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PyData Global 2021: Top 5 Highlights for the Python, Data Science, and Dask Lover

https://ift.tt/3mVDwlz image by Brian Goff via unsplash.com I don’t know about you, but I had a blast at last week’s PyData Global 2021...

https://ift.tt/3mVDwlz
image by Brian Goff via unsplash.com

I don’t know about you, but I had a blast at last week’s PyData Global 2021! I streamed the sessions to a projector in my living room and tweeted my way through some fantastic content!

To savour the fun just a little bit longer, I’ve put together a list of my favourite sessions and most important takeaways…for those of you without time machines who couldn’t attend multiple sessions in parallel 😉

666 Lines of Beas(t)ley Assembler Code

With his characteristic mix of genius and humour, David Beazley’s keynote wove a fascinating narrative about the history of Python and the values and strategies baked into its DNA. He shared some priceless anecdotes about accidentally programming a supercomputer nicknamed ‘The Beast’ with 666 lines of Assembler code and the magical things that can happen when your office-trailer gets struck by lightning. Watch the whole keynote here.

My takeaways:

  • Pythonistas ask for forgiveness, not permission.
  • Pythonistas tend to operate on the periphery…only to blast onto the stage and steal the show when the audience least expects it.
  • A community of tool-makers is always going to be more powerful than any single tool.

If you’re a PyData history buff like me, I highly recommend checking out Matthew Rocklin’s video on the history of Dask. For more on the current and future state of all things high-performance and distributed computing, check out this blog to access a candid conversation between Matt and Peter Wang from Anaconda on The State of Distributed Computing.

Illegal Pineapple Pizzas

Turning a highly technical topic into an engaging presentation is not an easy feat. I think Francesco Tisiot did a phenomenal job with his talk “Get to know Apache Kafka with Jupyter Notebooks”. Besides a clear explanation of how Apache Kafka works and how to apply it, Ialso learned some fascinating facts about pizza etiquette in Italy.

My takeaways:

  • Never (and I mean never, not even at 3am after a night out) order a Pizza Hawaii in Italy. They’re illegal. Sort of…
  • Using Apache Kafka from Jupyter Notebooks feels smooth and familiar.
  • It really pays off to invest time in crafting a presentation that has a clear, relatable storyline (preferably peppered with some humour) and helpful, visually appealing diagrams to communicate your message in a memorable way. Iwon’t be forgetting this one!

Boring is the new flashy

With all the flash and hype around Big Data, AI, and ML, it’s sometimes easy to forget that some of the more ‘boring’ down-to-earth stuff like data formats and compression algorithms is actually just as crucial to your data science success. While tuning your ML model’s hyperparameters is important, spending time optimizing the quality and format of your data input can also lead to massive performance gains.

My takeaways:

It’s all about the visuals

There were a lot of sessions about (interactive) visualisation this year. I especially enjoyed Nicolas Kruchten’s (Plotly) high-level overview of why visualisation matters and the 4 different levels of interactivity. For a brutally honest, on-the-spot comparison of competing visualisation libraries in Python, I recommend taking an hour to watch the Python Dashboarding Shootout and Showdown.

The Dask side is strong with this one!

And of course, this list wouldn’t be complete without mentioning the strong Dask presence at this first-ever PyData Global, both from Dask maintainers as well as other presenters from across the business and academic worlds.

Some highlights:

What were your top highlights from PyData Global 2021?

Tweet me your thoughts about this year’s PyData Global — or let me know if you think this list of highlights is missing something!

Originally published at https://coiled.io on November 1, 2021.


PyData Global 2021: Top 5 Highlights for the Python, Data Science, and Dask Lover was originally published in Towards Data Science on Medium, where people are continuing the conversation by highlighting and responding to this story.



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