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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[–] [email protected] 4 points 6 months ago

Cheers, always good to be aware of these concepts even if Pythons is far from 'blazingly fast'

[–] [email protected] 2 points 6 months ago (1 children)

Damn, I was hoping someone had python running a Megadeus.

[–] ericjmorey 3 points 6 months ago (1 children)

I don't know what that means

[–] [email protected] 1 points 6 months ago

Big O notation or something I'm not a compsci

[–] [email protected] 2 points 6 months ago* (last edited 6 months ago) (1 children)

sorted_sequence.index(item)

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.

[–] [email protected] 1 points 6 months ago (1 children)

Sets stay sorted, no?

[–] [email protected] 3 points 6 months ago* (last edited 6 months ago) (1 children)

Nope, sets are unordered.

[–] [email protected] 1 points 6 months ago (1 children)

Ah, sorry. Sets are unique, not ordered. Thanks!

[–] [email protected] 1 points 6 months ago

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.