Talk 1: Refactoring Python code to make it more testable by Colm Harrington (https://ie.linkedin.com/in/colm-harrington-249b463) (35 mins)

This main objective of this talk is about applying the principles defined by Robert Martin as regards 'Clean Architecture' ( http://blog.8thlight.com/uncle-bob/2012/08/13/the-clean-architecture.html ) and ported to the python ecosystem by Brandon Routh. I had a 'breakthrough' moment while carrying out some refactoring work recently by applying the principles outlined in the link above. This allowed me to refactor and write unit-tests 'easily' with the added benefit of making future refactoring efforts easier and safer in the future. It will consist of a few examples of how & why I refactored some existing python code to make it more testable by extracting the core business rules and placing them in 'pure' functions i.e. no side effects. Any IO i.e. DB or API calls are placed at the top of the call stack so that they can be easily replaced.

About Colm Harrington
I am an Automation Architect with VCE/EMC based in Cork with responsibilities for both front end (via Selenium) and API testing. I have worked in the software industry, for various companies including Microsoft, Realex Payments and Sage Ireland, for over 11 years. I have presented at a number of conferences around Europe on various topics around software automation My real passion is simplifying the test process of complex applications and integrating the test process seamlessly into the SDLC.

Talk 2: Ladyball: The Story of a Hashtag by Anthony Munnelly (https://ie.linkedin.com/in/anthonymunnelly) (30 Mins)

Lidl Ireland and the Ladies' Gaelic Football Association decided to do some guerrilla marketing to announce Lidl's sponsorship of the sport. It got people talking, but a lot of people just didn't think it was funny. So what I hope to do is to mine Twitter data that featured the #ladyball hashtag and see what we can conclude from it. Tweepy is the module I'll use to do this.

So the presentation will be

1. Intro to Tweepy
2. Using Tweepy to mine tweet data
3. Cleaning up that data for analysis
4. Searching for patterns in the data

All with a view to answering the question: is there really no such thing as bad publicity?

About Anthony Munnelly
I'm a former journalist now working in PR for an online bookmaker. I got into Python and Data Analysis around 2011, 2012 and I can't get enough of it. Fascinated by the sheer amount of information out there.