Python basics

Python basics#

This is a very quick introduction to Python. It is not meant to be comprehensive, but rather a quick overview of the most important concepts that we will use when operating Pyomo or Calliope in other chapters. If you already have basic Python skills, you can skip this.

Where and what to learn#

For our purposes you can get away with using Python in a basic way, like a scientific calculator.

However, learning some basic Python, like minimal use of control statements (especially for loops) will make some steps quicker and easier to do.

There are many online resources to learn Python. Some examples are listed below - check out different options and see what works best for you.

  • LearnPython. The website LearnPython.org provides a free, interactive introduction to Python.

  • QuantEcon: Python Programming for Economics and Finance. The website QuantEcon: Python Programming for Economics and Finance teaches you Python by giving you information, examples, and possibilities to try for yourself. In particular, their chapters “1. About Python” through “6. OOP I: Introduction to Object Oriented Programming” (leaving out chapter 7, which goes into more detail on object-oriented programming); then, all chapters from 8 onwards which give an overview of Python’s most important scientific packages.

  • Software Carpentry. The Plotting and Programming in Python lesson from Software Carpentry is a good hands-on tutorial.

  • YouTube videos: On YouTube there are many videos that teach Python. Try this playlist: “Python Programming Beginner Tutorials”.

Jupyter notebooks#

Some of the chapters in this reader are Jupyter notebooks. These are executable documents that combine elements of a written document with (Python) code and the results of that code (e.g. text or images).

If you are unfamiliar with Jupyter, I recommend watching this 25 minute YouTube video to get an overview of how these notebooks work: Jupyter Notebook Complete Beginner Guide 2023 - From Jupyter to Jupyterlab, Google Colab and Kaggle!.

Common issues and points to remember#

Python:

  • Use ** for exponent, not ^: e.g. 2**2 for \(2^2\).

  • Careful: whitespace has meaning in Python - it is used to structure the code into separate logical blocks. For example, to delineate what code is inside an if-block (in this example y only becomes 2 if x > 1, whereas z = 3 is outside the if-block and always executed):

if x > 1:
    y = 2
z = 3

Jupyter notebooks:

  • Jupyter notebooks consists of cells. Some cells contain text. Others contain code. Cells with code can be executed: while your cursor is inside the cell, press Shift + Return.

  • Notebook cells in a notebook all run in the same Python interpreter. For example, assign 1 to a variable: x = 1. If you execute this in a notebook cell, all other notebook cells now have access to the variable x.

  • Within the notebook environment, just executing a command will show you the results: writing 1 + 1 in a cell and executing that cell will print 2. Writing x in a cell will print 1 (if the variable x was previously assigned as above).

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