In an asynchronous application using Python, you may often find the need to split lists into smaller chunks for easier processing or parallel execution. This allows for improved performance and responsiveness in your applications. Below is an example of how to split a list using asynchronous programming in Python.
import asyncio
async def split_list(data, chunk_size):
for i in range(0, len(data), chunk_size):
yield data[i:i + chunk_size]
async def main():
my_list = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
chunk_size = 3
async for chunk in split_list(my_list, chunk_size):
print(chunk)
asyncio.run(main())
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?