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.

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.

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.

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.

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

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.

The largest ever cadre of ChiPy Mentorship participants meet to present their findings after 13 weeks of study with their mentors. You'll see demos and discussion for entry level projects, web development projects and data science experiments gone mad with the power of Python. Each presenter gets five minutes to tell the story of their journey and what they produced. Plus amazing prizes and announcements on how to apply for the spring term.

How to access a database using pyodbc, and how to execute basic queries through Python.

I was Ray's mentee during the summer of 2016. My project lets a player of Minecraft Pi 3D print an object they have built in the game. I will co-present this project with Peg Keiner, the Technology Director at GEMS World Academy in Chicago where my program was used in their elementary school classroom this Fall. I will also share some neat projects from my stint this Fall as a High School Marine Science teacher aboard the schooner Roseway during Ocean Classroom (worldoceanschool.org). I introduced students to Python and had them design and code a sensor kit with Raspberry Pi's to measure an aspect of the sailboat. The code is viewable on my github profile: https://github.com/thaneofcawdor.

Do you yearn? Have you ever tried to volunteer at a project but had an extremely difficult time trying to get everyone the right development environment? Do you ever work with a project that works in your computer but not in a server? Do you have a different dependency versions? (btw, that's kinda bad practice but don't fret, we gotchu) Yearn no more! With Docker, these things can be a thing of the past. Join in a brief, live coding session that will show you how to build a simple Bottle app and put it into a Docker container.