def test_can_recommend(test_ctx, caplog):
caplog.set_level(logging.INFO)
# Create a new instance of a SimilarityRecommender.
ctx = install_continuous_data(test_ctx)
r = SimilarityRecommender(ctx)
assert check_matrix_built(caplog)
# Test that we can't recommend if we have not enough client info.
assert not r.can_recommend({})
# Test that we can recommend for a normal client.
assert r.can_recommend(generate_a_fake_taar_client())
# Check that we can not recommend if any required client field is missing.
required_fields = CATEGORICAL_FEATURES + CONTINUOUS_FEATURES
for required_field in required_fields:
profile_without_x = generate_a_fake_taar_client()
# Make an empty value in a required field in the client info dict.
profile_without_x[required_field] = None
assert not r.can_recommend(profile_without_x)
# Completely remove (in place) the entire required field from the dict.
del profile_without_x[required_field]
assert not r.can_recommend(profile_without_x)
def test_soft_fail(test_ctx, caplog):
# Create a new instance of a SimilarityRecommender.
with mock_install_no_data(test_ctx):
r = SimilarityRecommender(test_ctx)
# Don't recommend if the source files cannot be found.
assert not r.can_recommend({})
def test_soft_fail(test_ctx, caplog):
# Create a new instance of a SimilarityRecommender.
ctx = install_no_data(test_ctx)
r = SimilarityRecommender(ctx)
# Don't recommend if the source files cannot be found.
assert not r.can_recommend({})
assert not check_matrix_built(caplog)
def test_soft_fail():
# Create a new instance of a SimilarityRecommender.
ctx = Context()
ctx['utils'] = MockNoDataUtils()
ctx['clock'] = Clock()
ctx['cache'] = JSONCache(ctx)
r = SimilarityRecommender(ctx)
# Don't recommend if the source files cannot be found.
assert not r.can_recommend({})
def test_can_recommend(instantiate_mocked_s3_bucket):
# Create a new instance of a SimilarityRecommender.
r = SimilarityRecommender()
# Test that we can't recommend if we have not enough client info.
assert not r.can_recommend({})
# Test that we can recommend for a normal client.
assert r.can_recommend(generate_a_fake_taar_client())
# Check that we can not recommend if any required client field is missing.
required_fields = CATEGORICAL_FEATURES + CONTINUOUS_FEATURES
for required_field in required_fields:
profile_without_x = generate_a_fake_taar_client()
# Make an empty value in a required field in the client info dict.
profile_without_x[required_field] = None
assert not r.can_recommend(profile_without_x)
# Completely remove (in place) the entire required field from the dict.
del profile_without_x[required_field]
assert not r.can_recommend(profile_without_x)
def test_soft_fail():
# Create a new instance of a SimilarityRecommender.
r = SimilarityRecommender()
# Don't recommend if the source files cannot be found.
assert not r.can_recommend({})