def test_multiple_models():
tfidf_matcher = TFIDF(n_gram_range=(3, 3),
min_similarity=0,
model_id="TF-IDF")
tfidf_large_matcher = TFIDF(n_gram_range=(3, 6), min_similarity=0)
base_edit_matcher = EditDistance(n_jobs=1)
ratio_matcher = EditDistance(n_jobs=1, scorer=fuzz.ratio)
rapidfuzz_matcher = RapidFuzz(n_jobs=1)
matchers = [
tfidf_matcher, tfidf_large_matcher, base_edit_matcher, ratio_matcher,
rapidfuzz_matcher
]
model = PolyFuzz(matchers).match(from_list, to_list)
# Test if correct matches are found
for model_id in model.get_ids():
assert model_id in model.get_matches().keys()
assert isinstance(model.get_matches(model_id), pd.DataFrame)
assert len(model.get_matches()) == len(matchers)
# Test if error is raised when accessing clusters before creating them
with pytest.raises(ValueError):
model.get_clusters()
with pytest.raises(ValueError):
model.get_cluster_mappings()
# Test if groupings are found
model.group()
for model_id in model.get_ids():
assert model_id in model.get_cluster_mappings().keys()
assert len(model.get_cluster_mappings()) == len(matchers)
def test_grouper_same_list():
model = PolyFuzz("TF-IDF").match(from_list, from_list)
model.group(link_min_similarity=0.75, group_all_strings=True)
matches = model.get_matches()
assert isinstance(matches, pd.DataFrame)
assert matches.Similarity.mean() > 0.3
assert len(matches) == 6
assert list(matches.columns) == ['From', 'To', 'Similarity', 'Group']
assert model.get_clusters() == {1: ['apples', 'apple', 'appl']}
assert model.get_cluster_mappings() == {'apples': 1, 'apple': 1, 'appl': 1}
def test_grouper(method):
model = PolyFuzz(method).match(from_list, to_list)
model.group(link_min_similarity=0.75)
matches = model.get_matches()
assert isinstance(matches, pd.DataFrame)
assert matches.Similarity.mean() > 0.3
assert len(matches) == 6
assert list(matches.columns) == ['From', 'To', 'Similarity', 'Group']
assert model.get_clusters() == {1: ['apples', 'apple']}
assert model.get_cluster_mappings() == {'apples': 1, 'apple': 1}
