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# 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))