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Python Tutorials - Elevate You…
1. Introduction to Python
2. Features of Python
3. How to install python in windows
4. How to Install Python on macOS
5. Install Python on Linux
6. Hello World Program in Python
7. Python Variables
8. Global Variable in Python
9. Python Keywords and Identifiers
10. Assert Keyword in Python
11. Comments in Python
12. Escape Sequence in Python
13. Print In Python
14. Python-if-else-statement
15. Python for Loop
16. Nested for loop in Python
17. While Loop in Python
18. Python’s do-while Loop
19. Break in Python
20. Break Pass and Continue Statement in Python
21. Python Try Except
22. Data Types in Python
23. Float in Python
24. String Methods Python
25. List in Python
26. List Methods in Python
27. Tuples in Python
28. Dictionary in Python
29. Set in Python
30. Operators in Python
31. Boolean Operators in Python
32. Arithmetic Operators in Python
33. Assignment Operator in Python
34. Bitwise operators in Python
35. Identity Operator in Python
36. Operator Precedence in Python
37. Functions in Python
38. Lambda and Anonymous Function in Python
39. Range Function in Python
40. len() Function in Python
41. How to Use Lambda Functions in Python?
42. Random Function in Python
43. Python __init__() Function
44. String Split function in Python
45. Round function in Python
46. Find Function in Python
47. How to Call a Function in Python?
48. Python Functions Scope
49. Method Overloading in Python
50. Method Overriding in Python
51. Static Method in Python
52. Python List Index Method
53. Python Modules
54. Math Module in Python
55. Module and Package in Python
56. OS module in Python
57. Python Packages
58. OOPs Concepts in Python
59. Class in Python
60. Abstract Class in Python
61. Object in Python
62. Constructor in Python
63. Inheritance in Python
64. Multiple Inheritance in Python
65. Encapsulation in Python
66. Data Abstraction in Python
67. Opening and closing files in Python
68. How to open JSON file in Python
69. Read CSV Files in Python
70. How to Read a File in Python
71. How to Open a File in Python?
72. Python Write to File
73. JSON Python
74. Python JSON – How to Convert a String to JSON
75. Python JSON Encoding and Decoding
76. Exception Handling in Python
77. Recursion in Python
78. Python Decorators
79. Python Threading
80. Multithreading in Python
81. Multiprocеssing in Python
82. Python Regular Expressions
83. Enumerate() in Python
84. Map in Python
85. Filter in Python
86. Eval in Python
87. Difference Between List, Tuple, Set, and Dictionary in Python
88. List to String in Python
89. Linked List in Python
90. Length of list in Python
91. Python List remove() Method
92. How to Add Elements in a List in Python
93. How to Reverse a List in Python?
94. Difference Between List and Tuple in Python
95. List Slicing in Python
96. Sort in Python
97. Merge Sort in Python
98. Selection Sort in Python
99. Sort Array in Python
100. Sort Dictionary by Value in Python
101. Datetime Python
102. Random Number in Python
103. 2D Array in Python
104. Abs in Python
105. Advantages of Python
106. Anagram Program in Python
107. Append in Python
108. Applications of Python
109. Armstrong Number in Python
110. Assert in Python
111. Binary Search in Python
112. Binary to Decimal in Python
113. Bool in Python
114. Calculator Program in Python
115. chr in Python
116. Control Flow Statements in Python
117. Convert String to Datetime Python
118. Count in python
119. Counter in Python
120. Data Visualization in Python
121. Datetime in Python
122. Extend in Python
123. F-string in Python
124. Fibonacci Series in Python
125. Format in Python
126. GCD of Two Numbers in Python
127. How to Become a Python Developer
128. How to Run Python Program
129. In Which Year Was the Python Language Developed?
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130. Indentation in Python
131. Index in Python
132. Interface in Python
133. Is Python Case Sensitive?
134. Isalpha in Python
135. Isinstance() in Python
136. Iterator in Python
137. Join in Python
138. Leap Year Program in Python
139. Lexicographical Order in Python
140. Literals in Python
141. Matplotlib
142. Matrix Multiplication in Python
143. Memory Management in Python
144. Modulus in Python
145. Mutable and Immutable in Python
146. Namespace and Scope in Python
147. OpenCV Python
148. Operator Overloading in Python
149. ord in Python
150. Palindrome in Python
151. Pass in Python
152. Pattern Program in Python
153. Perfect Number in Python
154. Permutation and Combination in Python
155. Prime Number Program in Python
156. Python Arrays
157. Python Automation Projects Ideas
158. Python Frameworks
159. Python Graphical User Interface GUI
160. Python IDE
161. Python input and output
162. Python Installation on Windows
163. Python Object-Oriented Programming
164. Python PIP
165. Python Seaborn
166. Python Slicing
167. type() function in Python
168. Queue in Python
169. Replace in Python
170. Reverse a Number in Python
171. Reverse a string in Python
172. Reverse String in Python
173. Stack in Python
174. scikit-learn
175. Selenium with Python
176. Self in Python
177. Sleep in Python
178. Speech Recognition in Python
179. Split in Python
180. Square Root in Python
181. String Comparison in Python
182. String Formatting in Python
183. String Slicing in Python
184. Strip in Python
185. Subprocess in Python
186. Substring in Python
187. Sum of Digits of a Number in Python
188. Sum of n Natural Numbers in Python
189. Sum of Prime Numbers in Python
190. Switch Case in Python
191. Python Program to Transpose a Matrix
192. Type Casting in Python
193. What are Lists in Python?
194. Ways to Define a Block of Code
195. What is Pygame
196. Why Python is Interpreted Language?
197. XOR in Python
198. Yield in Python
199. Zip in Python
Python has a long history that dates back to the late 1980s and has grown to be a standard in the field of software development. We shall examine the beginnings, development, and relevance of Python in this extensive manual. Let's go back in time to learn how Python developed into the force it is today. Guido van Rossum developed Python and originally made it available on February 20, 1991. The Python programming language takes its name from Monty Python's Flying Circus television comedy sketch series, even if you may only think of the Python as a huge snake.
A Dutch programmer named Guido van Rossum created Python in the late 1980s. In December 1989, Guido began developing Python, and in February 1991, Python 0.9.0, the first official version, was made available. The language's emphasis on code readability and simplicity makes it simple enough for beginners to learn while still being robust enough for experts.
Python is an interpreted, general-purpose programming language. Due to its readability and simplicity, it is one of the most often-used programming languages in the world. It is used for web development, scientific computing, artificial intelligence, data analysis, and other things. Its popularity may be linked to several important qualities and benefits that make it the top option for programmers all over the world.
Listed below are the different and important features of Python and the reasons why it is best for programmers.
The simplicity of Python is what makes it so appealing. Python is a great language for beginners because of its simple, readable syntax. The focus on readability enables programmers to properly communicate their thoughts and notions, cutting down on program maintenance expenses and development time. One of Python's most noteworthy benefits is its code readability, which frees developers to concentrate on solving problems rather than trying to understand complicated terminology.
Python's versatility is unparalleled. It is a general-purpose language, meaning it can be used for a wide range of applications. From web development and scientific computing to artificial intelligence, data analysis, and automation, Python is ubiquitous. The language's adaptability is evident in its ability to seamlessly integrate with other languages and technologies, allowing developers to leverage existing code and libraries, regardless of the programming language they were written in.
Python has a sizable standard library that covers everything from networking and web development to file I/O and regular expressions. This extensive library of modules and packages makes difficult jobs simple, enabling programmers to build reliable applications without having to reinvent the wheel. The development process is sped up by the availability of these pre-built modules, which frees up programmers to concentrate on addressing particular problems rather than writing boilerplate code.
Python's community is one of its most valuable assets. The global community of Python developers is incredibly active, contributing to an ever-expanding ecosystem of libraries, frameworks, and tools. This active collaboration ensures that Python remains at the forefront of technological advancements. The community-driven nature of Python's development means that developers can readily find support, documentation, and resources, fostering a collaborative and supportive learning environment.
Python is cross-platform compatible, meaning that Python code can be executed without modification on various operating systems, including Windows, macOS, and Linux. This platform independence makes software deployment and maintenance simpler and frees developers from worrying about compatibility when building apps that may be used by a large user base.
Python supports object-oriented programming (OOP) paradigms since it is an object-oriented language. Through the use of objects, OOP improves the efficiency, modularity, and reuse of code. Python is also a high-level language that abstracts away low-level aspects like memory management and hardware connections, enabling developers to concentrate on finding solutions to issues at a higher degree of abstraction.
Python is a great quick prototyping and development option because it is simple and user-friendly. Developers can test code quickly, iterate over concepts, and produce working prototypes quickly, thanks to its dynamic typing and interpreted nature. This rate of development is especially beneficial in fast-moving fields where time-to-market is essential.
Python's simplicity and adaptability attracted developers in the early 1990s, which led to its steady adoption across numerous industries. During this time, Python discovered its place in web development, automation, and scripting. Programmers who preferred to concentrate on solving issues rather than wrangling with complicated code found it to be an appealing option thanks to its simplicity and accessible syntax.
One of the defining aspects of Python's history is its vibrant community. The open-source nature of Python allowed developers worldwide to collaborate, contributing to its growth. Python enthusiasts created a plethora of libraries and frameworks, expanding the language's capabilities exponentially. The emergence of frameworks like Django for web development and NumPy for scientific computing further solidified Python's position in different domains.
Python 2. x and Python 3. x versions coexisted for several years, resulting in a distinctive period in Python's history. Although Python 2 was extensively used, the development community urged a switch to Python 3 because of its improved features. Although it happened gradually, this transition signaled a substantial change in the Python ecosystem as developers gradually migrated their projects to Python 3.
In the 2010s, Python saw a remarkable surge in popularity, especially in the fields of data science and artificial intelligence. Libraries like pandas, NumPy, and sci-kit-learn became fundamental tools for data analysis and machine learning. Python’s readability and the availability of powerful libraries made it the preferred language for researchers, data scientists, and AI engineers, cementing its position as the leading language in these domains.
Python’s simplicity and ease of learning also led to its widespread adoption in educational institutions. Python became widely used in academic institutions' curricula to introduce students to programming principles in an approachable fashion. This emphasis on education helped Python become more well-known and guaranteed that the Python community would always receive fresh developers.
In recent years, Python's global impact has been profound. It has become the backbone of numerous web applications, data analysis projects, artificial intelligence systems, and scientific research endeavors. Companies like Google, Facebook, Instagram, and NASA utilize Python for various purposes, highlighting its versatility and scalability.
Besides its technical applications, Python has also been instrumental in humanitarian efforts. During the COVID-19 pandemic, Python played a significant role in data analysis, modeling, and simulation for understanding the virus’s spread. Its application in tracking and predicting the pandemic showcased the real-world impact of Python in addressing global challenges.
The word "Python" is used to describe more than just the programming language. It has a distinct history. Monty Python was a favorite comedy troupe of Guido van Rossum. He wanted a name for Python that was brief, distinctive, and a little mysterious. So, in celebration of Monty Python's Flying Circus, he decided on the name "Python."
Guido van Rossum was reading the published scripts from the 1970s BBC comedy series "Monty Python's Flying Circus" when he started using Python. Van Rossum chose the name Python for the language because he felt it needed to be short, distinct, and a little mysterious.
Python has undergone various updates and improvements over the years. Here's a list of some key versions:
Python 3.7.3 introduced several new features and optimizations, including:
Python's future is bright and promising. With its vast ecosystem, active community, and adaptability, Python continues to evolve. Some trends and developments to watch out for in the future include:
Python's rise from its modest origins to its present position as a programming powerhouse is a testament to its ease of use, readability, and adaptability. Python is likely to continue to be a cornerstone of innovation and development as technology develops. The history of Python serves as both a record of its evolution and a case study of the programming community's culture of cooperation. Its development from a side project to a widely used language is evidence of its readability, simplicity, and adaptability. As technology develops, Python stays at the cutting edge, enabling programmers throughout the world to create new ideas, find solutions to issues, and influence the direction of computers.
Q1: In which year was the Python 3.0 version developed?
Python 3.0 was released in December 2008, marking a significant milestone in the language's evolution. Python 3.0 final was released on December 3rd, 2008. Python 3.0 (a.k.a. "Python 3000" or "Py3k") is a new version of the language that is incompatible with the 2. x line of releases.
Q2: What are the advantages of Python?
Python offers several advantages: easy readability, extensive libraries, versatility, and a strong community support system.
Advantages:
Q3: Who developed Python in the year 1989?
Python was conceived in the late 1980s. Its implementation was started in December 1989 by Guido van Rossum at CWI in the Netherlands as a successor to ABC, capable of exception handling and interfacing with the Amoeba operating system.
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