• Articles
  • Tutorials
  • Interview Questions

Exception Handling in Python with Examples

Tutorial Playlist

Exception Handling in Python

What is Exception Handling in Python? Well, before we get you started on Exception Handling in Python, let’s learn about it from the beginning. It is obvious for a developer to encounter a few errors or mistakes in their code file. But what if developers could minimize these errors? Wouldn’t it be great? There are exception handling in Python methods, which help developers deal with potential errors and mistakes. I hope by now you have understood what is exception handling in python.
Let’s see all the topics we will be covering in this module:

So, without further delay, let’s get started.

What Is an Error in Python?

Before discussing how to deal with errors, let us try and understand what errors are in Python. Errors are nothing but mistakes in the code that are potentially harmful.

There are two types of errors in Python:

  • Syntax Errors
  • Exceptions

Syntax Errors

Python Syntax Errors occur while writing the code structure.
Example:

test = [1,2,3]
test = [1,2,3]

for i in test:
print(i)

Output:
File “”, line 3
print(i)
^

IndentationError: expected an indented block

Certification in Full Stack Web Development

Exception in Python

Exception in Python is nothing but errors that are encountered at the run time.

Example:

test = [1,2,3]
for i in test:
print(i)

Output:
File “”, line 3
print(i)
^
Indentation Error: expected an indented block

Get 100% Hike!

Master Most in Demand Skills Now!

Some Built-in Exception in Python Classes

There are some built-in exceptions in Python classes that are already defined for generic cases. They are mentioned in the table below:

Exception Class Event
IOError It gets raised when an input/output operation fails.
Arithmetic Error It gets raised when numeric calculations fail.
Floating-point Error It gets raised when a floating-point calculation fails.
Zero Division Error It gets raised when division or modulo by zero takes place for all numeric types.
Assertion Error It gets raised when the assert statement fails.
Overflow Error It gets raised when the result of an arithmetic operation is too large to be represented.
Import Error It gets raised when the imported module is not found.
Index Error It gets raised when the index of a sequence is out of range.
Keyboard Interrupt Error It gets raised when the user interrupts program execution, usually by pressing (Ctrl+C).
Indentation Error It gets raised when there is an incorrect indentation.
Syntax Error It gets raised by the parser when a syntax error is encountered.
Key Error It gets raised when the specified key is not found in the dictionary.
Name Error It gets raised when an identifier is not found in the local or global namespace.
Type Error It gets raised when a function or operation is applied to an object of an incorrect type.
Value Error It gets raised when a function gets an argument of the correct type but of an improper value.
Runtime Error It gets raised when a generated error does not fall into any category.

Exception Handling In Python

In Python, exceptions can be handled by two new methods:

  • Try: Catches exceptions raised by Python or a program
  • Raise: A custom exception that triggers an exception manually

Become a Full Stack Web Developer

Try-except-else Clause

It gets initiated with a try header line which is followed by a block of indented statements and then by one or more optional except clauses and then at the end an optional else clause can be used as shown below:

try:
Your statements

except Exception_1:
If there is Exception_1 then execute this block- statement

except Exception_2:
If there is Exception_2 then execute this block-statement

else:
if no exception was raised-statement

Now, let us understand this with an example:

try:
fp = open(‘myfile.txt’)
line = f.readline()
i = int(s.strip())

except (IOError,ValueError) as e:
print (“check if the file is read-only.”,e.errno)

except:
print (“Unexpected error”)

What exactly is happening here?
Say, a chunk of code is written inside the try block that is suspected to raise a Python exception. Then, to handle that exception, we write the exception block.

Handling process

First, the try block is executed

  • Case 1:If no Python exception occurs, except blocks, are skipped and the else block gets executed
  • Case 2:If a Python exception occurs during the execution of the try block, the rest of the execution is stopped. Then, a matching Python exception handling block is looked for.
    • If found: Execute that exception block, and after the exception in Python is handled, execute the rest of the try block
    • If not found: Stop the whole execution with an error message

Note: Python can handle any number of exceptions.

Try-finally Clause

When a final clause is used in a try block, then its block of statements is always run by Python, whether an exception occurred while the try block was running or not:

  • If no exception occurs, Python runs the try block and the finally block and then continues executing the rest.
  • If an exception in Python0020occurs during the execution of the try block, Python starts executing the finally block but then propagates the execution to the except block to handle the exception.

Example:

try:
fp = open(“test.txt”, “w”)

try:
fp.write(“Test is not there”)

finally:
print (“So, let us close the file”)
fp.close()

except IOError:
print (“Error: File not found” )

Output:
So, let us close the file

Here, we can notice that the exception block is not executed. This is because the file gets closed after the execution of the final block.

Raise Exceptions Python

To trigger exceptions, we need to code raise statements. Their general form is simple: the keyword, ‘raise’, followed by the name of the exception to be raised.
Example:

class RaisingValueError(Exception):
def __init__(self, data):
self.data = data
def __str__(self):
return repr(self.data)Total_movie = int(input(“Enter Total Movies Seen: “))

try:
Num_of_genres = int(input(“Enter Num of genres: “))
if(Num_of_genres < 1):
raise RaisingValueError(“Number of genres can’t be less than 1”)

except RaisingValueError as e:
print (“Try entering again:”, e.data)

Conflicts in Python Exception Handling

Yes, it does make our codes robust and secure from potential errors, but exception handling in Python has a side effect too.
There are two types of errors in Python:

  • When programs using try-except to handle exception in Python run slightly slower
  • When the size of our code increases

Therefore, we should use exceptions in Python only when we are unsure of a certain part of the code, not for normal error handling cases. This can be understood with the help of an example.

import timeit
setup=”any=0″
statement_1 = ”’

try:
b=10/a

except ZeroDivisionError:
pass”’
satement_2 = ”’

if any !=0:
b=10/a”’

print(“time for statement_1=”,timeit.timeit(stmt1,setup,number=100000))
print(“time for statement_2=”,timeit.timeit(stmt2,setup,number=100000))

Output:
time= 0.07828223999999295
time= 0.0019908266666845975

Difference between errors and exceptions in Python

As we discussed earlier, errors are of two types, syntax errors, and logical errors. Logical errors are exceptions. That makes exceptions a specific type of error.

Syntax errors

amount = 10000
if(amount>2999)
    print("You are eligible")

Exception

They occur at runtime after the code has passed the syntax test.

# initialize the amount variable
marks = 10000
a = marks / 0
print(a)

User defined exception in Python

Programmers can define their own exceptions by creating a new exception class. They need to be derived, indirectly or directly, from the built-in class, Exception. Most built-in exceptions are also derived from the same class.

class MyError(Exception):
    def __init__(self, value):
        self.value = value
    def __str__(self):
        return(repr(self.value))
try:
    raise(MyError(3*2))
except MyError as error:
    print('A New Exception occurred: ',error.value)

The output will be
A New Exception occurred:  6

Python Built-in Exceptions

This table gives a list of some common built-in exceptions in Python

Exception Description
ArithmeticError Raised when an error occurs in numeric calculations
AttributeError Raised when attribute reference or assignment fails
EOFError Raised when the input() method hits an “end of file” condition (EOF)
FloatingPointError Raised when a floating-point calculation fails
GeneratorExit Raised when a generator is closed (with the close() method)
IndexError Raised when an index of a sequence does not exist
IndentationError Raised when indentation is not correct
KeyboardInterrupt Raised when the user presses Ctrl+c, Ctrl+z, or Delete
LookupError Raised when errors raised cant to be found
MemoryError Raised when a program runs out of memory
NotImplementedError Raised when an abstract method requires an inherited class to override the method
OverflowError Raised when the result of a numeric calculation is too large
RuntimeError Raised when an error occurs that do not belong to any specific exceptions
SyntaxError Raised when a syntax error occurs
SystemError Raised when a system error occurs
TabError Raised when indentation consists of tabs or spaces
UnboundLocalError Raised when a local variable is referenced before assignment
UnicodeError Raised when a Unicode problem occurs
ValueError Raised when there is a wrong value in a specified data type
ZeroDivisionError Raised when the second operator in a division is zero

This brings us to the end of this module in Python Tutorial. Now, if you want to know why Python is the most preferred language for data science, you can go through this blog on Python Data Science tutorial.

Best Practices for Exception Handling in Python

Let’s discuss the best practices of exception handling in Python,

  • Be Specific: Catch only the exceptions you expect and know how to handle them. Avoid catching overly broad exceptions like Exception or BaseException as they might hide unexpected issues.
  • Avoid Bare Excepts: Don’t use a bare except statement without specifying the exception type. Always catch specific exceptions to ensure that you handle the right errors.
  • Use Multiple Except Blocks: If different exceptions need different handling logic, use separate except blocks for each one. This makes your code more readable and maintainable.
  • Logging: Instead of just printing error messages, consider using the logging module to log exceptions along with relevant context information. This can be helpful for debugging in production environments.
  • Raising Exceptions: You can raise exceptions using the raise statement. This can be useful when you encounter a condition that shouldn’t occur and want to signal an error in your code.

Custom Exception Classes in Python

In addition to handling built-in exceptions, you can create your own custom exception classes to capture application-specific errors more accurately:

class CustomError(Exception):
    def __init__(self, message):
        self.message = message
try:
    age = int(input("Enter your age: "))
    if age < 0:
        raise CustomError("Age cannot be negative.")
except CustomError as ce:
    print(f"Custom Error: {ce.message}")
except ValueError:
    print("Invalid input. Please enter a valid number.")
else:
    print("Age entered:", age)
finally:
    print("Exception handling complete.")

Context Managers and the with Statement

Python’s context managers, often used with the with statement, provide a clean way to manage resources and ensure they are properly released:

try:
    with open("example.txt", "r") as file:
        content = file.read()
    # Perform operations on content
except FileNotFoundError:
    print("File not found.")
except Exception as e:
    print(f"An error occurred: {e}")
else:
    print("File successfully read.")
finally:
    print("Exception handling complete.")

Further, check out our offers for Python Certification Course and also refer to the trending Python coding interview questions prepared by industry experts.

Course Schedule

Name Date Details
Python Course 30 Nov 2024(Sat-Sun) Weekend Batch View Details
07 Dec 2024(Sat-Sun) Weekend Batch
14 Dec 2024(Sat-Sun) Weekend Batch

About the Author

Senior Consultant Analytics & Data Science

Sahil Mattoo, a Senior Software Engineer at Eli Lilly and Company, is an accomplished professional with 14 years of experience in languages such as Java, Python, and JavaScript. Sahil has a strong foundation in system architecture, database management, and API integration.