def test_classification_search_given_raw_data_returns_data_for_builders_v2():
# Given
# a classification search with a simple classifications
standardiser = pet_standardiser()
classification_collection = ethnicity_classification_collection_from_classification_list(
[ethnicity_classification_with_cats_and_dogs_data()])
classification_finder = EthnicityClassificationFinder(
standardiser, classification_collection)
# When
# we search with data that will fit the classification
raw_values = ["FELINE", "Canine "]
search_outputs = classification_finder.find_classifications(raw_values)
# Then
# we expect the data section will contain data needed to display
first_classification_data = search_outputs[0]["data"]
expected = [
{
"raw_value": "FELINE",
"standard_value": "Cat",
"display_value": "Cat",
"parent": "Cat",
"order": 1
},
{
"raw_value": "Canine ",
"standard_value": "Dog",
"display_value": "Dog",
"parent": "Dog",
"order": 2
},
]
assert expected == first_classification_data
def build_external_classification_collection():
return ethnicity_classification_collection_from_classification_list(
[
get_external_classification_simple(),
get_complex_external_classification_with_parents_and_optionals(),
get_complex_external_classification_without_parents(),
]
)
def test_synchronise_saves_only_one_internal_classification_for_external_pair_with_and_without_parents(
):
# given a synchroniser
synchroniser = reset_test_synchroniser()
# when we synchronise with 5A and 5A+ (which are a pair with and without parent values)
classification_collection = ethnicity_classification_collection_from_classification_list(
[get_5A(), get_5A_plus()])
synchroniser.synchronise_classifications(classification_collection)
# then we have a classification link
assert len(internal_classification_service.get_all_classifications()) == 1
def test_synchronise_adds_external_classifications_to_internal_classification_service(
):
# given a synchroniser
synchroniser = reset_test_synchroniser()
# when we synchronise with a very simple categorisation list
classification_collection = ethnicity_classification_collection_from_classification_list(
[get_2A()])
synchroniser.synchronise_classifications(classification_collection)
# a classification is saved to the
assert len(internal_classification_service.get_all_classifications()) == 1
def test_synchronise_saves_overwrites_internal_classification_name():
# given a synchroniser
synchroniser = reset_test_synchroniser()
# when we synchronise values with a simple classification collection from external classification 2A
classification_collection = ethnicity_classification_collection_from_classification_list(
[get_2A()])
synchroniser.synchronise_classifications(classification_collection)
# then we have an internal classification from 2A with expected name
classification_2a = internal_classification_service.get_classification_by_id(
"2A")
assert classification_2a.title == "White and Other"
# when we now synchronise values with a version of 2A with an alternate name
alt_collection = ethnicity_classification_collection_from_classification_list(
[get_2A_named_test_example()])
synchroniser.synchronise_classifications(alt_collection)
# then the internal classification now has the new expected name
classification_2a = internal_classification_service.get_classification_by_id(
"2A")
assert classification_2a.title == "test example"
def test_classification_collection_identifies_valid_classification():
# GIVEN
# a simple classification collect
classification = ethnicity_classification_with_cats_and_dogs_data()
classification_collection = ethnicity_classification_collection_from_classification_list([classification])
standardiser = pet_standardiser()
raw_values = ["Cat", "Dog"]
# WHEN
# we request valid classifications
valid_classifications = classification_collection.get_valid_classifications(raw_values, standardiser)
# THEN
# we expect our
assert 1 == len(valid_classifications)
assert classification.get_id() == valid_classifications[0].get_id()
def test_classification_collection_will_not_return_invalid_classifications():
# GIVEN
# a collection with two classifications and raw_values that could apply to only the first
classification_1 = ethnicity_classification_with_required_fish_cat_and_dog_data()
classification_2 = ethnicity_classification_with_required_fish_and_mammal_data()
classification_collection = ethnicity_classification_collection_from_classification_list(
[classification_1, classification_2]
)
standardiser = pet_standardiser()
raw_values = ["Cat", "Dog", "Fish"]
# WHEN
# we request valid classifications
valid_classifications = classification_collection.get_valid_classifications(raw_values, standardiser)
# THEN
# only 1 classification is returned
assert 1 == len(valid_classifications)
def test_classification_collection_can_return_multiple_valid_classifications():
# GIVEN
# a collection with two classifications and raw_values that could apply to either
classification_1 = ethnicity_classification_with_required_fish_cat_and_dog_data()
classification_2 = ethnicity_classification_with_required_fish_and_mammal_data()
classification_collection = ethnicity_classification_collection_from_classification_list(
[classification_1, classification_2]
)
standardiser = pet_standardiser()
raw_values = ["Cat", "Dog", "Fish", "Mammal"]
# WHEN
# we request valid classifications
valid_classifications = classification_collection.get_valid_classifications(raw_values, standardiser)
# THEN
# we 2 classifications to have been returned
assert 2 == len(valid_classifications)
def test_classification_search_given_raw_data_returns_only_output_for_valid_classifications():
# Given
# a classification search with multiple classifications
standardiser = pet_standardiser()
classification_collection = ethnicity_classification_collection_from_classification_list(
[
ethnicity_classification_with_required_fish_and_mammal_data(),
ethnicity_classification_with_required_fish_cat_and_dog_data(),
]
)
classification_finder = EthnicityClassificationFinder(standardiser, classification_collection)
# When
# we search with data that will fit only one classification
raw_values = ["Cat", "Dog", "Fish"]
search_outputs = classification_finder.find_classifications(raw_values)
# Then
# we expect output from one classification will be returned (plus the custom classification)
assert 2 == len(search_outputs)
