Tuesday, September 24, 2024
Google search engine
HomeLanguagesPython | Multiply all numbers in the list

Python | Multiply all numbers in the list

Given a list, print the value obtained after multiplying all numbers in a Python list. 

Examples: 

Input :  list1 = [1, 2, 3] 
Output :
Explanation: 1*2*3=6 

Input : list1 = [3, 2, 4] 
Output : 24 

Multiply all numbers in the list Using Traversal

Initialize the value of the product to 1(not 0 as 0 multiplied with anything returns zero). Traverse till the end of the list, multiply every number with the product. The value stored in the product at the end will give you your final answer.

Below is the Python implementation of the above approach:  

Python




# Python program to multiply all values in the
# list using traversal
 
 
def multiplyList(myList):
 
    # Multiply elements one by one
    result = 1
    for x in myList:
        result = result * x
    return result
 
 
# Driver code
list1 = [1, 2, 3]
list2 = [3, 2, 4]
print(multiplyList(list1))
print(multiplyList(list2))


Output

6
24

Time complexity: O(n), where n is the number of elements in the list.
Auxiliary space: O(1),

Multiply all numbers in the list Using numpy.prod()

We can use numpy.prod() from import numpy to get the multiplication of all the numbers in the list. It returns an integer or a float value depending on the multiplication result.

Below is the Python3 implementation of the above approach:  

Python3




# Python3 program to multiply all values in the
# list using numpy.prod()
 
import numpy
list1 = [1, 2, 3]
list2 = [3, 2, 4]
 
# using numpy.prod() to get the multiplications
result1 = numpy.prod(list1)
result2 = numpy.prod(list2)
print(result1)
print(result2)


Output: 
 

6
24

Time complexity: O(n), where n is the length of the input lists. 
Auxiliary space: O(1). 

Multiply all numbers in the list Using lambda function

Lambda’s definition does not include a “return” statement, it always contains an expression that is returned. We can also put a lambda definition anywhere a function is expected, and we don’t have to assign it to a variable at all. This is the simplicity of lambda functions. The reduce() function in Python takes in a function and a list as an argument. The function is called with a lambda function and a list and a new reduced result is returned. This performs a repetitive operation over the pairs of the list.

Below is the Python3 implementation of the above approach:  

Python3




# Python3 program to multiply all values in the
# list using lambda function and reduce()
 
from functools import reduce
list1 = [1, 2, 3]
list2 = [3, 2, 4]
 
 
result1 = reduce((lambda x, y: x * y), list1)
result2 = reduce((lambda x, y: x * y), list2)
print(result1)
print(result2)


Output

6
24

Time complexity: O(n) – where n is the length of the longer list.
Auxiliary space: O(1) – the memory used is constant, as no extra data structures are create.

Multiply all numbers in the list Using prod function of math library

Starting Python 3.8, a prod function has been included in the math module in the standard library, thus no need to install external libraries.

Below is the Python3 implementation of the above approach:  

Python3




# Python3 program to multiply all values in the
# list using math.prod
 
import math
list1 = [1, 2, 3]
list2 = [3, 2, 4]
 
 
result1 = math.prod(list1)
result2 = math.prod(list2)
print(result1)
print(result2)


Output: 
 

6
24

Time complexity: O(n), where n is the length of the input list. 
Auxiliary space: O(1), as the program only uses a fixed amount of memory to store the input lists and the output variables.

Multiply all numbers in the list Using mul() function of operator module. 

First we have to import the operator module then using the mul() function of operator module multiplying the all values in the list. 

Python3




# Python 3 program to multiply all numbers in
# the given list by importing operator module
 
from operator import*
list1 = [1, 2, 3]
m = 1
for i in list1:
  # multiplying all elements in the given list
  # using mul function of operator module
    m = mul(i, m)
# printing the result
print(m)


Output

6

Time complexity:

The program contains a single for loop that iterates through each element in the input list. Therefore, the time complexity of the program is O(n), where n is the length of the input list.
 

Auxiliary space:

The program uses a constant amount of auxiliary space throughout its execution. Specifically, it only creates four variables: list1, m, i, and the imported mul function from the operator module. The space required to store these variables does not depend on the size of the input list, and therefore the auxiliary space complexity of the program is O(1), which is constant.

Multiply all numbers in the list Using traversal by index

Python3




# Python program to multiply all values in the
# list using traversal
 
def multiplyList(myList) :
     
    # Multiply elements one by one
    result = 1
    for i in range(0,len(myList)):
        result = result * myList[i]
    return result
     
# Driver code
list1 = [1, 2, 3]
list2 = [3, 2, 4]
print(multiplyList(list1))
print(multiplyList(list2))


Output

6
24

Time complexity: O(n), where n is the length of the input list. 

Auxiliary space: O(1), as the program uses a single variable to store the result and does not use any additional data structure. 

Multiply all numbers in the list Using itertools.accumulate

Python




# Python3 program to multiply all values in the
# list using lambda function and accumulate()
 
from itertools import accumulate
list1 = [1, 2, 3]
list2 = [3, 2, 4]
 
 
result1 = list(accumulate(list1, (lambda x, y: x * y)))
result2 = list(accumulate(list2, (lambda x, y: x * y)))
print(result1[-1])
print(result2[-1])


Output:

6
24

The time complexity is O(n), where n is the length of the input list.

The auxiliary space is also O(n) 

Multiply all numbers in the list Using the recursive function 

The function product_recursive() takes a list of numbers as input and returns the product of all the numbers in the list, using a recursive approach.

The steps for this function are:

  1. Check if the list is empty. If it is, return 1 (the product of an empty list is defined as 1).
  2. If the list is not empty, recursively call the product_recursive() function on the rest of the list (i.e., all the elements except for the first one) and multiply the result by the first element of the list.
  3. Return the product obtained from step 2.
     

Python3




def product_recursive(numbers):
    # base case: list is empty
    if not numbers:
        return 1
    # recursive case: multiply first element by product of the rest of the list
    return numbers[0] * product_recursive(numbers[1:])
list1 = [1, 2, 3]
product = product_recursive(list1)
print(product)  # Output: 6
 
list2 = [3, 2, 4]
product = product_recursive(list2)
print(product)  # Output: 24


Output

6
24

The time complexity of this function is O(n), where n is the number of elements in the list. This is because the function needs to perform n recursive calls, one for each element in the list. 
The space complexity is also O(n) because the function creates n recursive calls on the call stack. This means that for large lists, the function can quickly use up a lot of memory, which can cause the program to crash or slow down significantly.

Multiply all numbers in the list Using  reduce() and the mul() function’s

One approach to solve this problem is to use the built-in reduce() function from the functools module, which can apply a function to an iterable in a cumulative way. We can use the operator.mul() function to multiply the elements together.

Here are the steps and code:

  1. Import the reduce() function and mul() function from the functools and operator modules, respectively.
  2. Define the input list.
  3. Apply the reduce() function to the list, using mul() as the function to apply.
  4. Print the result.

Python3




from functools import reduce
from operator import mul
 
list1 = [1, 2, 3]
result = reduce(mul, list1)
 
print(result)


Output

6

Time complexity: O(n)
Auxiliary space: O(1)

RELATED ARTICLES

Most Popular

Recent Comments