Exception Handling in Python with Examples

Exception Handling in Python

The great error-running ability that Python offers allows for running smooth your programs even in case unforeseen crimes occur. Similar to that functionality, the fact is that Python does not crash at runtime for such a scenario, as when one is trying to divide by zero pierce some indicator in the array, or attempt to open some missing train. Using pass, except, differently, and eventually constructs you catch and handle the error; provide meaningful dispatches to druggies, or perform some other specific conduct, independent of whether it has been performed correctly or not. This, piecemeal from perfecting the trustability of your law, boosts the stoner experience too. Exception running is a reliance on solid programming. It assists the inventors in building robust and user-friendly operations.

• What is an Error in Python?
• Exception Handling in Python
• Conflicts in Python Exception Handling
• Difference between errors and exceptions in Python
• User-defined exception in Python
• Python Built-in exceptions

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

Errors are nothing but mistakes in the code that are potentially harmful.

There are two types of errors in Python:

• Syntax Errors
• Exceptions

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

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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

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 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

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 = fp.readline()
   i = int(line.strip())
except (IOError,ValueError) as e:
    print ("check if the file is read-only.",e.errno)
except Exception as e:
    print ("Unexpected error", e)

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.

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:
  file1 = open("test.txt", "w")
except IOError:
  print("Error: File not found")
try:
  file1.write("Test is not present")
except IOError:
  print("Error: Writing to file failed")
finally:
   print("So, let's close the file")
   file1.close()

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.

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):</div>
         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="a = 0"
statement_1 = '''
try:
  b=10/a
except ZeroDivisionError:
  pass
  '''
statement_2 = '''
if a !=0:
   b= 10/a
 '''
print("time for statement_1=",timeit.timeit(statement_1,setup,number=100000))
print("time for statement_2=",timeit.timeit(statement_2,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

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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.")

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.

Further, you can also refer to the trending Python coding interview questions prepared by industry experts.