Past Meetings • Recent Topics

Python for Home-Ec
(0:25:00 Minutes)
By: Adam Forsyth
Experience Level: Novice

Have you ever tried to make something with scrap wood, and wondered how to use it optimally? Do have a bunch of pickles and jams you made, and you want to eat them in an order that maximizes variety? These are real problems a co-worker of mine had, and we used Python to solve them. I'll show the data we started with, the solutions we came up with, and a bit of the computer science behind them. See some examples of how to think through problems and design your own algorithms to solve them.

A Gentle Introduction to Context Managers
(0:15:00 Minutes)
By: Aly Sivji
Experience Level: Intermediate
Slides Link
We've all used context managers provided by the Python Standard Library to read from/write to a file. Have you ever wondered what was happening underneath the hood when you used a with statement? This talk will explore context managers, discuss various use cases, and show you how to implement a context manager to manage MongoDB connections.

Build a Game: HTML5 sockets + Phaser + flask
(0:25:00 Minutes)
By: Brian Ray
Experience Level: Intermediate

Brian will show how to use flask and Python to power a browser based HTML5 game over sockets. Events can be pushed to the browser or pushed to flask from the browser. Great starter for those who are interested in event driven programming.

Python for mathematical visualization: a four-dimensional case study
(0:30:00 Minutes)
By: David Dumas
Experience Level: Intermediate

This is a talk about creating pictures of a mathematical object---specifically, a 4-dimensional fractal "dust" that has been the subject of mathematical research in hyperbolic geometry since the 1980s. In the end this is accomplished using a little algebra, a little geometry, and a healthy dose of Python. That is, I will present a case study of using Python in several aspects of a mathematical visualization project, from the computation itself, to transforming and converting data, and finally for scripting the process of generating the images. Along the way I'll explain how Python's convenient idioms and containers (e.g. sets and set comprehensions) are a good fit for some of the algebraic and geometric questions that come up, how Scipy and Numpy enable fast numerical calculations, and how Python's strength as a language for scripting and automation allows easy orchestration of rendering of still images and frames of animations. The mathematical visualization project we describe is a collaboration with François Guéritaud (Université de Lille).

Letsencrypt with Python Webapps
(0:20:00 Minutes)
By: Joe Jasinski
Experience Level: Intermediate

In-browser encryption is more important now than ever. When building modern web-apps, encryption is a necessity. This talk will detail how you can secure your Python-based projects with Letsencrypt, a free certificate authority available to anyone. It will cover the Python-based tools available to configure Letsencrypt and an example project utilizing it.

Trolling databases with Python!
(0:07:00 Minutes)
By: Loren Velasquez
Experience Level: Novice
Slides Link
You are the data troll who allows what data can be pushed up. All data requests are in your hands but first you need to become an official data troll by getting your information in the data troll table (you need to be legit in the database or else it didn't happen). This is a super simple example of how Python can be friends with database, today we’ll look at Postgres!

TDD with PyTest
(0:10:00 Minutes)
By: Sand Ip
Experience Level: Novice

PyTest helps Python developers with test-driven development, continuous integration, and quality engineering. In this talk we’ll cover setup, data fixtures, case types, and results interpretation by walking through a PyTest demo.

Python Software Foundation Update + how you can be involved!
(0:10:00 Minutes)
By: Lorena Mesa
Experience Level: Novice

What's happening at the Python Software Foundation? Look no further Python Software Foundation Director Lorena Mesa will run through an update! Information about elections, a new PyCon organizers manual, the PSF Code of Conduct Committee will be briefly covered.

How a Study Group Can Help a ML Beginner Learn Deep Learning
(0:05:00 Minutes)
By: Apurva Naik
Experience Level: Novice

Deep learning has never been accessible to people with limited ML experience. All over the internet, beginners only come across discouragement, exclusion and elitism when they express an interest in doing deep learning. A recently released MOOC, fast.ai is specifically designed for those with some coding experience. The MOOC's creators use a hands-on approach of teaching that focuses on coding first and understanding later. I will talk about the balancing act between work, family and passion projects, how my study buddies help me stay on track, and what we're doing to help others learn.

Grok the GIL: Write Fast And Thread-Safe Python
(0:30:00 Minutes)
By: A. Jesse Jiryu Davis
Experience Level: Intermediate

This is a sneak preview of a talk accepted to PyCon 2017, this June in Portland. A. Jesse Jiryu Davis is a prominent open source developer who has spoken at the last three PyCons, so this talk promises to be thorough, technical, and fun. He describes the talk thus: "I wrote Python for years while holding mistaken notions about the Global Interpreter Lock, and I've met others in the same boat. The GIL's effect is simply this: only one thread can execute Python code at a time, while N other threads sleep or await network I/O. Let's read CPython interpreter source and try some examples to grok the GIL, and learn to write fast and thread-safe Python." Jesse is a Staff Engineer at MongoDB in New York City specializing in C, Python, and async. Lead developer of the MongoDB C Driver libraries libbson and libmongoc. Author of Motor, an async MongoDB driver for Tornado and asyncio. Contributor to Python, PyMongo, MongoDB, Tornado, and asyncio. Co-author with Guido van Rossum of "A Web Crawler With asyncio Coroutines", a chapter in the "500 Lines or Less" book in the Architecture of Open Source Applications series.

Introduction to Project Magellan
(0:25:00 Minutes)
By: Ancy Phillip
Experience Level: Intermediate

Day by day, the world is becoming more data driven, making data science extremely popular. Data Wrangling , Data Analysis form the two important stages in any Data Science problem and Entity Matching(EM) is extremely critical in the latter phase. EM has been a long-standing challenge in data management. Most current EM works focus only on developing matching algorithms. A solution to this, Magellan, is a new kind of EM systems, open sourced on top of the PyData eco-system. Magellan is novel in four important aspects. (1) It provides how-to guides that tell users what to do in each EM scenario, step by step. (2) It provides tools to help users do these steps; the tools seek to cover the entire EM pipeline, not just match- ing and blocking as current EM systems do. (3) Tools are built on top of the data analysis and Big Data stacks in Python, allowing Magellan to borrow a rich set of capabil- ities in data cleaning, IE, visualization, learning, etc. (4) Magellan provides a powerful scripting environment to fa- cilitate interactive experimentation and quick “patching” of the system. Magellan is used at Walmart Labs, Johnson Controls, Marshfield Clinic and as a teaching tool in UWM classes.

How I Taught My Dog To Text Selfies
(0:30:00 Minutes)
By: Greg Baugues
Experience Level: Novice

This talk is is for Python developers who would like to get started with hardware hacking but have been too intimidated in the past to do so. Also, it's for people who like dogs and/or selfies. Using a Raspberry Pi, Python, Twilio, and a big red button, I taught my dog to text selfies. In this talk, which features 25 minutes of live coding, we'll build the hardware hack from scratch. Developers will walk away knowing how to use Python to interact with Twilio and the Raspberry Pi's GPIO pins. A video of this hack was featured on Mashable and was watched over 2.5M times.

Quick prototyping with redis-helper
(0:30:00 Minutes)
By: Kenneth Wade
Experience Level: Novice

In this talk, I will demonstrate some uses of https://pypi.python.org/pypi/redis-helper and how you can easily store, index, and modify Python dicts in Redis. Some asciinema demos are available at https://asciinema.org/~kenjyco

How To Develop and Deploy Faster using Python APIs
(0:20:00 Minutes)
By: Paul
Experience Level: Intermediate

Building and deploying applications has never been easier, especially with the proliferation of APIs. In this talk, I will share the 4 concepts that will allow Python developers to quickly learn and use any Python-based API. The target audience for this talk are intermediate newbies who have a couple of projects under their belt.

Unsupervised machine learning in engineering and neuroscience: applications of ICA
(1:30:00 Minutes)
By: Mark V. Albert, Pavan Ramkumar, Anne Zhao, Jorge Yanar
Experience Level: Intermediate

This talk with be a set of four short presentations guiding everyone through three applications of unsupervised machine learning. We begin with the classic cocktail party problem - how to automatically separate mixed voices recorded by microphones - presented by Jorge Yanar. This will be followed by a brief, intuitive explanation of the algorithm used to perform the task - Independent Components Analysis (ICA) described by Professor Mark Albert. Dr. Pavan Ramkumar will demonstrate how the same technique is applied to filter unwanted noise during neural recordings using EEG, and Anne Zhao will end with a demonstration of how the same coding strategy has led to insights in how the brain encodes sensory information in the early auditory and visual systems. Her demo will allow participants to develop their own simulated neural codes for processing visual images. The brief talks will consist of a Jupyter notebook for running code and displaying results. For those who wish to run the examples during the talk, it will be necessary to install Jupyter running Python version 3 (the Anaconda Python distribution is recommended to set this up). Links and setup instructions will be given prior to the talks for people to follow along on their laptops and try the examples on their own if desired.