Whenever I teach the advanced for loop topic to students, they often get confused between two things: the break and continue statements. Students often say, “Why does the loop stop here?” and “Why does the loop skip this particular iteration?”
In this post, I will explain advanced for loop concepts in a simple and effective way, so that you can learn them easily and understand the basics behind them.
1. The break Statement:
It is used to stop a loop immediately if a particular condition is met.
Break statement flowchart:
1. The loop begins, and the program first checks the loop’s condition.
2. If the condition is false, the loop does not run. The flow immediately moves to the code written after the loop, and then the program ends.
3. If the condition is true, the loop enters its body and evaluates the point where the break decision is made.
4. At this point, the program checks whether the break statement should execute:
- If the answer is yes, the break executes, and the loop stops instantly. Control moves to the statements after the loop body.
- If the answer is no, the break does not run, and the program continues with the remaining statements inside the loop.
5. After completing the remaining statements, the flow goes back to the loop condition, and the cycle repeats.
6. Eventually, when the loop condition becomes false or break is triggered, the program moves ahead to the next statements and finally reaches the End.
I think this part becomes clearer once you actually see it in action, so let me show you a small example.
Example:
for num in range(10):
if num == 5:
break
print(num)Output:
0
1
2
3
4
Explanation:
In this example, the loop starts printing numbers from 0 onwards.
Python prints 0, 1, 2, 3, and 4 normally.
But when the number becomes 5, the break statement stops the loop immediately.
That’s why the program ends early and nothing after 4 is printed.
To be honest, I used to get confused (in my early days) about where the loop actually stops, so please don’t worry if it is difficult for you to understand (now) at this stage.
Read it 2-3 times and execute the program and understand the complete flow which would help you to get more clarity.
Real World Application:
a) It is used to search a username (during login) in a large database. It stops the loop immediately after the username is found in the database.
b) It is also used to scan files in antivirus software. The break statement immediately stops scanning of files once a virus signature is found inside any file.
c) Payment gateways (used by Razorpay, Stripe etc.) run multiple checks. It (break statement) breaks the loop once a check is failed.
Why It Matters:
It improves the performance of an application by preventing unwanted iterations.
2. The continue Statement:
It is used to skip the current iteration of a loop and move to the next one.
Please note that if a continue statement comes, then execution of the loop does not stop, only that particular step is skipped.
Example:
for num in range(5):
if num == 2:
continue
print(num)Output:
0
1
3
4
Explanation:
In this example, the loop goes through the numbers 0 to 4.
Everything prints normally, but when Python reaches the number 2, it hits the continue statement.
This tells Python: “Skip this number and move ahead.”
So 2 is not printed - Python simply jumps to 3 and continues the loop as usual.
That’s why the output shows 0, 1, 3, 4 instead of all five numbers.
Sometimes I still double-check my loops when using continue statement because it is easy to skip a value without noticing.
Real World Application:
a) It is used to skip empty rows in an Excel / CSV file.
b) In face recognition systems, you can use it to skip low-quality images during AI training time.
Why It Matters:
a) It is used to clean unwanted data.
b) It also saves a lot of time by ignoring “invalid entries”.
Difference between break and continue:
| Feature | Break | Continue |
| Meaning | If a condition is true, then it immediately stops the loop | If a condition is true, then it Skip the current iteration and moves to next one |
| Effect on Loop | Loop ends completely | Loop continues running |
| Used When | It is used if you want to exit early (found answer, error, etc.) | It is used if you want to skip unwanted values but still continue |
| Flow Control | If a condition is true, then it jumps out of the loop | If a condition is true, then it jumps to the next iteration |
| Inner vs Outer Loop | It only breaks the loop where it is written | It only affects that iteration of the loop where it is written |
3. Nested For loops:
A nested loop simply means:
• A loop inside another loop
• The inner loop runs completely for every single step of the outer loop.
Nested for loops are useful in scenarios where your data has two levels like:
a) rows and columns
b) students and subjects
c) products and categories
Example:
for x in range(2):
for y in range(3):
print(x, y)Output:
0 0
0 1
0 2
1 0
1 1
1 2
Explanation:
In this example, we have one loop inside another loop.
The outer loop runs first and gives us the value of x (0 and then 1).
For each value of x, the inner loop runs fully and gives us the values of y (0, 1, and 2).
So, the output looks like a small table of all possible combinations of x and y.
First x stays 0 while y changes, then x becomes 1 and again y goes through all its values.
That’s why you see the above output.
I personally prefer to visualize nested loops like a small grid or matrix because it makes the flow much easier to understand.
In simple words, it is simply showing every combination of the two loops.
When I first saw nested loops, it felt like too much to handle at that time and was difficult to understand, but it becomes super simple once you visualize it.
Real World Application:
a) It is used to process 2D arrays.
b) It is also used to test AI models across multiple parameters.
4. For Loop with Else:
In Python language, a for loop can have an else block as well.
• If the loop finishes all iterations, only then the else block is executed.
• If the loop is stopped using the break statement, then the else block is not executed.
Example 1:
for i in range(3):
print(i)
else:
print("Loop completed")Output:
0
1
2
Loop completed
Explanation:
In this example, the loop runs three times and prints the numbers 0, 1, and 2 one after another.
Once the loop finishes all its iterations normally, Python moves to the else block.
The important part is this: the else block runs only when the loop completes without using break.
Since we didn’t stop the loop in between, Python prints “Loop completed” at the end to show that everything ran smoothly.
So, the final output is the three numbers, followed by the confirmation message.
Most beginners miss this small detail, and trust me, even I ignored for- else for years until I actually needed it in a project and then I came to know about for-else.
Example 2:
for i in range(5):
if i == 2:
break
print(i)
else:
print("Done")Output:
0
1
Explanation:
In this example, the loop prints 0 and 1, but when it reaches 2, the break statement stops everything immediately.
Because the loop ended early, Python skips the else block completely.
That’s why only 0 and 1 appear, and “Done” is never printed.
Why Do We Need for…else?
1. It helps to know if a loop ran completely or ended early.
2. It also helps us to know if a search is completed successfully or failed.
I think many students overlook this feature because it is not used very often, but it actually simplifies a lot of real-world checks.
5. Looping Over Dictionaries:
A dictionary stores data in key-value pairs. Python allows you to loop through both keys and values using .items().
Example:
student = {"name": "Aadi", "age": 9, "grade": "4th"}
for key, value in student.items():
print(f"{key}: {value}")Output:
name: Aadi
age: 9
grade: 4th
Explanation:
This example has a small dictionary that stores a student’s details like name, age, and grade. When the loop runs, Python takes one key–value pair at a time from the dictionary.
It then prints them in a clean format like “name: Aadi” and “age: 9”. This is an easy way to read all information stored inside a dictionary.
Why It Matters:
Today, dictionaries are used in almost every real project like:
• JSON data from APIs
• Configuration settings
• Product information
• Database records
It becomes very important to know how to loop through them efficiently.
6. Commenting and Uncommenting Code:
Comments are lines inside your code that Python ignores completely.
Basically, comments are used in multiple ways:
a) It is used to explain the code
b) It is also used to disable certain lines temporarily
c) It becomes easier to understand the code
In Python language, you can start writing a comment using #.
Example 1: Single Style Comment
# Python will not run this line
print("Welcome")Output:
Welcome
Explanation:
The first line starts with #, so Python treats it as a comment and completely ignores it.
Only the second line runs, which simply prints “Welcome” on the screen.
Example 2: Inline Comment
print("Welcome”) # This line prints a messageOutput:
Welcome
Explanation:
This is another way of adding a short note beside your code using #.
The print statement runs normally, and the text after # is just a helpful comment for the reader.
Example 3: Multi-line Comment
"""
This explains
multiple lines
but Python ignores it
"""
print("Done")Output:
Done
Explanation:
This is a third way of writing a comment using triple quotes, and Python simply ignores everything inside them.
Only the print statement runs, so the output will just show “Done”.
Note:
If you want to comment a single or multiple line, then you can use shortcuts like Ctrl + / on Windows Operating System.
Why Commenting is Important?
Other developers can understand your code easily without asking any questions to you.
It also helps in teamwork, debugging, and code review as well.
Conclusion: Putting It All Together
Advance For Loop concepts (like break, continue, nested loop and for-else) look difficult initially, but they become easy to understand and work with after a few days of regular practice. These topics help you learn how real programs behave.
Honestly, if you are not able to understand any part completely, then don’t worry. This is common for every beginner. My advice is to study the concept, run the programs multiple times, understand the flow, and it will help you understand these concepts faster.