Advantages and Disadvantages of Python - How it has taken over the world of programming?

Getting its name from the famous comedy series Monty Python and the Holy Grail, Python was created by Guido van Rossum who also created the initial version of IDLE. As an open-source project, it was initially released in 1991.

As a result of its many programming paradigms, Python is a popular choice among bigger businesses and developers. Starting with Python is relatively simple since it uses English phrases rather than technical jargon like C++. There are also a number of online lessons that can help you get started fast with the language.

Knowing the Python benefits and downsides allows us to build strong programs. Let's take a look at Python's pros and drawbacks.

What are the advantages of Python?

1. Easy Learning Curve

The first advantage of using Python is its simplicity. You don’t need to learn all sorts of syntaxes like you do with most other languages. All you have to know is how to write simple statements which include variables, loops, functions, classes, modules, etc. The programming language Python has an English-like syntax. It's easier to read and comprehend the code with this.

A lot of people recommend Python to beginners because it is easy to pick up and learn. You don't need a lot of lines of code to do the same thing as in other languages (C++, Java). There are also several online courses available that teach you how to code in python. You will find these courses very useful if you want to start learning to code or even improve your existing skills.

2. It’s Open Source Software

The open-source nature of this software means anyone can use or modify it without any restrictions.

3. Its Object-Oriented Programming Language

It supports object-oriented programming which helps in creating reusable components. These objects have attributes and methods associated with them. They also support inheritance where one class inherits all the properties and methods of another class.

4. Very Fast Execution Speed

This is because it uses an interpreter rather than compiled into machine code. So there is no delay while executing your program.

5. Highly Compatible

You don't need to worry about compatibility issues when using python since it's very compatible across all the platforms. Can be Used on Windows, Linux & Mac OS X Platforms and is freely Available for Download.

Other amazing features of Python include:

Excellent Documentation
Supports Multiple Languages
Good Support from Community
Great IDE's
High Performance and can be easily Integrated With Other Tools
Has Extensive Libraries- It's possible to find almost all the functions you need for your task. It is not necessary for you to depend on external libraries. If you do, a python package manager makes it easier to import other great packages from the PyPi. There are over 200,000 packages in this picture.
Powerful Data Structures
Well Documented Code and offers Cross-platform development
You can easily integrate python into your existing applications.

With Python getting more popular-owing to its user-friendly data structures, simplified syntax, extensive support libraries, and evergreen presence of third-party modules, along with a host of other benefits-Data science specialists anticipate that this trend should proceed with expanding advancement in the Python ecosystem.

Disadvantages of Python

The disadvantages of using python include:

1. Lack of Standardized Design Patterns

Python doesn't provide standard design patterns such as MVC patterns. This may make some developers feel uncomfortable at times. But they can still create their own design patterns by following best practices.

2. No Built-In Database Management System

There isn't a built-in database management system in Python. However, we can always install the MySQLdb module to connect our application to databases.

3. Not Well Suited For Large Applications

If you're planning to build large-scale web apps then you might face problems due to a lack of memory allocation. Also, Python does not offer native threading capabilities so you'll have to rely on a multiprocessing library.

4. Poor Security Features

Security is a major concern nowadays, especially after the recent WannaCry attack. The security measures provided by Python aren't sufficient enough to protect against attacks like SQL injection.

5. Weak in Mobile Computing

Python has made its presence on many desktop and server platforms, but it is seen as a weak language for mobile computing. This is the reason very few mobile applications are built in it like Carbonnelle.

6. Trouble in Using Other Languages

'Die-hard Pythonites' become so familiar with its provisions and its broad libraries, so they deal with issues in learning or chipping away at other programming dialects. Syntax requirements of adding curly braces or semicolons may be seen by Python experts as an overly burdensome task.

7. Gets Slow in Speed

Python executes with the help of an interpreter instead of the compiler, which causes it to slow down because compilation and execution help it to work normally. Hence, as it uses bytecode rather than machine instructions, it performs slower than compiled languages.

8. The issue of run-time Errors

Many design restrictions are reported by some Python developers because the language is dynamically typed. Errors show up when the applications are finally run because it requires more testing.

Disadvantage: The dynamic typing means there's no compile-time checking for type safety; this can lead to runtime exceptions if you try to use an object or function with a different data type than what was expected. This makes debugging harder because you have to track down where your code went wrong in order to fix it.

Advantage: You don't need to write any special tests to check whether something works as intended before using it.

9. Lack of Documentation

It takes time to learn how to program in Python. There isn't much documentation available online about Python. It also doesn't provide good support for beginner programmers.

10. No Support For Multithreading

Multithreaded programs require multiple threads running simultaneously. In Python, only one process runs at once. If you want to create multithreaded programs, you will have to use another language.

Apart from this, Windows users cannot install Python directly from their operating system. They must download it separately.

Applications of Python

Python is a general-purpose programming language that can be used for many different types of applications-including web development, Data Analysis, Machine Learning, Artificial Intelligence, Natural Language Processing, Computer Vision & Robotics, Game Programming, Scientific Research, and more!

1. Web Development

Python can be utilized to make web applications at a fast rate. Why would that be? It is a direct result of the structures Python uses to make these applications. There is the common-backend rationale that goes into making these structures and various libraries that can assist with incorporating conventions like HTTPS, FTP, SSL, and so on, and even help in the processing of JSON, XML, E-Mail, and more!

Probably the most notable web development frameworks are Django, Flask, Pyramid. The security, versatility, accommodation that frameworks provide is commendable if we compare it to beginning the development of a website from level zero.

2. Game Development

The development of interactive games is done using Python. There are libraries such as PySoy, which is a 3D game engine that supports Python 3, and PyGame, which provides a library for game development. Games, for example, Civilization-IV, Disney's Toontown Online, Vega Strike, and so on have been fabricated utilizing Python.

3. Machine Learning and Artificial Intelligence

Machine Learning Artificial Intelligence is currently the raging technological phenomenon as they yield the most encouraging professions for what's to come. We use the data stored or better to make the computer learn from its past experiences, and then we use certain algorithms to create new software that makes it learn by itself. The programming language that for the most part, everybody picks? It's Python. Why? Backing for these areas with the libraries that exist currently like Pandas, Scikit-Learn, NumPy thus some more.

Learn the algorithm, employ the Python library, and voila! you have your solution to the problem at hand. However, assuming you need to go the bad-to-the-bone way, you can formulate your own code which yields a superior arrangement, which actually is a lot simpler when we contrast it with other languages.

4. Data Sciences

Data is money if you know how to use it to increase profits and take calculated risks, and one thing that sets apart Python from other languages is the fact that it offers a lot of built-in functions and tools that make life easier for developers. These include NumPy, Pandas, Matplotlib, SciPy, etc.

All these packages help programmers perform various tasks faster than they would otherwise do so. Various libraries frequently used for data analysis are- Pandas, NumPy, Matplotlib, and Seaborn. Common data science tasks such as data cleaning, exploratory data analysis, and feature engineering can be solved with those libraries.

Matplotlib, Seaborn, and many other data libraries are helpful in plotting graphs, and if you want to become a Data Scientist, this is the amazing array of benefits that Python has to offer.

We hope that this article cleared all your doubts concerning the advantages and disadvantages of Python in an elaborated manner and also made you aware of the world-class applications of Python.

Happy learning!