous Graphs with PyG
Ramona Bendias, Matthias Fey
Building and learning on heterogeneous graphs with PyG in a practical session
Rusty Python: A Case Study
Robin Raymond
Talk on optimizing Python performance with Rust and PyO3, including case study, code profiling, and live demonstration of speedup. Discussion on PyO3 features and tradeoffs with other FFI options.
Software Design Pattern for Data Science
Theodore Meynard
I will share some specific software design concepts that can be used by data scientists to build better data products.
Specifying behavior with Protocols, Typeclasses or Traits. Who wears it better (Python, Scala 3, Rust)?
Kolja Maier
Did you ever wonder how to elegantly & safely abstract over concepts in your code? Check out Python's `typing.Protocol`, Scala's Typeclasses, and Rust's Traits!
Staying Alert: How to Implement Continuous Testing for Machine Learning Models
Emeli Dral
ML monitoring might be easy for a single model, but hard at scale. In this talk, I will introduce the idea of test-based monitoring, and how to standardize data and model checks across models and lifecycle.
Streamlit meets WebAssembly - stlite
Yuichiro Tachibana
Streamlit, a pure-Python data app framework, has been ported to Wasm as "stlite". See its power and convenience with many live examples and explore its internals from a technical perspective. You will learn to quickly create interactive in-browser apps using only Python.
The State of Production Machine Learning in 2023
Alejandro Saucedo
Join us at the PyCon DE conference to learn about the current state of production machine learning in the Python ecosystem! We'll cover key principles, frameworks for end-to-end ML lifecycle, best practices, and recommended tools for deployment, security, and scaling.
What are you yield from?
Maxim Danilov
In this talk we will discover why many developers avoid using generators in regular python code.
Writing Plugin Friendly Python Applications
Travis Hathaway
Learn how to write plugin friendly applications with Python with the pluggy library!
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