What’s the runtime complexity of various list methods?
The following table summarizes the runtime complexity of all list methods.
Assume that the length of the data type is defined as n (that is—len(data_type)). You can now categorize the asymptotic complexity of the different complexity functions as follows:
| Operation | Example | Complexity |
|---|---|---|
| Index | l[i] | O(1) |
| Store | l[i] = 42 | O(1) |
| Length | len(l) | O(1) |
| Append | l.append(42) | O(1) |
| Pop | l.pop() | O(1) |
| Clear | l.clear() | O(1) |
| Slicing | l[a:b] | O(b-a) |
| Extend | l1.extend(l2) | O(len(l1)+len(l2)) |
| Constructor | list(iter) | O(len(iter)) |
| Equality | l1 == l2 | O(n) |
| Slice Assign | l[a:b] = ... | O(n) |
| Delete | del l[i] | O(n) |
| Remove | l.remove(...) | O(n) |
| Membership | x in l / x not in l | O(n) |
| Copy | l.copy() | O(n) |
| Pop | l.pop(0) | O(n) |
| Min | min(l) | O(n) |
| Max | max(l) | O(n) |
| Reverse | l.reverse() | O(n) |
| Iterate | for x in l: | O(n) |
| Sort | l.sort() | O(n log(n)) |
| Multiply | l*k | O(n k) |
Need to learn more about these methods? Watch me giving you a quick overview of all Python list methods:
You can read more about all methods in my detailed tutorial on the Finxter blog.
Here’s your free PDF cheat sheet showing you all Python list methods on one simple page. Click the image to download the high-resolution PDF file, print it, and post it to your office wall:
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