Python 101 - Flow Control in Python Code

ENV 859 - Geospatial Data Analytics   |   Fall 2025   |   Instructor: John Fay  

Introduction

As we move beyond the “building blocks” of Python, i.e., scalar variables and data structures, we shift focus onto how to integrate these objects into logical workflows. Specifically, we cover conditional processing (if… else) and iteration using two type of loops: for and while.

This session builds right off the last session again using VanderPlas’ Whirlwind Tour of Python as a guide. This document highlights the key concepts you should know, and then we cementing these concepts with a set of exercises to work on within your Jupyter environment.

Topics and Learning Objectives

Topic On completion, you should be able to…
1. Conditional Statements ♦ Use colons and whitespace to define code blocks
♦ Construct simple and compound Boolean conditions
♦ Conditionally execute code blocks using if
♦ Describe why else might be used with an if statement
♦ Describe wh yelif might be used with an if statement
2. Iteration with for loops ♦ Iterate through items in a collection using a for loop
♦ Use the variable created in the for loop within the repeated code
3. Iterators and the range() function ♦ Iterate through sequential numbers using range() w/ a for loop
♦ Modify the range function to count via steps and backwards
♦ Describe what an iterator is relative to a list object and why it is useful
4. Iteration with while loops ♦ Explain the difference between a for loop and a while loop
♦ Iterate until a condition is met using a while loop
♦ Explain why it’s necessary that the evaluator changes inside a while loop
♦ Use Jupyter’s interrupt command to exit out of an infinite loop
5. Fine tuning loops with break and continue ♦ Use the break statement in a loop to end the loop
♦ Use the continue statement in a loop to skip to its next iteration

1. Conditional Statements: if-elif-else

Reading: WToP: 07-Control-Flow-Statements.ipynb

Key Concepts:

  • Using the if statement to control what code gets run.
  • Code blocks in Python and the importance of colons (:) and white pace in constructing them.
  • Constructing simple and compound Boolean conditions for use in conditional statements.
  • How elif can be used to add more conditional code blocks.
  • How else can be used to run code when all the if’s and elif’s are not met.

Exercises:

  • 3.1.1 and 3.1.2 in PythonExercises3.ipynb

2. Iteration with for loops

Reading: WToP: 07-Control-Flow-Statements.ipynb - for loops

Key Concepts:

  • Using for loops to iterate through items in a collection
  • The structure and syntax of for loops:
    • The use of : and indentation to define the code blocks to repeat
  • How the variable used in for loops is used in the repeated code block:
    • In for x in [1,2,3]:, the value of x changes with each iteration of the code block

Exercises:

  • 3.2.1 thru 3.2.4 in PythonExercises3.ipynb

3. [Iterators and] The range() function

Reading: WToP: 10-Iterators.ipynb

Key Concepts:

  • The range() function to generate a collection of numbers.
  • → Python v2 vs v3: use list with range() in v3 to show values
    • Because in Python 3, range() returns an iterator object…
  • Setting only the end point: range(20)
  • Setting the start and end point range(10,20)
  • Setting the start and end points, and the step (range(10,20,2))
  • Counting down by making the step negative (range(10,0,-1))
  • Using the range() function in a for loop to iterate a set amount of times.

Exercises:

  • 3.3.1 thru 3.3.3 in PythonExercises3.ipynb

4. Iteration with while loops

Reading: WToP: 07-Control-Flow-Statements.ipynb - while loops

Key Concepts:

  • Using while to iterate until a condition is no longer met
  • The structure of the while loop syntax
    • The use of : , evaluation condition, and indentation to define the code blocks to repeat
  • The need to define a variable that gets evaluated as True/False before starting the while loop
  • The need to change the variable that gets evaluated within the while loop
  • How to stop infinite loops (interrupting the kernel in Jupyter)

Exercises:

  • 3.4.1 thru 3.4.2 in PythonExercises3.ipynb

5. Fine-Tuning your loops w/ break and continue

Reading: WToP: 07-Control-Flow-Statements.ipynb - break & continue

Key Concepts:

  • The break statement breaks-out of the loop entirely
  • The continue statement skips the remainder of the current loop, and goes to the next iteration

Exercises:

  • 3.5.1 thru 3.5.2 in PythonExercises3.ipynb

Recap - What’s next

Ok. That’s a lot of Python without much context of what we can actually do with it. You would be ahead of the game if you have all this material neatly packed in your head. More realistically, you now have a basic feel for how the language works but maybe still have to jump back and forth between the documentation to get it right. And that’s fine! (I hope it is, because I still do it quite often and I’ve been using Python for over a decade!)

So, what’s next is putting all this knowledge into context with examples of what Python can do for you, and how to go about doing that. We’ll explore some additional tools that help you code and techniques that should allow you to code more effectively and efficiently.