Day 10: Error Handling in Python

Goal: Master Python’s error handling using try, except, else, and finally blocks. Learn to create custom exceptions and debug code effectively.

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1. What Are Errors and Exceptions?

• Syntax Errors: Caused by incorrect code structure (e.g., missing colon or parenthesis).

if x > 5  # SyntaxError: Missing colon  

• Exceptions: Errors detected during execution (e.g., dividing by zero or accessing invalid keys).

print(10 / 0)  # ZeroDivisionError  

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2. The try-except Block

Basic Syntax

try:  
    # Code that might raise an error  
except ErrorType:  
    # Code to handle the error  

Example:

try:  
    num = int(input("Enter a number: "))  
except ValueError:  
    print("Invalid input! Please enter a valid integer.")  

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3. Handling Multiple Exceptions

Specific Exceptions

Catch different errors with multiple except blocks:

try:  
    x = 10 / int(input("Enter a non-zero number: "))  
    print(my_dict["invalid_key"])  
except ZeroDivisionError:  
    print("Cannot divide by zero!")  
except KeyError:  
    print("Key not found in dictionary!")  

Catch All Exceptions (Not Recommended)

Use sparingly to avoid hiding bugs:

try:  
    # Risky code  
except Exception as e:  
    print(f"An error occurred: {e}")  

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4. The else Clause

• Runs only if no exceptions occur.

• Useful for code that depends on the try block succeeding.

try:  
    result = 10 / int(input("Enter a number: "))  
except ZeroDivisionError:  
    print("Division by zero!")  
else:  
    print(f"Result: {result}")  # Executed only if no error  

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5. The finally Clause

• Runs regardless of whether an exception occurred.

• Use for cleanup tasks (e.g., closing files or database connections).

file = None  
try:  
    file = open("data.txt", "r")  
    content = file.read()  
except FileNotFoundError:  
    print("File not found!")  
finally:  
    if file:  
        file.close()  # Always executes  

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6. Built-in Exceptions

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7. Raising Exceptions

Force an error with raise to enforce constraints:

def calculate_age(age):  
    if age < 0:  
        raise ValueError("Age cannot be negative!")  
    return age  

try:  
    calculate_age(-5)  
except ValueError as e:  
    print(e)  # Output: Age cannot be negative!  

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8. Custom Exceptions

Create your own exceptions for specific use cases:

class InvalidEmailError(Exception):  
    """Raised when an email format is invalid."""  

def validate_email(email):  
    if "@" not in email:  
        raise InvalidEmailError(f"{email} is invalid!")  

try:  
    validate_email("alice.example.com")  
except InvalidEmailError as e:  
    print(e)  

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9. Logging Errors

Use the logging module to log errors (better than print() for debugging):

import logging  

logging.basicConfig(filename="errors.log", level=logging.ERROR)  

try:  
    10 / 0  
except ZeroDivisionError:  
    logging.error("Division by zero attempted!", exc_info=True)  

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10. Best Practices

1. Be Specific: Catch specific exceptions (avoid bare except:).

2. Use finally for Cleanup: Ensure resources (files, network connections) are released.

3. Log Errors: Use logging to track issues in production.

4. Fail Early: Validate inputs at the start of functions.

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Real-World Example: AI/ML Context

Handle errors when loading datasets:

try:  
    import pandas as pd  
    df = pd.read_csv("dataset.csv")  
except FileNotFoundError:  
    print("Dataset not found! Check the file path.")  
except pd.errors.EmptyDataError:  
    print("The dataset is empty!")  
except Exception as e:  
    print(f"Unexpected error: {e}")  

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Practice Exercise

1. Write a function that divides two numbers but raises a ValueError if either is not a number.

2. Create a custom exception InvalidInputError for non-numeric inputs.

3. Use try-except to handle file I/O and custom errors.

Solution:

class InvalidInputError(Exception):  
    pass  

def divide(a, b):  
    try:  
        if not (isinstance(a, (int, float)) and isinstance(b, (int, float))):  
            raise InvalidInputError("Non-numeric input!")  
        return a / b  
    except ZeroDivisionError:  
        return "Cannot divide by zero!"  

try:  
    print(divide(10, "2"))  
except InvalidInputError as e:  
    print(e)  

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Key Takeaways

• try-except: Gracefully handle runtime errors.

• Custom Exceptions: Improve code readability for domain-specific errors.

• Logging: Critical for debugging production code.

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What’s Next?

Day 11 introduces NumPy, the backbone of numerical computing in Python. You’ll use it for vectorized operations in AI/ML!

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By mastering error handling today, you’ll write robust, crash-resistant code—essential for real-world AI/ML pipelines! 🛠️