Python Big O: the time complexities of different data structures in Python
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from ericjmorey@programming.dev to python@programming.dev on 18 May 2024 18:35
https://programming.dev/post/14265030
from ericjmorey@programming.dev to python@programming.dev on 18 May 2024 18:35
https://programming.dev/post/14265030
Trey Hunner writes:
This article is primarily meant to act as a Python time complexity cheat sheet for those who already understand what time complexity is and how the time complexity of an operation might affect your code. For a more thorough explanation of time complexity see Ned Batchelder’s article/talk on this subject.
Read Python Big O: the time complexities of different data structures in Python
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Damn, I was hoping someone had python running a Megadeus.
I don’t know what that means
<img alt="Big O notation or something I’m not a compsci" src="https://beehaw.org/pictrs/image/c01c1319-c381-4258-8710-4d24994b4532.webm">
Cheers, always good to be aware of these concepts even if Pythons is far from ‘blazingly fast’
Shouldn’t this be
O(n log n)? I guess Python doesn’t have a list that stays sorted.As a workaround, just use dict keys with no values instead.
Sets stay sorted, no?
Nope, sets are unordered.
Ah, sorry. Sets are unique, not ordered. Thanks!
Yeah, I just think it’s kind of odd though. If a language only has lists and hash maps, my go-to is to use a hash map for uniqueness, and sort the list for ordered lists.
But in Python, it’s backwards where I use the hash map (dict) for ordered data and the set for uniqueness, because hash maps are unordered in most languages I’ve used.