The primary reason associated with the popularity of Python is, it is a great and easy way to learn to code. It has a feature of quickly writing complicated tasks. Many significant applications only support Python language.
The popularity of the Python language in 2020 will be very high. As per the survey of the TIOBE Index for February 2020, this programming language ranks in the number 3 slot. It honored with the title of fast-rising programing language that comes under the top 50.
In addition to it, PopularitY of Programming Language Index (PYPL) ranked Python as the most popular language based on search engine searches as opposed to different programming languages. The fact, as compared to the last five years, Python has been grown to 17.6%.
Reasons for being a popular language-Python
Python is a versatile language when needed for website development.
Python is considered instrumental in AI and data science
Python excessively and uninterruptedly used in the Internet of Things
Python highly recommended when learning to code
Moreover, the demand for Python developers is very high. As per StackOverflow’s Developer Survey, this programming language ranked 2nd in the world as of its versatile nature.
Moreover, Industry leaders like
make the use of this language. Even more prominent companies are adopting this language that makes the demand for Python developers very high.
According to SlashData, more than 8.2 million developers are using this language, while 7.6 million developers are using Java in the world. Moreover, the number of Python developers are increasing day by day.
The average salary of a:
Software developer with Python skills is around $76,746 and more for an entry-level developer and very high for a senior developer (around $90K).
Web Developer with Python skills is around $59,108 and $77000for a senior developer.
Data Scientist with Python skills is around $97,663, and for veteran and experienced specialists, it touches to $140000.
Python Developer Salary in India According to indeed.com
2. Python is simple & easy to learn
The aspirants looking to learn Python should never assume that this language is quite tough to learn and use. The fact, it is the simplest and easy to learn programming language as of having simple syntax and readability. Even this language is shorter as opposed to other programming languages like C, C++, etc.
Besides, easy to learn and featured with a simple syntax, the developers can quickly build a rapport that is not seamless in other languages. Thus, Python developers treat their coding more comfortable and even fun.
3. Python is portable & extensible
This programming language is also the best portable language. For instance: In a case, the users have a python code for windows, and they want to execute it on a platform like Mac, Unix, or Linus. They can do it without any amendment. Even they can run this code on any platform flawlessly and uninterruptedly.
Also, Python is also an extensible programming language. The users can write python code into C++ or C language. Even, they can compile that code in languages like C++ and C.
4. Python is used in Data Science
Python is a high-level programming language that is fast, open, friendly, and simple to learn. It plays flawlessly with others and even runs anywhere seamlessly.
Conceived in the late 1980s, Python didn’t make inroads into data science until recently. For a long time, as Tal Yarkoni of UT Austin says, “you couldn’t do statistics in Python unless you wanted to spend most of your time pulling your hair out.”
Now, however, tools for almost every aspect of scientific computing are readily available in Python. (Thanks in part, no doubt, to the $3 million the Defense Advanced Research Projects Agency (DARPA) put toward the development of data analytics and data processing libraries for Python in late 2012.)
Bank of America usesPython to crunch financial data. Facebook turns to the Python library Pandas for its data analysis because it sees the benefit of using one programming language across multiple applications.
“One of the reasons we like to use Pandas is because we like to stay in the Python ecosystem,” Burc Arpat, a quantitative engineering manager at Facebook, told Fast Company in May 2014.
Why does Python language preferable than other data science tools?
Robust and simple to use
Python is a language that is quickly learned and use even by the beginners or any student by just learning the basics of it. It has very minimized constraints and debugging codes. In other languages like C, C++, Java, etc. the time required to code implementation is less, which takes much to the time of developers to work on their algorithm.
Python proves to be a highly scalable programming language. It solves problems that can’t be solved by other languages like Java. Many businesses have been used in this language to establish applications and tools instantly.
Options of Libraries
When users use Python, they experience a big database of libraries, machine learning, and artificial intelligence. The most popular libraries it is using are Seaborn, Scikit Learn, Pytorch, Pytorch, and Matplotlib.
Extensive Visualization and Graphics options
Python developers find many options for visualization and graphics. Even they can use their charts, graphical layouts, web-ready plots, etc.
5. Python’s scripting & automation
Being an open-source scripting language, we can easily automate anything on Python. A python learner as a beginner can quickly learn its basics and gradually able to write its scripts to automate data or stuff available around.
To automate stuff in Python, only the following scripts needed to write:
The code must be written in scripts only to get an execution.
To check the error should during the run time.
The machine is used to read and interpret the code.
Once the developer checked the code, it can further run or used several times without any interruption. Thus, with automation, users can automate many tasks or stuff in a program.
6. Python used with Big Data
To complete the big data job accurately, Python is considered the best data science tool. When there is a need to integrate web application and data analysis with the production database, then big data and Python is the best solution.
Let’s shed light on reasons when Python is the best choice for big data:
It is a destination of robust scientific packages: Python programming language equips with powerful library packages that are needed to gratify data science and analytical needs and also the top priority for big data applications. The popular libraries used by big data and Python are:
Pandas: This library used to ensure demanded data structure and operations to manipulate data on numerical tables and time series.
SciPy: It is used in the case of technical and scientific computing. It has modules like:
Signal and image processing
FFT, and more.
NumPy: It makes scientific computing feasible. It offers support for random number crunching, linear algebra, etc. Even it is useful during matrices with an extensive library, multi-dimensional arrays, etc.
Mlpy: It ensures many machine learning methods to solve the problems. It assists in finding a reasonable compromise between usability, efficiency, reproducibility, modularity, and maintainability.
NetworkX: This library is used for studying graphs that are assisting in establishing, manipulating, and reading the structure and functions of complicated networks.
SymPy: This library is used for symbolic computation having features like
Basic symbolic arithmetic
Quantum physics, and more
Besides, it has more libraries like- Dask, Dmelt, TensorFlow, Scikit-learn, Regression, Matplotlib, etc. Easy Compatibility with Hadoop The fact, Python big data is easily compatible like Hadoop. It has been made easy compatibility with Hadoop to work during the bid data. It also enables MapReduce programming used to overcome significant data problems only with fewer efforts.
Large Community Support The developers will also experience a smooth dealing of complex problems with big data analysis. Python has an extensive and active community to assist programmers and data scientists with expert support needed during the issues in coding.
Briefly, Python and big data together ensure robust computational competencies in big data analysis platform. If you are a newbie in this industry, you will find this language easy to learn and use.
pytest: It is the most recommended test framework that is available in any language. It is further used and handles in any functional tests, integration, and unit.
The Zen of Python: It is an ideal choice for test automation as it offers the test in a readable and descriptive form. In a nutshell, Python is a robust destination to follow from test cases to test code.
Multi-Paradigm: Python is a functional and object-oriented language. It is significant for test automation because of having simple syntax and stateless functions.
Ease of Entry: This language is always friendly even to beginners. This gives a significant advantage to Python, as it tests the results quickly and accurately.
Typing Your Way: It offers the best results with becoming picky about types. Moreover, in a case, static types are required like Pyre, and MonkeyType resulted to the rescue, this language offers typing in both ways.
The Python Computer Graphics is used in any domain wherein the users have to deal with 3D data, be it of any sort or kind. Thus for visualization, Virtual Reality, photorealistic images, or even games, Python high language is highly used.
It offers the basic functionality needed to write your tools to process 3D data. For instance, the cgtypes module is used or required to reveal the fundamental kinds for Computer Graphics like matrices, cri modules that have the entire RenderMan API to establish RIB files, and more.
With these modules, it becomes easier to keep a 3D scene in memory that can manipulate in Python.
9. Python used in Artificial Intelligence
This programming language offers the least code as compared to others. It is highly used in AI (Artificial Intelligence) as opposed to other programming languages as of the following reasons:
It is an independent platform, the most preferable and popular choice to use in the different platforms with the least tweaks required even in necessary coding.
It has prebuilt libraries such as Scipy used for advanced computing, Numpy used in scientific computation, and Pybrain for machine learning, being the best language used in AI.
It is highly dynamic, along with having an option to choose scripting and OOPs approach. Even the users can use IDE itself to get the required codes. It is also the best choice for developers that are struggling with different algorithms.
Decoding Python equal with AI
Python, being the highly recommended programming language along with packages like iPython, matplotlib, NumPy, scikit-learn, Notebook, creates the basis to begin an artificial intelligence test.
Matplotlib: It is a 2D plotting library ensuring publication-quality figures. The users can also matplotlib as the interface toolkits, Python scripts, and web application servers.
NumPy: Used for generic data comprising in a case of N-dimensional array tools to integrate C or C++ code, random number capabilities, etc
Even pandas is also a useful library to provide users with simple data structures and even analytical tools needed in Python. The commonly used libraries in Python are pyDatalog, EasyAi, AIMA, SimpleAI, etc.
Python Libraries for General AI
AIMA: It is a modern approach used for the implementation of algorithms in Python from Artificial Intelligence.
EasyAI: It is the best engine used in the case of two-players games with Artificial Intelligence.
SimpleAI: This approach used to provide easy access, complete documentation, and tested library.
There is no secret to say that Python becomes the most common language and has been hiking its demand tremendously for the last five years. To build up a website with Python means the users produce code that is responsive to execute the server instead of in the browser. The fact, establishing the server side of a website is imperative for storing user information.
Those who are seeking ahead to use Python for web development, they must learn about the programming and principles of this language before taking up any real project. Thus, beginners must learn this programming language before commencing to use it to create a website.
How does Python helpful for web development?
This easy syntax of Python helps the users to build a complete and complex system quickly. Even developers will find the process of recognition of relationships between indicate structures and elements easier.
Abundant of frameworks: One of the best features of using this language is its ecosystem. It means it has plentiful frameworks to use. Since the usage of Python web development has been increasing significantly timely, the developers can experience abundant web-oriented modules that are designed to assist people in needing functional websites.
In the Python web development criteria, dominating frameworks that users can use are Flask, Django, TurboGears, Pyramid, Flask, Bottle, and CherryPy. Let’s know the use of these briefly:
Django: To build up a website by using Python language, the developers need Django that is a web-oriented framework. It offers many elements of intricate programs such astemplate engine, management panel, signing out, signing up, URL routing, and uploading file template driver. Once the user establishes up the framework, all these features become ready to use. However, without using this module, the users must require to write or use these features manually.
Flask: Another module that is used as web development in Python is Flask. All of the components that are the part of this module are ready to execute in the server context. Moreover, this module a micro-framework that means it exhibits zero or very little rely on other libraries.
Pyramid: This Python web framework is very famous and recommendable as it offers more attributes than Flask. However, it is not as better as Django. Moreover, it is a flexible framework where the users don’t need to use a particular approach for finishing up a project. This will assist the users with URL routing and authentication support. However, this is only possible when users use it by connecting to storage or database with the help of external libraries.
TurboGears: When there is a need to establish small-scale or large-scale web projects, then TurboGears is a highly recommended and scalable framework. It has abundant features commencing fromauthentication, caching, identification,management ofsessions, and pluggable applications.
Bottle: Whenever there is a need for using dynamic and lightweight Python web development framework, Bottle is highly needed. It is highly suggested for small scale projects. It is also designed with a single-source library. Moreover, it is even easier to learn by beginners and more advanced developers.
Programming approach: Another feature of using Python for web development is having an approach to the programming style. It means there are programming languages that are highly strict as these can’t be switch to another approach easily or randomly. But, in Python, the beginners or even advanced programmers can do the same task easily as per the object-oriented, functional, or procedural way. Thus, you will experience flexibility while using this language as being a user, you can choose which programming paradigm is as per your need.
Python 3 is the latest version of Python. Moreover, Python 2 is not so updated but still in use and quite popular.
We can write this language in a text editor and an integrated development environment like Eclipse, Netbeans, Pycharm, Thonny, etc. All these are recommended, especially when there is a need to manage vast collections of Python files.
Why beginners should learn Python language first as opposed to other programming languages?
Since all programming languages are useful accordingly the development of applications, however, Python is easier to understand and use than other languages. Besides, it has the following attributes:
It was designed to read as it has many similarities like the English Language.
It depends upon indentation by using whitespace with an intention to define scope like classes, a scoop of loops, etc. However, in the case of other programming languages, there is a need to use curly-brackets to fulfill this purpose.
It uses new lines to finish a command while in case of other programming languages, parentheses or semicolons are used often.
Thus, learning programming language buy joining a course is highly recommended to use it in different ways during the programming.
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