Python lists: why is .sort() much faster than sorted()?
python, sorting
Solution
The `sort` version operates on the list in-place, but `sorted` makes a copy of the list. When the actual sorting is so easy (Timsort detects that the whole list is one big backwards run and reverses it), the creation of the copy can have a significant runtime impact.
Problem
I measure the time it takes to sort a list of 10 million entries: ``` import time a = range(10000000, 0, -1) b = range(10000000, 0, -1) start = time.time() a.sort() end = time.time() print end - start start = time.time() sorted(b) end = time.time() print end - start ``` The output I get: ``` 0.272000074387 0.468999862671 ``` The reason might be because `sorted` is more generic, but this is not consistent with this post where the difference became miniscule in large lists. What is causing the huge difference? I am using python 2.7.3 32 bit on 32 bit windows 7, Q6600 processor.