New Approach for the Automation: Python

New Approach for the Automation: Python

January 13, 2021 / Eternal Team

Nowadays as we see everything is automated. So if we need something to be automated we must write the desired sequence of steps in a programming language or in some scripting language.

There is a difference between a programming language and a scripting language.

We believe that you already know some basic programming language, if not then no worry, we are here!!.

Let’s firstly go through with what is a programming language

  • A programming language “high-level languages is that, which programmers use to create code, commands and instructions. And programming languages use a set of different instructions, commands and syntax for making coding logic.
  • A programming language is used to write scripts, and other sets of instructions for computers to execute.
  • Examples of high-level languages include C++, Java, Perl, and PHP.
  • Languages like Perl and PHP are called “interpreted languages”.
  • Low-level languages include assembly and machine languages. Assembly language contains a list of basic instructions and is much more difficult to read than a high-level language.

There is much more about programming languages but now, let’s understand what is an automation language and what is a scripting language.

  • A scripting language is used to write scripts. Scripts provide automation in our infracture by using different instructions and commands in one single file.
  • Scripting languages can be divided into two categories:
  • Server Side Scripting Languages
  • Client-Side Scripting Languages
  • Server Side Scripting Languages – Server-side scripting languages create the scripts that run on the serve. For example, Python,
  • Client-Side Scripting Languages – Client-side scripting languages create the scripts that run on the client-side (i.e. your browser). examples are JavaScript, jQuery, CSS etc.

What is Automation?

new-approach-for-the-automation-python

In IT, infrastructure automation is used for repeatable tasks and different instructions and processes to replace or reduce human interaction in IT. Automation is key to IT optimization and digital transformation. Nowadays IT environments need to be able to scale faster than ever and IT automation is primary for everyone.

  • It provides a clear process.
  • Reduces work for IT pros.
  • Improves the speed of delivery.
  • It Reduces the cost of delivery.
  • Improves the accuracy of delivery.
  • saves time.
  • Improves customer satisfaction.

Now let’s come to our main topic, Why Python is so popular in automation. So let’s start with a very basic question, What is Python?

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Python is an interpreted, high-level and general-purpose programming language.

Python increased productivity. Python’s simple, easy to learn syntax.

Python supports modules , Funcationsand packages

Python language can help a lot in automation, which makes things much more comfortable.

The History Of Python

  1. Python was developed by Guido van Rossu in
  2. Python has been an inspiration for many other coding languages such as Ruby, Cobra, Boo, CoffeeScript ECMAScript, Groovy, Swift Go, OCaml, Julia etc.
  3. Open-source
  4. Python Version 1.X in 1994
  5. Python Current Version 3.9.0 in 2020

Some Key Points of python

  1. Easy to Learn and Use
  2. Automation
  3. Mature and Supportive Python Community
  4. Hundreds of Python Libraries and Frameworks
  5. Versatility, Efficiency, Reliability, and Speed
  6. Big data, Machine Learning and Cloud Computing
  7. First-choice Language
  8. The Flexibility of Python Language
  9. Use of python in academics
  10. Python is a cross-platform programming language i.e. it can be used for Windows, Linux, Mac, Raspberry Pi and others.
  11. It has a simple syntax which is very similar to the English language

There are many frameworks and libraries are available for python language, such as

  • matplotlib for plotting charts and graphs
  • SciPy for engineering applications, science, and mathematics
  • BeautifulSoup for HTML parsing and XML
  • NumPy for scientific computing
  • Django for server-side web development
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