Chunking lists in Python is a common task that can be easily accomplished with the standard library. This method helps break down large lists into smaller, more manageable parts or "chunks". Below is a simple function that demonstrates how to achieve this using basic Python constructs.
def chunk_list(input_list, chunk_size):
"""Splits a list into chunks of specified size."""
for i in range(0, len(input_list), chunk_size):
yield input_list[i:i + chunk_size]
# Example Usage:
my_list = [1, 2, 3, 4, 5, 6, 7, 8, 9]
chunked = list(chunk_list(my_list, 3))
print(chunked) # Output: [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
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?