Home Backend Development Python Tutorial Assertions vs. Exceptions: When to Use Each for Error Handling?

Assertions vs. Exceptions: When to Use Each for Error Handling?

Oct 30, 2024 am 11:38 AM

 Assertions vs. Exceptions: When to Use Each for Error Handling?

Distinguishing the Roles of Assertions and Exceptions for Error Handling

In software development, one often confronts the choice between using assertions and exceptions for error handling. While both mechanisms serve the purpose of flagging potential errors, their intended usage differs significantly.

Assertions: Crash Early to Detect Corruption

Assertions are primarily intended for checking conditions that should never occur under normal circumstances. Their goal is to help you catch program state corruption early on and crash the application immediately. Consider the following example:

assert x >= 0, 'x is less than zero'
Copy after login

This assertion checks that x is a non-negative value. If x is ever found to be negative, it raises an assertion error and crashes the program. Assertions are particularly valuable for detecting internal errors introduced by bugs or corrupted data.

Exceptions: Handling Recoverable Errors

Exceptions, on the other hand, are designed to handle errors that can potentially occur but are not inherently catastrophic. These errors can be gracefully recovered from, allowing the program to continue execution. For instance:

if x < 0:
    raise Exception('x is less than zero')
Copy after login

This code raises a user-defined Exception if x is negative, providing a meaningful error message. Exceptions can be caught using try/except blocks, allowing you to handle the error and potentially recover.

Setting Business Rules without Try/Except

You may also want to enforce business rules that trigger errors unconditionally, regardless of the code's position. While assertions can check conditions at the function level, they do not propagate throughout the code. To achieve this desired behavior, you can define your own custom exceptions and raise them wherever the business rule is violated. For example:

class BusinessRuleViolationException(Exception):
    pass

def check_x_non_negative(x):
    if x < 0:
        raise BusinessRuleViolationException('x must be non-negative')
Copy after login

This ensures that whenever this function is called with a negative x, an exception is raised, providing a robust way to enforce your business rules.

The above is the detailed content of Assertions vs. Exceptions: When to Use Each for Error Handling?. For more information, please follow other related articles on the PHP Chinese website!

Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

Video Face Swap

Video Face Swap

Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

Dreamweaver CS6

Dreamweaver CS6

Visual web development tools

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

Hot Topics

Java Tutorial
1664
14
PHP Tutorial
1266
29
C# Tutorial
1239
24
Python vs. C  : Applications and Use Cases Compared Python vs. C : Applications and Use Cases Compared Apr 12, 2025 am 12:01 AM

Python is suitable for data science, web development and automation tasks, while C is suitable for system programming, game development and embedded systems. Python is known for its simplicity and powerful ecosystem, while C is known for its high performance and underlying control capabilities.

The 2-Hour Python Plan: A Realistic Approach The 2-Hour Python Plan: A Realistic Approach Apr 11, 2025 am 12:04 AM

You can learn basic programming concepts and skills of Python within 2 hours. 1. Learn variables and data types, 2. Master control flow (conditional statements and loops), 3. Understand the definition and use of functions, 4. Quickly get started with Python programming through simple examples and code snippets.

Python: Games, GUIs, and More Python: Games, GUIs, and More Apr 13, 2025 am 12:14 AM

Python excels in gaming and GUI development. 1) Game development uses Pygame, providing drawing, audio and other functions, which are suitable for creating 2D games. 2) GUI development can choose Tkinter or PyQt. Tkinter is simple and easy to use, PyQt has rich functions and is suitable for professional development.

Python vs. C  : Learning Curves and Ease of Use Python vs. C : Learning Curves and Ease of Use Apr 19, 2025 am 12:20 AM

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.

How Much Python Can You Learn in 2 Hours? How Much Python Can You Learn in 2 Hours? Apr 09, 2025 pm 04:33 PM

You can learn the basics of Python within two hours. 1. Learn variables and data types, 2. Master control structures such as if statements and loops, 3. Understand the definition and use of functions. These will help you start writing simple Python programs.

Python and Time: Making the Most of Your Study Time Python and Time: Making the Most of Your Study Time Apr 14, 2025 am 12:02 AM

To maximize the efficiency of learning Python in a limited time, you can use Python's datetime, time, and schedule modules. 1. The datetime module is used to record and plan learning time. 2. The time module helps to set study and rest time. 3. The schedule module automatically arranges weekly learning tasks.

Python: Exploring Its Primary Applications Python: Exploring Its Primary Applications Apr 10, 2025 am 09:41 AM

Python is widely used in the fields of web development, data science, machine learning, automation and scripting. 1) In web development, Django and Flask frameworks simplify the development process. 2) In the fields of data science and machine learning, NumPy, Pandas, Scikit-learn and TensorFlow libraries provide strong support. 3) In terms of automation and scripting, Python is suitable for tasks such as automated testing and system management.

Python: Automation, Scripting, and Task Management Python: Automation, Scripting, and Task Management Apr 16, 2025 am 12:14 AM

Python excels in automation, scripting, and task management. 1) Automation: File backup is realized through standard libraries such as os and shutil. 2) Script writing: Use the psutil library to monitor system resources. 3) Task management: Use the schedule library to schedule tasks. Python's ease of use and rich library support makes it the preferred tool in these areas.

See all articles