Error Handling in Python: Best Practices. Explore how to handle exceptions effectively

Summary:

Program errors are unrecoverable; when a program encounters an error, it will exit or crash immediately.

Good programmers ensure that their code or software can gracefully handle errors/exceptions that may arise during the use of the software without crashing or producing undesirable results. Imagine writing software for a financial institution that only accepts numeric input, if the user enters letters instead of numbers for arithmetic operations, this will usually throw an error and the software will crash because of a single user, if there isn't any mechanism in place to handle the error words. This is definitely not a good thing - it's bad for business, can lead to frustrated customers, and someone could lose their job due to incompetence.

In this article, we will learn how to best handle errors in your code that may arise due to user interaction. stay tuned.

Prerequisites

This article is suitable for:

• Python software developers looking to learn how to handle exceptions in their code.
• People who are already familiar with Python and want to learn the concepts of error handling in Python.
• Existing professionals looking to improve their knowledge of Python error handling.

Goal

After reading through this article, readers should be able to:

• Clearly understand the concept of error handling in Python and its importance.
• Learn about custom exception classes and how to implement them.
• Understand the key difference between errors and exceptions in Python.

Explanation of errors and exceptions

Error and Exception are often used interchangeably, but they technically mean different things. In Python, Error and Exception are both subclasses of BaseException, This further shows that even though they are different, they have something in common.

Error

Errors are unrecoverable; when our program encounters an error, it will exit or crash immediately. Even though you might expect errors, there is no way to handle them programmatically. Some errors are listed below:

SyntaxError：

This is one of the most common types of errors faced by programmers, it occurs when the code does not follow correct Python syntax and can be detected during parsing. This is a question that easily arises for learners or people switching to Python from other programming languages.

<code class="language-python">name = “Austin”;
print(name)</code>

This results in SyntaxError because in Python statements do not end with a semicolon.

IndentationError：

This error occurs when Python code is indented incorrectly and is detected when parsing the code. Indentation in Python is very important. It is the only way in Python that you can define blocks of code, unlike most languages ​​that use curly braces.

<code class="language-python">name = “Austin”;
print(name)</code>

This code will cause errors due to improper indentation. It should be:

<code class="language-python">active = True
if (active):
print(“The user is active”)</code>

Exception

Exceptions in Python occur at runtime. Unlike errors, they can be properly handled or caught programmatically so that our program can continue running without crashing. In other words, they are recoverable. Here are some common exceptions in Python:

Built-in exceptions

These types of exceptions are part of the Python programming language. Some of them are listed below:

ValueError：

This error occurs when an invalid parameter is passed to a function, even though the type may be correct.

<code class="language-python">if (active):
    print(“The user is active”)</code>

From the above code snippet, if we pass a numeric string to the function, it will successfully convert to number, otherwise, it will produce ValueError.

<code class="language-python">def str_num(num_string):
    return(int(string))</code>

TypeError：

This error is raised when an inappropriate type parameter is passed to a function.

<code class="language-python">print(str_num(“123”)) #works perfectly
print(str_num(“abc”)) #raises a ValueError</code>

This will trigger TypeError.

IndexError：

This error occurs when you try to access a value in a list using the wrong index.

<code class="language-python">def addition(num1, num2):
    return num1 + num2
# calling the function
addition(5, A)</code>

This results in IndexError because my_list[2] is inaccessible.

KeyError：

This error is raised when an attempt is made to access a value in a dictionary using an incorrect or non-existent key.

<code class="language-python">my_list = [“dog”, “cat”]
my_list[2]</code>

This will trigger KeyError. You can find other built-in exceptions here.

Custom exception

Custom exceptions are defined by the programmer. Here, Python enables programmers to manually define conditions that a program should check during execution and throw an exception if found. You can achieve this by creating a class that inherits from the Exception class.

Handling exceptions

Handling exceptions ensures that our software applications have predictable performance when encountering certain errors that arise during the application lifecycle. In this section, you will learn how to implement this in programming.

Use the try-except statement

The

try-except statement provides a safe way to handle code that may throw errors or exceptions. try statements wrap problematic code or try clauses; this is the part of the code that will most likely cause the entire program to go wrong; this is likely to happen when receiving input from the user, reading from a file, to name a few example.

The

except statement marks the beginning of the except clause; this is the rest of the code wrapped in a except block. The except clause handles exceptions raised within the try block.

Let me walk you through the execution workflow. Your Python program will normally execute until it reaches the try block containing the "problematic" code, and if there are no possible errors while executing the code in the try block at that time, it will skip the except block and continue Execute the rest of the code base. However, if an error is encountered while executing code in the try block, immediately after the exception object is created, control jumps to the except block where it should be handled by the matching exception class.

<code class="language-python">name = “Austin”;
print(name)</code>

From the above code snippet, if a non-numeric value is passed to the program, an exception object is created and ValueError is thrown. Control immediately jumps to the except block, where it scans for the appropriate exception class. Here, the ValueError class is sufficient. Errors have been handled correctly. However, if the correct class is not found, control moves to the outer try block (if there is one), and if the exception is still not handled correctly, the program crashes.

Use one except statement to handle multiple exception classes

Can check multiple exception classes and handle specific exceptions. This approach is preferred if you are not sure which of several exceptions resulted in code execution. See the code snippet below.

<code class="language-python">active = True
if (active):
print(“The user is active”)</code>

Wildcard exception class

The

Exception class is a direct subclass of BaseException. The Exception class is the base class for all non-fatal exceptions.

In most cases, the Exception class is sufficient to handle most exceptions thrown during code execution.

<code class="language-python">if (active):
    print(“The user is active”)</code>

Even though the Exception class can handle non-fatal exceptions, it is best to use it with caution. Use the correct Exception class as it is better for debugging and improves code readability.

Use the finally statement

The portion of code wrapped in a finally block will be executed regardless of whether an exception occurs. This makes it suitable for handling cleanup tasks; closing files and freeing memory resources.

<code class="language-python">def str_num(num_string):
    return(int(string))</code>

Create a custom exception class

Creating custom exceptions enables programmers to raise specific exceptions for software programs. This may include special conditions or edge cases that may be detrimental to the functionality of a particular software program. Custom exception classes defined must inherit from the Exception class.

<code class="language-python">print(str_num(“123”)) #works perfectly
print(str_num(“abc”)) #raises a ValueError</code>

The code snippet above shows how to create and use custom exceptions. Depending on the use case, it can be used in more complex ways.

Why error/exception handling is important

"Don't trust the user" is a common saying among software developers, which reiterates that you can't be completely sure how your users will interact with your software application; what types of input they put in, and what you, the programmer, are doing when writing your application There are some other corner cases that may not have been thought of. Some important reasons for proper error/exception handling are explained below:

1. Prevent crashes Without exception handling, unhandled errors can cause a program to suddenly crash. This may result in data loss or poor user experience. Example: No exception handling:

print(10 / 0) # ZeroDivisionError: division by zero

Use exception handling:

try: print(10/0) except ZeroDivisionError: print("Cannot divide by zero!")

1. Improve user experience Properly handled exceptions make applications easier to use by providing meaningful error messages instead of cryptic system errors. Example:

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

1. Maintain application stability It allows applications to continue running even after encountering errors, ensuring stability. Example:

def divide(a, b): try: return a/b except ZeroDivisionError: return "Division by zero is not allowed!"

print(divide(10, 2)) # Output: 5.0 print(divide(10, 0)) # Output: Division by zero is not allowed!

1. Handling extreme situations Exception handling allows you to account for unpredictable situations such as network failures, missing files, or invalid user input. Example:

try: with open("data.txt", "r") as file: content = file.read() except FileNotFoundError: print("The file cannot be found.")

1. Encourage writing concise code
   Exception handling makes your code easier to read, debug, and maintain by separating normal logic from error handling logic.

2. Facilitates debugging
   With detailed error messages and exception logs, developers can quickly identify and fix issues in their code.
   Example:
   

import logging

try: result=10/0 except Exception as e: logging.error("An error occurred", exc_info=True)

1. Critical for critical systems In systems where reliability is critical (e.g. banking, healthcare), exception handling is necessary to ensure that errors are managed safely without causing data corruption or loss.

Conclusion

In programming terms, errors and exceptions are most often used interchangeably. The key difference between errors and exceptions in Python is how they affect our software programs. Errors such as syntax errors and indentation errors can crash a program when the interpreter parses it. On the other hand, exceptions can crash the program at runtime if they are not handled correctly. Custom exceptions extend error handling capabilities by enabling programmers to define exception classes specific to a particular software application.

Error handling is also very important for debugging. It allows us to see why errors occur in the application, thus providing software maintainers with enough information to solve the problem. Always ensure that exception handling is introduced appropriately in your code to ensure the robustness of your software application.

Thank you for reading.

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