Summary
Python will be a general-purpose programming language with many excellent features, such as being easy to learn, easy to write readable code, and usable for a wide range of applications Python was developed by Guido van Rossum in 1991.
As a relatively new language, Python can utilize a variety of effective programming techniques, including object-oriented programming, procedural programming, and functional programming. It is also widely used in web applications, desktop applications, scientific and technical computing, machine learning, artificial intelligence, and other fields because of the many libraries and frameworks available. Furthermore, it is cross-platform and runs on many operating systems such as Windows, Mac, and Linux, etc. Because Python is an interpreted language, it does not require compilation and has a REPL-like structure, which speeds up the development cycle.
This section describes the implementation of various algorithms using Python based on the “Textbook of Algorithms in Python: Acquire Lifelong Knowledge and Skills”.
In this issue, I will discuss those reading notes.
A Textbook of Algorithms in Python
This book covers the basics of Python programming and building basic algorithms, as shown in the table of contents below.
I think it is better to find and copy the main code for each purpose from the web, but I think it is suitable as reference information for writing algorithms and codes when modifying them.
Chapter 1 Programming Basics Lesson1-1 Input and Output Lesson1-2 Variables Lesson1-3 Conditional Branching Lesson1-4 Repetition Lesson1-5 Functions Lesson1-6 Arrays Chapter 2 Developing Programming Skills Lesson2-1 Finding the Average Lesson2-2 Adding 1 to n Lesson2-3 Calculating the Ninety-Nine Formula Lesson2-4 Finding Prime Numbers Lesson2-5 Finding the Factorial of n (n!) Chapter 3 Learning Data Structures Lesson3-1 Stacks Lesson3-2 Queues Lesson3-3 Lists Lesson3-4 Trees Lesson3-5 Graphs Etra Lesson3-1 Working with Stacks and Queues Etra Lesson3-2 Saving Data Chapter 4 Searching Lesson4-1 Linear Search Lesson4-2 Binary Trees Lesson4-3 Tree Search Lesson4-4 Calculators Learn about Etra Lesson4-1 Landau's Symbols Etra Lesson4-2 Guess the Number Game Etra Lesson4-3 Learn Bitwise Operations Chapter 5 Sorting Lesson5-1 Sorting Lesson5-2 Selective Sorting Lesson5-3 Bubble Sorting Lesson5-4 Insertion Sort Lesson5-5 Quick Sort Lesson5-6 Merge Sort Lesson5-7 Heap Sort Etra Lesson5-1 Outputting the Regression Process of Quick Sort Etra Lesson5-2 Merge Sort Using the Recursive Function Etra Lesson5-3 Python's Sort Instructions and Using the heapq Module Etra Lesson5-4 Amount of Calculation and Calculation Time for Sorting Chapter 6 Hashing Lesson6-1 What is Hashing Lesson6-2 Hash Functions Lesson6-3 Hash Tables Lesson6-4 Avoiding Collisions Etra Lesson6-1 Cryptography Chapter 7 Hash Functions Lesson7-1 Euclidean Reciprocity Lesson7-2 String Search Lesson7-3 Shortest Path Problem Etra Lesson7-1 Hints for Understanding Algorithms Chapter 8 Visualizing Algorithms Lesson 8-1 Drawing the curve of an nth-order function Lesson8-2 Drawing fractals Lesson8-3 Drawing the process of solving a maze Etra Lesson8-1 Using different algorithms Etra Lesson8-2 Drawing the Mandelbrot set Appendix 1 How to install Python Appendix 2 Text Editor and Integrated Development Environment Appendix 3 Python Writing Rules
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