"DevOps" is the operations people’s crafty plan to make developers do other people's work, but we are smart enough to see right through this naive rebranding trick! Baruch suggests you think about it: we, the developers, have written all the code. It passes all the tests; it obviously works, and works well (Are we a little proud? We are!); so we are DONE. Now, out of the blue, a bunch of "thought leaders" (all with an operations background, mind you!) are trying to tell us that we have to learn YAML, Docker, Kubernetes, and Terraform to deploy our software because suddenly it is our concern?! In this talk, we'll discuss why developers do or don’t need DevOps. We'll consider arguments made by DevOps visionaries and see whether they hold water. Hopefully, by the end of the talk, we'll understand whether DevOps really helps developers to deploy better code to production more often, or if it is just another scam made up by marketing and evangelists.

The ChiPy Web Guild recently completed a one-week sprint to rehaul the ChiPy Homepage. In this talk we'll talk about what, why, and how the redesign took place.

Have you ever opened a file using the with keyword in Python? That little keyword is one of the many fascinating parts of the Python programming language, the Context Manager. The Python Context Manager is a tool that allows the programmer to reliably create and tear down temporary contexts within a program. This allows programmers to reduce duplicate code, improving the maintainability and reliability of the code. This talk will cover all things Context Manager, from what they are, how to build them, when to use them, and more.

Data science is too often discussed as a technical discipline, rather than a social and cultural one. But the role of data science is to both inform and automate decision-making processes, which require, in turn, humans to collaborate and communicate with each other and humans to collaborate with machines, both of which have key cultural and social dimensions. Why do so many executives feel that so little of the data work in their organizations actually delivers returns? How can we reduce friction in factoring the process of turning business questions into business answers through the intermediaries of data questions and data answers? What provisions need be in place to make sure that everybody is speaking enough of the same data languages to excel at their jobs? How do we promote data literacy throughout organizations while getting the job done? This talk is aimed at data professionals (and anybody else) who want to figure out how to establish healthy and productive data cultures in the workplace. I’ll conclude by interrogating the example of establishing the culture of modern distributed data science work in organizations and all the moving parts that need to be in place for it to function.

Ever been curious about the Rust programming language? This talk will describe the experience of going through the Advent of Code puzzles in Rust from the point of view of a Python user. Discover the alternatives to pip, functions and passing values, exception handling, and more.

Recalling my experience doing Advent of Code for the first time. How being part of a small community of others completing each challenge really motivated me to complete each challenge myself. It was also really amazing being able to look at the solutions from other, more experienced participants and discuss the solutions through Slack. I learned a lot of really useful tricks and insight to going about challenging coding problems and it really helped prepare me for future technical interviews. It was also really great getting to interact with others during the pandemic.

You've participated in our events, but who are we. With elections around and volunteering options in our virtual world, this will be an in depth look at ChiPy, its history, and its future. If you ever wanted to know more, hear about what we've been working on, or get involved....now is your chance!

This talk will discuss a python implementation of image processing firmware for the rPi and Jetson Nano boards. The software architecture covers a camera frame grab -> image processing -> output loop as well as some machine learning models for feature detection, a Flask-based front end, and an OpenAPI-based Swagger interface and API design using connexion.

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.

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