Mistakes are a normal part of programming, but don’t let them take you down; you may not even need to stop. The try-except block in Python is a helpful tool to avoid program crashes by catching and process the dealing of the mistakes so that your code can continue to run if something goes wrong.
Beginners often struggle with unexpected errors during runtime. Many of the most common Python errors students make are caused by incorrect assumptions about how code behaves.
TL;DR
What you will learn | Why it matters? |
What exceptions are? | They’re runtime problems – not problems in your code – like bad input or bad files. |
How try-except can help? | It allows your code to keep running even if something bad happens. |
Using else and finally | It helps separate success handling and cleanup. |
Real-world usage | This applies to everything from files to inputs to networks – it will help prevent crashes. |
Common mistakes | Don’t catch everything blindly or hide problems; there are consequences. |
Quiz recap | At the end, there are a couple of short questions that will help make sure you are on track and have picked up the concepts. |
If you’re working on an assignment and struggling to manage errors without breaking your entire code, understanding how try-except works can be a game-changer. You can also check out our Python homework help guide for step-by-step support on common student problems.
What are exceptions and how do they work in Python?
Lapses occur, that’s the nature of coding, a program will not function even if it’s a tiny mistake (placing a file in the wrong folder, etc). Perhaps the user types in text where it should be a number. These are not syntax errors that prevent your code from executing—they’re issues that arise while your code is already running. Python refers to them as exceptions.
Here’s an example:
x = 5
y = 0
print(x / y)
This will crash on a ZeroDivisionError because you’re dividing by zero. Python will throw an error and stop executing the program immediately.
There are loads of other exceptions as well, such as IndexError if you pass the end of a list, or ValueError if you’re trying to convert the wrong type of string to a number. These are standard, and they don’t necessarily imply your logic is faulty. Sometimes it simply means the program encountered something it wasn’t anticipating.
The good news is you don’t have to enclose every line in terror. Python offers a mechanism for exceptions—and that’s what we’re going to explore next.
Syntax of a try-except Block
Since you now understand exceptions, it is time to figure out how to handle them. Python has a try-except construct to allow you to execute your code that can fail and do something upon failure rather than bring down the whole program.
Python’s try-except construct is just as essential to mastering the language as understanding dunder methods, which also control special behavior behind the scenes.
The general form is:
try:
# Code which might throw an exception
except:
# Code that executes if an exception occurs.
For instance:
a = 10
b = 0
try:
result = a / b
print("Result:", result)
except:
print("Something went wrong.")
The above example illustrates the fact that Python attempts to execute the code a / b. When it executes the code, it is faced with an error because b = 0. Rather than crashing the program, it executes the except code, which prints a friendly message.
A few things to keep in mind:
- Only the code inside the try block gets checked for errors.
- If an error occurs, then Python proceeds to the except code block and executes it.
- If no error is found, then Python bypasses the except code block altogether.
- This simple framework works; however, it is good practice to catch specific exceptions (which we will discuss in a minute). But for now, it gives you the essentials.
Let’s move on and see how to deal with multiple exceptions more precisely.
How to Handle Multiple Exceptions in Python?
Not every error is the same. Sometimes you’re dealing with a file that doesn’t exist. Other times it’s a type mismatch or a division by zero. The point is—your code can fail in more than one way, and you’ll often want to handle different problems differently.
If your code processes lists, inputs, or other user data, you’ll often need to handle different types of errors. A strong grasp of Python data structures makes this process more predictable.
That is where we use several except blocks. You can catch individual exceptions and handle each one accordingly.
Here is an example:
try:
num = int(input("Enter a number: "))
result = 10 / num
except ValueError:
print("That wasn't a number.")
except ZeroDivisionError:
print("You can't divide by zero.")
Let’s dissect:
- If they enter something that’s not a number, int() will throw a ValueError.
- If they enter 0, the division will throw a ZeroDivisionError.
- In all these situations, we catch the specific problem and return a definite message.
You can even catch several exceptions in a single line if you’d like to handle them both the same way:
try:
# dangerous stuff
except (ValueError, TypeError):
print("Something went wrong with your input.")
This is neater if you don’t require individual messages for each case.
The important thing here is readability. Catching exceptions is wonderful, but having an idea of what you’re catching and why allows your code to be readable and to a certain extent predictable.
When to use else and finally in try-except blocks?
The try-except block does not only catch errors. Python also provides you with two optional components: else and finally, which make your code cleaner and more predictable.
Let’s begin with else.
The else clause
The else block will execute only if no exception occurs in the try block. It’s handy for partitioning the dangerous code from the code that must execute only when all goes well.
Here’s one example of try/except/else/finally in action:
try:
num = int(input("Enter a number: "))
except ValueError:
print("Is not a valid number.")
else:
print(f"You entered {num}.")
When the conversion works, the block under the elif will be executed. If it fails, we skip it and go straight to the exception.
We don’t need the else, but it provides better structure to our code, particularly when our success path is multi-step.
The finally clause
The finally clause will always run, irrespective of whether there was an error or not. This is typically used for cleanup purposes – closure of files, releasing resources, or printing a completion message.
Example:
try:
f = open("data.txt", "r")
content = f.read()
except FileNotFoundError:
print("File was not found.")
finally:
print("Complete trying to read the file.")
Even if the file does not exist, the finally clause will run. If the file does open, the finally will still run. This makes it a perfect place for things that should be done regardless of success – think logging, closing the file, or resetting values.
To sum up:
- Use else to run code if the previous blocks did not break.
- Use finally to run code regardless of success or failure.
Next, we will examine how these blocks are utilized in real-world examples.
How try-except is used in real-world code?
Understanding how try-except works in theory is one thing, but seeing how it helps in real-world coding is a really big difference. Here are some examples of everyday situations where exception handling really comes in handy.
1. File Handling
Countless things can go wrong when opening files—the file might not exist, your program may not have permission to read it, etc With exception handling, you can simply let users deal with it instead of crashing the program!
try:
f = open("notes.txt", "r")
print(f.read())
except FileNotFoundError:
print("File not found.")
This way, if the file doesn’t exist, the program doesn’t crash; it simply passes the error to the user.
2. User Input Validation
Users don’t always give you what you expect. If you need to have a number and they enter some text, you will get an error unless you catch it.
try:
age = int(input("Enter your age: "))
except ValueError:
print("Please enter a valid number.")
Without this exception, even a simple mistype from the user is enough to crash your program, and now you are even at the mercy of the user!
3. API Requests or Network Errors
Whenever you’re working with the internet (APIs, downloads…), things can go wrong: slow connections, timeouts, faulty responses. Using try-except blocks can help you organize and handle these issues nicely.
import requests
try:
response = requests.get("https://example.com/data")
print(response.json())
except requests.exceptions.RequestException:
print("Network error. Try again later.")
Rather than a long traceback log when you get a network failure, your program returns a simple error message.
These types of errors aren’t rare edge cases. These types of errors happen all the time. Wrapping your logic with try-except blocks means you are building software that won’t fall apart at the first sign of unexpected behaviour.
Common Mistakes To Avoid and Best Practices To Follow
Using try-except is a very straightforward idea. That said, it’s just as easy to misuse it. Some carefulness can make a lot of difference to writing exception handling that is useful and not just obscuring issues. Below are some mistakes to avoid and some good practices to use.
1. Using a bare except: (don’t do this)
There are scenarios where it might be convenient to catch all exceptions, but it is not a good idea. You may also catch system-level errors by accident that you don’t want to handle.
try:
# do something dangerous
except:
print("Some error happened.") # too general
This totally removes any useful error details, and then debugging becomes harder. Unless you have very good reasons, you should not use this pattern.
2. Not specifying the exception type
Catch only what you expect. If you are aware that a specific function may raise a ValueError when using it, then catch that, not all exceptions.
try:
value = int("abc")
except ValueError:
print("Invalid number.") # clear and specific
You also protect yourself from accidentally masking bugs generated from other unexpected behavior.
3. Silently ignoring errors
When you’re in the exception-catching stage, even when you catch and ignore exceptions, your behavior is almost the same as if you weren’t catching them at all.
try:
result = risky_function()
except SomeError:
pass # Bad practice
If you’re not going to fix the problem, at least log it or inform the user. Silently swallowing errors makes it much harder to know when things go wrong.
4. Writing huge try blocks
Only place code in the try that can fail. Otherwise, if something unrelated fails, you might catch it by accident.
Bad:
try:
connect_to_db()
process_data()
send_email()
except Exception:
print("Something failed.") # What failed? No idea.
Better:
try:
connect_to_db()
except ConnectionError:
print("Unable to connect to the database.")
Conclusion
Properly managing errors is what distinguishes just-okay code from robust code. Python’s try-except blocks give you a simple and elegant method of managing unexpected problems, so that your program does not crash or act strangely.
Key Takeaways:
Exceptions are runtime errors that can stop the execution of your program unless you deal with them.
- The try-except block allows you to handle problems in a consistent way.
- You can have multiple except clauses to deal with different issues.
- Else and finally give you even more control over what is run, and when.
- Exception handling is important for realistic (real-world) scenarios, such as file I/O operations, incoming user input, and network data transfers.
- Do not get into bad habits, such as using bare except blocks, or ignoring exceptions totally.
Once you become comfortable with these concepts, your code will become more robust, easier to debug, and safer to run in the real world. So, the next time something does not work as expected, do not panic, simply catch it, deal with it, and move along.
