Introduction to Python Programming Language
Python is a popular programming language created by Guido van Rossum and introduced in 1991. Used for;
Why does learn Python language?
What is the functioning of Python?
Although, abundant reasons are associated with using Python language in 2020, let’s highlight the best below:
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%.
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:
Python Developer Salary in India According to indeed.com
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.
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.
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 uses Python 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.
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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.
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.
Python developers find many options for visualization and graphics. Even they can use their charts, graphical layouts, web-ready plots, etc.
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.
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.
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:
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
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.
Python is a valuable programming language that supports testing flawlessly. It is the best choice for test automation said by Dan Callahan because having;
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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.
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:
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.
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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.
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:
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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:
Thus, learning this programming language buy joining a course is highly recommended to use it in different ways during the programming.
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