This talk is a practical introduction to SQL testing using Python. We’ll cover why testing SQL can be tricky, compare strategies for preparing a SQL test environment and preparing data, how to check for schema breakages, data validation checks, automated formatting, and automated testing in local or remote environments. Attendees will leave with patterns and code examples to make SQL pipelines more reliable and maintainable.

Many people in the data science community are familiar with jupyter notebooks and use them regularly as part of their day-to-day tooling. While jupyter notebooks have a lot of extensions and are a great way to combine documentation with code, they don't come without drawbacks. One of the biggest drawbacks is the execution order of the cells. The other drawback is looking at the code changes between commits when trying to upload notebooks to GitHub. To solve these shortcomings, marimo notebooks were created. This talk will demonstrate marimo notebooks' functionality, the modes in which you can run them, and other marimo features.

In this presentation, I will summarize my experience dealing with malicious actors who attempted to infiltrate my research study. I will discuss what happened, outline the stages we went through, the fixes we implemented, and our decision-making process. I will also conclude with a broader discussion of the state of behavioral science in addressing such cyber threats. More generally, I will discuss how technology companies and tech-savvy individuals can help the social sciences/Academia protect themselves from deceptive actors and raise awareness among academics about potential pitfalls.

You can build Python from source, use a Docker image, install it with a package manager, or use the version that comes with your operating system.  They're all the same Python, right?

Yes and no.  This talk will 1) define Python, and 2) look at what changes, depending on how you install it.   

"There is nothing so permanent as a temporary solution". Come learn how a combination of misunderstanding, bad assumptions, tech debt and general chaos created the world's worst data pipeline.

It's slow. It's inaccurate and sadly it lived in production for 3 years. Learn from my mistakes!

Have you ever wanted to do some financial research, but struggled. Well maybe not, but if you're here with us tonight, maybe check out some packages that Wayy Research has been creating. Even if you're not a seasoned fin-head, you might be wondering how to get started in quantitative finance. And if you were, boy, are you in luck!

We will go over 3 packages:

Wayy-Research/wrdata - a financial data gathering package

Wayy-Research/fracTime - a time series forecasting library

Wayy-Research/wrtrade - a quantitative trading libarary

All of these will allow you to get started with quantitative trading right in the comfort of your own home. This will be a lightning round covering the basics and we will get you from zero - to - hero faster than you can say Benoit Mandelbrot. So bring your thinking caps and lets get ready to do some digging!

We spend much of our time collecting and analyzing data. That data is only useful if it can be displayed in a meaningful, understandable way.

Yale professor Edward Tufte presented many ideas on how to effectively present data to an audience or end user.

In this session, I will explain some of Tufte's most important guidelines about data visualization and how you can apply those guidelines to your own data. You will learn what to include, what to remove, and what to avoid in your charts, graphs, maps and other images that represent data.

The 2025 OWASP Top Ten release candidate came out on November 6.  Let's look at what's changed since 2021.

Python runs on chips. Python can be used to help make chips. 
A little on making chips, open silicon, and the state of the industry. 

Hello,

I love film cameras. Especially multiple lens film cameras that take photos all at once or in a sequence. The true pain is getting my scans back from the film lab I use and a set of photos being put into one photo because of how the cameras take the photos in the first place.

In this talk I will show how to perfectly crop a set of images into multiple images even if the vary in size.