ADVANTAGES AND DISADVANTAGES OF PYTHON

1. ADVANTAGES AND DISADVANTAGES OF PYTHON

2.  Like other general-purpose programming languages, Python is used widely by developers for building desktop GUP applications and web applications.  Python is highly flexible. Unlike other general purpose programming languages, Python is used widely by programmers for scientific programming, text processing, networking, database computing, and artificial intelligence projects.  At the same time, it is currently the most preferred programming language for machine learning. Like other modern programming languages, Python also supports commonly used programming paradigms like object-oriented, functional, procedural and imperative.  The design philosophy of the programming language emphasizes extensively on code readability.  The simple and expressive syntax rules of Python enable programmers to express concepts without writing additional code.  At the same time, Python helps developers to accelerate software development and maintenance by keeping the code base concise, clean, and readable.

3.  The developers can further build custom software applications based on varied business requirements by choosing from a wide range of Python frameworks and libraries.  The Python interpreters, at the same time, make it easier for programmers to integrate Python seamlessly with other programming languages.  Hence, the developers can always pick Python for their next software development project. But no developer should pick Python just because of its popularity and usage.  They must remember that Python, like other programming languages, has its own pros and cons.  It is always important for developers to understand the major advantages and disadvantages of Python to choose the right programming language for their next project.

4. Advantages and Disadvantages of Python A Ad dv vantag antages es of of P Pyth Emphasis on Code Readability ython on P Pr rog ogr ramming amming La Lang nguag uage e  As noted earlier, Python is a programming language whose design philosophy emphasizes on code readability.  In addition to supporting commonly used programming paradigms, Python further enables programmers to add functionality to the applications without writing additional code.  Its simple and expressive syntax rules further make Python easier to learn and use. Both beginners and skilled developers can learn and use Python without putting extra time and effort.  They can even learn a single programming language to build a variety of software applications.

5. Interoperability with Other Programming Languages  The applications written Python run smoothly on varied devices and platforms.  The developers can further use specific Python interpreters to run the same code on multiple platforms.  Also, they can run the same code on multiple platforms without recompilation, as Python is an interpreted programming language.  At the same time, the developers also have option to use programming language specific implementations.  For instance, they can use Jython to convert the Python source code into Java byte code that run on devices with Java Virtual Machine.

6. Loads of Frameworks and Libraries  Python is an open source programming language. Hence, developers can use Python for building a variety of software applications without paying any licensing fees.  At the same time, they can simplify and accelerate custom software application development by taking advantage of several open source Python frameworks and tools.  The developers even have option to choose from a wide range of Python frameworks based on similar project requirements.  For instance, the developers can write custom web applications in Python rapidly by using a number of full-stack and micro web frameworks for Python.  The features and tools provided by full-stack Python web frameworks even help developers to accelerate complex web application development without increasing project overheads.

7. D Dis isad Two Incompatible Versions adv vantag antages es of of P Pyth ython on P Pr rog ogr ramm amming ing La Lang nguag uage e At present, developers have option to write software applications in two distinct versions of Python – 2.x and 3.x.  The Python Software Foundation provides support to both versions of Python. The Foundation has even announced its decision to support Python 2.x till 2020. It even recommends developers to write applications in Python 3.x. But Python 3.x is not fully backward compatible with Python 2.x. There are even a number of Python frameworks and development tools that do not support both versions of the programming language. The programmers even need to invest extra time and effort to upgrade existing applications from Python 2.x to 3.x.

8. Developers Have to Use Frameworks and Tools At present, Python is used widely as a server-side programming language by web developers. But Python was not designed with built-in web development capabilities. Hence, developers cannot write web applications in Python without using web frameworks like Django, Pyramid, Flask or Bottle. Likewise, the developers have to use Python GUI Frameworks like PyQT, PyGUI, PyJs, WxPython or PyGTK to write desktop GUI applications in Python quickly and efficiently.  These framework and development toolkits enable programmers to write large and complex applications in Python rapidly. But the additional features provided by these frameworks often impact the performance and speed of small applications adversely.

9. Slower than Compiled Programming Language A large percentage of users nowadays abandon slow websites and mobile app. Many programmers even opt for compiled programming languages to speed up applications. Python is an interpreted programming language. The source code written in Python needs to be executed through a Python interpreter. The default Python interpreter – CPython – makes Python slower than compiled programming languages like C and C++. Interested readers can read more on why Python is so popular despite being so slow. Many developers replace CPython with other Python implementations to boost code execution speed. Here is an interesting read on the difference between Python and Cython.

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