`sum()` Function in Python [ English ]

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1. Introduction

The sum() function in Python is a built-in function used to calculate the total of all elements in an iterable object such as a list, tuple, or set. It adds all the numeric values together and returns the sum of those values.

The function is commonly used in programs where total values need to be calculated, such as totals of marks, prices, or numbers in a dataset.

2. Syntax

sum(iterable, start)

Parameters

1. iterable A sequence of numbers such as a list, tuple, or set whose values will be added.

2. start (optional) A value that is added to the total. The default value is 0.

3. Return Value

• Returns the sum of all elements in the iterable.

4. Basic Example

numbers = [10, 20, 30, 40]

result = sum(numbers)

print(result)

Output

100

Explanation

• The function adds all numbers in the list: 10 + 20 + 30 + 40 = 100

5. Example with Tuple

numbers = (5, 10, 15)

print(sum(numbers))

Output

30

Explanation

• The numbers in the tuple are added together.

6. Using the start Parameter

numbers = [1, 2, 3]

print(sum(numbers, 10))

Output

16

Explanation

• First the numbers are added: 1 + 2 + 3 = 6
• Then the starting value is added: 6 + 10 = 16

7. Example with a Set

numbers = {2, 4, 6, 8}

print(sum(numbers))

Output

20

Explanation

• The sum() function works with any iterable containing numeric values.

8. Practical Example

marks = [85, 90, 78, 88]

total = sum(marks)

print("Total Marks:", total)

Output

Total Marks: 341

Explanation

• The function calculates the total marks of a student.

9. Important Points

• sum() works only with numeric values.
• It cannot directly sum strings or mixed data types.
• It works with lists, tuples, sets, and other iterables containing numbers.

10. Summary

• sum() is a built-in Python function used to calculate the total of numeric elements in an iterable.
• It takes an iterable and an optional starting value.
• It returns the sum of all elements.
• It is commonly used for calculations such as totals, scores, and numeric data processing.