Is there a way to filter a django queryset based on string similarity (a la python difflib)?

Question

I have a need to match cold leads against a database of our clients.

The leads come from a third party provider in bulk (thousands of records) and sales is asking u

Answer 1

If you need getting there with django and postgres and don't want to use introduced in 1.10 trigram-similarity https://docs.djangoproject.com/en/2.0/ref/contrib/postgres/lookups/#trigram-similarity you can implement using Levensthein like these:

Extension needed fuzzystrmatch

you need adding postgres extension to your db in psql:

CREATE EXTENSION fuzzystrmatch;

Lets define custom function with wich we can annotate queryset. It just take one argument the search_term and uses postgres levenshtein function (see docs):

from django.db.models import Func

class Levenshtein(Func):
    template = "%(function)s(%(expressions)s, '%(search_term)s')"
    function = "levenshtein"

    def __init__(self, expression, search_term, **extras):
        super(Levenshtein, self).__init__(
            expression,
            search_term=search_term,
            **extras
        )

then in any other place in project we just import defined Levenshtein and F to pass the django field.

from django.db.models import F

Spot.objects.annotate(
    lev_dist=Levenshtein(F('name'), 'Kfaka')
).filter(
    lev_dist__lte=2
)