问题
I've been unable to find a source for this information, short of looking through the Python source code myself to determine how the objects work. Does anyone know where I could find this online?
回答1:
Checkout the TimeComplexity page on the py dot org wiki. It covers set/dicts/lists/etc at least as far as time complexity goes.
回答2:
Raymond D. Hettinger does an excellent talk (slides) about Python's built-in collections called 'Core Python Containers - Under the Hood'. The version I saw focussed mainly on set and dict, but list was covered too.
There are also some photos of the pertinent slides from EuroPython in a blog.
Here is a summary of my notes on list:
- Stores items as an array of pointers. Subscript costs O(1) time. Append costs amortized O(1) time. Insert costs O(n) time.
- Tries to avoid
memcpywhen growing by over-allocating. Many small lists will waste a lot of space, but large lists never waste more than about 12.5% to overallocation. - Some operations pre-size. Examples given were
range(n),map(),list(),[None] * n, and slicing. - When shrinking, the array is
realloced only when it is wasting 50% of space.popis cheap.
回答3:
If your asking what I think your asking, you can find them Here... page 476 and on.
It's written around optimization techniques for Python; It's mostly Big-O notation of time efficiencies not much memory.
来源：https://stackoverflow.com/questions/45228/where-can-i-find-the-time-and-space-complexity-of-the-built-in-sequence-types-in