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Exception Handling in Python

Updated on 22/05/20245,565 Views


In the programming world, especially in Python, challenges often emerge in the form of unexpected errors. The power of Python lies not just in its vast capabilities but also in how it allows developers to handle these unforeseen errors. This tutorial will guide professionals through the labyrinth of exception handling in Python, ensuring that your applications run seamlessly, even when they encounter unexpected bumps.


Exception handling is the process by which Python allows a programmer to handle these aforementioned "bumps" or errors. Beyond just managing errors, exception handling in Python ensures that your application's user experience remains unhindered. As we navigate this tutorial, we'll uncover the essence of exceptions, their types, and the advantages and disadvantages of managing them in Python.

What is Meant by an Exception?

In programming, errors are akin to unforeseen obstacles on a well-planned road trip. These aren’t just trivial disruptions; they can potentially halt our journey, demanding immediate attention. As seasoned developers, we recognize that no matter how meticulous our code is or how well we chart our path, these errors remain an inevitable part of the journey.

In the context of Python—a language celebrated for its simplicity and power—an "exception" stands as a testament to this unpredictability. Specifically, an exception in Python is an event that arises unexpectedly during the execution phase of a program, causing a disruption in the expected flow of the program's instructions. Imagine crafting a sequence of actions, only to have an unanticipated event render a portion of it unworkable. That's precisely the scenario exceptions present.

Catching Exceptions with try and except Statements

The try and except statement is used for handling exceptions or errors that may occur during the execution of your code. It allows us to gracefully handle errors without crashing the program.

Here is the syntax:

    # Code that may raise an exception

except ExceptionType:
    # Code to handle the exception

In the above syntax,

  • try: The code block where you anticipate an exception to occur.
  • except ExceptionType: The code block that gets executed when an exception of the specified type occurs.

Here is an example of catching a division by zero exception:


    result = 10 / 0  # For raising a ZeroDivisionError
except ZeroDivisionError:
    print("Division by zero is not allowed.")

In the above code, the try block tries dividing 10 by 0, raising a ZeroDivisionError. This specific exception is caught by the except block and it prints a message.

Raising an Exception

You can raise an exception manually using the raise statement. This is useful when you want to signal an error condition explicitly.

Here is the syntax:

raise ExceptionType("Optional error message")

In the above syntax,

  • raise: The keyword used to raise an exception.
  • ExceptionType: The type of exception you want to raise.
  • "Optional error message": An optional error message that provides additional information about the exception.

Here is an example of raising a custom exception:

def divide(a, b):
    if b == 0:
        raise ValueError("Division by zero is not allowed")
    return a / b

    result = divide(10, 0)
except ValueError as e:
    print("Error:", str(e))

In this example, the divide function raises a custom ValueError exception with a specific error message when attempting to divide by zero.

assert Statement in Python

Assertions are used for debugging and testing purposes. They allow you to check whether a condition holds true and raise an exception if it does not.

Here is the syntax:

assert condition, "Optional error message"

In the above syntax,

  • assert: The keyword used to perform an assertion check.
  • condition: The expression to be evaluated for truthiness.
  • "Optional error message": An optional error message that gets displayed if the condition is False.

Here is an example of using assert for debugging:

def divide(a, b):
    assert b != 0, "Division by zero is not allowed"
    return a / b

result = divide(10, 0)

In this example, the assert statement is used to check that b is not equal to zero before performing the division. If the condition is False, an AssertionError is raised with the specified error message.

Types of Exceptions in Python

  • ArithmeticError: At the heart of many programs are complex calculations, but not all mathematical operations go off without a hitch. This exception is Python's way of flagging an arithmetic operation that's hit a snag. Prime examples include trying to divide a number by zero or operations resulting in an overflow.
  • AttributeError: Python is made up of objects, and every object comes with attributes. However, not all attribute references or assignments proceed as planned. This exception signals when you're trying to access or assign an attribute that doesn't exist or isn't available in the current context.
  • EOFError: Data streams are essential, but what happens when they unexpectedly run dry? This exception pops up when the input() function runs into an end-of-file condition without having read any data. It's like trying to draw water from a well, only to find it has suddenly run dry.
  • ImportError: Modules enhance the functionality of Python scripts, but they need to be available to do so. This exception is raised when a module, vital to the program's operation, can't be located or loaded. It's akin to missing a crucial ingredient while cooking a complex dish.
  • IndexError: Lists and arrays are central to data storage in Python. This exception arises when there's an attempt to access an index that's out of the range of the list or array. Imagine trying to pick a book from a shelf that doesn't exist.
  • KeyError: Python dictionaries store data in key-value pairs. This exception is the result of trying to retrieve a value using a key that's not present in the dictionary. It's much like looking for an entry in an index that's not listed.
  • TypeError: Data types are fundamental in Python. This exception comes into play when an operation or function is applied to an object of inappropriate type, like trying to add a string to an integer.

Catching Specific Exceptions in Python

As we discussed before, we can use the try and except statement to catch specific exceptions by specifying the exception type(s) you want to handle. This allows us to handle different exceptions differently based on their types.

Let us try catching a ValueError exception:

    age = int(input("Enter your age: "))
except ValueError:
    print("Invalid input. Please enter a valid age.")

In this example, we catch a ValueError exception that occurs when trying to convert user input to an integer.

try and except With else Clause

You can use the else clause in conjunction with the try and except statement. The code in the else block gets executed if no exceptions are raised in the try block.

Here is the syntax:

    # Code that may raise an exception

except ExceptionType:

    # Code to handle the exception

    # Code to execute if no exception occurs

Here is an example of using: Using try with else Clause:
    result = 10 / 0
except ZeroDivisionError:
    print("Division by zero is not allowed.")
    print("Result:", result)

In this example, if no ZeroDivisionError occurs, the code in the else block will execute and print the result.

The finally keyword in Python

The finally keyword is used to define a block of code that will be executed regardless of whether an exception occurs or not. This is useful for tasks like resource cleanup.

Here is the syntax:

    # Code that may raise an exception
except ExceptionType:
    # Code to handle the exception


# Code that always executes, regardless of exceptions

Example of using try with finally clause:

    file = open("example.txt", "r")
    # Code that may raise an exception while working with the file
except FileNotFoundError:
    print("File not found.")


file.close() # Ensure the file is always closed, even if an exception occurs

In this example, the finally block ensures that the file is closed, whether or not an exception occurs.

Exceptions List in Python

Here is a list of some common built-in exceptions in Python:

BaseException: The base class for all built-in exceptions.

SystemExit: Raised when Python interpreter is quitting.

KeyboardInterrupt: Raised when the user interrupts program execution, typically by pressing Ctrl+C.

Exception: The base class for all built-in exceptions except SystemExit, KeyboardInterrupt, and GeneratorExit.

StopIteration: Raised when an iterator is exhausted. This is typically caught implicitly in for loops and other iteration constructs.

GeneratorExit: Raised when a generator is closed.

ArithmeticError: The base class for numeric errors like ZeroDivisionError and OverflowError.

OverflowError: Raised when an arithmetic operation exceeds the limits of its numeric type.

FloatingPointError: Raised when a floating-point operation fails.

ZeroDivisionError: Raised when division or modulo operation is performed with zero as the divisor.

AssertionError: Raised when an assert statement fails.

AttributeError: Raised when an attribute reference or assignment fails.

BufferError: Raised when a buffer-related operation cannot be performed.

EOFError: Raised when the input() function hits an end-of-file condition (Ctrl+D on UNIX, Ctrl+Z on Windows).

ImportError: Raised when an import statement fails to find the module or name being imported.

ModuleNotFoundError: A subclass of ImportError, raised when a module could not be found.

LookupError: The base class for lookup errors (e.g., IndexError and KeyError).

IndexError: Raised when trying to access an index that doesn't exist in a sequence (e.g., list or tuple).

KeyError: Raised when trying to access a dictionary key that doesn't exist.

NameError: Raised when an identifier is not found in the local or global namespace.

UnboundLocalError: Raised when trying to access a local variable before it has been assigned a value.

TypeError: Raised when an operation or function is applied to an object of inappropriate type.

ValueError: Raised when an operation or function receives an argument of the correct type but an inappropriate value.

UnicodeError: The base class for all Unicode-related errors (e.g., UnicodeEncodeError and UnicodeDecodeError).

UnicodeEncodeError: Raised when encoding a Unicode string fails.

UnicodeDecodeError: Raised when decoding a Unicode string fails.

UnicodeTranslateError: Raised when translating a Unicode string fails.

AssertionError: Raised when an assert statement fails.

IndentationError: The base class for indentation-related errors (e.g., TabError and IndentationError).

TabError: Raised when inconsistent use of tabs and spaces in indentation is detected.

EnvironmentError: The base class for exceptions that can occur outside the Python system (e.g., IOError and OSError).

IOError: Raised when an I/O operation (e.g., file operations) fails.

OSError: Raised for operating system-related errors.

FileNotFoundError: A subclass of OSError, raised when a file or directory is not found.


Navigating the complexities of Python's exception handling elucidates its indispensable role in modern-day programming. Adeptly leveraging this feature ensures software robustness and user satisfaction. For professionals eager to delve deeper into Python's vast landscape, upGrad's extensive upskilling courses stand as invaluable resources.


1. How is the Python raise exception employed?

The raise statement allows developers to forcefully generate a specified exception, facilitating testing of exception handling routines.

2. What does Python try-except: print error accomplish?

This structure captures exceptions and prints the corresponding error message, offering clarity on the nature of the issue.

3. Can you explain the user-defined exception in Python?

Python allows developers to define bespoke exceptions to cater to specific application needs, enhancing error detection and handling efficiency.

4. What encompasses a Python exception message?

It's a descriptive text tied to an exception, shedding light on the anomaly for developers and users.

5. Could you explain the exception hierarchy in Python?

Python's exceptions are structured hierarchically, with a base class at the summit. This hierarchy enables systematic handling based on exception specificity.



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