Internally Python uses classes and therefore types everywhere. However, when we declare our methods, we omit the types and end up with limited functionality for our code editors. In this post we look at type hints and how they can improve our experience to write code.
You may run into code examples where the parameters are prefixed with a star or a double star. This little feature of Python comes in handy when we need a bit more flexibility for our methods. Let us explore how that works.
In last week's post we overwrote a method in the SSL module to use Feedparser with self-signed certificates. Today we take a closer look at the so called "monkey patching" and how it works under the hood.
Feedparser is a great Python library to read RSS and ATOM feeds that I covered in Python Friday #102. When I tried to read a local RSS feed with Feedparser, I ran into a problem with my self-signed SSL certificate. Let us see how we can tell Feedparser that our certificate is trustworthy.
Time flies, and with it come new versions of Python and older ones reach the end of their lifespan. Let us use this opportunity to check if we use a Python version that is still supported.
Python is usually a straightforward language without surprises. However, when you use the round() function you may run into some strange behaviour. Let us have a look at the specialities of round() and what is going on.
A few weeks back we were running a data preparation script that took a long time to complete. The main part of the work should not take that much time, but somehow that script was sloooow. I expected that the print() statement for each record would have an impact on performance, but I had no indication of the magnitude. Is it significant? Or is it neglectable? Let us find out how big the impact can be.
It is unbelievable that this is already post #200 for my Python Friday series. Let us use this milestone to look back at the topics we covered since Python Friday #100. Again, you get an easy-to-use reference that lets you jump right to the topics you are interested in.
With Dash and Plotly we can create complex interactive dashboards, while Flask works in the background to gives us all the web capabilities. In this post we turn the tables and add Dash to an existing Flask application.
After our first steps with Dash last week, we create in this post a more complex dashboard with multiple components that we can update simultaneously.