def test_match_raises_error_when_doc_not_doc_obj(searcher: FuzzySearcher,
nlp: Language) -> None:
"""It raises a TypeError if doc is not a Doc object."""
doc = "G-rant Anderson lives in TN."
query = nlp("xenomorph")
with pytest.raises(TypeError):
searcher.match(doc, query)
def test_match_raises_error_if_query_not_doc_obj(searcher: FuzzySearcher,
nlp: Language) -> None:
"""It raises a TypeError if query not a doc."""
doc = nlp("This is a doc")
query = "Not a doc"
with pytest.raises(TypeError):
searcher.match(doc, query)
def test_compare_raises_error_with_unknown_func_name(searcher: FuzzySearcher,
nlp: Language) -> None:
"""It raises a ValueError if fuzzy_func does not match a predefined key name."""
with pytest.raises(ValueError):
assert searcher.compare(nlp("spaczz"),
nlp("spacy"),
fuzzy_func="unknown")
def test__calc_flex_warns_if_flex_longer_than_query(
nlp: Language, searcher: FuzzySearcher) -> None:
"""It provides UserWarning if flex > len(query)."""
query = nlp("Test query")
with pytest.warns(FlexWarning):
flex = searcher._calc_flex(query, 5)
assert flex == 2
def test__scan_with_no_matches(searcher: FuzzySearcher, nlp: Language,
scan_example: Doc) -> None:
"""It returns None if no matches >= min_r1."""
query = nlp("xenomorph")
assert (searcher._scan(
scan_example, query, fuzzy_func="simple", min_r1=30, ignore_case=True)
is None)
def test__calc_flex_warns_if_flex_less_than_0(nlp: Language,
searcher: FuzzySearcher) -> None:
"""It provides UserWarning if flex < 0."""
query = nlp("Test query")
with pytest.warns(FlexWarning):
flex = searcher._calc_flex(query, -1)
assert flex == 0
def test__scan_returns_none_w_empty_query(searcher: FuzzySearcher,
nlp: Language,
scan_example: Doc) -> None:
"""It returns None if passed an empty query string."""
query = nlp("")
assert (searcher._scan(
scan_example, query, fuzzy_func="simple", min_r1=25, ignore_case=True)
is None)
def test_match_finds_best_matches3(searcher: FuzzySearcher,
nlp: Language) -> None:
"""It returns all the fuzzy matches that meet threshold correctly sorted."""
doc = nlp("My favorite wine is white gold riesling.")
query = nlp("goldriesling")
assert searcher.match(doc, query, flex="max") == [
(5, 7, 96),
]
def test_match_finds_best_matches(searcher: FuzzySearcher,
nlp: Language) -> None:
"""It returns all the fuzzy matches that meet threshold correctly sorted."""
doc = nlp("chiken from Popeyes is better than chken from Chick-fil-A")
query = nlp("chicken")
assert searcher.match(doc, query, ignore_case=False) == [
(0, 1, 92),
(6, 7, 83),
]
def test__scan_returns_matches_over_min_r1(searcher: FuzzySearcher,
nlp: Language,
scan_example: Doc) -> None:
"""It returns all spans of len(query) in doc if ratio >= min_r1."""
query = nlp("Shirley")
assert searcher._scan(scan_example,
query,
fuzzy_func="simple",
min_r1=30,
ignore_case=True) == {
4: 86
}
def test__optimize_finds_better_match_with_max_flex(
searcher: FuzzySearcher, nlp: Language, adjust_example: Doc) -> None:
"""It optimizes the initial match to find a better match when flex = max."""
query = nlp("Kareem Abdul-Jabbar")
match_values = {0: 33, 1: 39, 2: 41, 3: 33, 5: 37, 6: 59, 7: 84}
assert searcher._optimize(
adjust_example,
query,
match_values,
pos=7,
fuzzy_func="simple",
min_r2=70,
ignore_case=True,
flex=4,
thresh=100,
) == (8, 11, 89)
def test__scan_returns_all_matches_with_no_min_r1(searcher: FuzzySearcher,
nlp: Language,
scan_example: Doc) -> None:
"""It returns all spans of len(query) in doc if min_r1 = 0."""
query = nlp("Shirley")
assert searcher._scan(scan_example,
query,
fuzzy_func="simple",
min_r1=0,
ignore_case=True) == {
0: 0,
1: 0,
2: 18,
3: 22,
4: 86
}
def test__optimize_with_no_flex(searcher: FuzzySearcher,
nlp: Language) -> None:
"""It returns the intial match when flex value = 0."""
doc = nlp("Patient was prescribed Zithroma tablets.")
query = nlp("zithromax")
match_values = {3: 94}
assert searcher._optimize(
doc,
query,
match_values,
pos=3,
fuzzy_func="simple",
min_r2=70,
ignore_case=True,
flex=0,
thresh=100,
) == (3, 4, 94)
def searcher(nlp: Language) -> FuzzySearcher:
"""It returns a fuzzy searcher."""
return FuzzySearcher(vocab=nlp.vocab)
def test_compare_without_ignore_case(searcher: FuzzySearcher,
nlp: Language) -> None:
"""Checks ignore_case is working."""
assert searcher.compare(nlp("SPACZZ"), nlp("spaczz"),
ignore_case=False) == 0
def test_compare_works_with_defaults(searcher: FuzzySearcher,
nlp: Language) -> None:
"""Checks compare is working as intended."""
assert searcher.compare(nlp("spaczz"), nlp("spacy")) == 73
def test_match_returns_empty_list_if_doc_query_empty(searcher: FuzzySearcher,
nlp: Language) -> None:
"""Returns empty list if doc is empty string."""
doc = nlp("")
query = nlp("")
assert searcher.match(doc, query) == []
def test__check_ratios_passes_valid_values_wo_flex(
searcher: FuzzySearcher) -> None:
"""It passes through valid ratios changing `min_r1` to equal `min_r2`."""
assert searcher._check_ratios(50, 75, 100, 0) == (75, 75, 100)
def test__calc_flex_with_min(nlp: Language, searcher: FuzzySearcher) -> None:
"""It returns 0 if set with "min"."""
query = nlp("Test query")
assert searcher._calc_flex(query, "min") == 0
def test__check_ratios_warns_if_thresh_less_min_r2(
searcher: FuzzySearcher) -> None:
"""It raises a `RatioWarning`."""
with pytest.warns(RatioWarning):
ratios = searcher._check_ratios(50, 75, 70, 1)
assert ratios == (50, 75, 75)
def test__check_ratios_passes_valid_values_w_flex(
searcher: FuzzySearcher) -> None:
"""It passes through valid ratios with no changes."""
assert searcher._check_ratios(50, 75, 100, 1) == (50, 75, 100)
def test__filter_overlapping_matches_filters_correctly(
searcher: FuzzySearcher, ) -> None:
"""It only returns the first match if more than one encompass the same tokens."""
matches = [(1, 2, 80), (1, 3, 70)]
assert searcher._filter_overlapping_matches(matches) == [(1, 2, 80)]
def test__optimize_where_bpl_would_equal_bpr(searcher: FuzzySearcher,
nlp: Language) -> None:
"""It returns the intial match when flex value = 0."""
doc = nlp("trabalho, investimento e escolhas corajosas,")
query = nlp("Courtillier Musqué")
assert searcher.match(doc, query, flex="max") == []
def test__calc_flex_with_default(nlp: Language,
searcher: FuzzySearcher) -> None:
"""It returns len(query) // 2 if set with "default"."""
query = nlp("Test query")
assert searcher._calc_flex(query, "default") == 1
def test__calc_flex_with_max(nlp: Language, searcher: FuzzySearcher) -> None:
"""It returns len(query) if set with "max"."""
query = nlp("Test query two")
assert searcher._calc_flex(query, "max") == 3
def test_match_return_empty_list_when_no_matches_after_adjust(
searcher: FuzzySearcher, nlp: Language) -> None:
"""It returns an empty list if no fuzzy matches meet min_r2 threshold."""
doc = nlp("G-rant Anderson lives in TN.")
query = nlp("Garth, Anderdella")
assert searcher.match(doc, query) == []
def test__calc_flex_passes_through_valid_value(
nlp: Language, searcher: FuzzySearcher) -> None:
"""It passes through a valid flex value (<= len(query))."""
query = nlp("Test query")
assert searcher._calc_flex(query, 0) == 0
def test__check_ratios_warns_if_minr1_greater_min_r2(
searcher: FuzzySearcher) -> None:
"""It raises a `RatioWarning`."""
with pytest.warns(RatioWarning):
ratios = searcher._check_ratios(80, 75, 100, 1)
assert ratios == (75, 75, 100)
def test__calc_flex_raises_error_if_non_valid_value(
nlp: Language, searcher: FuzzySearcher) -> None:
"""It raises TypeError if flex is not an int or "default"."""
query = nlp("Test query.")
with pytest.raises(TypeError):
searcher._calc_flex(query, None) # type: ignore
def test__check_ratios_ignores_issues_wo_flex(searcher: FuzzySearcher) -> None:
"""Changes `min_r1` to equal `min_r2` but ignores unnecessary `thresh`."""
assert searcher._check_ratios(80, 75, 70, 0) == (75, 75, 70)