Getting Started With Python

👋 Hi there, I am Nirmal. I am a former software engineer with a keen interest in data science and analytics domains. Besides, I love to contribute to open source and help others to understand various tech stuffs.
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👋 Hi there, I am Nirmal. I am a former software engineer with a keen interest in data science and analytics domains. Besides, I love to contribute to open source and help others to understand various tech stuffs.
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This series will provides the core concepts of python programming starting from variables, data types, control flow, and functions to some problem solving.
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Python is a high-level general purpose that welcomes both newcomers and experienced developers with its user-friendly approach and simplicity, making it accessible for anyone to learn and utilize effectively. It is massively used in various domains like Artificial Intelligence, Data Science, Web Development, Utilities Tools and Scripts and many more.
Easy to Learn and Use: Python has an easy-to-understand syntax that makes it simple to learn and use. Even non-programmers can quickly grasp Python's basic concepts.
Interpreted and Interactive: Python is an interpreted language, which means it executes code line-by-line, making it fast and easy to test and debug. Python also has an interactive mode that allows developers to experiment with code on the fly.
Cross-platform: Python is a cross-platform language, which means it can run on multiple operating systems like Windows, Mac, and Linux.
Open Source: Python is an open-source language, which means its source code is freely available and can be modified and distributed by the community.
Large Standard Library: Python comes with a large standard library that includes built-in modules for various functions like string manipulation, file I/O, and network programming.
Dynamic Typing: Python is dynamically-typed, which means you don't have to declare variable types. A variable's type is determined at runtime based on the value it holds.
Versatile and Robust: Python is versatile and robust, thanks to its ability to integrate with other languages and libraries. It's used in many areas like web development, data science, artificial intelligence, and even game development.
Object-Oriented Programming (OOP) Support: Python supports OOP concepts like encapsulation, inheritance, and polymorphism, making it easier to write reusable and maintainable code.
Web Development: Python frameworks like Django and Flask are widely used for building robust and scalable web applications..
Data Science and Analytics: Libraries like NumPy, Pandas, and scikit-learn provide powerful tools for data manipulation, analysis, and modeling.
Scientific Computing: Python, along with libraries like SciPy and matplotlib, is commonly used in scientific computing. It enables researchers and scientists to perform complex computations, visualize data, and solve scientific problems efficiently.
Automation and Scripting: Python's ease of use and cross-platform compatibility make it a preferred language for automating repetitive tasks, scripting, and system administration. It simplifies tasks such as file manipulation, process automation, and network automation.
Game Development: Python, along with libraries like Pygame, allows developers to create interactive games and multimedia applications.
Internet of Things (IoT): It enables communication with sensors, data collection, and control of IoT devices.
Scripting and Rapid Prototyping: Python's concise syntax and quick development cycles make it an excellent language for scripting and rapid prototyping.
DevOps and Cloud Computing: Python is commonly used in DevOps practices for automating deployment processes, managing infrastructure, and configuring systems. It also has extensive support for cloud computing platforms, such as AWS and Azure.
Natural Language Processing (NLP): Python, along with libraries like NLTK and spaCy, is widely used in NLP applications. It allows developers to process, analyze, and understand human language, enabling tasks like sentiment analysis, text classification, and language generation.
Windows:
Go to the Python Downloads page (https://www.python.org/downloads/windows/)
Download the latest version of Python for Windows
Open the installer and follow the instructions
Make sure to check the option that adds Python to your PATH environment variable
MacOS:
Go to the Python Downloads page (https://www.python.org/downloads/mac-osx/)
Download the appropriate macOS installer for your version of macOS
Double-click the downloaded file and follow the installer instructions
Alternatively, you can install using Homebrew by running brew install python in your terminal
Linux (Ubuntu/Debian):
Open a terminal and run the command sudo apt install python3
This will install the latest version of Python 3.x alongside the required dependencies
Linux (CentOS/Fedora):
Open a terminal and run the command sudo yum install python3 on CentOS or sudo dnf install python3 on Fedora
This will install Python 3.x along with the necessary dependencies
Note: Make sure to check the official documentation for the specific installation instructions for your OS.
print("Hello World")
#The text "Hello Python" once it is executed in the Python shell.