Time complexity of zip_longest?

Question

I want to join two lists of dictionaries on a single key, and I saw the following answer to use zip_longest in Python 3.5+. In my case is the same as the question join two lists of dictionaries on a single key.

However, I failed to find how efficient is this method. If I'll use it for long lists, should it work well?

@KlausD: `timeout` does not determine time complexity — merely how long something took to execute. — martineau, Jun 30 '21 at 13:46
@martineau Well, isn't that the value you are interest in if you are talking about time complexity? Of cause you have to do it multiple times with reasonable sample sizes. — Klaus D., Jun 30 '21 at 13:48
@KlausD: No, it's the computational complexity that describes the amount of computer time it takes to run an algorithm, usually with respect to the size of its input, and is expressed in "Big O" notation (not execution time or rate of processing per unit of time). See @ Faboor's answer. Also see the [Wikipedia article](https://en.wikipedia.org/wiki/Time_complexity) on the subject. — martineau, Jun 30 '21 at 14:03

score 1 · Accepted Answer · answered Jun 30 '21 at 13:49

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zip_longest will create an iterator over the longest list. So if you you then consume it all it will be O( length_of_longest_list )

Whether the process of merging the dicts like that is efficient is an entirely different question :)

answered Jun 30 '21 at 13:49

Faboor

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Is there any more efficient way for my case? – ChikChak Jun 30 '21 at 13:51
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@ChikChak: Doubtful since every dictionary in the list has to be processed so intrinsically its an **O(n)** task. – martineau Jun 30 '21 at 14:21

Time complexity of zip_longest?

1 Answers1