In Python, you can reduce dictionaries to a single value using the built-in `functools.reduce` function. This function applies a rolling computation to sequential pairs of values in an iterable, making it possible to combine dictionary values based on custom logic. Below is an example of how to reduce a dictionary to sum its values:
For instance, if you have a dictionary with integers as values and you want to find their total sum, you can use the following code:
from functools import reduce
my_dict = {'a': 1, 'b': 2, 'c': 3, 'd': 4}
total_sum = reduce(lambda x, y: x + y, my_dict.values())
print(total_sum) # Output: 10
How do I avoid rehashing overhead with std::set in multithreaded code?
How do I find elements with custom comparators with std::set for embedded targets?
How do I erase elements while iterating with std::set for embedded targets?
How do I provide stable iteration order with std::unordered_map for large datasets?
How do I reserve capacity ahead of time with std::unordered_map for large datasets?
How do I erase elements while iterating with std::unordered_map in multithreaded code?
How do I provide stable iteration order with std::map for embedded targets?
How do I provide stable iteration order with std::map in multithreaded code?
How do I avoid rehashing overhead with std::map in performance-sensitive code?
How do I merge two containers efficiently with std::map for embedded targets?