When: Aug. 9, 2018, 6 p.m.

Where: Sully's House

1501 N Dayton St, Chicago, IL 60642
(773) 244-1234

Topics


  • Pandas MultiIndex Tutorial and Best Practices
    (0:25:00 Minutes)
    By: Zax
    Experience Level: Novice
    While Pandas is one of the most well known Python libraries for working with array-like data, many users limit themselves to just two dimensions of data. This talk will walk through Pandas' MultiIndex DataFrames, which extend traditional DataFrames by enabling effective storage and manipulation of arbitrarily high dimension data in a 2-dimensional tabular structure. ((If that sentence doesn't make sense yet, don't worry - it should by the end of the tutorial.)) While the displayed version of a multiindexed DataFrame doesn't appear to be much more than a prettily-organized regular DataFrame, it's actually a pretty powerful structure if the data warrants its use. This talk is beginner friendly, and will start from the assumption of having never used Pandas, though some Pandas experience will aid understanding.
  • Interactive Introspection with `ls`
    (0:05:00 Minutes)
    By: Aly Sivji
    Experience Level: Novice
    Walkthrough of `python-ls`, a new utility that allows users to interactively introspect Python objects.
  • Mocking with MITM
    (0:30:00 Minutes)
    By: Quentin Bayart
    Experience Level: Intermediate
    Every developer (eventually) writes tests. Unit tests, Integration tests, End-to-end tests, Regression tests.. All of those tests are necessary but can become a nightmare when you need to refactor some code. I personally don't like the amount of time I spend to manually mock my dependencies / functions / objects. This talk is about a simple docker-compose / pytest / mitm setup which aims at speeding up the mocking process and the maintenance of those mocks when refactoring or when updating the interface of your services. Q&A: Many of you are dealing with this mocking process regularly so you can expect many comments / questions if you come to this talk :) Contact: Quentin Bayart, Software Engineer @ Nielsen qbayart@hawk.iit.edu https://github.com/QuentinBay A couple of days before the presentation, I will push my demo to my github so you should be able to find it there after the presentation.
  • Python Magic Methods
    By: Nick Timkovich
    Experience Level: Intermediate
    Everything in Python is an object and nothing is special. Python's built-in objects can be added, called, indexed, or with'd, and with a little magic, so can yours! Use of magic methods, those prefixed/suffixed with double underscores, can increase the flexibility of your code while also making it shorter and simpler.