Why Global Variables Should Be Avoided in Programming
In the realm of programming, the use of global variables is often frowned upon. But what's the underlying reason for this skepticism?
Global Variables: A Double-Edged Sword
Global variables are accessible from anywhere within a program, making them convenient for storing shared data. However, this convenience comes at a cost: it introduces hidden side effects into functions.
The Dangers of Hidden Side Effects
When a function modifies a global variable, it creates side effects that can be difficult to detect and debug. This is because other functions in the program can also access and modify the same global variable, leading to unexpected outcomes.
As a result, using global variables can increase the complexity of the code, making it more challenging to maintain and ensure its correctness. This can ultimately lead to spaghetti code, where the connections between code elements become tangled and difficult to understand.
Exceptions: Global Constants vs. Global Variables
It's important to note that global constants are conceptually different from global variables. Global constants are assigned values that never change, while global variables can be modified at runtime. In Python, global constants are typically written in all-uppercase letters.
When to Consider Global State
While global variables are generally discouraged, there are some cases where global state may be necessary. For example, it can be useful for caching, memoization, or maintaining consistent data shared across different parts of a program. However, it's essential to use global state sparingly and carefully to avoid introducing unwanted side effects.
Additional Resources
For further insights into why global variables can be problematic and for additional learning on functional programming, consider the following resources:
- Global Variables Are Bad - Wiki Wiki Web
- Why is Global State so Evil? - Software Engineering Stack Exchange
- Are Global Variables Bad?
- Side Effect (Computer Science) - Wikipedia
- Functional Programming - Wikipedia
The above is the detailed content of Why Should Programmers Avoid Global Variables?. For more information, please follow other related articles on the PHP Chinese website!

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.

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 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 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.

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 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.

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.

How to teach computer novice programming basics within 10 hours? If you only have 10 hours to teach computer novice some programming knowledge, what would you choose to teach...


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

Atom editor mac version download
The most popular open source editor

MinGW - Minimalist GNU for Windows
This project is in the process of being migrated to osdn.net/projects/mingw, you can continue to follow us there. MinGW: A native Windows port of the GNU Compiler Collection (GCC), freely distributable import libraries and header files for building native Windows applications; includes extensions to the MSVC runtime to support C99 functionality. All MinGW software can run on 64-bit Windows platforms.

EditPlus Chinese cracked version
Small size, syntax highlighting, does not support code prompt function

Dreamweaver Mac version
Visual web development tools

Notepad++7.3.1
Easy-to-use and free code editor