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
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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. 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
Python, a popular and versatile programming language, offers various operators and functions to compare values and objects. Among these are identity operators, specifically the "is" and "is not" operators. These operators enable you to compare objects based on their memory locations, a crucial concept in Python. In this article, we will explore the Identity operator in Python, the id() function, and their practical applications in Python.
Identity operators in Python allow you to determine if two variables or objects reference the same memory location. This concept is essential when working with mutable and immutable data types as it impacts how data is stored and compared in Python.
Let's begin by understanding what Identity operators in Python are and how they function through practical examples.
Identity operators in Python are used to compare the memory addresses of two objects, determining whether two variables or objects reference the same memory location. There are two primary identity operators in Python:
To comprehend the basic functionality of identity operators, let's explore identity operators in Python with an example:
Python
Copy code
x = [1, 2, 3]
y = x
result = x is y
print(result) # Output: True
In this example, both x and y reference the same memory location, leading to a True result.
python code
a = "hello"
b = "world"
result = a is not b
print(result) # Output: True
Here, a and b reference different memory locations, resulting in a True output.
python code
num1 = 10
num2 = 10
result = num1 is num2
print(result) # Output: True
Although the values of num1 and num2 are the same, Python optimizes small integer objects to share the same memory location, leading to a True output.
Example to Understand the Use of id() Function
Before further exploring identity operators, it is essential to understand the id() function, which returns the memory address of an object. This function allows us to visualize how Python manages memory. Let's explore the id() function with three examples:
python code
x = 5
y = x
print(id(x)) # Output: 140732337151648
print(id(y)) # Output: 140732337151648
In this example, both x and y reference the same memory location, as indicated by their identical id() values.
python code for list identity operator in Python
list1 = [1, 2, 3]
list2 = list1
print(id(list1)) # Output: 140732337133888
print(id(list2)) # Output: 140732337133888
Again, list1 and list2 reference the same memory location, demonstrating Python's memory-saving optimization.
python code
a = 10
b = 20
print(id(a)) # Output: 140732337151904
print(id(b)) # Output: 140732337152224
In this case, a and b reference different memory locations because they hold distinct values.
The id() function is a fundamental tool for understanding memory management in Python. It allows you to examine the memory addresses of objects, offering insights into how Python handles memory allocation.
Now that we understand the id() function, let's delve into the types of identity operators in Python.
Python features two types of identity operators in Python: "is" and "is not." Let's explore each of them with practical examples:
The "is" operator checks if two objects refer to the same memory location.
Example 1: Using the "is" Operator
Python
Copy code
x = [1, 2, 3]
y = x
result = x is y
print(result) # Output: True
In this case, both x and y reference the same memory location, resulting in a True output.
The "is not" operator checks if two objects do not refer to the same memory location.
Example 2: Using the "is not" Operator
Python
Copy code
a = "hello"
b = "world"
result = a is not b
print(result) # Output: True
Here, a and b reference different memory locations, leading to a True output.
Identity operator in Python Example 3: Using "is" with Numeric Values
Python
Copy code
num1 = 10
num2 = 10
result = num1 is num2
print(result) # Output: True
Even though the values of num1 and num2 are the same, Python optimizes small integer objects to share the same memory location, resulting in a True output.
These identity operators are fundamental for comparing objects based on their memory addresses, which can be especially useful when working with complex data structures.
Membership operators in Python are closely related to identity operators. They are used to check for the presence of a value within a sequence, such as a list, tuple, or string. The two primary membership operators are:
python code
fruits = ["apple," "banana," "cherry"]
result1 = "banana" in fruits # Output: True
result2 = "orange" in fruits # Output: False
result3 = "mango" in fruits # Output: False
In the membership operators in Python with example, the in operator checks if "banana" is present in the list of fruits, resulting in True. In the subsequent examples, it checks for "orange" and "mango," with False outputs indicating their absence.
python code
languages = ["Python," "Java," "C "]
result1 = "Ruby" not in languages # Output: True
result2 = "Java" not in languages # Output: False
result3 = "C#" not in languages # Output: True
In the example, the not in operator checks if "Ruby" is not present in the list languages, resulting in True. In the subsequent examples, it checks for "Java" and "C#," with False and True outputs, respectively, based on their presence or absence in the list.
Indeed, there is a crucial difference between the equality operator (==) and the identity operator (is) in Python:
Python code
a = [1, 2, 3]
b = [1, 2, 3]
result1 = a == b # Output: True (values are the same)
result2 = a is b # Output: False (memory locations are different)
In this example, result1 is True because the values of a and b are the same. However, result2 is False because the memory locations of a and b are different. This distinction is vital when comparing objects in Python.
The "is" operator is typically used when you specifically want to check if two variables or objects reference the same memory location. It is especially useful in the following scenarios:
Checking for Object Identity: The primary use of the "is" operator is to check whether two variables or objects are the same. This is particularly useful when you want to confirm that two variables are referencing the exact same object in memory.
a = [1, 2, 3]
b = a
if a is b:
print("a and b reference the same object.")
Singletons and Constants: In Python, certain objects like small integers (-5 to 256) and some constants (e.g., None) are implemented as singletons. This means that every variable with the same value will reference the same memory location. The "is" operator is useful for comparing such values.
num1 = 100
num2 = 100
if num1 is num2:
print("num1 and num2 reference the same memory location.")
Mutable Objects: When working with mutable objects like lists, dictionaries, and custom classes, it's crucial to check if two variables reference the same object. The "is" operator ensures you are manipulating the same instance and not creating copies.
list1 = [1, 2, 3]
list2 = list1
if list1 is list2:
print("list1 and list2 reference the same object.")
Object Identity and Identity Verification: In some situations, you may need to verify that two variables indeed refer to the same object, ensuring the integrity of your program's logic.
# Check if two objects are the same user.
user1 = User(name="Alice", age=30)
user2 = user1
if user1 is user2:
print("user1 and user2 represent the same user.")
Identity operators in Python, particularly the "is" and "is not" operators, are pivotal in Python for comparing objects based on their memory locations. They play a vital role in ensuring that developers work with the same objects, especially in scenarios involving mutable data structures and object identity. By using the id() function alongside these operators, you gain deeper insights into Python's memory management and object referencing.
Q1: When should I use the "is" operator instead of "==" in Python?
Use the "is" operator when you want to check if two objects reference the same memory location. Use "==" when you want to compare their values.
Q2: Are identity operators used with all data types in Python?
Identity operators can be used with all data types in Python, as they are designed to compare memory locations, a fundamental concept in the language.
Q3: How do membership operators relate to identity operators in Python?
Membership operators, such as "in" and "not in," are related to identity operators in that they check for the presence of a value within a sequence, like a list or string. While identity operators compare objects based on memory, membership operators test for the inclusion or exclusion of values in data structures.
Q4: In what scenarios is using the "is not" operator more appropriate than "is"?
The "is not" operator is appropriate when you want to confirm that two variables do not reference the same memory location. This can be useful in error-checking and negating certain conditions.
Q5: How do identity operators relate to memory management in Python?
Identity operators are closely related to memory management because they help you track how objects are stored and shared in memory. They are useful for avoiding unnecessary memory consumption.
Q6: Can you use identity operators with custom classes and objects in Python?
Yes, identity operators can be used with custom classes and objects. Whether two objects of a custom class reference the same memory location depends on how the class is defined.
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...