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# built-in
from itertools import islice
from pathlib import Path
from sys import argv
# project
from textdistance import EntropyNCD
# read files
licenses = dict()
for path in Path('choosealicense.com', '_licenses').iterdir():
licenses[path.stem] = path.read_text()
# show licenses list if no arguments passed
if len(argv) == 1:
print(*sorted(licenses.keys()), sep='\n')
exit(1)
# compare all with one
qval = int(argv[1]) if argv[1] else None
compare_with = argv[2]
distances = dict()
for name, content in licenses.items():
distances[name] = EntropyNCD(qval=qval)(
licenses[compare_with],
content,
)
# show 5 most similar
sorted_distances = sorted(distances.items(), key=lambda d: d[1])
for name, distance in islice(sorted_distances, 5):
print('{:20} {:.4f}'.format(name, distance))
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