When I introduce myself as a Python developer, most people ask me “So you are a web developer”. It is one of the most common misconceptions: “that Python cannot handle desktop applications“. Well, Python can handle desktop application development. So the real question is “What is it that Python cannot do”.
As a number of surveys have indicated, Python is one of the most popular coding languages of 2015. Along with being an open source and high level programming language, Python also supports object-oriented, functional and imperative programming paradigms. It is also used widely by developers for creating a wide variety of software applications. The syntax of the programming language helps programmers to express concept with less and readable code. Also, the developers have option to use several Python frameworks to reduce the time and effort required for building complex and mission critical applications.
However, like other popular programming languages, Python also has a number of limitations. Python is not designed with in-built capabilities to develop certain types of applications. For instance, it does not come with built-in web development features like PHP. So developers have to use additional tools and frameworks to write specific applications. At the same time, Python is also not considered to be the best option for writing mobile apps. That is why; it is important for programmers to understand some of the most prominent shortcomings of the widely used programming language.
Major Shortcomings of Python Programming Language
Two Distinct Versions
At present, programmers have option to use either Python 2 or Python 3. In 2008, Python 3 was released as a major but backward incompatible release. A number of major features were backported to Python 2.6 and Python 2.7 when Python 3 was released. The Python Software Foundation has announced its decision to provide support to Python 2.7 till 2020. So many developers still use Python 2 they hesitate to use Python 3. That is why; beginners often find it a daunting challenge to choose the right version of the programming language.
Lacks In-built Functionality
Python was originally designed as a successor to ABC programming language. Major new features were added to the programming during the subsequent years. So Python, unlike other programming languages, is not designed with any specific built-in functionality. But its highly extensible nature enables developers to use Python as a general-purpose programming language for writing GUI application, websites and web applications. The developers have to use additional tools and frameworks to use Python for developing a variety of software applications.
Slower than Other Compiled Languages
Python is an interpreted programming language. The users have to install Python interpreter on their operating system to execute the Python code. So the code remains separated from the runtime. The separation affects the overall speed and performance of the programming language. As highlighted by several reports, Python is slower than other widely used compiled programming languages like C++ and C. Many developers even use third-party tools like Pyinstaller, Py2Exe and Pypy to execute the Python code faster.
Does Not Support Block Comments
Often developers use block comments as a mechanism to deactivate a large block of code temporarily. When a programming language supports block comments, it becomes easier for developers to check their code by deactivating a specific block of code. But Python does not support block comments. So developers have to write comment for each line of code or remove the block of code while executing the code. These options require programmers to put additional time and effort to test the Python code.
Errors Can be Identified Only at Runtime
Over the years, many developers have highlighted the flaws in Python’s design. The programming language features a dynamic type system. The dynamic type system allows programmers to check the type safety of the program at the runtime. So Python developers can identify the bugs in the application only at the runtime. So they need to test the Python application thoroughly and repeatedly to identify the defects and performance issues.
Several Python Modules lack Good Support
The Python packages or modules help developers to add functionality to the software without writing longer lines of code. They also have option to choose from a variety of packages. But the quality of individual packages varies. Some of these packages are maintained and updated regularly. However, there are many modules that lack good documentation and regular support. Programmers have to put both time and effort to check if a particular module or package can be used instantaneously. The lack of adequate documentation further makes it difficult for beginners to understand and use these Python modules.
Poor Performance of Global Interpreter Lock
While writing Python code, programmers have to explore ways to overcome the limitation of global interpreter lock (GIL). GIL prevents the program from running multiple threads at a time. It allows only a single thread to access Python internals at a time. To overcome the performance issue, some programmers use multiprocessing modules to assign tasks to different processes. Many developers even prefer writing asynchronous code to avoid the poor performance of GIL.
Not Supported by Major Mobile Platforms
Nowadays each enterprise wants to invest in mobile app development. But none of the popular mobile platforms supports Python. Apple required programmers to write iOS apps in Swift, whereas Google require developers to write Android apps in Java. The developers still have option to write mobile apps in Python using frameworks like Kivy. Kivy enables programmers to write the mobile app code once, and deploy the same code on iOS, Android and Windows Phone. But the developers still prefer writing mobile apps in the programming language prescribed by Apple, Google or Microsoft.
Difficult to Deploy Software in Uncontrolled Environments
Many developers find it difficult to install, update or uninstall Python applications in an uncontrolled environment. The developers have to put additional time and effort to ensure that the application is deployed in the most appropriate way. Unlike large organizations, the small businesses and start-ups cannot deploy their application in a tightly-controlled environment. They also lack the resources and expertise to maintain the application properly in an uncontrolled environment. That is why; the organizations have to decide the best way to deploy the Python application before starting the development.
On the whole, each developer needs to evaluate the pros and cons of Python according to the specific needs of the project. He also needs to check if other programmers have already used Python for developing similar applications. Python has a lot of positive factors and in a recent survey, it has been voted as one of the most popular programming languages. Personally, I love Python and I am confident that Python is here to stay and maintain its popularity over other languages. There are also chances that he has to use additional tools to accomplish specific tasks. However, the programmer still has option to take advantage of the powerful programming language using specific tools and frameworks additionally.
Python also has some great stuff for machine learning, statistics, scientific and physics computations, graphic computing and GUI, Web. a whole lot of stuff is simple with python.
You can do anything that you want. Python is very powerful and easy to read and write.
Learning a ton from these neat article.
To be honest, isn’t some of this directed at the CPython interpreter of Python?
I would have gone straight to an obvious yet not-mentioned Python cannot be used to write an Operating System Kernel.
Of course if we think about all the things something cannot be used to do, it is incredibly limiting; as-is pidgin-holing entire languages to a narrow use-case.
Python is a general-purpose high-level programming language… It’s best suited to being flexible and expressive. It can take weeks or months to ship a Python program. Months at the least for a C program with the same documentation, dependency management and even the most spartan of feature-sets.
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