Comparing Python to Other Programming Languages: Pros and Cons
Published: 2023-09-02 18:50:56

### Table of Contents

- Introduction
- Overview of Python
- Pros of Using Python
- Cons of Using Python
- How Python compares to other Languages
- Conclusion

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## **INTRODUCTION**

Python, created in the late 1980s by _Guido van Rossum_, has grown in popularity over the years. Python is frequently used for web development, data analysis, scientific computing, and artificial intelligence because of its simplicity and readability. Let us look at the benefits and drawbacks of utilizing Python. Python drives many of today's most popular web frameworks, scientific computing tools, and data science applications, thanks to its vast and active open source community. It is utilized by large corporations like Google, Facebook, Netflix, and NASA.

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## **OVERVIEW OF PYTHON**

Python is a general purpose, interpreted, high-level programming language. Key features include:
- Dynamic typing - No need to declare variable types


- Automatic memory management - No manual memory allocation or deallocation.


- Emphasis on code readability - Uses significant whitespace and intuitive syntax.


- Supports multiple programming paradigms - Object-oriented, imperative, functional, and procedural styles.


- Large standard library - Comes batteries included with many pre-built modules and functions.


- Cross-platform - Python code runs on Windows, Mac, Linux, and more.


- Open source - Guido van Rossum started Python at CWI in Netherlands. Now managed by the Python Software Foundation.


- Beginner friendly - Very easy to start coding in Python compared to other languages.


Python's popularity is growing due to its ease of use and wide range of applications, which include web development, data analysis, and machine learning. Let us take a look at some of the language's significant advantages and disadvantages.


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## **PROS OF USING PYTHON**

- **_Easy to Learn and Read_**: Python is one of the easiest programming languages to learn for beginners due to its emphasis on code readability and plain grammar. The simple, English-like syntax denotes blocks using whitespace rather than curly braces or keywords, making programming highly intuitive. Python is thus incredibly readable, even for individuals with no programming knowledge.

- **_Large Standard Library_**: Python comes pre-installed with a large standard library of modules for everything from math to web protocols to compression. This "batteries included" philosophy means developers can get a lot done without needing to import or install additional modules. The extensive standard library makes many tasks quick and easy in Python.

- **_Cross-Platform Compatibility_**: Python's smooth cross-platform compatibility is a big advantage. Python code runs unaltered on Windows, Mac, Linux, and other platforms. Python is thus a highly portable language for developing software that may run everywhere.

- **_Open Source and Free_**: As an open source programming language managed by the non-profit Python Software Foundation, Python is freely available for anyone to use or modify. This has helped spur adoption and development of supplementary modules and frameworks.

- **_Extensive Support Libraries and Frameworks_**: Python has an active open source community. NumPy, Pandas, Matplotlib, Django, Flask, and TensorFlow are among of the most popular support libraries and web frameworks. This enables developers to rapidly build on top of high-quality libraries for a wide range of applications.

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## **CONS OF USING PYTHON**


- **_Performance Limitations_**: Python code executes slower than compiled languages like C, C++, and Java since it is an interpreted language. As a result, it is less suitable for programs requiring high performance and speed. Dynamic typing in Python can potentially cause runtime issues and delayed performance.

- **_Significant Whitespace_**: Instead of braces or keywords, Python employs whitespace indentation to delimit blocks. This can be confusing for new developers who are used to working in other languages. Indentation mistakes can cause issues that can be difficult to debug.

- **_Global Interpreter Lock (GIL)_**: Python's GIL causes some limitations in multi-threaded programs. The GIL essentially limits a Python process to only use one thread at a time even on multi-core processors. This can cause issues with CPU-bound concurrent programs.

- **_Mobile Development_**: Python is not the ideal language for developing mobile apps. While frameworks such as Kivy and Beeware exist to help developers create mobile apps in Python, the performance and native capabilities of languages such as Swift (for iOS) and Java/Kotlin (for Android) are often favored.

- **_Limited Access to Low-Level Functionality_**: Python is a high-level programming language that abstracts many low-level elements. This makes Python applications easier to build, but it also limits control over memory management, processors, and so on. Lower-level languages like C++ may be a better fit for some complex systems development applications.

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## **HOW PYTHON COMPARES TO OTHER LANGUAGES**

Now that we have reviewed Python's strengths and limitations, let us examine how it stacks up against other programming languages for significant applications.

**PYTHON VS. JAVA**

![Image description](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/hu3nqyl3besdbx9tdmlw.png)

Java is a general-purpose, object oriented programming language that has been around since the mid-1990s. Here’s how the Python compares to Java:

- **_Syntax_**: Python's syntax is simpler and more understandable than Java's, making it easier to learn and write code rapidly. Java, on the other hand, has a more sophisticated grammar and necessitates a greater amount of redundant code.

- **_Performance_**: Java is often faster than Python due to Just-In-Time (JIT) compilation and static typing. Python's interpreted nature makes it slower in contrast. However, Python's numerous libraries and frameworks can assist bridge this speed gap.

- **_Platform Independence_**: Both Python and Java are platform-independent, meaning they can run on multiple operating systems. However, Java's "write once, run anywhere" philosophy is more widely adopted, particularly in enterprise-level applications.


Overall, Java may be a superior choice for system programming and applications where efficiency and performance are crucial. However, Python provides faster development times and more readable code for many applications.

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**PYTHON VS. JAVASCRIPT**

![Image description](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/w25pp2tqd4s2eo676yi6.png)

JavaScript is a widely-used scripting language primarily used for web development. Let's compare Python and JavaScript:

- **_Application_**: Python is adaptable and may be used for a variety of applications, whereas JavaScript is primarily utilized for web development. Python's numerous libraries and frameworks make it well-suited to scientific computing, data analysis, and machine learning, but JavaScript excels in the browser environment.
- **_Syntax_**: Python's syntax is more readable and consistent than JavaScript's, making it easier to write and maintain code. The syntax of JavaScript can be more complex and prone to errors.
- **_Concurrency_**: The GIL in Python limits concurrency, whereas JavaScript is single-threaded but provides asynchronous programming via callbacks, promises, and async/await syntax.


Overall, JavaScript and Python are both used for web development, however Python gives advantages on the back-end/server side, whilst JS focuses on the front-end client side.

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**PYTHON VS. C++**

![Image description](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/iy9p1sez4gvvbnkl1hlc.png)

C++ is a powerful and widely-used programming language known for its performance and low-level control. Here's a comparison of Python and C++:
- **_Memory Management_**: Python uses automatic memory management (garbage collection), while C++ requires manual memory management. This makes Python easier to learn and write code quickly, but C++ provides more control over memory usage.
- **_Performance_**: Because to its compiled nature and low-level control, C++ is faster than Python. Python is slower in contrast due to its interpreted nature and dynamic typing. However, Python's rich libraries, such as NumPy, can reach equivalent numerical calculation performance.
- **_Application_**: C++ is frequently used for system-level programming, game development, and other performance-critical applications. Python is better suited for quick development, scripting, and data processing.

Overall, C++ is a better choice than Python for performance-critical applications requiring direct hardware manipulation or advanced memory management.


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## **CONCLUSION**

Python is a dynamic and adaptable programming language that excels in readability, adaptability, and speed of development. While Python may not be the ideal choice in every situation, its rich libraries, active community, and simple syntax make it a popular language for a wide range of applications. To make an informed conclusion when comparing Python to other programming languages such as Java, JavaScript, or C++, evaluate the unique requirements and limits of your project.