How is set() implemented?

According to this thread:

Indeed, CPython's sets are implemented as something like dictionaries with dummy values (the keys being the members of the set), with some optimization(s) that exploit this lack of values

So basically a set uses a hashtable as its underlying data structure. This explains the O(1) membership checking, since looking up an item in a hashtable is an O(1) operation, on average.

If you are so inclined you can even browse the CPython source code for set which, according to Achim Domma, was originally mostly a cut-and-paste from the dict implementation.

Note: Nowadays, set and dict's implementations have diverged significantly, so the precise behaviors (e.g. arbitrary order vs. insertion order) and performance in various use cases differs; they're still implemented in terms of hashtables, so average case lookup and insertion remains O(1), but set is no longer just "dict, but with dummy/omitted keys".

When people say sets have O(1) membership-checking, they are talking about the average case. In the worst case (when all hashed values collide) membership-checking is O(n). See the Python wiki on time complexity.

The Wikipedia article says the best case time complexity for a hash table that does not resize is O(1 + k/n). This result does not directly apply to Python sets since Python sets use a hash table that resizes.

A little further on the Wikipedia article says that for the average case, and assuming a simple uniform hashing function, the time complexity is O(1/(1-k/n)), where k/n can be bounded by a constant c<1.

Big-O refers only to asymptotic behavior as n → ∞. Since k/n can be bounded by a constant, c<1, independent of n,

O(1/(1-k/n)) is no bigger than O(1/(1-c)) which is equivalent to O(constant) = O(1).

So assuming uniform simple hashing, on average, membership-checking for Python sets is O(1).