zoneinfo: A stunning module of exceptional quality
(45 Minutes)
By: Paul Ganssle
Experience Level: Intermediate
Slides Link

Python 3.9 introduces the `zoneinfo` module, which brings concrete time zone support to the standard library. In this talk, I'll discuss the history of time zone support in Python, make the case for migrating your code to `zoneinfo`, and hopefully give you an understanding of everything you'll need to know to successfully make use of the new module.

https://docs.python.org/3/library/zoneinfo.html

Venmo @ Graduation
(30 Minutes)
By: Josh Martin
Experience Level: Novice
Slides Link

In search of good memes, emojis, and a quick scheme to make fast cash: I decided to put an LED Matrix into my college graduation cap. While making some missteps along the way, I learned a lot of valuable lessons including how to retrieve data from websites easily and regularly (even if they do not want you to), sourcing and evaluating hardware components, and connecting everything using plain Python. I will describe my experience going from a complete beginner to an expert as I step into the next phase of my life, making my mother proud along the way.

Don't be beholden to your tools
(15 Minutes)
By: Dave Trollope
Experience Level: Novice

How KnowledgeHound innovated by breaking usage of existing tools to solve two immediate problems. A discussion of Django, SQLAlchemy, Pure Python, and Pandas.

Fun with Finite State Machines
(15 Minutes)
By: Aly Sivji
Experience Level: Novice

Finite State Machines (FSM) are tools we can use to model simple and complex workflows. In this (non-mathematical) talk, we will learn about FSMs and examine how they can be used to improve software design. We’ll finish by diving deep into a couple of Python implementations of FSMs. Full disclosure: one of the implementations is a library I created.

Snakes on a Car: Or, Over-engineering a Toy
(30 Minutes)
By: Kat Cosgrove
Experience Level: Novice

Like a lot of engineers, I like to tinker. I also like hardware hacking, video games, and over-engineering the hell out of something. When my team at work decided to build a proof of concept demonstrating the possibility of fast over-the-air updates for edge devices, we settled on using a car as the example of an edge device. It’s flashy, you know? This also presented me with an opportunity to do all of the things I love, and call it work: build a self-driving RC car, and then let people race it around a track using a repurposed USB racewheel, a handful of open source tools, and whole lotta Python. DevOps, but make it fun.

Principles Driven Development - How PursuedPyBear decides what's important.
(30 Minutes)
By: Piper Thunstrom
Experience Level: Intermediate

PursuedPyBear (ppb) is a Python game development library.

PPB started like many projects: “How do I make my life easier?” Then teachers started asking if it could be built for teaching CS. That started the project on a path to have an extreme focus on API design and education. This distills the concepts that the ppb community have decided matter for long term health of the project, and the technical principles that came out of it.

What the heck's a Pixel and the California Consumer Privacy Act (CCPA)
(10 Minutes)
By: Sree Prasad
Experience Level: Novice

Even though it's technically only applicable to residents of California, the California Consumer Privacy Act (CCPA) is a major step in comprehensive data privacy legislation in the US that affects every single person in the US's most populated state. I'll go over what's in the CCPA and why it matters as well as share how my team managed to meet all the requirements for compliance just in time for the new year (when the CCPA went into effect).

Goodbye Print, Hello Debugger!
(25 Minutes)
By: Nina Zakharenko
Experience Level: Intermediate

Still debugging your code with print? Learn how to level up your ability to troubleshoot complex code situations by using the power of a fully-featured debugger in this talk aimed at all levels of programming ability. Debuggers allow you to examine your program state, watch as the values of important variables change, and even modify the content of variables on the fly. Once I gave up using print to debug, my productivity as a programmer increased, and yours can too! I’ll showcase the variety of debugger tools available - from pdb, the simplest command line debugger that’s part of the standard library, to fancy graphical debuggers available in Python IDEs. Join me as we walk through real code together using debugger tools in a hands-on way to help us diagnose problems and bugs. The skills you’ll learn in this talk will allow you to quickly use these tools in your own code bases for fun, school, or work.

ChiPy Mentorship Returns
(15 Minutes)
By: Ben Xia-Reinert
Experience Level: Novice

The new ChiPy Mentorship site is going live on July 4th. While the structured, 13-week ChiPy Mentorship program is not returning, this app will enable members of the Chicago Python community who wish to be mentees and mentors to find and connect with each other. In this talk, we will explain how the app was made, what we are looking to accomplish, and how you can be a part of it.

Ten Ways to Fizz Buzz
(15 Minutes)
By: Joel Grus
Experience Level: Novice

Fizz Buzz is the following (simple) problem:

Print the numbers from 1 to 100, except that if the number is divisible by 3, instead print "fizz"; if the number is divisible by 5, instead print "buzz"; and if the number is divisible by 15, instead print "fizzbuzz".

My association with this problem began in 2016, when I wrote a blog post called Fizz Buzz in Tensorflow, the (possibly fictional) story of one such insulted programmer who decided to show up his interviewer by approaching Fizz Buzz as a deep learning problem. This post went modestly viral, and ever since then I have been seen as a thought leader in the Fizz Buzz space.

Accordingly, over the years I have come up with and/or collected various other stupid and/or clever ways of solving Fizz Buzz. I have not blogged about them, as I am not the sort of person who beats a joke to death, but occasionally I will tweet about them, and recently in response someone suggested that I write a book on "100 Ways of Writing Fizz Buzz in Python."

Now, I could probably come up with 100 ways of solving Fizz Buzz, but most of them would not be very interesting. Luckily for you, I was able to come up with 10 that are interesting in various ways, which I will barrel through in 15 minutes or less.

Introduction to AutoML
(60 Minutes)
By: Paco Nathan
Experience Level: Novice
Slides Link

AutoML is a very active area of AI research in academia as well as R&D work in industry. The public cloud vendors each promote some form of AutoML service. Tech unicorns have been developing AutoML services for their data platforms. Many different open source projects are available, which provide interesting new approaches.

But what does AutoML mean? Ostensibly automated machine learning will help put ML capabilities into the hands of non-experts, help improve the efficiency of ML workflows, and accelerate AI research overall. While in the long-term AutoML services promise to automate the end-to-end process of applying ML in real-world business use cases, what are the capabilities and limitations in the near-term?

This talk surveys the landscape and history for projects and research efforts related to AutoML, looking beyond just hyperparameter optimization and considering the impact on end-to-end workflows and data science practices. We'll show sample code using different open source projects and provide pointers to online resources to learn more.