Module the Month: Turtle
In keeping with the education theme, I thought I would give a talk on the Turtle module in Python, which is more or less a clone of Logo.
Introducing Python in an after school setting
I've lead a couple once-a-week, 10-week apprenticeships that allow 5th-8th grade
students to explore the basics of Python through an interactive shell at their
elementary school. The students primarily use lab computers, but they are also
exposed to general command-line concepts through the use of several customized
In this talk I will discuss my goals for the students, the concepts that I
introduce, how I interact with the students, some of the challenges that arise
(for myself and the students), and some tips that may be helpful to other
Migrating django application data
Discussion of common problems migrating Django application databases, particularly when switching DBMS.
100 Python enthusiasts attended this meeting.
Ultimate Langauge Shootout
Multiple Langauge competition:
* Clojure - Cezar Jenkins
* SQL - Heather White
* Babbage's Analytical Engine programming cards - Phil Robare
* R - Parfait
* Assembly (AVR) - Nick Timkovich
* Groovy - Jerry Dumblauskas
* Swift - Matt Green
* Julia - Andrew Webster
110 Python enthusiasts attended this meeting.
Developing with Python at Telnyx
This talk will cover the development cycle, build tools, and python frameworks commonly used by Telnyx Python engineers.
Using Tasks in Asyncio Web Apps
In this talk, I will be talking about starting, stopping, and displaying incremental data from long-running tasks in an asyncio-based web application.
Popular ORM Libraries
What's the main difference between SQLAlchemy and Django's ORM? When might a person prefer Pony ORM or peewee? -- popular Object-Relational Mapping libraries in Python are compared and contrasted.
117 Python enthusiasts attended this meeting.
Predictive Enforcement of Pollution and Hazardous Waste Violations in New York State
New York State’s Department of Environmental Conservation (NYSDEC) is the regulatory agency for environmental issues in the state. Their mission is to conserve, improve and protect New York State’s natural resources and environment and to prevent, abate and control water, land and air pollution. NYSDEC currently conducts approximately 700 inspections each year of facilities in the state that manage hazardous waste.
DSSG will work on more effectively allocating inspection resources by creating predictive models that identify facilities with high likelihood of violating environmental regulations. In 2015, we worked with the federal EPA targeting hazardous waste facilities subject to the Resource Conservation and Recovery Act (RCRA). With inspection data from NYSDEC and the public RCRA dataset, we will build a similar model to identify RCRA violators specifically in the New York region, as well as further explore the possibility of applying models to other compliance inspection programs, such as the Clean Air and Clean Water Acts.
Expanding Our Early Intervention System for Adverse Police Interactions
Many police departments in the United States use “early intervention systems” to identify officers who may benefit from additional training, resources, or counseling. These systems attempt to determine behavioral patterns that predict a higher risk of future adverse incidents, ranging from excessive use of force and citizen complaints to on-duty accidents and personal injury. Detecting these risk factors enables departments to develop targeted interventions and make operational changes to protect officer safety and improve police/community interactions.
Last summer, DSSG worked with the Charlotte-Mecklenburg Police Department on building a better early intervention system, applying data analysis to provide insights on individual and situational risk factors for adverse interactions. This year, we will partner with additional police departments, including the Metro Nashville Police Department, to test and expand this work in new municipalities, improving both the overall model and local performance. Like last year, we will use anonymized police data and contextual data about local crime and demographics to detect the factors most indicative of future issues, so that departments can provide additional support to their officers.
143 Python enthusiasts attended this meeting.
Computer Vision in Python: How to build a basic face detection system
In this short talk Jeremy will describe the universal pipeline for performing object detection (that is, the automatic detection of objects in digital images) in Python. This will include a discussion of various classification schemes, feature extraction methods, and their fusion in the form of deep neural networks. Demo code illustrating these concepts will be shown using the IPython notebook environment.
Getting meaningful results from unit tests
We count on unittests failure messages to give us reasonable feedback on how to proceed with a failing test. When you're working with builtin data structures and objects, unit test feedback is usually pretty good. It helps you identify and solve the problem. In contrast, the default results you get from custom objects can be practically useless.
Intro to Deploying Django with Ansible
Deploying Django is a breeze when using Ansible. Learn a bit about the power that Ansible provides and how easy it is to get started using it!
144 Python enthusiasts attended this meeting.