Ask me why Python is so popular amongst the programming languages. The answer to this is quite short, crisp and simple yet very satisfying similar to the code built on it. There are many coding languages, and a handful of those will wake you up from a happy sleep. Python showcases a very smooth outlook to the traditional way of developing a program. Don't believe me? Have a look at the sample code online.
Now compare it with other languages like Perl, Java, Tcl, C++. It seems that my words are entirely justified eh.
Either you are looking for a headstart in an aggressively progressing career or waiting for a leaping step in your current stream Python outstands all of its competitors. With its increasing credibility, demand and adoption of learning Python can help in forming a firm base for its coders. Python professionals well paid as per the industry standards. Widely accepted, flexible, compatible and runs swiftly on many operating systems like Mac, Windows, Linux and .net.merging with the back-end processes of organizations worldwide. Its legacy dates from the late 1980's. Python is developed, supported, managed and monitored by the Python Software Foundation(PSF).
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With its intensive set of features supporting the starters and professionals migrating to Python, it stands out as an excellent choice of skillset.
Python has a free open source license(OSL) which is also valid for commercial purposes. It can be downloaded and installed for free directly from the official site.
Python is a giant in advanced coding languages with most of its instructions acutely resembling the English language. It can be learned quickly by a rookie compared to complex coding languages like C++ and Java. It adds convenience to a professional with expertise on software other than Python with its resemblance to object-oriented structures with other software.
Python is an interpreted language, the code gets checked during the execution unlike compiling and then running the system followed by others. The instructions written in Python by one developer can be understood and modified by another developer easily. Code developed on Windows os can be executed and improvised on another os.
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Python Package Index provides with the detailed listings of the catered packages. Python contains several standard libraries for including modules like GUI, Test, Automation, DB, Networking, Web Development, Image processing and Text processing, etc. Part played by these libraries are detailed below.
Dealing with high volumes of data and performing analytics at the same time is a considerable issue these days as it keeps on adding to the vault. Data Science with Python training provides advanced features to hit this targeted arena. Python with its support to scientific libraries is rapidly improving on data processing levels. Python drives into clearing the blocks in statistic data modeling with the help of its Numpy, Scipy, Pandas, and Matplotlib
Coding in Python follows procedural functions and Object Oriented programming concepts. Long lines of the program written in procedural pattern with a mix of code and data to feed. It involves functions and program subroutines and is often less manageable. Where as Oops includes the programming with class, objects, and methods. These three pave the way to inheritance, abstraction, and polymorphism functional behaviors.
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The below mentioned curve relates to the learning process in Python. Learning Python may vary from 2 to 6 months depending on the pace and the hours spent on it.
As displayed in the curve a beginner learns from the basics steadily stepping the ladder of expertise. Some may leave the track due to lack of commitment yet most of them are sure to reach a higher mark with their gradual and consistent efforts.
Most of the earning more than their expectations with endless opportunities in Python. We would have quoted a figure but do not want to limit you there.
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Anjaneyulu Naini is working as a Content contributor for Mindmajix. He has a great understanding of today’s technology and statistical analysis environment, which includes key aspects such as analysis of variance and software,. He is well aware of various technologies such as Python, Artificial Intelligence, Oracle, Business Intelligence, Altrex, etc. Connect with him on LinkedIn and Twitter.
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