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Python Programming
  • Python Programming
  • Installation and Setup
  • Part 1: Basics
    • Variables
      • Primitive Data Types
      • Secondary Data Types
    • Control Flow and Loop
    • Functions
    • Error Handling
    • Decorators
    • Constructor
    • Built-in Functions and Modules
    • Pythonic Code
    • Miscellaneous Functionalities
    • Understanding Checkpoint I
    • Python Problem Practice I
      • Solutions
  • Part 2: Level Up
    • Real Life Application I
    • Real Life Application II
    • OOP Concepts
    • Creating Library
    • Real Life Application III
  • Processing Related
    • Parallel Processing
    • Oreilly - High Performance Python
    • Memory Management
      • Memory Leak
      • String
      • Array
      • Dictionary
    • Ubuntu CPU and RAM
    • Time and Space Complexity
  • Data Structure
    • Data Structure Overview
    • Array
    • Stack
    • Queue
    • LinkedList
    • Hash-table and Hash-map
    • Recursion
    • Binary Tree
    • Heap Data Structure
    • Graphs
      • Python Graph Visualisation
    • Dynamic Programming
    • Problem Solving Techniques
    • Additional topics
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Python Programming

NextInstallation and Setup

Last updated 1 year ago

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  • About Different Sections
  • References for Python Basics
  • Quick Points About Python

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Every programming language essentially has two parts to it: Syntactic and Algorithms or in simple words, programming languages are instructions to the computer, how we give instructions is defined by syntactic part, and what are all the instructions, the logical part can be put in the category of algorithm part.

Only Syntactic parts vary, in general, from one programming language to other, at least from the implementation point of view. The algorithmic part almost remains the same for any programming language (at least for all object-oriented programming languages)

About Different Sections

Prior knowledge of computer science terminology is expected, or if you have worked on any of the programming languages then it would be the best. Here, the focus is not to explain the basic and nitty-gritty, but to explain all concepts through real-life applications.

Use cases that have value, or tangible aspects of coding helps more in the learning process, at least in my opinion. Therefore, this series has been created keeping in view, how should one proceed step by step to develop a full-scale website, just based on Python Programming Language.

If you don't understand or find it difficult to understand the use cases, better to go through few quick python courses, as mentioned in the next reference section

I will be referring to System Design (still updating, you can see the outline at least) for practical use cases whenever required

If there is anything particular you would like to discuss or understand, feel free to contact:

Ankit Choudhary | ankit.apdc@gmail.com | Linkedin

References for Python Basics

If don't have exposure to any programming language, then better to go through some well-organized content from the theory point of view.

Mosh Hamedani 6.25 hours long tutorial

freeCodeCamp.org 4.5 hours long Youtube Lecture

Edureka: 12 hours Youtube Video

Programiz is good for a quick recap

Quick Points About Python

Many well-known firms are now using Python in their technology stacks

  • Instagram. Instagram, the world's biggest online photo-sharing app, uses Python on its backend.

  • Google. Google is the most widely used search engine in the world with over 75% of the market share.

  • Spotify, Netflix, Uber, Dropbox, Pinterest

  • Python is completely object oriented, and not “statically typed” (search difference between object oriented and functional programming, it's ok if you don't know the difference)

  • No not need to declare variables before using them, or declare their type

  • Every variable in Python is an object

  • Indentation is required, no need to add line ending symbol (Example ; in Javascript etc)

  • Python 2.x and 3.x are available, I would recommend to use python version > 3 (try above 3.6)

  • Creating virtual environment and working in that virtual environment is the best (if not working in a container, if not already aware with Docker and would like to read: )

  • Python is an interpreted language. Meaning, unlike languages like C and its variants, Python does not need to be compiled before it is run. Other interpreted languages include PHP and Ruby.

here is the link