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Effortlessly Calculate Summation: Python Tutorial


Python’s sum(): The Pythonic Way to Sum Values

Python’s built-in function sum() is an efficient and Pythonic way to sum a list of numeric values. Adding several numbers together is a common intermediate step in many computations, so sum() is a pretty handy tool for a Python programmer.

As an additional and interesting use case, you can concatenate lists and tuples using sum(), which can be convenient when you need to flatten a list of lists.

Understanding the Summation Problem

Summing numeric values together is a fairly common problem in programming. For example, say you have a list of numbers [1, 2, 3, 4, 5] and want to add them together to compute their total sum. With standard arithmetic, you’ll do something like this:

1 + 2 + 3 + 4 + 5 = 15

As far as math goes, this expression is pretty straightforward. It walks you through a short series of additions until you find the sum of all the numbers.

It’s possible to do this particular calculation by hand, but imagine some other situations where it might not be so possible. If you have a particularly long list of numbers, adding by hand can be inefficient and error-prone. What happens if you don’t even know how many items are in the list? Finally, imagine a scenario where the number of items you need to add changes dynamically or unpredictably.

In situations like these, whether you have a long or short list of numbers, Python can be quite useful to solve summation problems.

If you want to sum the numbers by creating your own solution from scratch, then you can try using a for loop:

numbers = [1, 2, 3, 4, 5]
total = 0
for number in numbers:
total += number
total # Output: 15

Here, you first create total and initialize it to 0. Then, you iterate over each number in the list numbers and add it to the total. Finally, you get the sum of all the numbers by printing total.

Getting Started With Python’s sum()

Python’s sum() function provides a more concise and efficient way to achieve the same result. Instead of manually iterating over the list and adding each number, you can simply pass the list as an argument to sum():

numbers = [1, 2, 3, 4, 5]
total = sum(numbers)
total # Output: 15

The sum() function takes an iterable as its argument, in this case, the list numbers. It automatically iterates over the elements of the list and adds them together, returning the total sum.

The Required Argument: iterable

The iterable argument is the required argument for the sum() function. It specifies the sequence of values that you want to sum. The iterable can be any object that can be looped over, such as lists, tuples, sets, or even strings.

Here are some examples of using sum() with different types of iterables:

numbers = [1, 2, 3, 4, 5] # List
total = sum(numbers)
total # Output: 15
numbers_tuple = (1, 2, 3, 4, 5) # Tuple
total = sum(numbers_tuple)
total # Output: 15
numbers_set = {1, 2, 3, 4, 5} # Set
total = sum(numbers_set)
total # Output: 15
string = "12345" # String
total = sum(map(int, string)) # Convert each character to int
total # Output: 15

The Optional Argument: start

The sum() function also has an optional second argument called start. This argument specifies the initial value of the sum. By default, the start value is 0. If you want to start with a different initial value, you can pass it as the second argument to sum():

numbers = [1, 2, 3, 4, 5]
total = sum(numbers, 10) # Start with initial value of 10
total # Output: 25

In this example, the sum of the numbers in the list numbers is calculated starting from an initial value of 10. So the final sum is 10 + 1 + 2 + 3 + 4 + 5 = 25.

Summing Numeric Values

The sum() function works not only with integers but also with other numeric types, such as floats, complex numbers, and decimals. It automatically handles the summation of different numeric values correctly. Here are some examples:

floats = [1.1, 2.2, 3.3, 4.4, 5.5]
total = sum(floats)
total # Output: 16.5
complex_numbers = [1j, 2j, 3j, 4j, 5j]
total = sum(complex_numbers)
total # Output: 10j
from decimal import Decimal
decimals = [Decimal("0.1"), Decimal("0.2"), Decimal("0.3")]
total = sum(decimals)
total # Output: Decimal('0.6')

In the first example, the list floats contains floating-point numbers. The sum() function calculates their total sum correctly, even though floating-point numbers have limited precision.

In the second example, the list complex_numbers contains complex numbers. Again, the sum() function handles the summation of complex numbers correctly.

In the third example, the list decimals contains numbers of the Decimal type from the decimal module. The sum() function correctly adds these numbers together, preserving their precision.

Concatenating Sequences

Another interesting use of the sum() function is concatenating sequences. Instead of summing numeric values, you can use sum() to concatenate lists, tuples, sets, or even strings.

lists = [[1, 2], [3, 4], [5, 6]]
concatenated = sum(lists, [])
concatenated # Output: [1, 2, 3, 4, 5, 6]
tuples = [(1, 2), (3, 4), (5, 6)]
concatenated = sum(tuples, ())
concatenated # Output: (1, 2, 3, 4, 5, 6)
strings = ["Hello", " ", "World", "!"]
concatenated = sum(strings, "")
concatenated # Output: 'Hello World!'

In these examples, sum() is used to concatenate the subsequences within the lists, tuples, and strings. The second argument, in these cases, is an empty list, an empty tuple, and an empty string, respectively. This ensures that the elements are concatenated correctly into a single sequence.

Practicing With Python’s sum()

Now that you’ve learned the basics of using Python’s sum() function, let’s explore some more advanced use cases and problem-solving techniques.

Computing Cumulative Sums

Sometimes, you may need to compute cumulative sums, which are the running totals of a sequence. For example, given the list [1, 2, 3, 4, 5], the cumulative sums would be [1, 3, 6, 10, 15]. You can achieve this using sum() together with list comprehensions:

numbers = [1, 2, 3, 4, 5]
cumulative_sums = [sum(numbers[:i+1]) for i in range(len(numbers))]
cumulative_sums # Output: [1, 3, 6, 10, 15]

In this example, a list comprehension is used to iterate over the indices of the list numbers. For each index i, sum(numbers[:i+1]) calculates the cumulative sum up to that index.

Calculating the Mean of a Sample

The mean, or average, of a sample is another common calculation that involves summation. The formula to calculate the mean is:

mean = sum(values) / count

where values is the list of values and count is the number of values in the list.

You can use sum() to calculate the mean of a sample by first finding the sum of all values and then dividing it by the count:

values = [1, 2, 3, 4, 5]
mean = sum(values) / len(values)
mean # Output: 3.0

In this example, sum(values) calculates the sum of all values, which is then divided by len(values) to get the mean.

Finding the Dot Product of Two Sequences

The dot product of two sequences is another application of summation. The dot product is calculated as the sum of the products of corresponding elements in the sequences.

For example, given the two lists [1, 2, 3] and [4, 5, 6], the dot product would be 1 * 4 + 2 * 5 + 3 * 6, which is equal to 32.

You can use sum() with a list comprehension to calculate the dot product:

list1 = [1, 2, 3]
list2 = [4, 5, 6]
dot_product = sum(x * y for x, y in zip(list1, list2))
dot_product # Output: 32

In this example, zip(list1, list2) pairs up the corresponding elements of list1 and list2, creating a sequence of tuples. The list comprehension then calculates the product of each pair (x, y) and sums them up using sum().

Flattening a List of Lists

Sometimes, you may come across a list that contains other lists as its elements. To flatten such a list, you can use sum() together with an empty list as the second argument.

nested_list = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
flattened = sum(nested_list, [])
flattened # Output: [1, 2, 3, 4, 5, 6, 7, 8, 9]

In this example, sum(nested_list, []) concatenates all the sublists in nested_list into a single flat list.

Using Alternatives to sum()

Although sum() is a powerful function for summation, there are some cases where alternative tools may be more appropriate or efficient.

Summing Floating-Point Numbers: math.fsum()

When dealing with floating-point numbers, especially when precision is important, the math.fsum() function provides a more accurate alternative to sum(). This function uses a more precise algorithm to calculate the sum of floating-point numbers.

import math
floats = [1.1, 2.2, 3.3, 4.4, 5.5]
total = math.fsum(floats)
total # Output: 16.5

In this example, math.fsum() is used to calculate the sum of the floating-point numbers in the list floats.

Concatenating Iterables With itertools.chain()

If you need to concatenate multiple iterables together, the itertools.chain() function provides an efficient way to do so.

import itertools
lists = [[1, 2], [3, 4], [5, 6]]
concatenated = list(itertools.chain.from_iterable(lists))
concatenated # Output: [1, 2, 3, 4, 5, 6]

In this example, itertools.chain.from_iterable(lists) is used to concatenate the lists in lists into a single iterable, which is then converted to a list using list().

Concatenating Strings With str.join()

If you need to concatenate strings, using the str.join() method is usually more efficient than using sum().

strings = ["Hello", " ", "World", "!"]
concatenated = "".join(strings)
concatenated # Output: 'Hello World!'

In this example, "".join(strings) concatenates the strings in the list strings into a single string, with empty string "" as the separator.


Python’s sum() function is a versatile tool for summation and sequence concatenation. It provides a concise and efficient way to add numeric values together, as well as concatenate sequences. By understanding the different arguments and use cases of sum(), you can efficiently approach and solve summation problems in your code.

Whether you need to sum a list of numbers, compute cumulative sums, calculate the mean, find the dot product of two sequences, or flatten a list of lists, sum() can simplify your code and make it more readable.

So, the next time you encounter a summation problem in your Python code, remember that sum() is there to help you!