Having decided to improve my skills in the short space of time left between my professional life and personal life, I started researching the available data science options.

I recently had a use case at work where I wanted to check that file paths given in a Python script actually existed. These paths were in various GitHub repositories, so all I had to do was pull out the paths and check if they exist on GitHub. There were a few catches though.

As a project idea for a young engineer we wanted to build a Raspberry Pi-based Weather Station . Our last attempt at building something – a sound-responsive LED display – was a failure. So it was important to build something really easy to help us get back on track. Here are some notes. We essentially followed this guide from Adafruit which links out to this guide for the CircuitPython part.

I was working on a work task last week, and needed to filter out one instance of a class from a list of class instances. No matter how you do this speed doesn’t matter too much if you’re doing this operation once or a few times. However, I this operation needs to be done about 100K times each time the script runs - so speed definitely does matter in this case.

It’s been interesting switching jobs with respect to programming languages. I used to write 95% R - now I write 95% Python. I have been using Python for many years, but not seriously or getting paid either. I’ve learned alot in the first 6 months. Some Python things learned: Functions and methods I used to think functions and methods were the same thing. But during the last 6 months I learned that functions and methods are not the same.

A guest blog post by Steve Moss Why Python? A little background! I started using Python in the summer of 2010. I had applied for the Master of Research postgraduate degree in Computational Biology at the University of York. They teach the programming portion of their course using Python. I thought it might be useful to learn it, before starting, to give me a bit of a head start.