How do I reduce dicts in Python in an async application?

async, Python, reduce dicts, dictionary reduction, async applications, Python async programming
Learn how to effectively reduce dictionaries in asynchronous Python applications using various techniques. This guide covers methods to optimize dictionary management in concurrent code execution. 

import asyncio
from collections import defaultdict

async def reduce_dicts(dicts):
    result = defaultdict(int)
    for d in dicts:
        for key, value in d.items():
            result[key] += value
    return dict(result)

async def main():
    dicts = [{'a': 1, 'b': 2}, {'a': 3, 'c': 5}, {'b': 4}]
    reduced_dict = await reduce_dicts(dicts)
    print(reduced_dict)

asyncio.run(main())

async Python reduce dicts dictionary reduction async applications Python async programming

Related Questions

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?