A way to characterise the relevance of a search result is the span in which the search terms are found. Large span means that the search terms are scattered sparsely around that spot and there is a high probability that the search result isn't very relevant or useful.
Minimum span text search tries to find such combination of found search terms that it minimises the span that covers all of them. This increases the meaningfulness of the results (except in some pathological cases).
Usually full text search results are just occurences of search terms (perhaps agumented with some score that depends on was the hit a whole word or just a part of it). Especially when the search terms are a bit vague or the subject that the user is looking for doesn't have very specific vocabulary associated with it the simple search term matching doesn't provide the results as accurately as needed.
When searching with multiple search terms, it comes more pronouced that the system should rank the results in a meaningful and preferably well-defined way. Minimum span text search provides a way to enhance the search results so that the results are more useful to the user.
from Cirrina import Cirrina
text = read_from_file(....)
# Parse text into a searchable corpus
search = Cirrina( text )
# search for a minimum span that contains all given search terms
result = search( search_terms )
# Show results
lines = text.splitlines()
print lines[ result[0] : result[1] + 1 ]