Elevate Your Career by Skilling Yourself in Python Programming. Dive into Python to Wing Your Dreams!

Abstract

Python, a high-level, interpreted programming language, has garnered immense popularity and become one of the most beloved languages among developers worldwide. With its clean and readable syntax, extensive libraries, and wide-ranging applications, Python has established itself as a go-to language for various domains, from web development and data science to artificial intelligence and automation.

Keywords

Python, Programming Language,General-Purpose Language,

Learning Outcomes

After undergoing this article you will be able to understand the following

1. What's exactly Python?

2. What's the latest version of Python?

3. Why Python is so popular?

4. What's industries have adopted Python?

5. How Python is applied in modern organisations?

6. What's Essential syllabus of Python - one must know?

7. Top Strategies to implement Python

8. Conclusions

9. FAQs

References

1. What's exactly Python?

Python is an open source and high-level programming language designed by Guido van Rossum. Released in 1991, this programming language’s design philosophy aims at code readability, which is why it’s one of the easiest languages to learn. It features dynamic typing, dynamic binding, and high-level data structures, all of which make it a good choice for rapid application development.

Python is a multipurpose, high-level, object-oriented programming language — three properties that make it popular with coders and developers. Python is multipurpose because it can be used to create software and apps, design websites, and automate repetitive tasks.

It's based on the CPython interpreter which translates the Python code into something the machine can read. Python gives us the ability to use a lot of modules and packages with our code, which are standard libraries built in with the interpreter.

As of now, there are three major versions of Python, Python 3 being the latest. It also supports a wide range of libraries to simplify writing the code.

Python’s features are:

Open source and free: Python is open source, and you can download its code for free to use and modify it for your projects.
Easy to learn: Python is becoming popular because it’s easy to learn compared to other languages. Its simpler syntax uses plain English with less complexity. Hence, it’s developer-friendly and easy to code.
Extensive libraries: Python’s standard library is extensive with rich modules and functions that help you complete your projects faster instead of writing code from scratch. You can find reusable code for processes like image manipulation, unit testing, CGI, and more. Examples include Django, Flask, NumPy, and SciPy.
Extensible: Python is highly extensible with different modules to extend the core functionality. For example, you can add a programmable interface to an existing application.
Object-oriented: Python uses object-oriented programming concepts, such as objects, classes, inheritance, data encapsulation, and more.
Interpreted and easy to debug: Python executes code linearly, like Java, C, and C++. This way, there’s no need for compilation, and debugging becomes easy.
Dynamically-typed: Specifying a variable type such as char, int, double, etc., is not needed in Python as it’s decided during code run time rather than at the start. As a result, it makes programming simpler and reduces many lines of code.
Portable: Python uses portable code. So, you can use the same code across different platforms like Windows, macOS, Unix, or Linux.

2. What's the latest version of Python?

Python 3 is the latest version. Python 3 being the latest and containing new features, syntax and improved performance is actively maintained

Python 3's syntax is considered easier to understand and more readable than Python 2's, which uses more complex syntax. Backward compatibility. Python 3 is not backward compatible with Python 2, whereas Python 2 is backward compatible with previous versions of Python; in other words, code written for Python 1.

Python 2 has reached end-of-life and is no longer updated, while Python 3 is actively maintained.

Python 3 is the most recent version, and you don't need Python 2 experience to learn it. It makes sense to learn Python 3 first if you're just learning this programming language.

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

Release	Released	Active Support	Security Support	Latest
3.12	6 months ago (02 Oct 2023)	Ends in 12 months (02 Apr 2025)	Ends in 4 years and 7 months (31 Oct 2028)	3.12.2 (06 Feb 2024)
3.11	1 year and 5 months ago (24 Oct 2022)	Ended yesterday (01 Apr 2024)	Ends in 3 years and 7 months (31 Oct 2027)	3.11.8 (06 Feb 2024)
3.10	2 years and 6 months ago (04 Oct 2021)	Ended 12 months ago (05 Apr 2023)	Ends in 2 years and 7 months (31 Oct 2026)	3.10.14 (19 Mar 2024)
3.9	3 years and 6 months ago (05 Oct 2020)	Ended 1 year and 10 months ago (17 May 2022)	Ends in 1 year and 7 months (31 Oct 2025)	3.9.19 (19 Mar 2024)
3.8	4 years and 5 months ago (14 Oct 2019)	Ended 2 years and 11 months ago (03 May 2021)	Ends in 7 months (31 Oct 2024)	3.8.19 (19 Mar 2024)
3.7	5 years and 9 months ago (26 Jun 2018)	Ended 3 years and 9 months ago (27 Jun 2020)	Ended 9 months ago (27 Jun 2023)	3.7.17 (05 Jun 2023)

The end-of-life is scheduled 5 years after the first release, but can be adjusted by the release manager of each branch.

In the first 1.5 years there are planned releases with bugfixes. In the next 3.5 year there are only security fixes and source distribution without precompiled binaries. Starting with Python 3.13 it will change to 2 + 3 years.

The detailed release information (including schedules) can be found among Release PEPs

A Python release only supports a Windows platform while Microsoft considers the platform under extended support. Python 3.8 was the last version to support Windows 7.

More information is available on the Python website.

You should be running one of the supported release numbers listed above in the rightmost column.

You can check the version that you are currently using by running:

python --version

# or alternatively
python3 --version

3. Why Python is so popular?

One of the key factors contributing to Python’s popularity is its status as a general-purpose programming language. Python’s versatility allows developers to work on diverse projects, ranging from web applications and mobile apps to desktop software and system administration.

Simple and Readable Syntax

Python’s syntax is designed to be simple and easily readable, making it an excellent choice for beginners and experienced programmers alike. The language’s focus on readability and reduced use of complex syntax enable developers to express their ideas more effectively, leading to higher productivity and better collaboration.

Extensive Libraries and Frameworks

Python boasts a vast collection of libraries and frameworks that expedite the development process significantly. These libraries, such as NumPy, Pandas, and Matplotlib, cater to data manipulation, analysis, and visualization, making Python the preferred choice for data scientists and analysts.

Python’s Popularity in Web Development

Django: The Robust Web Framework

Django, a powerful and feature-rich web framework, has played a crucial role in propelling Python’s popularity in web development. Its ability to handle complex web applications efficiently, coupled with ease of use and extensive documentation, has made Django a preferred choice for developers and organizations alike.

Flask: Lightweight and Flexible

Flask, a lightweight and flexible web framework, appeals to developers seeking simplicity and minimalism in their projects. While it may not offer the same level of functionality as Django, Flask’s flexibility allows developers to customize their applications according to specific project requirements.

Data Science and Machine Learning with Python

NumPy and Pandas: Data Manipulation

When it comes to data manipulation and analysis, Python’s libraries, such as NumPy and Pandas, are second to none. Data scientists leverage these libraries to perform complex operations on large datasets efficiently, making Python a favorite language in the data science community.

SciPy and Scikit-learn: Machine Learning

Python’s extensive ecosystem includes SciPy and Scikit-learn, which provide powerful tools for machine learning. These libraries empower developers to implement sophisticated machine learning algorithms with ease, thus driving Python’s adoption in the machine learning domain.

Automation and Scripting Capabilities

Automating Repetitive Tasks

Python’s versatility extends beyond web development and data science; it excels at automating repetitive tasks, making it a valuable asset for system administrators and DevOps professionals. Its simplicity and ease of integration with other tools make Python an ideal choice for automating various processes.

Command-Line Scripting

Python’s availability as an interpreted language allows developers to write command-line scripts with ease. This feature simplifies tasks for system administrators and developers who frequently work with the command-line interface.

Python’s Role in Artificial Intelligence

TensorFlow: Deep Learning Made Easy

TensorFlow, an open-source machine learning library, has revolutionized the field of deep learning. Python’s seamless integration with TensorFlow has made it a popular language for building and deploying AI applications, including computer vision, natural language processing, and more.

Natural Language Processing with NLTK

Python’s Natural Language Toolkit (NLTK) provides extensive support for natural language processing tasks, further strengthening Python’s position in the AI and natural language processing domains.

Python in the Internet of Things (IoT)

Controlling Devices with Python

Python’s lightweight nature and ease of use have made it a preferred language for programming IoT devices. Its ability to control and interact with hardware makes Python a valuable asset for IoT developers.

Analyzing IoT Data

Python’s data manipulation and analysis capabilities extend to the IoT domain, enabling developers to process and analyze data generated by IoT devices effectively.

Community and Support

Active Online Community

Python’s popularity is further fueled by its active and vibrant online community. Developers can easily find solutions, seek help, and share knowledge through various forums, Stack Overflow, and GitHub repositories.

Extensive Documentation

Python’s official documentation is comprehensive and well-maintained, providing clear guidance for developers of all skill levels. This detailed documentation contributes to Python’s ease of learning and adoption.

4. What's industries have adopted Python?

Python supports a vast ecosystem of libraries and frameworks. You can use these libraries and frameworks for scripting, developing web applications, and processing large amounts of data. Prominent examples of its application are web development, data science, ML and AI, Cyber Security, and Finance.

Python is extensively applied in data science, data analysis, machine learning, data engineering, web development, software development, and other fields.

5. How Python is applied in modern organisations?

Applications of Python also include building ERP and ecommerce systems. Business applications are different from typical consumer software because they offer a set of specific features instead of a variety of features. Besides, they target a very tight-knit user group, usually an organization.

Python is perfect for delivering best-performance custom solutions for business applications as well as consumer applications.

Odoo is a well-rounded management software that offers numerous business applications that constitute a complete set of enterprise management applications

Tryton is a three-tier high-level application platform designed for general purposes

6. What's Essential syllabus of Python - one must go through?

About Python Syllabus

Python covers a vast area of expertise such as Introduction to Python and Computer Programming, Data Types, Variables, Basic Operators, Boolean Values, Conditional Execution, Loops, Lists and many more.
Python Programming is an important part while learning Python. Some of the topics covered are Introduction to Python Language, Python Language Syntax, Python Keywords and Identifiers, Python Variables, Data Types, Operators, etc.
Django, a high-level Python web framework that is used for rapid development of secure and maintainable websites, covers Python scripts, file operations in Python, Database, Views, Python Object Oriented Programming, etc.
Python for Data Science requires knowledge of Python Programming and is opted by many.

The full syllabus for Python is vast. It covers various topics such as Introduction to Python, Control Statements, List, Ranges & Tuples in Python, Python Dictionaries and Sets, etc. The list of topics for Python Courses is given below in the table.

Introduction to Python	Control Statements
List, Ranges & Tuples in Python	Python Dictionaries and Sets
Input and Output in Python	Python built in function
Python Object Oriented	Exceptions
Python Regular Expressions	Python Multithreaded Programming
Using Databases in Python	Regular Expression
Thread Essentials	Web Scraping in Python
Data Science Using Python	Graphical User Interface
Django Web Framework in Python	-

7. Top Strategies to implement Python

Top Strategies for sucessful learning and implementation depends on the following Practical Applications of Python

Operating Systems

The robust standard library of Python makes it perfect for building entire operating systems. The object-oriented design of the language ensures large projects are easily managed. Python is compatible with most operating systems and can be easily used to build native applications for Windows and Mac computers.

Web and Internet Development

Python offers several choices for complex web development projects. HTML and JavaScript are the main languages used to build the front end of an application. But Python-based web frameworks like Django, Pyramid, and Flask are used to handle backend or server-side functionality of sites and services like Spotify, Reddit, and Mozilla. Giant platforms like Google and YouTube depend largely on Python for critical infrastructure.

The standard library of Python also supports many Internet protocols like HTML and XML, JSON, Email processing, FTP, and IMAP.

Game Development

Just like for web development, Python offers an array of tools and libraries for game development. Would you believe, Battlefield 2 – one of the most popular shooting games of the early 2000s, was developed with the use of Python.

Python’s 2D and 3D game development libraries are PyGame, Pycap, Panda#D, Construct, PySoy, and PyOpenGL.

Python has been used to develop popular games, including Sims 4, World of Tanks, Eve Online, Mount & Blade, Doki Doki Literature Club, and Disney’s Toontown Online, to name a few.

Scientific and Numeric Computing

The Python ecosystem offers numerous tools and libraries that help scientists and researchers in scientific and numeric computing.

SciPy is a set of packages for mathematics, science, and engineering
Pandas is a library used for data analysis and modeling
IPython is a strong interactive shell that provides hassle-free editing and recording of a work session and aid in visualizing and parallel computing.
FreeCAD and Abaqus are real-life numerical and scientific applications built with Python

Artificial Intelligence and Machine Learning

The hottest buzzwords of the decade – Artificial Intelligence (AI) and Machine Learning are mostly about algorithms, code, and logic. Python, along with a few other programming languages, is increasingly being used for developing AI and ML-powered solutions. The scope and power of Python, along with its stability and security, make it ideal for running AI and ML systems.

Some important libraries for the job are:

Scikit-Learn – for building various machine learning models
SciPy – for scientific and technical computing
TensorFlow – for state-of-the-art neural networks
Keras – for artificial neural networks
Pandas – for data analysis and manipulation

Desktop GUI

Python is an excellent choice for desktop GUI (Graphical User Interface) programming. The language offers numerous options for developers to build a fully functional GUI. The comprehensive syntax and modular programming approach of the Python framework help create a super-fast and responsive GUI.

Some prominent applications of Python tools for GUI development are PyQt, Tkinter, wxWidgets, Python GTK+, and Kivy. Standard applications like Dropbox and BitTorrent are primarily written in Python.

Business Applications

Python is perfect for delivering best-performance custom solutions for business applications as well as consumer applications.

Odoo is a well-rounded management software that offers numerous business applications that constitute a complete set of enterprise management applications

Tryton is a three-tier high-level application platform designed for general purposes

Why Use Python in Web Development?

Technology giants such as Spotify, Instagram, and Google use the open-source, easy-to-understand Python programming language for developing enterprise-level, robust, and responsive web applications.

Packaged to expedite installation, the ActivePython software, with a comprehensive set of extensions, allows Python developers to start working with state-of-the-art Python frameworks such as Tornado, Django, and Flask within minutes.

Integrating the Python programming language, the ActivePython software package, offered via the ActiveState Platform, also permits users to connect to AWS (Amazon Web Services) API and SDK libraries. This heightens the appeal of the software, making it the preferred choice for web developers around the world.

Now, before we learn what is Python used for, here are the top advantages of using Python in web development.

Python is Easy to Learn

Compared to other programming languages like C++ or Java, the design philosophy of Python - emphasizing general expressions and code readability with significant use of whitespace - makes the programming language easy to understand, even for beginners. Additionally, developers using Python can get their job done by writing much less code.

Python Has a Rich Ecosystem

The extensive Python library offers a wide range of packages and tools, such as SLQALchemy, Pygal, Pandas, and Numpy, which allow developers to access pre-defined code, ensuring fast and smooth application development.

Speedy Prototyping

In comparison to programming languages like C++ or Java, Python reduces the development time to a great extent, making things easier for developers to build prototypes quickly and gain feedback on their projects.

8. Conclusions

9. FAQs

Q. Why Python is preferred by Developers?

Ans: In comparison to programming languages like C++ or Java, Python reduces the development time to a great extent, making things easier for developers to build prototypes quickly and gain feedback on their projects.

What order is better to learn Python?

Follow these interesting steps

How to Learn Python: Steps for Success.
Understand why you're learning Python.
Get started with the Python basics.
Master intermediate Python concepts.
Learn by doing.
Build a portfolio of projects.
Keep challenging yourself.

Which Python module / library I should be learnt first?

You should learn basic python first then intermediate and then advanced.

basic	intermediate	advanced
random	itertools	threading
collections	functools	subprocess
math	numpy	socket
sys (exit)	pandas	requests
datetime	tkinter	openpyxl
string	keyboard	django
pygame/turtle	statistics	flask
copy	csv	matplotlib

References

Python.org

https://www.python.org

https://pythoninstitute.org

W3Schools

https://www.w3schools.com

W3Schools

https://www.tutorialspoint.com/python/index.htm

https://www.edx.org/learn/python

https://www.codecademy.com

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