Tutorial Playlist
200 Lessons1. 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
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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. Reverse a List in Python
92. Python List remove() Method
93. How to Add Elements in a List in Python
94. How to Reverse a List in Python?
95. Difference Between List and Tuple in Python
96. List Slicing in Python
97. Sort in Python
98. Merge Sort in Python
99. Selection Sort in Python
100. Sort Array in Python
101. Sort Dictionary by Value in Python
102. Datetime Python
103. Random Number in Python
104. 2D Array in Python
105. Abs in Python
106. Advantages of Python
107. Anagram Program in Python
108. Append in Python
109. Applications of Python
110. Armstrong Number in Python
111. Assert in Python
112. Binary Search in Python
113. Binary to Decimal in Python
114. Bool in Python
115. Calculator Program in Python
116. chr in Python
117. Control Flow Statements in Python
118. Convert String to Datetime Python
119. Count in python
120. Counter in Python
121. Data Visualization in Python
122. Datetime in Python
123. Extend in Python
124. F-string in Python
125. Fibonacci Series in Python
126. Format in Python
127. GCD of Two Numbers in Python
128. How to Become a Python Developer
129. How to Run Python Program
130. In Which Year Was the Python Language Developed?
131. Indentation in Python
132. Index in Python
133. Interface in Python
134. Is Python Case Sensitive?
135. Isalpha in Python
136. Isinstance() in Python
137. Iterator in Python
138. Join in Python
139. Leap Year Program in Python
140. Lexicographical Order in Python
141. Literals in Python
142. Matplotlib
143. Matrix Multiplication in Python
144. Memory Management in Python
145. Modulus in Python
146. Mutable and Immutable in Python
147. Namespace and Scope in Python
148. OpenCV Python
149. Operator Overloading in Python
150. ord in Python
151. Palindrome in Python
152. Pass in Python
153. Pattern Program in Python
154. Perfect Number in Python
155. Permutation and Combination in Python
156. Prime Number Program in Python
157. Python Arrays
158. Python Automation Projects Ideas
159. Python Frameworks
160. Python Graphical User Interface GUI
161. Python IDE
162. Python input and output
163. Python Installation on Windows
164. Python Object-Oriented Programming
165. Python PIP
166. Python Seaborn
167. Python Slicing
168. type() function in Python
169. Queue in Python
170. Replace in Python
171. Reverse a Number in Python
172. Reverse a string in Python
173. Reverse String in Python
174. Stack in Python
175. scikit-learn
176. Selenium with Python
177. Self in Python
178. Sleep in Python
179. Speech Recognition in Python
180. Split in Python
181. Square Root in Python
182. String Comparison in Python
183. String Formatting in Python
184. String Slicing in Python
185. Strip in Python
186. Subprocess in Python
187. Substring in Python
188. Sum of Digits of a Number in Python
189. Sum of n Natural Numbers in Python
190. Sum of Prime Numbers in Python
191. Switch Case in Python
192. Python Program to Transpose a Matrix
193. Type Casting in Python
194. What are Lists in Python?
195. Ways to Define a Block of Code
196. What is Pygame
197. Why Python is Interpreted Language?
198. XOR in Python
199. Yield in Python
200. Zip in Python
Object-oriented programming is used in Python for representing and working with data in the form of various classes and objects. The fundamental idea of OOPs in Python is to unite various functions and data and use them in such a manner that no other portion of the program can gain access to this particular data. OOPs concepts in Python include polymorphism, inheritance, data encapsulation, data abstraction, and so on.
In this tutorial, we dive deep into the study of OOPs concepts in Python. This comprehensive guide serves as a necessary arsenal for Python fans looking to advance their skill set, covering everything from comprehending their fundamental nature to the use of object-oriented programming in Python. This tutorial will help you to grasp the utility of OOP in Python.
OOPs concepts in Python act as the fundamental building blocks for developing reusable codes in various programming languages. Integral to fostering efficient and clean coding, they provide a mechanism to reduce data redundancy to create and store error-free codes. The data are encapsulated within smaller objects to ensure code is not just readable but also reusable. In this comprehensive tutorial, we’ll cover OOPs concepts in Python along with its advantages, disadvantages, and a lot more.
Object-oriented programming is a popular approach to working with programming languages that exhibit data in the form of objects. This is a very common approach and is used in various programming languages including Python. OOP in Python helps to develop error-free codes that you can use multiple times which makes it reusable in nature. In this way, object-oriented programming helps to avoid redundancy of work.
Object-oriented programming is mainly classified into multiple mini-programs or self-contained objects. You can view each of the objects separately that contain distinct features and data and are used for better communication among various programmers. OOP follows a button-up approach and provides the feature of inheritance.
You may use object-oriented programming in Python as it is an efficient technique for working with various different types of codes. It is an effective way of programming that makes the codes easy to understand. Also, it offers reusability of course as they are contained in shareable classes or objects. Its attributes like data abstraction and polymorphism keep the data safe and also protect data from unauthorized users. Polymorphism allows you to share the same interface for various objects so that you can write efficient programs that will be preserved.
There is a diverse range of applications of object-oriented programming which are enumerated as follows:
OOP is applied in client-server systems so that clients can communicate with each other through a common interface. It has a centralized server for communication and to request access to various resources. the client-server processes the request and generates a response accordingly. OOP enhances code reusability, maintainability, and modularity for building software components through client-server systems.
Hypertext is a form of text that connects people from one text to another. It has the feature of cross-referencing that works in a multi-sequential and non-linear way. Hypermedia is a broader category when compared to hypertext. Hypertext and hypermedia frameworks can be developed with the help of object-oriented programming.
In order to retain the integrity and identity of an object, op databases are used to build a close correlation between the physical counterparts of objects and the various databases.
Neural networks can be defined as a collection of multiple algorithms that work to identify the true sense of data using various procedures that work like a human brain. OOP is applied in parallel programming where a big issue is divided into smaller subproblems that can be looked up to and dealt with separately without messing with the other counterparts. In this way, object-oriented programming helps to streamline the problem-solving procedure and enhances the procedure of prediction and approximation.
Modeling complex systems is a difficult task as the specification of the variables is different and not universal. The complex system stimulation requires precise modeling and a grave understanding of the interactions. OOP has to simplify complex structures with useful approaches.
The AI expert systems provide solutions for complex programming issues and address a range of technical problems that become very difficult for the human brain to process. The features of OOP assist in creating AI expert systems that offer high performance, increased responsiveness, dependability, and understandability.
Computer-aided design (CAD) software uses object-oriented programming to build classes of diverse design components such as solids, curves, lines, points, surfaces, etc. These designs also incorporate various methods and attributes to develop relationships between various design elements.
OOP is used by office automation systems to build high-performing and reusable programming components. It develops various documentation tasks with the help of efficient management and work collaboration. The automation duties are enhanced with the help of object-oriented programming.
Object-oriented programming is all about the concepts of objects and how data is classified and represented with the help of objects.
Take a glimpse of the various advantages of using object Oriented programming in Python:
Object-oriented programming in Python is a very popular concept but it also comes with certain limitations that are enumerated as follows:
In summary, OOPs concepts in Python are a programming paradigm that deals with the concepts of objects. We have seen that object-oriented programming possesses the ability to reusability of codes, making data more secure and efficient to use at a later time. It incorporates numerous real-life aspects such as inheritance and abstraction. In the end, having a solid understanding of OOP functions allows for more efficient, modular programming, which ensures Python's appeal and usefulness across a range of applications.
We at upGrad offer upskilling courses that can assist you at the beginning of your career as a Python developer.
1. What are the four fundamental pillars of Python?
OOP concepts in Python are based on 4 major pillars that are inheritance, polymorphism, abstraction, and encapsulation. Without these, programmers cannot work on Python.
2. What is class and object in Python?
OOP works on the basis of classes and objects in Python. An object is known as a collection of data. There can be many classes as data can be divided and put in multiple objects. A class is a blueprint of those objects. The user develops a class in a certain way that specifies what kind of objects it will contain.
3. How do OOP concepts in Java work?
The function of OOP concepts in Java is similar to that of their function in Python. However, the code that is written in Java is different from that of Python but the concepts remain the same. OOP concepts in Java include inheritance polymorphism abstraction and encapsulation.
PAVAN VADAPALLI
Director of Engineering
Director of Engineering @ upGrad. Motivated to leverage technology to solve problems. Seasoned leader for startups and fast moving orgs. Working …Read More
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upGrad does not grant credit; credits are granted, accepted or transferred at the sole discretion of the relevant educational institution offering the diploma or degree. We advise you to enquire further regarding the suitability of this program for your academic, professional requirements and job prospects before enr...