Python Program to Convert a list of multiple integers into a single integer
Given a list of integers, write a Python program to convert the given list into a single integer. Examples:
Input : [1, 2, 3] Output : 123 Input : [55, 32, 890] Output : 5532890
There are multiple approaches possible to convert the given list into a single integer. Let’s see each one by one. Approach #1 : Naive Method Simply iterate each element in the list and print them without space in between.
Python3
# Python3 program to convert a list # of integers into a single integer # creating a list lst = [ 12 , 15 , 17 ] # iterating each element for i in lst: print (i, end = "") |
Output:
121517
Approach #2 : Using join() Use the join() method of Python. First convert the list of integer into a list of strings( as join() works with strings only). Then, simply join them using join() method. It takes a time complexity of O(n).
Python3
# Python3 program to convert a list # of integers into a single integer def convert( list ): # Converting integer list to string list s = [ str (i) for i in list ] # Join list items using join() res = int ("".join(s)) return (res) # Driver code list = [ 1 , 2 , 3 ] print (convert( list )) |
Output:
123
Approach #3 : Using map() Another approach to convert a list of multiple integers into a single integer is to use map() function of Python with str function to convert the Integer list to string list. After this, join them on the empty string and then cast back to integer.
Python3
# Python3 program to convert a list # of integers into a single integer def convert( list ): # Converting integer list to string list # and joining the list using join() res = int ("".join( map ( str , list ))) return res # Driver code list = [ 1 , 2 , 3 ] print (convert( list )) |
Output:
123
Approach #4 : Multiplying by corresponding power of 10 A more mathematical way, which does not require to convert the integer list to string list is, to multiply each integer element with its corresponding power of 10, and then summing it up. It takes a time complexity of O(n).
Python3
# Python3 program to convert a list # of integers into a single integer def convert( list ): # multiply each integer element with its # corresponding power and perform summation res = sum (d * 10 * * i for i, d in enumerate ( list [:: - 1 ])) return (res) # Driver code list = [ 1 , 2 , 3 ] print (convert( list )) |
Output:
123
Method: Using list comprehension
Python3
lst = [ 1 , 2 , 3 ] s = [ str (i) for i in lst] print ("".join(s)) |
123
A small variation to this program leads to less computation in calculation of sum, i.e. using reduce(). This makes use of Horner’s rule, which factors the polynomial representing the number to reduce the number of multiplications.
Python3
res = functools. reduce ( lambda total, d: 10 * total + d, list , 0 ) |
Using list comprehension and the reduce method:
This approach first converts the elements of the list to strings using list comprehension, then concatenates the strings using the reduce function and a lambda function, and finally casts the resulting concatenated string back to an integer before returning it.
Python3
from functools import reduce def convert(lst): # Use list comprehension to concatenate the elements of the list as strings concat_lst = [ str (i) for i in lst] # Use the reduce function to concatenate the strings in the list res = reduce ( lambda x, y: x + y, concat_lst) # Cast the resulting concatenated string back to an integer and return it return int (res) # Test the function lst = [ 1 , 2 , 3 ] print (convert(lst)) # Output: 123 #This code is contributed by Edula Vinay Kumar Reddy |
123
The time complexity of the approach using list comprehension and the reduce method is O(n), where n is the length of the input list. This is because the reduce function iterates through the elements of the list once and performs a constant number of operations on each element.
The space complexity of this approach is also O(n), because a new list of strings is created and a new string is created to store the concatenated elements. In addition, the reduce function may require additional space to store intermediate results during the reduction process.
Note that the specific time and space complexity of this approach may depend on the implementation details of the particular Python version and environment being used.
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