Pros And Cons of Python


Python was introduced in the year 1991 from then on it continuously evolved in the field of coding. This language is used by many social media websites like Spotify, Instagram, Facebook, and many more. The daily activities of the users such as storing, editing, sharing the photos or videos in their album has completely relied on python in the social media of Instagram. The music streaming app like Spotify also uses python to manage its radio by using Data Analytics. Python is used in many projects from simple to complex for example it is used in different fields like finance, travel, healthcare, transportation, and many others through web development, scripting, generation, and software testing. Because it’s a globally used language it will have a few positives and negatives let us see both of them. 

features of python

User-Friendly with the easy syntax:

Simple and easy are the two words that can best describe the syntax for python. And due to this easy syntax, most of the elements which are used in this language have a clear relationship with each other. Any novice can learn this language very easily and adapt to the program and coding communities very well. At the end of the day; charts and plots are the two main ways for the data to be understood well. Comprehending and presenting data can be very efficiently done in this language. It is very easy to understand the code written by anyone and if someone wants to alter the code in a particular software it can be very easily done. Because of Its easy syntax, the communication between the developers is extremely efficient.


Less limited programming approach, when compared to the other coding languages, is one of the features in the coding language of python. Procedural, object-oriented, and functional programming styles are extremely supported by this language because it has multiple paradigms. Because it has fewer limitations, any beginners can learn this language very easily and this language is an excellent language to learn for the startup. Prewritten code is one of the features of python. This is included in the language so that the developers can use these basic codes. These codes can be used and altered according to the final application in which it is used. In machine learning the data should be continuously processed and the libraries in Python allow any programmer to transform or handle the data required.

Scientific and Numeric Applications:

The scientific and numeric applications can be developed by using many libraries and tool kits, imaging libraries, and many different tools. Many make use of Scipy, Pandas, IPython, Numeric Python, Natural Language Toolkit.

Used in Prototyping:

Python is famous to create prototypes in a simple and fast method. The final product is completely dependent on the initial prototype and this language helps to code real quick to create the initial prototype.

Portability & Interactivity:

The fast prototyping and dynamic semantics are related to the interactivity and portability of this coding language. Regardless of what coding languages and apps, Python can be very easily embedded in a huge range of applications. The vocabulary can be extended and you can fix new models in this language. The concept called glue language which connects two different components is also available in this.

Let us see a few cons for Python:

  • Fewer Seasoned Developers:

When you are willing to write a code to create an app; it is always better to hire a professional coder than experimenting yourself, because coding in Python is not so easy as you do in Java.

  • Lack of True Multiprocessor support:

A few limitations are made up by using Python when writing code for the application. Since applications require multiprocessor and this does not support it.

  • Design Restrictions:

Python executes particular tasks during app run time which would otherwise be completed in a statically typed language. This inserts some restrictions on the design. If your design is filled with elements, it might slow the program and prevent smooth operation. Accountancy and parallelism are not progressive for good use in Python because of this the design will not look as sophisticated as you expect.