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Python | Check if tuple and list are identical

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Sometimes while working with different data in Python, we can have a problem of having data in different containers. In this situations, there can be need to test if data is identical cross containers. Let’s discuss certain ways in which this task can be performed. 

Method #1 : Using loop This is the brute force method to perform this particular task. In this, we just iterate for list and tuple to test if at each index the elements are similar. 

Python3

# Python3 code to demonstrate working of
# Check if tuple and list are identical
# Using loop
 
# Initializing list and tuple
test_list = ['gfg', 'is', 'best']
test_tup = ('gfg', 'is', 'best')
 
# printing original list and tuple
print("The original list is : " + str(test_list))
print("The original tuple is : " + str(test_tup))
 
# Check if tuple and list are identical
# Using loop
res = True
for i in range(0, len(test_list)):
    if(test_list[i] != test_tup[i]):
        res = False
        break
 
# printing result
print("Are tuple and list identical ? : " + str(res))

                    
Output : 
The original list is : ['gfg', 'is', 'best']
The original tuple is : ('gfg', 'is', 'best')
Are tuple and list identical ? : True

Time Complexity: O(n*n) where n is the number of elements in the list “test_list”. loop performs n*n number of operations.
Auxiliary Space: O(n), extra space is required where n is the number of elements in the list

  Method #2 : Using all() + zip() This task can also be performed in a single line using combination of above functions. In this, we just combine the container elements using zip(), and use all() to test for equality of elements at corresponding index. 

Python3

# Python3 code to demonstrate working of
# Check if tuple and list are identical
# Using all() + zip()
 
# Initializing list and tuple
test_list = ['gfg', 'is', 'best']
test_tup = ('gfg', 'is', 'best')
 
# printing original list and tuple
print("The original list is : " + str(test_list))
print("The original tuple is : " + str(test_tup))
 
# Check if tuple and list are identical
# Using all() + zip()
res = all( [i == j for i, j in zip(test_list, test_tup)] )
 
# printing result
print("Are tuple and list identical ? : " + str(res))

                    
Output : 
The original list is : ['gfg', 'is', 'best']
The original tuple is : ('gfg', 'is', 'best')
Are tuple and list identical ? : True

Time Complexity: O(n*n), where n is the length of the list test_list 
Auxiliary Space: O(n) additional space of size n is created where n is the number of elements in the res list 

Method #3: Using list() method

Python3

# Python3 code to demonstrate working of
# Check if tuple and list are identical
 
# Initializing list and tuple
test_list = ['gfg', 'is', 'best']
test_tup = ('gfg', 'is', 'best')
 
# printing original list and tuple
print("The original list is : " + str(test_list))
print("The original tuple is : " + str(test_tup))
res=False
# Check if tuple and list are identical
x=list(test_tup)
if(test_list==x):
    res=True
# printing result
print("Are tuple and list identical ? : " + str(res))

                    

Output
The original list is : ['gfg', 'is', 'best']
The original tuple is : ('gfg', 'is', 'best')
Are tuple and list identical ? : True

Method#4: using tuple() method

Python3

# Initializing list and tuple
test_list = ['gfg', 'is', 'best']
test_tup = ('gfg', 'is', 'best')
 
# printing original list and tuple
print("The original list is : " + str(test_list))
print("The original tuple is : " + str(test_tup))
 
# Check if tuple and list are identical
res = tuple(test_list) == test_tup
 
# printing result
print("Are tuple and list identical ? : " + str(res))
#This code is contributed Vinay Pinjala.

                    

Output
The original list is : ['gfg', 'is', 'best']
The original tuple is : ('gfg', 'is', 'best')
Are tuple and list identical ? : True

Time Complexity: O(n)

Auxiliary Space: O(n)

Method#5: using all() and lambda function :

This code checks whether a list and a tuple are identical in Python. It does so by first initializing a list and a tuple with the same values, and then using the all() function and a lambda function with the zip() function to compare the elements of the two sequences. The zip() function takes two or more iterables and returns an iterator of tuples that aggregates their elements. The lambda function checks if the elements in each corresponding tuple are equal, and the all() function returns True if all elements in the resulting sequence are True.

In essence, this code uses built-in Python functions to compare a list and a tuple element-wise and determine if they have the same values in the same order. If all elements are equal, the code outputs True. Otherwise, it outputs False.

Python3

# Python code to demonstrate checking if tuple and list are identical
# Using all() and lambda function
# Initializing list and tuple
test_list = ['gfg', 'is', 'best']
test_tup = ('gfg', 'is', 'best')
# printing original list and tuple
print("The original list is : " + str(test_list))
print("The original tuple is : " + str(test_tup))
# Check if tuple and list are identical
# Using all() and lambda function with zip function
res = all(map(lambda pair: pair[0] == pair[1], zip(test_list, test_tup)))
# printing result
print("Are tuple and list identical? : " + str(res))
#This code is contributed by Jyothi pinjala.

                    

Output
The original list is : ['gfg', 'is', 'best']
The original tuple is : ('gfg', 'is', 'best')
Are tuple and list identical? : True

# Time complexity: O(n), where n is the length of the shortest sequence (list or tuple) because all() and zip() functions take linear time to process the inputs.
# Auxiliary Space: O(1) because no extra space is used, only temporary variables are created inside the  lambda function.

Method#5: Using numpy:

Algorithm:

  1. Create a NumPy array from the given list and tuple.
  2. Compare the NumPy array of the list with the NumPy array of the tuple using the np.array_equal() method.
  3. If the arrays are equal, print “Are tuple and list identical? : True”, else print “Are tuple and list identical? : False”.

Python3

import numpy as np
 
# Initializing list and tuple
test_list = ['gfg', 'is', 'best']
test_tup = ('gfg', 'is', 'best')
 
# Convert list to NumPy array
list_arr = np.array(test_list)
 
# Convert tuple to NumPy array
tup_arr = np.array(test_tup)
 
# Check if NumPy arrays are equal
res = np.array_equal(list_arr, tup_arr)
 
# printing original list and tuple
print("The original list is : " + str(test_list))
print("The original tuple is : " + str(test_tup))
 
# Print the result
print("Are tuple and list identical? :", res)

                    

Output:

The original list is : ['gfg', 'is', 'best']
The original tuple is : ('gfg', 'is', 'best')
Are tuple and list identical? : True

Time Complexity:
The time complexity  is O(n), where n is the number of elements in the input list or tuple. Creating the NumPy arrays, comparing them, and printing the output all take constant time for this particular use case.

Space Complexity:
The space complexity  is O(n), where n is the number of elements in the input list or tuple. This is because we create a NumPy array from the input list and tuple, which requires additional memory to store. However, this additional memory usage is negligible for small inputs.



Last Updated : 04 May, 2023
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