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I am trying to construct a function called 'and_query' that takes as input a single string, consisting of one or more words, such that the function returns a list of matching documents for the words being in the abstracts of the documents.

First, I put all the words in an inverted index with the id being the id of the document and the abstract the plain text.

inverted_index = defaultdict(set)

for (id, abstract) in Abstracts.items():
for term in preprocess(tokenize(abstract)):
 inverted_index[term].add(id)

Then, I wrote a query function where finals is a list of all the matching documents.

Because it should only return documents for which every word of the function parameter has a match in the document, I used the set operation 'intersecton'.

def and_query(tokens):
 documents=set()
 finals = 
 terms = preprocess(tokenize(tokens))

 for term in terms:
 for i in inverted_index[term]:
 documents.add(i)

 for term in terms:
 temporary_set= set()
 for i in inverted_index[term]:
 temporary_set.add(i)
 finals.extend(documents.intersection(temporary_set))
 return finals

def finals_print(finals):
 for final in finals:
 display_summary(final) 

finals_print(and_query("netherlands vaccine trial"))

However, it seems like the function is still returning documents for which only 1 word is in the abstract of the document.

does anyone know what i did wrong concerning my set operations??

(I think the fault should be anywhere in this part of the code):

for term in terms:
 temporary_set= set()
 for i in inverted_index[term]:
 temporary_set.add(i)
 finals.extend(documents.intersection(temporary_set))
return finals 

Thanks in advance

basically what i want to do in short:

for word in words:
 id_set_for_one_word= set()
 for i in get_id_of that_word[word]:
 id_set_for_one_word.add(i)
pseudo:
 id_set_for_one_word intersection (id_set_of_other_words)

finals.extend( set of all intersections for all words)

and then i need the intersection of the id sets on all of these words, returning a set in which the id's are that exist for every word in words.

To elaborate on my code smells comment, here's a rough draft of what I have done before to solve this kind of problems.

def tokenize(abstract):
 #return <set of words in abstract>
 set_ = .....
 return set_

candidates = (id, abstract, tokenize(abstract)) for abstract in Abstracts.items():


all_criterias = "netherlands vaccine trial".split()


def searcher(candidates, criteria, match_on_found=True):

 search_results = 
 for cand in candidates:
 #cand[2] has a set of tokens or somesuch... abstract.
 if criteria in cand[2]:
 if match_on_found:
 search_results.append(cand)
 else:
 #that's a AND NOT if you wanted that
 search_results.append(cand)
 return search_results


for criteria in all_criterias:
 #pass in the full list every time, but it gets progressively shrunk
 candidates = searcher(candidates, criteria)

#whats left is what you want
answer = [(abs[0],abs[1]) for abs in candidates] 

Question: returns a list of matching documents for the words being in the abstracts of the documents

The term with the min number of documents, hold always the result.

If a term does not exists in inverted_index, gives no match at all.

For the sake of simplicity, predefined data:

Abstracts = 1: 'Lorem ipsum dolor sit amet,',
 2: 'consetetur sadipscing elitr,',
 3: 'sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat,',
 4: 'sed diam voluptua.',
 5: 'At vero eos et accusam et justo duo dolores et ea rebum.',
 6: 'Stet clita kasd gubergren,',
 7: 'no sea takimata sanctus est Lorem ipsum dolor sit amet.',
 


inverted_index = 'Stet': 6, 'ipsum': 1, 7, 'erat,': 3, 'ut': 3, 'dolores': 5, 'gubergren,': 6, 'kasd': 6, 'ea': 5, 'consetetur': 2, 'sit': 1, 7, 'nonumy': 3, 'voluptua.': 4, 'est': 7, 'elitr,': 2, 'At': 5, 'rebum.': 5, 'magna': 3, 'sadipscing': 2, 'diam': 3, 4, 'dolore': 3, 'sanctus': 7, 'labore': 3, 'sed': 3, 4, 'takimata': 7, 'Lorem': 1, 7, 'invidunt': 3, 'aliquyam': 3, 'accusam': 5, 'duo': 5, 'amet.': 7, 'et': 3, 5, 'sea': 7, 'dolor': 1, 7, 'vero': 5, 'no': 7, 'eos': 5, 'tempor': 3, 'amet,': 1, 'clita': 6, 'justo': 5, 'eirmod': 3

def and_query(tokens):
 print("tokens:".format(tokens))
 #terms = preprocess(tokenize(tokens))
 terms = tokens.split()

 term_min = None
 for term in terms:
 if term in inverted_index:
 # Find min
 if not term_min or term_min[0] > len(inverted_index[term]):
 term_min = (len(inverted_index[term]), term)
 else:
 # Break early, if a term is not in inverted_index
 return set()

 finals = inverted_index[term_min[1]]
 print("term_min: inverted_index:".format(term_min, finals))
 return finals


def finals_print(finals):
 if finals:
 for final in finals:
 print("Document []:".format(final, Abstracts[final]))
 else:
 print("No matching Document found")

if __name__ == "__main__":
 for tokens in ['sed diam voluptua.', 'Lorem ipsum dolor', 'Lorem ipsum dolor test']:
 finals_print(and_query(tokens))
 print()

Output:

tokens:sed diam voluptua.
term_min:(1, 'voluptua.') inverted_index:4
Document [4]:sed diam voluptua.

tokens:Lorem ipsum dolor
term_min:(2, 'Lorem') inverted_index:1, 7
Document [1]:Lorem ipsum dolor sit amet,
Document [7]:no sea takimata sanctus est Lorem ipsum dolor sit amet.

tokens:Lorem ipsum dolor test
No matching Document found

Tested with Python: 3.4.2

Found the solution eventually myself.
replacing

 finals.extend(documents.intersection(id_set_for_one_word))
return finals 

with

 documents = (documents.intersection(id_set_for_one_word))
return documents

seems to work here.

Still, thanks for all the effort y'all.