Book Review: Python Tricks
Review of Dan Bader's Python Tricks, with an example from each of its seven sections, from clean Python patterns to dictionaries and productivity.
PyCon has a very nice history of releasing videos of all of their sessions in a very timely manner. Although, it’s up to me to actually have time to watch them.
Now that I’ve gone through several videos I wanted to share the top ten of them that I think will give the most to people who are interested in which sessions they should watch.
With the announcement of Python 2 coming to a complete end in the very beginning of 2020, it’s a good idea to start thinking of how to upgrade your existing Python 2 code to Python 3. Trey gives a great talk on ways you can start upgrading and the best features of Python 3 you can start using.
Shannon goes through some nice tips on how to better teach programming. These tips, I believe, also can help you give better presentations, as well.
This was a cool one to watch. Using BeeWare we were able to see Russell show how to create, not only desktop applications, but mobile applications. This is pretty big because Python isn’t known for creating mobile applications, but now that we have BeeWare perhaps it’s time that it is.
I’m sure we’ve all encountered or, at least, worried about our credentials and API keys getting checked into GitHub for all to see. Miguel talks about how to resolve it if it does happen and also goes into ways to prevent it from happening again.
In this talk, Nina goes over several interesting Python tricks that you could use to up your Python game. Such solutions that she provides are:
This was a fun one to watch. Adam and Jonathan go into how they used StreetFighter II for reinforcement learning. They detail how they coded it and what they found when they first started letting the AI play the game.
I’m sure we’ve all had some imposter syndrome at some point. Having that can hinder improving ourselves as developers. Sara goes over what she did to get out of the pleateau of stagnating at an intermediate level and offers tips on how we can do the same.
You often learn best from failure. In this talk Alex goes over that failure happens and you have to learn from it. He then goes into that one of the best ways to do that is by writting a post mortem of the project which can serve as documentation and allow others who weren’t part of the project learn from it as well.
New in Python 3.7, data classes are a new way to build, well, data classes. In this talk Raymond goes over what you get when you use a data class, compares it to named tuples, and offers an example of using data classes.
In this talk Christopher goes over PyMC3, a packge to build Bayesian statistical models, and how to use it to build non-parametric, or parameters that scale with your data, models.