#116: 10 top talks of PyCon 2017 reviewed
Whether you got to attend PyCon, there were just too many good talks to attend them all. Luckily our friends at the PSF were on top of publishing the videos online for the whole world to watch for free. On this episode, we'll meet up with Brett Slatkin and replay his path through PyCon. We touch on his top 10 sessions from PyCon 2017.
12 Jun 20171h
#115: Python for Humans projects
When you think of popular Python packages, what comes to mind? There's a good chance that this week's guest, Kenneth Reitz, wrote that package you just thought of. He's the author of so of Python's most popular libraries, including Requests, Records, Maya, and pipenv just to name a few.
8 Jun 201753min
#114: Empowering developers at the Hidden Genius project
As most of you know, learning to program opens doors. It takes every day people and turns them into creators. Once you know programming, and Python, you've passed through a door to a place with much more opportunity.
30 Mai 201738min
#113: Dedicated AI chips and running old Python faster at Intel
Where do you run your Python code? No, not Python 3, Python 2, PyPy or the other implementations. I'm thinking waaaaay lower than that. This week we are talking about the actual chips that execute our code.
27 Mai 201753min
#112: Geeking out in the golden years
I've always thought that if I retired, I'd more or less do what I had been doing as my job - except without the meetings and reports. That is, write interesting and fulfilling software.
18 Mai 20171h 7min
#111: Pythonic Career Advice and More
Time for some Pythonic job and career advice with Matt Harrison. Listen in as we discuss how most developer jobs never make it to full job listings and how you can get in on them. We also discuss his books and his avalanche research with the Pandas library.
13 Mai 201757min
#110: Data Democratization with Redash
Are you asked to generate reports from your company's data? Has someone suggested that you buy / deploy massive BI software that expensive, closed source, and generally underwhelming?
2 Mai 201756min
#109: MongoDB Applied Design Patterns
Database design and decisions use to be fairly straightforward. Pick your relational database engine, map out the general entities, apply the third- normal-form (3NF) to them and you're basically done. With the Cambrian explosion of database options and variations created from 2009 to present, it gets much harder to even choose the database much less follow the well-worn path of 3NF.
29 Apr 20171h
