Menu iconMenu iconPython Programming Unlocked for Beginners
Python Programming Unlocked for Beginners

Chapter 9: Error Handling and Exceptions

9.1 Common Python Errors

When working with Python, it is important to note that you will inevitably encounter errors or exceptions. These errors are a crucial aspect of programming, as they aid in identifying issues within your code and provide opportunities to learn how to fix them. By learning how to handle exceptions, you will become more proficient at troubleshooting and debugging your code. 

Moreover, the ability to create custom exceptions will allow for more efficient and effective error management throughout your program. In this chapter, we will delve into the different types of errors you may encounter, the various methods of handling exceptions, and how custom exceptions can improve your overall programming experience. 

Before diving into error handling, let's first understand the most common types of errors you might encounter when writing Python code. Errors can be broadly categorized into two types: Syntax Errors and Exceptions.

When we talk about syntax errors, we are referring to errors that occur when our code violates the rules of Python syntax. These errors are usually easy to spot, as they will often be accompanied by an error message that points directly to the problematic line of code. On the other hand, exceptions are errors that occur when our code is syntactically correct, but something goes wrong during execution.

These types of errors can be much more difficult to track down, as they can be caused by a wide range of factors, including incorrect input values or unexpected changes to the state of the program. While it can be frustrating to encounter errors in your Python code, understanding the different types of errors and how to handle them is an essential part of becoming a proficient Python developer.

9.1.1: Syntax Errors:

Syntax errors, also known as parsing errors, occur when the Python interpreter fails to understand your code due to incorrect syntax. These errors usually arise from typing mistakes, incorrect indentation, or misuse of language constructs. Some examples of syntax errors are:

  • Missing colons in control structures like iffor, and def.
  • Mismatched parentheses, brackets, or quotes.
  • Incorrect indentation, which is particularly important in Python.

Example of a syntax error: 

if x > 0
    print("x is positive")

In this example, there's a missing colon at the end of the if statement, which leads to a syntax error.

9.1.2: Exceptions:

Exceptions are runtime errors that occur when your code encounters an unexpected situation or condition. Unlike syntax errors, exceptions do not necessarily result from incorrect code syntax. Instead, they may arise from unanticipated circumstances during code execution, such as file I/O errors, invalid user input, or unhandled edge cases. Some common exceptions include:

  • TypeError: Raised when you perform an operation on an inappropriate data type.
  • NameError: Raised when you try to use a variable or function that has not been defined. 
  • ValueError: Raised when you pass an invalid argument to a function.
  • ZeroDivisionError: Raised when you attempt to divide a number by zero.
  • FileNotFoundError: Raised when you try to open a file that does not exist.

Example of an exception:

x = 0
y = 10
result = y / x

In this example, we're trying to divide y by x. Since x is zero, a ZeroDivisionError exception will be raised.

By understanding these common errors, you'll not only be better equipped to diagnose and fix issues in your Python programs, but you'll also be able to write more efficient and effective code. In the following sections, we'll learn how to handle exceptions and even create our own custom exceptions to improve error handling in our code.

By doing so, we'll not only improve the stability and reliability of our programs, but we'll also be able to write more robust and scalable applications that can handle a wide range of inputs and use cases. This can be particularly important when working with large datasets or complex algorithms, where even a small error can have a significant impact on the final output. As such, mastering error handling in Python is an essential skill for any programmer or data scientist looking to take their skills to the next level.

Exercise 9.1.1: Identify Syntax Errors 

In this exercise, you will be given a Python code snippet containing syntax errors. Your task is to identify and fix these errors.

Instructions:

  1. Read the following code snippet.
  2. Identify the syntax errors present in the code.
  3. Fix the syntax errors and run the corrected code to make sure it works as intended.

Code Snippet:

x = 5
y = 10

if x < y
print("x is less than y")

Solution:

x = 5
y = 10

if x < y:
    print("x is less than y")

Output:

x is less than y

Exercise 9.1.2: Identify Exception Errors

In this exercise, you will be given a Python code snippet containing an exception error. Your task is to identify the exception and fix the code to prevent the error.

Instructions:

  1. Read the following code snippet.
  2. Identify the exception error in the code.
  3. Fix the exception error and run the corrected code to make sure it works as intended.

Code Snippet:

numerator = 7
denominator = 0

result = numerator / denominator
print(result)

Solution:

numerator = 7
denominator = 0

if denominator != 0:
    result = numerator / denominator
    print(result)
else:
    print("Cannot divide by zero")

Output:

Cannot divide by zero

Exercise 9.1.3: Raise Custom Exception

In this exercise, you will create a function that raises a custom exception when an invalid input is detected.

Instructions:

  1. Create a function called validate_age that takes one argument, age.
  2. Inside the function, check if age is less than 0.
  3. If age is less than 0, raise a ValueError exception with the message "Age cannot be negative."
  4. Call the function with a positive and a negative age value to test the exception handling.

Code Snippet:

def validate_age(age):
    # Your code here

validate_age(25)
validate_age(-5)

Solution:

def validate_age(age):
    if age < 0:
        raise ValueError("Age cannot be negative.")

try:
    validate_age(25)
    validate_age(-5)
except ValueError as ve:
    print(ve)

Output:

Age cannot be negative.

9.1 Common Python Errors

When working with Python, it is important to note that you will inevitably encounter errors or exceptions. These errors are a crucial aspect of programming, as they aid in identifying issues within your code and provide opportunities to learn how to fix them. By learning how to handle exceptions, you will become more proficient at troubleshooting and debugging your code. 

Moreover, the ability to create custom exceptions will allow for more efficient and effective error management throughout your program. In this chapter, we will delve into the different types of errors you may encounter, the various methods of handling exceptions, and how custom exceptions can improve your overall programming experience. 

Before diving into error handling, let's first understand the most common types of errors you might encounter when writing Python code. Errors can be broadly categorized into two types: Syntax Errors and Exceptions.

When we talk about syntax errors, we are referring to errors that occur when our code violates the rules of Python syntax. These errors are usually easy to spot, as they will often be accompanied by an error message that points directly to the problematic line of code. On the other hand, exceptions are errors that occur when our code is syntactically correct, but something goes wrong during execution.

These types of errors can be much more difficult to track down, as they can be caused by a wide range of factors, including incorrect input values or unexpected changes to the state of the program. While it can be frustrating to encounter errors in your Python code, understanding the different types of errors and how to handle them is an essential part of becoming a proficient Python developer.

9.1.1: Syntax Errors:

Syntax errors, also known as parsing errors, occur when the Python interpreter fails to understand your code due to incorrect syntax. These errors usually arise from typing mistakes, incorrect indentation, or misuse of language constructs. Some examples of syntax errors are:

  • Missing colons in control structures like iffor, and def.
  • Mismatched parentheses, brackets, or quotes.
  • Incorrect indentation, which is particularly important in Python.

Example of a syntax error: 

if x > 0
    print("x is positive")

In this example, there's a missing colon at the end of the if statement, which leads to a syntax error.

9.1.2: Exceptions:

Exceptions are runtime errors that occur when your code encounters an unexpected situation or condition. Unlike syntax errors, exceptions do not necessarily result from incorrect code syntax. Instead, they may arise from unanticipated circumstances during code execution, such as file I/O errors, invalid user input, or unhandled edge cases. Some common exceptions include:

  • TypeError: Raised when you perform an operation on an inappropriate data type.
  • NameError: Raised when you try to use a variable or function that has not been defined. 
  • ValueError: Raised when you pass an invalid argument to a function.
  • ZeroDivisionError: Raised when you attempt to divide a number by zero.
  • FileNotFoundError: Raised when you try to open a file that does not exist.

Example of an exception:

x = 0
y = 10
result = y / x

In this example, we're trying to divide y by x. Since x is zero, a ZeroDivisionError exception will be raised.

By understanding these common errors, you'll not only be better equipped to diagnose and fix issues in your Python programs, but you'll also be able to write more efficient and effective code. In the following sections, we'll learn how to handle exceptions and even create our own custom exceptions to improve error handling in our code.

By doing so, we'll not only improve the stability and reliability of our programs, but we'll also be able to write more robust and scalable applications that can handle a wide range of inputs and use cases. This can be particularly important when working with large datasets or complex algorithms, where even a small error can have a significant impact on the final output. As such, mastering error handling in Python is an essential skill for any programmer or data scientist looking to take their skills to the next level.

Exercise 9.1.1: Identify Syntax Errors 

In this exercise, you will be given a Python code snippet containing syntax errors. Your task is to identify and fix these errors.

Instructions:

  1. Read the following code snippet.
  2. Identify the syntax errors present in the code.
  3. Fix the syntax errors and run the corrected code to make sure it works as intended.

Code Snippet:

x = 5
y = 10

if x < y
print("x is less than y")

Solution:

x = 5
y = 10

if x < y:
    print("x is less than y")

Output:

x is less than y

Exercise 9.1.2: Identify Exception Errors

In this exercise, you will be given a Python code snippet containing an exception error. Your task is to identify the exception and fix the code to prevent the error.

Instructions:

  1. Read the following code snippet.
  2. Identify the exception error in the code.
  3. Fix the exception error and run the corrected code to make sure it works as intended.

Code Snippet:

numerator = 7
denominator = 0

result = numerator / denominator
print(result)

Solution:

numerator = 7
denominator = 0

if denominator != 0:
    result = numerator / denominator
    print(result)
else:
    print("Cannot divide by zero")

Output:

Cannot divide by zero

Exercise 9.1.3: Raise Custom Exception

In this exercise, you will create a function that raises a custom exception when an invalid input is detected.

Instructions:

  1. Create a function called validate_age that takes one argument, age.
  2. Inside the function, check if age is less than 0.
  3. If age is less than 0, raise a ValueError exception with the message "Age cannot be negative."
  4. Call the function with a positive and a negative age value to test the exception handling.

Code Snippet:

def validate_age(age):
    # Your code here

validate_age(25)
validate_age(-5)

Solution:

def validate_age(age):
    if age < 0:
        raise ValueError("Age cannot be negative.")

try:
    validate_age(25)
    validate_age(-5)
except ValueError as ve:
    print(ve)

Output:

Age cannot be negative.

9.1 Common Python Errors

When working with Python, it is important to note that you will inevitably encounter errors or exceptions. These errors are a crucial aspect of programming, as they aid in identifying issues within your code and provide opportunities to learn how to fix them. By learning how to handle exceptions, you will become more proficient at troubleshooting and debugging your code. 

Moreover, the ability to create custom exceptions will allow for more efficient and effective error management throughout your program. In this chapter, we will delve into the different types of errors you may encounter, the various methods of handling exceptions, and how custom exceptions can improve your overall programming experience. 

Before diving into error handling, let's first understand the most common types of errors you might encounter when writing Python code. Errors can be broadly categorized into two types: Syntax Errors and Exceptions.

When we talk about syntax errors, we are referring to errors that occur when our code violates the rules of Python syntax. These errors are usually easy to spot, as they will often be accompanied by an error message that points directly to the problematic line of code. On the other hand, exceptions are errors that occur when our code is syntactically correct, but something goes wrong during execution.

These types of errors can be much more difficult to track down, as they can be caused by a wide range of factors, including incorrect input values or unexpected changes to the state of the program. While it can be frustrating to encounter errors in your Python code, understanding the different types of errors and how to handle them is an essential part of becoming a proficient Python developer.

9.1.1: Syntax Errors:

Syntax errors, also known as parsing errors, occur when the Python interpreter fails to understand your code due to incorrect syntax. These errors usually arise from typing mistakes, incorrect indentation, or misuse of language constructs. Some examples of syntax errors are:

  • Missing colons in control structures like iffor, and def.
  • Mismatched parentheses, brackets, or quotes.
  • Incorrect indentation, which is particularly important in Python.

Example of a syntax error: 

if x > 0
    print("x is positive")

In this example, there's a missing colon at the end of the if statement, which leads to a syntax error.

9.1.2: Exceptions:

Exceptions are runtime errors that occur when your code encounters an unexpected situation or condition. Unlike syntax errors, exceptions do not necessarily result from incorrect code syntax. Instead, they may arise from unanticipated circumstances during code execution, such as file I/O errors, invalid user input, or unhandled edge cases. Some common exceptions include:

  • TypeError: Raised when you perform an operation on an inappropriate data type.
  • NameError: Raised when you try to use a variable or function that has not been defined. 
  • ValueError: Raised when you pass an invalid argument to a function.
  • ZeroDivisionError: Raised when you attempt to divide a number by zero.
  • FileNotFoundError: Raised when you try to open a file that does not exist.

Example of an exception:

x = 0
y = 10
result = y / x

In this example, we're trying to divide y by x. Since x is zero, a ZeroDivisionError exception will be raised.

By understanding these common errors, you'll not only be better equipped to diagnose and fix issues in your Python programs, but you'll also be able to write more efficient and effective code. In the following sections, we'll learn how to handle exceptions and even create our own custom exceptions to improve error handling in our code.

By doing so, we'll not only improve the stability and reliability of our programs, but we'll also be able to write more robust and scalable applications that can handle a wide range of inputs and use cases. This can be particularly important when working with large datasets or complex algorithms, where even a small error can have a significant impact on the final output. As such, mastering error handling in Python is an essential skill for any programmer or data scientist looking to take their skills to the next level.

Exercise 9.1.1: Identify Syntax Errors 

In this exercise, you will be given a Python code snippet containing syntax errors. Your task is to identify and fix these errors.

Instructions:

  1. Read the following code snippet.
  2. Identify the syntax errors present in the code.
  3. Fix the syntax errors and run the corrected code to make sure it works as intended.

Code Snippet:

x = 5
y = 10

if x < y
print("x is less than y")

Solution:

x = 5
y = 10

if x < y:
    print("x is less than y")

Output:

x is less than y

Exercise 9.1.2: Identify Exception Errors

In this exercise, you will be given a Python code snippet containing an exception error. Your task is to identify the exception and fix the code to prevent the error.

Instructions:

  1. Read the following code snippet.
  2. Identify the exception error in the code.
  3. Fix the exception error and run the corrected code to make sure it works as intended.

Code Snippet:

numerator = 7
denominator = 0

result = numerator / denominator
print(result)

Solution:

numerator = 7
denominator = 0

if denominator != 0:
    result = numerator / denominator
    print(result)
else:
    print("Cannot divide by zero")

Output:

Cannot divide by zero

Exercise 9.1.3: Raise Custom Exception

In this exercise, you will create a function that raises a custom exception when an invalid input is detected.

Instructions:

  1. Create a function called validate_age that takes one argument, age.
  2. Inside the function, check if age is less than 0.
  3. If age is less than 0, raise a ValueError exception with the message "Age cannot be negative."
  4. Call the function with a positive and a negative age value to test the exception handling.

Code Snippet:

def validate_age(age):
    # Your code here

validate_age(25)
validate_age(-5)

Solution:

def validate_age(age):
    if age < 0:
        raise ValueError("Age cannot be negative.")

try:
    validate_age(25)
    validate_age(-5)
except ValueError as ve:
    print(ve)

Output:

Age cannot be negative.

9.1 Common Python Errors

When working with Python, it is important to note that you will inevitably encounter errors or exceptions. These errors are a crucial aspect of programming, as they aid in identifying issues within your code and provide opportunities to learn how to fix them. By learning how to handle exceptions, you will become more proficient at troubleshooting and debugging your code. 

Moreover, the ability to create custom exceptions will allow for more efficient and effective error management throughout your program. In this chapter, we will delve into the different types of errors you may encounter, the various methods of handling exceptions, and how custom exceptions can improve your overall programming experience. 

Before diving into error handling, let's first understand the most common types of errors you might encounter when writing Python code. Errors can be broadly categorized into two types: Syntax Errors and Exceptions.

When we talk about syntax errors, we are referring to errors that occur when our code violates the rules of Python syntax. These errors are usually easy to spot, as they will often be accompanied by an error message that points directly to the problematic line of code. On the other hand, exceptions are errors that occur when our code is syntactically correct, but something goes wrong during execution.

These types of errors can be much more difficult to track down, as they can be caused by a wide range of factors, including incorrect input values or unexpected changes to the state of the program. While it can be frustrating to encounter errors in your Python code, understanding the different types of errors and how to handle them is an essential part of becoming a proficient Python developer.

9.1.1: Syntax Errors:

Syntax errors, also known as parsing errors, occur when the Python interpreter fails to understand your code due to incorrect syntax. These errors usually arise from typing mistakes, incorrect indentation, or misuse of language constructs. Some examples of syntax errors are:

  • Missing colons in control structures like iffor, and def.
  • Mismatched parentheses, brackets, or quotes.
  • Incorrect indentation, which is particularly important in Python.

Example of a syntax error: 

if x > 0
    print("x is positive")

In this example, there's a missing colon at the end of the if statement, which leads to a syntax error.

9.1.2: Exceptions:

Exceptions are runtime errors that occur when your code encounters an unexpected situation or condition. Unlike syntax errors, exceptions do not necessarily result from incorrect code syntax. Instead, they may arise from unanticipated circumstances during code execution, such as file I/O errors, invalid user input, or unhandled edge cases. Some common exceptions include:

  • TypeError: Raised when you perform an operation on an inappropriate data type.
  • NameError: Raised when you try to use a variable or function that has not been defined. 
  • ValueError: Raised when you pass an invalid argument to a function.
  • ZeroDivisionError: Raised when you attempt to divide a number by zero.
  • FileNotFoundError: Raised when you try to open a file that does not exist.

Example of an exception:

x = 0
y = 10
result = y / x

In this example, we're trying to divide y by x. Since x is zero, a ZeroDivisionError exception will be raised.

By understanding these common errors, you'll not only be better equipped to diagnose and fix issues in your Python programs, but you'll also be able to write more efficient and effective code. In the following sections, we'll learn how to handle exceptions and even create our own custom exceptions to improve error handling in our code.

By doing so, we'll not only improve the stability and reliability of our programs, but we'll also be able to write more robust and scalable applications that can handle a wide range of inputs and use cases. This can be particularly important when working with large datasets or complex algorithms, where even a small error can have a significant impact on the final output. As such, mastering error handling in Python is an essential skill for any programmer or data scientist looking to take their skills to the next level.

Exercise 9.1.1: Identify Syntax Errors 

In this exercise, you will be given a Python code snippet containing syntax errors. Your task is to identify and fix these errors.

Instructions:

  1. Read the following code snippet.
  2. Identify the syntax errors present in the code.
  3. Fix the syntax errors and run the corrected code to make sure it works as intended.

Code Snippet:

x = 5
y = 10

if x < y
print("x is less than y")

Solution:

x = 5
y = 10

if x < y:
    print("x is less than y")

Output:

x is less than y

Exercise 9.1.2: Identify Exception Errors

In this exercise, you will be given a Python code snippet containing an exception error. Your task is to identify the exception and fix the code to prevent the error.

Instructions:

  1. Read the following code snippet.
  2. Identify the exception error in the code.
  3. Fix the exception error and run the corrected code to make sure it works as intended.

Code Snippet:

numerator = 7
denominator = 0

result = numerator / denominator
print(result)

Solution:

numerator = 7
denominator = 0

if denominator != 0:
    result = numerator / denominator
    print(result)
else:
    print("Cannot divide by zero")

Output:

Cannot divide by zero

Exercise 9.1.3: Raise Custom Exception

In this exercise, you will create a function that raises a custom exception when an invalid input is detected.

Instructions:

  1. Create a function called validate_age that takes one argument, age.
  2. Inside the function, check if age is less than 0.
  3. If age is less than 0, raise a ValueError exception with the message "Age cannot be negative."
  4. Call the function with a positive and a negative age value to test the exception handling.

Code Snippet:

def validate_age(age):
    # Your code here

validate_age(25)
validate_age(-5)

Solution:

def validate_age(age):
    if age < 0:
        raise ValueError("Age cannot be negative.")

try:
    validate_age(25)
    validate_age(-5)
except ValueError as ve:
    print(ve)

Output:

Age cannot be negative.