Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. In order to be run on any one machine, it first has to be installed; you can download it here. For more info on Python, I'd strongly suggest watching this YouTube video series.
You may know a coding language like Python, but you need a medium through which you can send this code to the machine you want to run your code on, that medium is called an Integrated Development Environment (IDE)). There are many out there, such as VSCode; but I will use Jupyter Lab, as it allows us to use Notebooks in which we write code 'cells' and text 'cells' next to each other, helping me explain what happens in each code cell. (FYI (For Your Information): I do not use Anaconda, but you may chose to, it's up to you.)
We mentioned, in Tutorial 1, a few interesting Python Libraries; let's dig deeped into the most useful ones.
| Tutorial Source Code |
Examples referenced: |
| Last Update | June 2024 |
| Interpreter | Python 3.11.x or greater |
| Pre-requisites | Familiarity with Python and a basic understanding of Jupyter Notebook. If accessing content from:
The majority of the examples are built to work within Jupyter Notebook. Ensure this package is installed. |