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
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
Now Reading
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
Lists are adaptable data structures that enable the storage of a collection of things. They have the capacity to hold complex objects as well as numbers, lines, and other data. What if you wish to determine how many things are in a list, though? It's crucial to know how extensive the list is for this reason. This article will teach us many methods for quickly determining how lengthy a list is. Join us as we quickly uncover the ease of Python's built-in functions and strategies to determine the loop length of list Python, regardless of your programming expertise level.
Python has a sequential data type called lists. This changeable Python length of array-like data structure makes it simple to store a group of objects. The total number of entries in a list, often known as the list length, may be determined using various techniques in Python. This article demonstrates many methods for determining the list length C# in Python.
The easiest technique is to go over the list and count each item individually.
Take a look at this example :
# Initialize a list
my_list = [1, 2, 3, 4, 5]
# Use len() function to get the length of the list
count = len(my_list)
print("Length of the list:", count)
Output:
Length of the list: 5
The Python function "len()" is used to calculate the length of an object that is enclosed in parentheses. Use the 'len()' function instead of the other method since it is quicker and more accurate. Here is an example
# Initialize a list
my_list = [1, 2, 3, 4, 5]
# To determine the list's length, use the len() function.
length = len(my_list)
# The value of 'length' now represents the length of the list
print("Length of the list:", length)
Output:
Length of the list: 5
The len() method accepts a sequence as a parameter and returns the sequence's total number of items. It is the suggested approach since it is both straightforward and effective for determining Python length of string.
This is a lesser-known method for determining list length. This method is specified in the operator class and may also inform the number of entries in the list. Here, we use len() and length_hint() to determine the length of list Java.
# code to demonstrate
# list length
# using len() and length_hint
from operator import length_hint
# Initializing list
test_list = [1, 3, 5, 7, 8]
# Printing test_list
print("The list is : " str(test_list))
# Finding list length
# using len()
list_len = len(test_list)
# Finding list length
# using length_hint()
list_len_hint = length_hint(test_list)
# Printing listlength
print("The length of a list calculated using len() is : " str(list_len))
print("The length of a list calculated using length_hint() is : " str(list_len_hint))
Output :
The list is : [1, 3, 5, 7, 8]
The length of a list calculated using len() is : 5
The length of a list calculated using length_hint() is : 5
To compare the performance of the naive method, the built-in len() function, and the length_hint() function from the collections module, let's analyze each approach in terms of time complexity and conduct some benchmarking.
Naive Method (Iterating Through the List):
Time Complexity: O(n) - Linear time, where n is the number of elements in the list.
Space Complexity: O(1) - Constant space, as it only uses a single integer variable for counting.
Python len() Function:
Time Complexity: O(1) - Constant time. The len() function maintains an internal counter of the list's length, so it can return the length in constant time.
Space Complexity: O(1) - Constant space, as it doesn't use additional memory proportional to the Python size of list in bytes.
Python length_hint() Function:
Time Complexity: O(1) - Constant time. Similar to len(), length_hint() aims to provide an estimate of the length in constant time.
Space Complexity: O(1) - Constant space, as it doesn't use additional memory proportional to the list's size.
Now, let's conduct some benchmarking to compare the actual performance of these methods:
import timeit
from collections.abc import Sequence
# Define a custom list-like object
class MyListLike(Sequence):
def __init__(self, data):
self.data = data
def __getitem__(self, index):
return self.data[index]
def __len__(self):
return len(self.data)
# Create a list with a large number of elements
large_list = list(range(1, 10**6))
custom_list = MyListLike(range(1, 10**6))
# Benchmarking the naive method
naive_time = timeit.timeit(lambda: len(large_list), number=10000)
print("Naive Method Time:", naive_time)
# Benchmarking the Python len() function
len_time = timeit.timeit(lambda: len(large_list), number=10000)
print("Python len() Time:", len_time)
# Benchmarking the Python length_hint() function
length_hint_time = timeit.timeit(lambda: len(large_list), number=10000)
print("Python length_hint() Time:", length_hint_time)
Keep in mind that for this comparison, we are utilizing a big list with one million entries and timing the length-finding process 10,000 times for each technique. Your hardware and system utilization may affect the actual execution times.
We can use iteration within the sum to add one at a time until we have the entire length of the list at the conclusion of the iteration.
# code to demonstrate
# listlength using sum()
# Initializing list
test_list = [1, 4, 5, 7, 8]
# Printing test_list
print("The list is : " str(test_list))
# Finding listlength
# using sum()
list_len = sum(1 for i in test_list)
# Printing listlength
print("The Length of list calculated using len() is : " str(list_len))
print("Length of list calculated using length_hint() is : " str(list_len))
The enumerate() function in Python is typically used to iterate over both the indices and elements of an iterable, such as a list. However, it doesn't directly give you the length of a list. To find the length of list using the enumerate() function, you can iterate through the list and count the elements manually. Here's an example:
# Initialize a list
my_list = [1, 2, 3, 4, 5]
# Initialize a variable to keep track of the count
count = 0
# Use enumerate() to iterate through the list and count the elements
for index, element in enumerate(my_list):
count = 1
# The value of 'count' now represents the length of the list
print("Length of the list:", count)
Output:
Length of the list: 5
If you're searching for a different approach that uses the collections module, you may get a Python 3 length of list using the deque class from that module.
from collections import deque
# Initialize a list
my_list = [1, 2, 3, 4, 5]
# Create a deque from the list
my_deque = deque(my_list)
# Use the len() function to find the length of the deque, which is the same as the list
length = len(my_deque)
# The value of 'length' now represents the length of the list
print("Length of the list:", length)
Output:
Length of the list: 5
In this code, we first create a deque from the list my_list. Then, we use the len() function to find the length of the deque, which is the same as the length of the original list.
While this method works, it's important to note that using collections.deque for the sole purpose of finding the length of a list is less common and less efficient than directly using len(my_list) because it involves creating an additional data structure (deque) unnecessarily. It's generally recommended to use len() directly on the list for simplicity and efficiency.
You can use Python add to list comprehension to find the length of a list indirectly by creating a new list with a specific value for each element in the original list and then using the len() function on the new list. Here's an example:
# Initialize a list
my_list = [1, 2, 3, 4, 5]
# Create a new list with a specific value for each element
new_list = [1 for _ in my_list]
# Use the len() function to find the length of the new list (which is the same as the original list)
length = len(new_list)
# The value of 'length' now represents the length of the list
print("Length of the list:", length)
Output:
Length of the list: 5
You can also find the length of a list using recursion. Here's an example:
def list_length(lst):
# Base case: an empty list has a length of 0
if not lst:
return 0
# Recursive case: the length is 1 plus the length of the rest of the list
else:
return 1 list_length(lst[1:])
# Initialize a list
my_list = [1, 2, 3, 4, 5]
# Find the length of the list using the recursive function
length = list_length(my_list)
# The value of 'length' now represents the length of the list
print("Length of the list:", length)
Output:
Length of the list: 5
In the recursive function list_length, we have a base case that returns 0 when the list is empty. In the recursive case, we add 1 to the length of the rest of the list (which is obtained by slicing the list from the second element onward). This process continues until the list becomes empty, at which point the recursion stops, and the lengths are summed up to give the total length of the original list.
As we get to the end of the article, knowing about several ways enables you to select the one that best fits your unique use case. You should now understand how to use Python to determine the length of any given list after reading this material.
1. How do you determine a list's length?
To determine the total number of elements in a list, tuple, array, dictionary, etc., use the built-in function len().
2. What is the distinction between the list's size and length?
Since ArrayList lacks a length() function, its size() method counts the number of objects in the collection. The length attribute of an array indicates the array's length or capacity. It is the total amount of space allotted at the array's initialization.
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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...