Search#
Exact search#
Find all individuals with the last_name “Groskopf”:
family = table.where(lambda r: r['last_name'] == 'Groskopf')
Fuzzy search by edit distance#
By leveraging an existing Python library for computing the Levenshtein edit distance it is trivially easy to implement a fuzzy string search.
For example, to find all names within 2 edits of “Groskopf”:
from Levenshtein import distance
fuzzy_family = table.where(lambda r: distance(r['last_name'], 'Groskopf') <= 2)
These results will now include all those “Grosskopfs” and “Groskoffs” whose mail I am always getting.
Fuzzy search by phonetic similarity#
By using Fuzzy to calculate phonetic similarity, it is possible to implement a fuzzy phonetic search.
For example to find all rows with first_name phonetically similar to “Catherine”:
import fuzzy
dmetaphone = fuzzy.DMetaphone(4)
phonetic_search = dmetaphone('Catherine')
def phonetic_match(r):
return any(x in dmetaphone(r['first_name']) for x in phonetic_search)
phonetic_family = table.where(lambda r: phonetic_match(r))