Worum es bei uns geht

The Bay Area Python Interest Group (BAyPIGgies) was formed in July 1999. Although we use MeetUp.com for advertising to new members, our governance and main communication happens at https://baypiggies.net/ (http://baypiggies.net/) and https://mail.python.org/mailman/listinfo/baypiggies.

We meet the fourth Thursday of every month from 7:00pm - 9:00pm (except on November and December where we make special arrangements for the holidays). We are always looking for new speakers. Please reach out to our current organizers (Glen Jarvis and Jeff Fischer ) if you would like to give a talk. You don't have to be an expert programmer to give a talk.

Bevorstehende Events (3)

Pigs, Pythons and Goats: The Animal Guide to TDD

Benötigt einen Veranstaltungsort

Abstract ======== There are often many buzzwords that are used incorrectly and abused. Often people hear about Test Driven Development (TDD) and think this is just a term that means “Testing your code.” Although Testing your code is important, Test Driven Development is a special paradigm that is often used in certain companies. After this talk, you may decide that full Test Driven Development (TDD) isn’t for you (or, it may be a turning point for you). Regardless, you should fully understand the paradigms and what it is - as it will come up in discussions some time in your career. To make it accessible to everyone, we will start this talk with an introduction to Unit Tests and testing frameworks (e.g, unittest, pytest, nose, etc.) We do a few very basic live demonstrations of both succeeding and failing unit tests. We quickly, however ramp up building a data structure (e.g., stack, queue, tree, etc.) using a full Red, Green, Refactor TDD cycle (cycles within Test Driven Development). This will be somewhat interactive and there will be a lot of slides with Python code. Biography ========== Glen Jarvis has worked for companies such as IBM, Informix, UC-Berkeley, Sprint and many Silicon Valley Start-ups. He has worked in the fields of DevOps, Databases, Data Science, Bioinformatics and Web Technologies. He has been exclusively working in DevOps the past five years. He has been programming in the Python programming language for over 10 years. And, he has been certified in Linux/Unix administration by UC-Berkeley. He is also certified in MongoDB as developer and administrator. Before that, he gained the highest certification available for Informix database administration and supported administrators. He is currently working on his Amazon AWS certification. Glen is currently putting the “Dev” in “DevOps” using Ansible and Python. He additionally owns a training and consulting company, Glen Jarvis Training & Consulting, LLC that mentors budding programmers and DevOps engineers. He has also been an open source contributor and a member and co-organizer of the Bay Area Python Interest Group, Silicon Valley Python MeetUp, and Learn about Amazon Web Services MeetUp.

Statistical analysis of complex networks using NetworkX with applications

Benötigt einen Veranstaltungsort

Abstract ======== Networks can be used to model many types of relations and processes in physical, biological, social and information systems. Many practical problems can be represented by networks, also called graphs. This tutorial will first go over the basic building blocks of graphs (nodes, edges, paths, etc) and common methods to get data structures into NetworkX-compatible format. Then, we can solve common problems like shortest-path on a real graph, and less common ones, like implementing PageRank on a directed network to get PageRank of each node in the network. Bio === Lisa is a Data Scientist at Lagrangian.io, a startup focused on the use of Terraform modules for backend services optimization. Previously, she was a bioinformatician with Geisinger Health System working on large-scale genomics applications related to human health outcomes. She earned her MS in Bioinformatics at SoongSil University in Korea where she worked on chemical analysis methods for simulated chemical structure (QSAR/QSPR) in Python.

Interactive Python Visualizations with Bokeh

Benötigt einen Veranstaltungsort

Abstract ======== Effective data visualization is critical to communicating results, and as developers we are always looking to save time and write more clear code. All projects use static graphs, and we see growing interest in interactive visualizations that help us find insights difficult to see in static graphics. Data science projects often use the foundational library Matplotlib which is awesome but very complicated and sometimes hard to understand. In this talk, we'll touch on Matplotlib and use a more modern library - Bokeh - to create static and interactive visualizations. Speaker ======== Christopher Brousseau

Vergangene Events (55)

Debugging Google services via Google APIs and PDB

700 W Middlefield Rd

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