With our authentication system in place, it is time to put our to-do application into production. For this post I start with a basic Docker container and when that runs, we can add more parts to create a production-ready setup.
The Garbage Collector (GC) in Python frees the memory from no longer needed objects. This usually works without any problem in the background and prevents us from memory leaks. However, for certain tasks we may pay a performance penalty that we can prevent by tuning the GC. Let us explore the options we have.
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.
On a freshly installed computer, I got this error message when I installed a package with pip:
error: Microsoft Visual C++ 14.0 or greater is required. Get it with "Microsoft C++ Build Tools": https://visualstudio.microsoft.com/visual-cpp-build-tools/
This error shows up because pip needs to compile a few files as part of the installation, but there are no C++ build tools installed. Let us figure out how we can fix this problem.
For some problems it would be great if our application could access the clipboard of the current user and do some copy & paste actions. Let's look how we can access the clipboard from Python.
As last week's post showed, our application gets its own copy of the environment variables when we start it. Would it not be great if we could extend that specific copy to include sensitive configuration values like API keys? We can achieve this with a .env file and this post shows you how to do that.
Environment variables are a useful way to store computer specific configuration values, like the home directory of the user or the temp folder. Let's look how we can access the environment variables from our Python code.
After creating dev containers for Ruby, Rails and .Net 6 it is time to take a look at Python and how we can put our development environment into a Docker container.
Time goes by quickly and before you know it your Python interpreter is a few versions behind. Pip tells you that a new version is around, but Python keeps working and so we easily forget that Python itself deserves an update from time to time.
While working through the VS Code tutorial on Flask, I noticed some difficulties that took more time to fix than they should have. Some problems came from the Python extension while others where my lack of understanding of VS Code. In the meantime, I found solutions for those problems that I like to share.