I would like to search in a set of sets in a specific way:
Example (Pseudocode):
search = {{1}, {3}}
search_base = {{1, 2}, {3, 4}}
# search results in True
because the 1 can be found in the first set and the 3 in the second. Order doesn't matter, but the number of subsets has to be identical, the search consists always of singletons.
Example (Intuition):
search = {{"Vitamin D"}, {"Sodium"}}
search_base = {{"Vitamin D", "Vitamin"}, {"Sodium", "NA"}}
I want to know if search (a combination of two materials with different hierachical names) is in the search base. The search base here only contains a single entry.
What I tried:
Using frozensets instead if sets for the hash.
search = frozenset([frozenset([1]), frozenset([3])])
search_base = frozenset([frozenset([1, 2]), frozenset([3, 4])])
all_matched = []
for i, set_ in enumerate(search):
for bset_ in search_base:
if not set_.isdisjoint(bset_):
all_matched.append(True)
print(len(all_matched) == len(search))
It feels very clunky and therefore my question is if there is a much smarter (better performance) way to solve this.
As you said the data type is not important, I will just use a list of numbers and a list of sets. You can nest all and any, with in to check set membership:
def search(nums, sets):
return all(any(x in y for y in sets) for x in nums)
print(search([1, 3], [{1, 2}, {3, 4}])) # True
print(search([1, 2], [{1, 2}, {3, 4}])) # True
print(search([1, 5], [{1, 2}, {3, 4}])) # False
print(search(["Vitamin D", "Sodium"], [{"Vitamin D", "Vitamin"}, {"Sodium", "NA"}])) # True
As for performance, this does not improve upon your current code. I doubt there are any (performance-wise) better ways unless there are more restrictions on the input data.