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!
I read the release notes to you don't have to. A quick tour of changes that have gone into Python this year. Some significant, most of which are invisible until you need them.
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.
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.
AI coding assistants are now generating more code in three days than developers previously wrote in three years, fundamentally transforming how software gets built.
Yet our research shows 48-62% of AI-generated code contains security vulnerabilities, with these PRs being rejected 3x more often than human-written code despite their speed.
Just as Tony Stark's attempt to create a peacekeeping AI resulted in Ultron nearly destroying the world, giving AI unrestricted access to our codebases without proper constraints leads to cascading failures in production systems.
Through analyzing 1000+ AI pull requests, we've developed a six-stone framework that determines exactly when AI should draft code (Jarvis mode), when it needs human review (Vision mode), and when it should never touch the code at all (preventing Ultron mode).
We will examine how pandas can be used to read data files with different formats. There will be some surprising results!
In this lightning talk, I will demonstrate how to import packages that have not been installed in a virtual environment.
Ripping and archiving thousands of music CDs for personal use can be a daunting task—especially when you care about safety, automation, and system reliability. In this talk, I’ll share how I built a secure workflow using Python, shell scripts, and Docker to ingest and organize a large CD collection into a Plex server. I’ll demo the Nimbie disc autoloader (“the hopper”), explain how containerization helps isolate untrusted media, and show how I monitor throughput and reliability using Datadog metrics. This session focuses on the technical challenges of automation, security, and observability in large-scale media archiving.