Iterating with For Loops

Welcome to our next lesson. In our previous session, we established how to control the flow of a program by making decisions with if, elif, and else statements. These tools allow your code to choose which path to take. Today, we'll explore another fundamental type of flow control: repetition.

Often in programming, especially in the data-centric fields of AI and NLP you're interested in, you need to perform the same action on many items—for example, cleaning every word in a sentence or processing every data point in a file. Instead of writing the same code over and over, we use loops. This lesson focuses on the for loop, Python's primary tool for iterating over a sequence of items. By the end of this lesson, you will be able to write for loops to process items in sequences and repeat actions a specific number of times using ranges.

The Power of Repetition: Introducing the for Loop

Imagine you have a list of prices and need to apply a discount to each one. You could write a line of code for each price, but what if you had a thousand prices? This is where loops become essential. A for loop automates this repetition, saving you time and making your code cleaner and more scalable.

The "Visually Explained" channel provides a fantastic introduction to why we need loops and how they work.

As the video showed, the basic structure of a for loop is intuitive. It follows a simple logic: "for each item in this collection, do this action."

Let's formalize the syntax, which you saw in the video.

# for `variable` in `sequence`:
#     # Indented code block (the "loop body")
#     # This code runs once for each item in the sequence.

fruits = ["apple", "banana", "cherry"]
for fruit in fruits:
    print(f"I have a {fruit}")

print("Loop finished!")

In this example, fruit is the loop variable. In the first pass, fruit is "apple". In the second, it's "banana", and in the third, it's "cherry". The indented print() statement is the loop body. The final, unindented print() statement runs only once, after the loop has processed every item in the list.

Iterating Over Common Sequences

The for loop is designed to work with any "sequence" or collection of items. Let's look at the two most common types you'll encounter at this stage: lists and strings.

The article "Python for Loop | Iterating Sequences" provides clear code examples for both.

As you can see, the for loop provides a consistent way to work through a collection, whether it's a list of numbers or a string of characters. This is a powerful idea. In NLP, you will use this exact technique to loop through sentences (lists of words) or words (lists of characters).

The flowchart below illustrates this process for a string. The loop checks if there are more items (letters) in the sequence. If yes, it processes the current item and repeats. If no, it exits.

Repeating Actions a Specific Number of Times with range()

Sometimes you don't have a pre-existing list to loop over. Instead, you just want to repeat an action a specific number of times. For this, Python gives us the built-in range() function.

The range() function generates a sequence of numbers that you can use with a for loop. This is perfect for tasks like "run this simulation 100 times" or "create 10 test users".

The Visually Explained video has another clear segment on this.

The range() function is very flexible. Let's look at its three main forms, which are essential to master.

1. range(stop): Generates numbers from 0 up to (but not including) stop.
   • range(5) produces 0, 1, 2, 3, 4.
2. range(start, stop): Generates numbers from start up to (but not including) stop.
   • range(2, 6) produces 2, 3, 4, 5.
3. range(start, stop, step): Generates numbers from start up to (but not including) stop, incrementing by step.
   • range(1, 10, 2) produces 1, 3, 5, 7, 9.

This infographic is a great visual summary of how range() works.

For a more detailed textual reference on range(), the "Iterating Sequences" article is also an excellent resource.

Practical Application: The Accumulator Pattern

One of the most common and powerful ways to use a for loop is to "accumulate" a result. You start with a variable initialized to a starting value (like 0 or an empty string), and then you use the loop to update that variable in each iteration.

A classic example is summing the numbers in a list.

Here is the logic step-by-step:

1. Create an "accumulator" variable, total_score, and set it to 0.
2. The for loop begins. In the first iteration, score is 88. The line total_score = total_score + score becomes total_score = 0 + 88, so total_score is now 88.
3. In the second iteration, score is 92. The line becomes total_score = 88 + 92, so total_score is now 180.
4. This continues for all scores.
5. After the loop finishes, total_score holds the final sum.

Your Turn: Practice with Loops and Conditionals

Now it's time to combine what you've learned about for loops with the if statements from our last lesson. The following exercise asks you to loop through a list of numbers and print only the ones that meet certain criteria.

To solve this, you'll need two more keywords that give you finer control inside a loop:

• break: Immediately exits the entire loop. No more iterations will run.
• continue: Immediately stops the current iteration and jumps to the beginning of the next one.

For example:

for i in range(10):
    if i == 5:
        break # Stops the loop when i is 5. Only 0, 1, 2, 3, 4 will be printed.
    print(i)

for i in range(10):
    if i % 2 != 0: # If i is odd...
        continue # ...skip the print statement and go to the next iteration.
    print(i) # This will only print even numbers: 0, 2, 4, 6, 8.

Now, try the exercise from learnpython.org.

Conclusion

In this lesson, we moved from making decisions to performing repetitions. You've learned how to use for loops, one of the most essential tools in a programmer's toolkit.

Key takeaways include:

• for loops are used to iterate over items in a sequence (like a list or a string).
• The for item in sequence: syntax is clean and readable.
• The range() function is your tool for repeating an action a fixed number of times by generating a sequence of numbers.
• The accumulator pattern (initializing a variable before a loop and updating it inside) is a fundamental technique for tasks like summing numbers or building strings.
• break and continue give you extra control over a loop's execution.

You now understand the two main pillars of flow control: conditional execution (if/else) and iteration (for loops). In the next lesson, we will explore Python's other type of loop, the while loop, which repeats an action as long as a condition is true, rather than for a fixed number of items.