Python check if exception raised

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Learn how to use pytest assert raises to test if your code raises an exception or not

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Time is a precious resource so I won’t waste yours. Here’s how you can assert an exception is raised and how to check that in pytest .

Solution: Use pytest.raises

And here’s how you assert no exception is raised.

Solution: Enclose your code in a try/except block and and if the code raises, you can catch it and print a nice message. pytest is smart enough to make the test fail even if you don’t catch it but having a message makes your test cleaner.

And that’s it, if you want to know more, please follow along.

Introduction

In this tutorial, you’ll learn how to use pytest to:

• assert that an exception is raised
• assert the exception message
• assert the exception type
• assert that an exception is not raised

In a nutshell, we’ll see how to use pytest.raises for each of those cases with examples.

Table of Contents

How to Assert That an Exception Is Raised

In this section, I’m going to show you how you can assert that your code raises an exception. This is a frequent use case and can sometimes tricky. The wonderful thing is, if you are using pytest you can do that in an idiomatic and cleaner way.

Let’s imagine that we have a function that checks for some keys in a dictionary. If a key is not present, it should raise a KeyError . As you can see, this is very generic and doesn’t tell the users much about the error. We can make it cleaner by raising custom exceptions, with different messages depending on the field.

Now, time to test this. How can we do that with pytest ?

This code is deliberately wrong, as you can see we’re not raising anything. In fact, we want to see test failing first, almost like TDD. After seeing the test failing, we can fix our implementation and re-run the test.

Then we get the following output:

Ok, this makes sense, now it’s time to fix it. We’ll check if the data dict has both x and y , otherwise we raise a MissingBothCoordException .

And when we re-run the test, it passes.

Great! And that is pretty much it. This is how you check if an exception is raised with pytest . In the next section, we’re going to improve our function and we’ll need another test.

How to Assert the Exception Message — And Type

In this section, we’ll improve our sum_x_y function and also the tests. I’ll show you how you can make your test more robust by checking the exception message.

With that in mind, let’s expand the sum_x_y function.

The new test goes like this:

However, it’s a bit fragile. In case you haven’t noticed it, when «x» is missing, the exception message is: «The Y coordinate is not present in the data.» . This is a bug, and one way to detect it is by asserting we return the right message. Thankfully, pytest makes it easier to do.

If we refactor the test to take into account the message, we get the following output:

That’s exactly what we want. Let’s fix the code and re-run the test.

This is possible because pytest.raises returns an ExceptionInfo object that contains fields such as type , value , traceback and many others. If we wanted to assert the type , we could do something along these lines.

However, we are already asserting that by using pytest.raises so I think asserting the type like this a bit redundant. When is this useful then? It’s useful if we are asserting a more generic exception in pytest.raises and we want to check the exact exception raised. For instance:

One more way to assert the message is by setting the match argument with the pattern you want to be asserted. The following example was taken from the official pytest docs.

As you can see, we can verify if the expected exception is raised but also if the message matches the regex pattern.

How to Assert That NO Exception Is Raised

The last section in this tutorial is about yet another common use case: how to assert that no exception is thrown. One way we can do that is by using a try / except . If it raises an exception, we catch it and assert False.

When we run this test, it passes.

Now, let’s create a deliberate bug so we can see the test failing. We’ll change our function to raise an ValueError before returning the result.

And then we re-run the test.

It works! Our code raised the ValueError and the test failed!

Conclusion

That’s it for today, folks! I hope you’ve learned something new and useful. Knowing how to test exceptions is an important skill to have. The way pytest does that is, IMHO, cleaner than unittest and much less verbose. In this article, I showed how you can not only assert that your code raises the expected exception, but also assert when they’re not supposed to be raised. Finally, we saw how to check if the exception message is what you expect, which makes test cases more reliable.

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Python Exceptions: An Introduction

Table of Contents

Watch Now This tutorial has a related video course created by the Real Python team. Watch it together with the written tutorial to deepen your understanding: Raising and Handling Python Exceptions

A Python program terminates as soon as it encounters an error. In Python, an error can be a syntax error or an exception. In this article, you will see what an exception is and how it differs from a syntax error. After that, you will learn about raising exceptions and making assertions. Then, you’ll finish with a demonstration of the try and except block.

Exceptions versus Syntax Errors

Syntax errors occur when the parser detects an incorrect statement. Observe the following example:

The arrow indicates where the parser ran into the syntax error. In this example, there was one bracket too many. Remove it and run your code again:

This time, you ran into an exception error. This type of error occurs whenever syntactically correct Python code results in an error. The last line of the message indicated what type of exception error you ran into.

Instead of showing the message exception error , Python details what type of exception error was encountered. In this case, it was a ZeroDivisionError . Python comes with various built-in exceptions as well as the possibility to create self-defined exceptions.

Raising an Exception

We can use raise to throw an exception if a condition occurs. The statement can be complemented with a custom exception.

If you want to throw an error when a certain condition occurs using raise , you could go about it like this:

When you run this code, the output will be the following:

The program comes to a halt and displays our exception to screen, offering clues about what went wrong.

The AssertionError Exception

Instead of waiting for a program to crash midway, you can also start by making an assertion in Python. We assert that a certain condition is met. If this condition turns out to be True , then that is excellent! The program can continue. If the condition turns out to be False , you can have the program throw an AssertionError exception.

Have a look at the following example, where it is asserted that the code will be executed on a Linux system:

If you run this code on a Linux machine, the assertion passes. If you were to run this code on a Windows machine, the outcome of the assertion would be False and the result would be the following:

In this example, throwing an AssertionError exception is the last thing that the program will do. The program will come to halt and will not continue. What if that is not what you want?

The try and except Block: Handling Exceptions

The try and except block in Python is used to catch and handle exceptions. Python executes code following the try statement as a “normal” part of the program. The code that follows the except statement is the program’s response to any exceptions in the preceding try clause.

As you saw earlier, when syntactically correct code runs into an error, Python will throw an exception error. This exception error will crash the program if it is unhandled. The except clause determines how your program responds to exceptions.

The following function can help you understand the try and except block:

The linux_interaction() can only run on a Linux system. The assert in this function will throw an AssertionError exception if you call it on an operating system other then Linux.

You can give the function a try using the following code:

The way you handled the error here is by handing out a pass . If you were to run this code on a Windows machine, you would get the following output:

You got nothing. The good thing here is that the program did not crash. But it would be nice to see if some type of exception occurred whenever you ran your code. To this end, you can change the pass into something that would generate an informative message, like so:

Execute this code on a Windows machine:

When an exception occurs in a program running this function, the program will continue as well as inform you about the fact that the function call was not successful.

What you did not get to see was the type of error that was thrown as a result of the function call. In order to see exactly what went wrong, you would need to catch the error that the function threw.

The following code is an example where you capture the AssertionError and output that message to screen:

Running this function on a Windows machine outputs the following:

The first message is the AssertionError , informing you that the function can only be executed on a Linux machine. The second message tells you which function was not executed.

In the previous example, you called a function that you wrote yourself. When you executed the function, you caught the AssertionError exception and printed it to screen.

Here’s another example where you open a file and use a built-in exception:

If file.log does not exist, this block of code will output the following:

This is an informative message, and our program will still continue to run. In the Python docs, you can see that there are a lot of built-in exceptions that you can use here. One exception described on that page is the following:

Raised when a file or directory is requested but doesn’t exist. Corresponds to errno ENOENT.

To catch this type of exception and print it to screen, you could use the following code:

In this case, if file.log does not exist, the output will be the following:

You can have more than one function call in your try clause and anticipate catching various exceptions. A thing to note here is that the code in the try clause will stop as soon as an exception is encountered.

Warning: Catching Exception hides all errors…even those which are completely unexpected. This is why you should avoid bare except clauses in your Python programs. Instead, you’ll want to refer to specific exception classes you want to catch and handle. You can learn more about why this is a good idea in this tutorial.

Look at the following code. Here, you first call the linux_interaction() function and then try to open a file:

If the file does not exist, running this code on a Windows machine will output the following:

Inside the try clause, you ran into an exception immediately and did not get to the part where you attempt to open file.log. Now look at what happens when you run the code on a Linux machine:

Here are the key takeaways:

• A try clause is executed up until the point where the first exception is encountered.
• Inside the except clause, or the exception handler, you determine how the program responds to the exception.
• You can anticipate multiple exceptions and differentiate how the program should respond to them.
• Avoid using bare except clauses.

The else Clause

In Python, using the else statement, you can instruct a program to execute a certain block of code only in the absence of exceptions.

Look at the following example:

If you were to run this code on a Linux system, the output would be the following:

Because the program did not run into any exceptions, the else clause was executed.

You can also try to run code inside the else clause and catch possible exceptions there as well:

If you were to execute this code on a Linux machine, you would get the following result:

From the output, you can see that the linux_interaction() function ran. Because no exceptions were encountered, an attempt to open file.log was made. That file did not exist, and instead of opening the file, you caught the FileNotFoundError exception.

Cleaning Up After Using finally

Imagine that you always had to implement some sort of action to clean up after executing your code. Python enables you to do so using the finally clause.

Have a look at the following example:

In the previous code, everything in the finally clause will be executed. It does not matter if you encounter an exception somewhere in the try or else clauses. Running the previous code on a Windows machine would output the following:

Summing Up

After seeing the difference between syntax errors and exceptions, you learned about various ways to raise, catch, and handle exceptions in Python. In this article, you saw the following options:

• raise allows you to throw an exception at any time.
• assert enables you to verify if a certain condition is met and throw an exception if it isn’t.
• In the try clause, all statements are executed until an exception is encountered.
• except is used to catch and handle the exception(s) that are encountered in the try clause.
• else lets you code sections that should run only when no exceptions are encountered in the try clause.
• finally enables you to execute sections of code that should always run, with or without any previously encountered exceptions.

Hopefully, this article helped you understand the basic tools that Python has to offer when dealing with exceptions.

Watch Now This tutorial has a related video course created by the Real Python team. Watch it together with the written tutorial to deepen your understanding: Raising and Handling Python Exceptions

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About Said van de Klundert

Said is a network engineer, Python enthusiast, and a guest author at Real Python.

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