Python is very popular language in the modern era and It is most highly demanded programming language over the world. It is interpreted general purpose programming language which supports both structure programming and object-oriented programming. Python is being used widely in different sector like Machine Learning, Data Science, Website Development etc. It will not be surprising If I say Python has replaced java as the most popular programming language in Industries, Universities and Colleges . Python is growing & growing and never looked back.
If you are beginner, it's simple, start with Python because it is easy to learn and powerful enough to build a web application and automate the boring stuff. If you are experienced programmer and know Java, Javascript or C++, then Python is boon for you. By learning it you can acquire a new and enough powerful tool in your dump.
Python gives you ability to automate complex and boring stuffs and let you focus on your other useful things. With python Django framework you can develop large and scalable web applications. It means by learning just one language you can do multiple task like web development, Game development, Machine Learning & AI, Data Science, Web Scrapping, Desktop GUI, Embedded Applications and more.
In this article, I will cover 10 Reasons Why you should Learn Python as a Programmer? If you are thinking of learning Python but not sure why you should do that, then here are 10 reasons which highlight the benefits of learning Python in 2021.
Though the questions depend upon who is asking that, i.e., for a beginner, learning Python makes sense because its foremost and straightforward reason for learning Python is simplicity.
Anyway, Without adding more words, here are my 10 reasons to Learn Python.
1. Easy to Learn and Setup –
The main reason why python is an excellent choice is due to it's simple syntax and highly readability factor. When you want to do programming for the first time, you would not like to start with wild syntax and complex rules.
You can learn python in shorter time in comparison of C/C++ or Java. Python is similar to English Language that's why it's a popular choice for the beginners and It's very easy to setup and doesn't need extra tools to run it.
Download it from here then just install it, While installing, it will also ask you to add Python in PATH, which means you can run Python from anywhere on your machine.
Let's see an example of code for python vs java.
Python:
stuff = ["Hello, World!", "Hi there, Everyone!", 6]
for i in stuff:
print(i)
Java:
public class Test {
public static void main(String args[]) {
String array[] = {"Hello, World", "Hi there, Everyone", "6"};
for (String i : array) {
System.out.println(i);
}
}
}
2. Flexible and Extensible -
Python Language is very flexible and extensible and that's why It gives you ability to perform cross language operations hassle free. And many platforms support python such as Windows, Linus, Macintosh etc. Python has a lot of libraries which creates different programming environment for different tasks. Example- For data science and data analysis - Numpy, Pandas, Matplotlib are the most commonly used libraries in Python. For App Development - Kivy, Tkinter are the most commonly used libraries in python. For Machine Learning and AI - Tensorflow, Keras, Sklearn are the most commonly used libraries in python.
There are many more libraries developed for python so that the programming gets way easier than other programming languages.
You can write some of your Python code in other languages like C++. This makes Python an extensible language, meaning that it can be extended to other languages
3. Data Science -
The demand for data scientists is growing in the corporate world since the scope of data science is increasing. Data science is one of the significant reasons many developers are jumping to learn Python. Python is undoubtedly the best language to learn if you want to proceed with Data Science as a career. Since Python code is considered to be easier to maintain and more scary than the R, Python has increased the popularity of data science, especially among professionals who are not educated in mathematics or mathematical fields. Intially Data Science was only flexible to R , but now with evolution roads have been widen and Python is the best for it.The reasons behind python in the data science is hat it provides many libraries and frameworks such as PyBrain, NumPy, SymPy, PyMySQL, etc. Another reason is diversity, Python experience allows you to do a lot more than R, for example, you can create scripts to automate stuff, go into web development and so much more.
4. Python has wide Range of Uses -
The reason behind the demands of Python is because it has many applications. Some of its main uses include:
- Hosting web servers
- Analyzing data sets
- Performing mathematical computations
- Generating computer graphics
- Creating basic games
- Investing in financial assets
- Automating system administration
- Testing websites
This a compelling reason for studying the language, particularly taking into consideration that it is so easy to learn. Within months, you could be analyzing large data sets. And, because the language is so simple, the techniques used by beginners and experts are not so different. They are, in fact, all based on the same fundamentals. This means that, once you know the basics, there is no limit to what you can build.
5. Python has extensive collection of libraries
A library is a collection of pre-written code that developers can use to solve common tasks. This saves loads of time because you don’t have to code everything from scratch. Python has a range of libraries, packages, frameworks, and modules for data manipulation, statistical calculations, web development, machine learning, and data science.
Moreover, Python’s libraries are great for processing and analysing data to fish out meaningful information from it. This is especially useful for Machine Learning models since it requires continuous data processing. Here are some of the most used libraries for AI and ML.
Sci-Kit, Keras, and TensorFlow: Helps in handling basic ML algorithms, assists in quick calculations, and helps you set up deep learning systems.
Pandas: Used for analysing data. Helps you work with data from external sources like Excel. You can also merge and filter data easily using Panda.
PyBrain: Contains algorithms for neural networks, reinforcement learning, unsupervised learning, and evolution. This is specifically built for entry level students.
Matplotlib: Matplotlib helps you create histograms, charts, etc, to help interpret your data easily.
6. Python in ML and AI -
This is another reason why programmers are learning python in 2019. The growth of machine learning is phenomenal in last a couple of years and it’s rapidly changing everything around us algorithms become sophisticated day by day, the best example is Google which can now answer what you are expecting.
If you are interested in machine learning, want to do a pet project or just want to play around, This is the only major programming language which makes it easy.
7. Python for Web Development
Python is used in the field of web development to build the back-end of web applications. Python is an amazing coding language that has been around for a long time. Its simple and straightforward syntax makes it ideal as a first-choice language for beginners, yet it is powerful enough to be behind some of the worlds' most popular websites.
Both of its most popular frameworks - Django and Flask - have their merits, and you can go with either of them to build your web application. Yet, if you are a less experienced developer, we recommend using Django once it provides an easier and faster web development. There's a popular saying in the Python community that is both funny and self-explanatory: "Pirates use Flask, The Navy uses Django."
Python highly versatile than PHP : Python’s versatility is almost infinite. Python website development is not for only one use! But, NLP, image processing, data science, desktop application development, mobile app development, etc. are a few more Python uses.
PHP, on the other hand, is mainly used in web development intended for creating web pages. Therefore, Python’s versatility is never questioned in creating sophisticated software, mobile, and web programs.
###Web Frameworks These are some popular Python web frameworks:
1. Django: a "high-level Python Web framework that encourages rapid development and clean, pragmatic design."
2. Flask: a very popular microframework used to develop web applications in Python.
3. Pyramid: a "small, fast, down-to-earth Python web framework."
4. Web2Py: a "free open source full-stack framework for rapid development of fast, scalable, secure and portable database-driven web-based applications."
5. Bottle: a "fast, simple and lightweight WSGI micro web-framework for Python."
8. Python in GUI
Python is interesting because it describes itself as an easy-to-use and read language, but creating a GUI application can be tedious. Python is an interpreted language and is all written in code (unlike Java’s GUI or VB.net’s GUI graphical construction), so making programs will be harder, but using a GUI library such as wxPython is somewhat daunting.
Having said that, Python is still considerably easier to use than one written in a language such as C/C++ since library names are more readable, there are fewer lines of code needed, and Python has a habit of being less error-prone.
Making graphical applications for 2D games, however, is incredibly easy with libraries such as PyGame, and a decent FPS can be achieved. But since Python is interpreted, you can expect a heavy penalty on processing speed. So it is not suitable for programs that may need to process large amounts of data while updating a graphical window.
If you need to get a program out fast and don’t mind coding the individual buttons, Python is a good language for graphical routines. However, if you need processing power and a high FPS, you are better off looking at other languages. Pycairo is a great library for creating high quality vector graphics in Python. But I recommend to to learn C or C++ for computer graphics and learn how computer graphics works
9. Python in Game Development -
In the Python ecosystem, you’ll find a rich set of tools, libraries, and frameworks that will help you create your games quickly. You can write whole games in Python using PyGame Python is an excellent choice for rapid prototyping of games. But it has limits with performance. Therefore for more resource-intensive games, you should consider the industry standard which is C# with Unity or C++ with Unreal. Some popular games like EVE Online and Pirates of the Caribbean were created using Python. There are libraries and frameworks such as Pygame, Pyglet, and PyOgre to help you create your own games in Python. If you want to get into game development with Python, the Pygame framework has pretty much everything you need to create a simple 2D game. Pygame is a low-level graphics library, built as a wrapper around SDL (which is an open-source 2D graphics library)
10. Largest supportive community
One of the greatest tools a programmer will ever have is the support of their community. Being a newbie programmer or a student, you will always seek help from the technical community to master any programming language and Python has a healthy, friendly and Large community around it. However, "the user community is so large, that anyone encountering any coding problems can quickly find the solution by simply posting a question or searching for the answer on a Python developer community site.
🔶In Short - 🔶 Python is an Object-Oriented Programming language. By using it you can create classes with multiple inheritance.
- Python has a wide range of functionalities that allow you to program in functional programming: lambda, map, filter, reduce, partial...
- Python checks the type of the variables during runtime, this makes the declaration of variable easier. But it's also possible to do static typing to catch potential bugs sooner.
- Python has a very extensive standard library. It contains many types (lists, maps, sets, numerics, ...), it has IO functions to read/write files, mathematics functions (complex numbers, fractions, statistics functions, random...), compression (zlib, gzip, zip, ...), parsing (xml, csv, ...), cryptography, threads, sockets, http modules, graphical interface, and many more.
- More that 150,000 libraries are available using the package management tool pip.