starmind.py

# %% 
# unless you would like me to code the Levenshtein algo from hand, 
# I will just use a library...
from Levenshtein import distance # !pip install python-Levenshtein
assert distance("ah", "aho") == 1

# %%
# loading dataset, quick inspection
import pandas as pd 
# https://opendata.swiss/en/dataset/hundenamen-aus-dem-hundebestand-der-stadt-zurich2/resource/3e48403f-1ca2-434f-8766-cf0a73d7c2a1
h_namen = pd.read_csv('/Users/ren/Desktop/20210103_hundenamen.csv')
print(h_namen.columns)
h_namen.head()
# %%
# loop over dog names 
matching_names = []
for n in h_namen.HUNDENAME.unique():  # we want disstinct values, so let's work with unique names
    if 3 <= len(n) <= 5: # shortcut: anyway, name can't be shorter or longer than +/-1 of 4
        if distance('Luca', n) <= 1:
            #print(n)
            matching_names.append(n)

', '.join(matching_names)