The talks presented at the 21st annual EuroPython conference are now available for free on YouTube. Topics ranged from Code and Tech to Social and Career advice.

EuroPython is the oldest and longest running volunteer-led Python programming conference, always hosting innovative sessions on the past, present and future of Python. Year 2022 marked the 21st conference in the series, this time taking place in beautiful Dublin.

The conference featured around 16 tutorials/workshops and 120 talk sessions:

• Four tracks of tutorials/workshop on 11-12 July
  
  
• Four tracks of talk sessions of Python general topics on 13-15 July, e. g. Programming, Software Engineering, Cloud, DevOps, Web, Django.
  
  
• Two tracks of talk sessions of PyData related topics on 13-15 July.

These tracks the conference was comprised of were :

Python Internals
Career, Life, . . .
Community & Diversity
DevOps
Django
Education, Teaching & Further Training
Events
Infrastructure: Cloud & Hardware
Makers
Posters
PyData: Data Engineering
PyData: Deep Learning, NLP, CV
PyData: Ethics in AI
PyData: Machine Learning, Stats
PyData: Software Packages & Jupyter
Python Friends
Python Libraries
Security
Software Engineering & Architecture
Sponsor
Testing
Web

Now all the sessions/tracks as well as the live streams have been made available online, free of charge.

The recorded live streams are up to 6 continuous hours if you want to see it all. Otherwise it is preferable to pick your recorded session from the available 126 videos long YouTube playlist.

There's many great options there, so we'll try to mention some that are noteworthy. Like:

Multithreaded Python without the GIL where Sam Gross software engineer at Meta AI and co-author of PyTorch talks us through CPython’s "Global Interpreter Lock", or "GIL", which prevents multiple threads from executing Python code in parallel and the "nogil" project. The "nogil" project aims to remove the GIL from CPython to make multithreaded Python programs more efficient, while maintaining backward compatibility and single-threaded performance. The talk covered the changes to Python to made to let it run efficiently without the GIL as well as what these changes mean for Python programmers and extension authors.

PySnooper: Never use print for debugging again
Ram Rachum is a software developer specializing in Python, and a Fellow of the Python Software Foundation, who presents
his debugging solution for Python, PySnooper, that doesn't require complicated configuration like PyCharm.

He details how :

• PySnooper can help you debug your code.
• you can write your own debugging / code intelligence tools.
• to make your open-source project go viral.
• to use PuDB, another debugging solution, to find bugs in your code.

Memory Problems, Did Collector Forgot to Clean the Garbage?
This presentation gave a quick overview of:

• How CPython manages the Memory allocation
• Common memory errors we see in day to day production code and how we can improve them

How to embed a Python interpreter in an iOS app
Native mobile applications have many advantages over mobile websites or apps made with cross-platform toolkits. They will use less battery, allow for richer graphics, more consistent UI behavior, and enable more functionality through device-specific APIs. Wouldn't it be great to have access to all this from Python?

In this talk Łukasz Langa, marries a native iOS app written in Swift with an embedded Python 3. 10 interpreter to allow users to customize what the application is doing. To that end he details the entire process of:

• embedding Python from source;
• building it into the Swift mobile app in Xcode;
• adding a few pre-compiled third-party libraries like numpy and Pillow to broaden the scope of what the user can do;
• running the resulting app on an iPhone 13;
• modifying the app behavior at runtime thanks to our new Python superpowers!

Embedding Python interpreters and why we should do so is something we've examined in "Python and . NET - An Ongoing Saga"

So how does Python. NET differ from Iron Python?
Python. NET integrates with the . NET Common Language Runtime (CLR) and provides a powerful application scripting tool for . NET developers. It allows Python code to interact with the CLR, and may also be used to embed Python into a . NET application. Using this package you can script . NET applications or build entire applications in Python, using . NET services and components written in any language that targets the CLR (C#, VB. NET, F#, C++/CLI).

On the other hand IronPython is an implementation of the Python Programming language written for the . NET framework. This makes it a pure managed-code implementation of the Python language which renders IronPython a first-class . NET programming language. IronPython can use . NET and Python libraries, and other . NET languages can use Python code just as easily. IronPython is built on top of the Dynamic Language Runtime (DLR), while the DLR itself is built on top of the Common Language Runtime (CLR) of the NET platform.

There's still many more sessions to go through so jump right into the Playlist.

More Information

EuroPython 2022 - Live Stream Playlist
EuroPython 2022- Sessions Playlist

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Python and .NET - An Ongoing Saga

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