Python – Extract tuples having K digit elements

Last Updated : 30 Apr, 2023

Given a list of tuples, extract all tuples having K digit elements.

Input : test_list = [(54, 2), (34, 55), (222, 23), (12, 45), (78, )], K = 2
Output : [(34, 55), (12, 45), (78,)]
Explanation : All tuples have numbers with 2 digits.

Input : test_list = [(54, 2), (34, 55), (222, 23), (12, 45), (782, )], K = 3
Output : [(782,)]
Explanation : All tuples have numbers with 3 digits.

Method #1 : Using all() + list comprehension

In this, we check for each element being of K digit by converting to string and checking its length. The all() is used to check if all elements are of similar size.

Python3

# Python3 code to demonstrate working of
# Extract K digit Elements Tuples
# Using all() + list comprehension
 
# initializing list
test_list = [(54, 2), (34, 55), (222, 23), (12, 45), (78, )]
 
# printing original list
print("The original list is : " + str(test_list))
 
# initializing K
K = 2
 
# using len() and str() to check length and 
# perform string conversion
res = [sub for sub in test_list if all(len(str(ele)) == K for ele in sub)]
 
# printing result
print("The Extracted tuples : " + str(res))

Output:

The original list is : [(54, 2), (34, 55), (222, 23), (12, 45), (78,)] The Extracted tuples : [(34, 55), (12, 45), (78,)]

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

Method #2 : Using all() + filter() + lambda

This is similar to above method, difference being filter() and lambda is used to solve problem of filtering.

Python3

# Python3 code to demonstrate working of
# Extract K digit Elements Tuples
# Using all() + filter() + lambda
 
# initializing list
test_list = [(54, 2), (34, 55), (222, 23), (12, 45), (78, )]
 
# printing original list
print("The original list is : " + str(test_list))
 
# initializing K
K = 2
 
# filter() and lambda used for task of filtering
res = list(filter(lambda sub: all(len(str(ele)) == K for ele in sub), test_list))
 
# printing result
print("The Extracted tuples : " + str(res))

Output:

The original list is : [(54, 2), (34, 55), (222, 23), (12, 45), (78,)] The Extracted tuples : [(34, 55), (12, 45), (78,)]

Method #3: Using list(),map(),str() and len() methods

Converting each tuple element to string and converting that tuple to list after that iterating over the list finding the length of each element and appending to a new list.If the new list is [K,K] or[K] then the tuples have K digit elements.

Python3

# Python3 code to demonstrate working of
# Extract K digit Elements Tuples
 
# initializing list
test_list = [(54, 2), (34, 55), (222, 23), (12, 45), (78, )]
 
# printing original list
print("The original list is : " + str(test_list))
 
# initialising K
K = 2
 
res=[]
for i in test_list:
    x=list(map(str,i))
    p=[]
    for j in x:
        p.append(len(j))
    if(p==[K,K] or p==[K]):
        res.append(i)
     
# printing result
print("The Extracted tuples : " + str(res))

Output

The original list is : [(54, 2), (34, 55), (222, 23), (12, 45), (78,)]
The Extracted tuples : [(34, 55), (12, 45), (78,)]

Method#4:Using a for loop and string slicing

Algorithm:

Initialize the list of tuples.
Print the original list.
Initialize the value of K to 2.
Initialize an empty list called res to store the extracted tuples.
For each tuple in the list, set the flag to True.
For each element in the tuple, check if the length of the string representation of the element is equal to K. If it’s not, set the flag to False and break out of the loop.
If the flag is still True after checking all elements of the tuple, append the tuple to the res list.
Print the extracted tuples.

Python3

# Python3 code to demonstrate working of 
# Extract K digit Elements Tuples
# Using for loop and string slicing
 
# initializing list
test_list = [(54, 2), (34, 55), (222, 23), (12, 45), (78, )]
 
# printing original list
print("The original list is : " + str(test_list))
 
# initializing K
K = 2
 
# using a for loop and string slicing to check length
res = []
for tup in test_list:
    flag = True
    for ele in tup:
        if len(str(ele)) != K:
            flag = False
            break
    if flag:
        res.append(tup)
 
# printing result
print("The Extracted tuples : " + str(res))
#This code is contributed by Vinay Pinjala.

Output

The original list is : [(54, 2), (34, 55), (222, 23), (12, 45), (78,)]
The Extracted tuples : [(34, 55), (12, 45), (78,)]

Time complexity:
The time complexity of this code is O(n*m), where n is the length of the list of tuples and m is the average length of the tuples. The for loop iterates over each tuple in the list, and then iterates over each element in the tuple to check its length. Since the length of the tuples can vary, we use m to represent the average length of the tuples.

Space complexity:
The space complexity of this code is O(k), where k is the length of the res list. The res list stores the extracted tuples, which can be at most the same length as the original list of tuples.

Method #6: Using a generator expression and tuple unpacking

We can use a generator expression to iterate through the tuples and yield only the tuples that contain K digits elements. We can use tuple unpacking to check the length of each element in the tuple.

Python3

# Python3 code to demonstrate working of
# Extract K digit Elements Tuples
 
# initializing list
test_list = [(54, 2), (34, 55), (222, 23), (12, 45), (78, )]
 
# printing original list
print("The original list is : " + str(test_list))
 
# initialising K
K = 2
 
# Using a generator expression and tuple unpacking
res = tuple(t for t in test_list if all(len(str(e)) == K for e in t))
 
# printing result
print("The Extracted tuples : " + str(res))

Output

The original list is : [(54, 2), (34, 55), (222, 23), (12, 45), (78,)]
The Extracted tuples : ((34, 55), (12, 45), (78,))

Time complexity: O(nk), where n is the length of the list and k is the length of the largest element in the list.
Auxiliary space: O(1), because we are not using any extra data structures to store intermediate results.