Python sum(): Calculate the Sum of Numbers in an Iterable

The sum() function adds up all the numbers in a list, tuple, or other iterable. It’s useful for mathematical calculations, data analysis, and aggregating values.

Example

numbers = [1, 2, 3, 4, 5]
print(sum(numbers))

Output:

15

Adds all numbers in the list.

Syntax

sum(iterable, start=0)

• iterable → A sequence (list, tuple, set, range) of numbers.
• start (optional) → A number to add to the sum (default: 0).
• Returns → The total sum of all elements.

1. Summing a List of Numbers

nums = [10, 20, 30]
print(sum(nums))  
# Output: 60

Adds all elements in the list.

2. Summing a Tuple

nums = (4, 5, 6)
print(sum(nums))  
# Output: 15

Works the same way for tuples.

3. Using sum() with a range()

print(sum(range(1, 6)))  
# Output: 15  (1 + 2 + 3 + 4 + 5)

Efficiently adds up a sequence of numbers.

4. Using start to Add an Extra Value

print(sum([1, 2, 3], 10))  
# Output: 16  (1 + 2 + 3 + 10)

Adds an extra start value before summing.

5. Summing Floating-Point Numbers

values = [1.5, 2.5, 3.0]
print(sum(values))  
# Output: 7.0

Works with floating-point numbers too.

6. Summing a Set

numbers = {3, 6, 9}
print(sum(numbers))  
# Output: 18

Works with sets as well.

7. Using sum() on a List of Expressions

squared_numbers = [x**2 for x in range(1, 4)]
print(sum(squared_numbers))  
# Output: 14  (1² + 2² + 3² = 1 + 4 + 9)

Allows custom calculations before summing.

8. Summing Values from a Dictionary

prices = {"apple": 2, "banana": 3, "cherry": 5}
print(sum(prices.values()))  
# Output: 10

Use values() to sum dictionary values.

9. Using sum() with map()

numbers = ["1", "2", "3"]
print(sum(map(int, numbers)))  
# Output: 6

Converts strings to integers before summing.

Key Notes

• ✔ Adds up numbers from a list, tuple, set, or range.
• ✔ Supports floating-point numbers.
• ✔ Works with dictionary values using .values().
• ✔ Use sum(map(...)) for type conversion before summing.

By using sum(), you can quickly compute totals, perform calculations on sequences, and analyze numerical data efficiently. 🚀