def test_companion_recommendation(self):
obj = RecommendationValidator.load_package_list_local(
self.input_folder_name, self.additional_path, self.input_ecosystem)
obj = RecommendationValidator.load_package_list_local(
self.input_folder_name, self.additional_path, self.input_ecosystem)
input_list = ['A', 'B', 'C', 'D']
recommended_dependency_set = set(['A', 'B', 'C', 'D', 'E'])
diff_list = obj.check_companion_recommendation_validity(
recommended_dependency_set, input_list)
self.assertTrue(len(diff_list) == 3)
self.assertTrue(diff_list == ['E', 'E', 'F'])
recommended_dependency_set = set(['A', 'B', 'C', 'D', 'Q'])
diff_list = obj.check_companion_recommendation_validity(
recommended_dependency_set, input_list)
self.assertTrue(len(diff_list) == 0)
def test_check_companion_recommendation(self):
"""Test the method check_companion_recommendation()."""
obj = RecommendationValidator.load_package_list_local(
self.input_folder_name, self.additional_path)
input_list = ['A', 'B', 'C', 'D']
companion_packages = [
{
"cooccurrence_probability": 0.49942501008907109,
"package_name": "E",
"topic_list": ["some_topic"]
},
{
"cooccurrence_probability": 0.42699967636612329,
"package_name": "F",
"topic_list": ["some_topic"]
},
{
"cooccurrence_probability": 0.42699967636612329,
"package_name": "G",
"topic_list": ["some_topic"]
}
]
result_companion_list = obj.check_companion_recommendation(
input_list, companion_packages)
self.assertTrue(len(result_companion_list) == 2)
comp_name = [c.get('package_name') for c in result_companion_list]
self.assertEqual(set(comp_name), {'E', 'F'})
comp_confidence = [c.get('cooccurrence_probability')
for c in result_companion_list]
self.assertEqual(set(comp_confidence), {100, 50})
def test_load_manifest_file(self):
"""Test if package list can be deserialized properly."""
obj = RecommendationValidator.load_package_list_local(
self.input_folder_name, self.additional_path)
self.assertTrue(obj is not None)
self.assertTrue(isinstance(obj, RecommendationValidator))
self.assertTrue(obj.manifest_len == 4)
def test_check_alternate_recommendation(self):
"""Test the method check_alternate_recommendation()."""
obj = RecommendationValidator.load_package_list_local(
self.input_folder_name, self.additional_path)
input_list = ['A', 'B', 'C', 'D']
alternate_packages = {
"B": [
{
"package_name": "E",
"similarity_score": 0.75,
"topic_list": ["some_topic"]
},
{
"package_name": "P",
"similarity_score": 0.75,
"topic_list": ["some_topic"]
}
]
}
result_alternate_list = obj.check_alternate_recommendation(
input_list, alternate_packages)
self.assertTrue(len(result_alternate_list) == 1)
self.assertTrue(result_alternate_list.get(
'B', [{'test': 'failed'}])[0].get('package_name') == 'E')
self.assertTrue(result_alternate_list.get(
'B', [{'test': 'failed'}])[0].get('similarity_score') == 2)
def test_score_eco_user_package_dict(self):
"""Test the dependency dict deserialization, frequency list deserialization etc."""
input_data_store = LocalFileSystem(
"tests/data/data_pgm/input-score-data/")
self.assertIsNotNone(input_data_store)
output_data_store = LocalFileSystem(
"tests/data/data_pgm/output-score-data/")
self.assertIsNotNone(output_data_store)
frequency_dict_data_store = LocalFileSystem(
src_dir="tests/data/data_apollo/")
self.assertIsNotNone(frequency_dict_data_store)
user_eco_kronos_dict = load_user_eco_to_kronos_model_dict(
input_kronos_data_store=input_data_store, additional_path="")
self.assertIsNotNone(user_eco_kronos_dict)
eco_to_kronos_dependency_dict = get_eco_to_kronos_dependency_dict(
data_store=input_data_store, folderpath="data_kronos_dependency")
self.assertIsNotNone(eco_to_kronos_dependency_dict)
user_request = [{
"ecosystem": "pypi",
"comp_package_count_threshold": 10,
"alt_package_count_threshold": 1,
"outlier_probability_threshold": 0.61,
"unknown_packages_ratio_threshold": 0.4,
"outlier_package_count_threshold": 2,
"package_list": ["p1", "p2", "p3", "np1"]
}]
frequency_dict = frequency_dict_data_store.read_json_file(
filename=KD_PACKAGE_FREQUENCY)
self.assertIsNotNone(frequency_dict)
all_package_list_obj = RecommendationValidator.load_package_list_local(
input_folder_name="tests/data/data_recom_valid/",
additional_path="")
response = score_eco_user_package_dict(
user_request,
user_eco_kronos_dict=user_eco_kronos_dict,
eco_to_kronos_dependency_dict=eco_to_kronos_dependency_dict,
all_package_list_obj=all_package_list_obj,
package_frequency_dict=frequency_dict,
use_filters=USE_FILTERS)
self.assertIsNotNone(response)
output_data_store.write_json_file(filename="response.json",
contents=response)
expected_response = output_data_store.read_json_file(
filename="expected_response.json")
self.assertIsNotNone(expected_response)
self.assertDictEqual(response[0], expected_response[0])
def test_generate_companion_set(self):
obj = RecommendationValidator.load_package_list_local(
self.input_folder_name, self.additional_path)
input_list = ['A', 'B', 'C']
companion_package = 'D'
comp_set = obj.generate_companion_dependency_set(
input_list, companion_package)
self.assertEqual(comp_set, {'A', 'B', 'C', 'D'})
def test_filter_input_list(self):
obj = RecommendationValidator.load_package_list_local(
self.input_folder_name, self.additional_path)
input_set = {'A', 'B', 'C', 'Z'}
missing_packages = ['Z']
filtered_input_list = obj.get_filtered_input_list(
input_set, missing_packages)
self.assertTrue(sorted(filtered_input_list) == ['A', 'B', 'C'])
def test_filter_input_list(self):
obj = RecommendationValidator.load_package_list_local(
self.input_folder_name, self.additional_path, self.input_ecosystem)
input_list = ['A', 'B', 'C', 'Z']
missing_packages = ['Z']
filtered_input_list = obj.get_filtered_input_list(
input_list, missing_packages)
self.assertTrue(filtered_input_list == ['A', 'B', 'C'])
def test_generate_alternate_set(self):
obj = RecommendationValidator.load_package_list_local(
self.input_folder_name, self.additional_path)
input_list = ['A', 'B', 'C']
alternate_package = 'B123'
alternate_to = 'B'
alt_set = obj.generate_alternate_dependency_set(
input_list, alternate_package, alternate_to)
self.assertEqual(alt_set, {'A', 'B123', 'C'})
def test_companion_recommendation(self):
obj = RecommendationValidator.load_package_list_local(
self.input_folder_name, self.additional_path)
recommended_dependency_set = {'A', 'B', 'C', 'D', 'E'}
count = obj.check_companion_or_alternate_recommendation_validity(recommended_dependency_set)
self.assertEqual(count, 2)
recommended_dependency_set = {'A', 'B', 'C', 'D', 'Q'}
count = obj.check_companion_or_alternate_recommendation_validity(recommended_dependency_set)
self.assertEqual(count, 0)
def test_filter_alternate_list(self):
"""Test the method to get filtered alternate list."""
obj = RecommendationValidator.load_package_list_local(
self.input_folder_name, self.additional_path)
outlier_packages = [{
"outlier_prbability": 0.99434381708188857,
"package_name": "A",
"topic_list": [
"some_topic",
"some_topic"
]
}]
alternate_packages = {
"B": [
{
"package_name": "Q",
"similarity_score": 0.75,
"topic_list": ["some_topic"]
},
{
"package_name": "R",
"similarity_score": 0.75,
"topic_list": ["some_topic"]
}
],
"C": [
{
"package_name": "Q",
"similarity_score": 0.75,
"topic_list": ["some_topic"]
},
{
"package_name": "R",
"similarity_score": 0.75,
"topic_list": ["some_topic"]
}
],
"A": [
{
"package_name": "Q",
"similarity_score": 0.75,
"topic_list": ["some_topic"]
},
{
"package_name": "R",
"similarity_score": 0.75,
"topic_list": ["some_topic"]
}
]
}
filtered_alternate_list = obj.get_filtered_alternate_list(
alternate_packages, outlier_packages)
self.assertTrue(len(filtered_alternate_list) == len(outlier_packages))
self.assertTrue(outlier_packages[0][
'package_name'] == list(filtered_alternate_list.keys())[0])
def test_alternate_recommendation(self):
obj = RecommendationValidator.load_package_list_local(
self.input_folder_name, self.additional_path, self.input_ecosystem)
recommended_dependency_set = set(['A', 'F', 'C', 'D'])
count = obj.check_alternate_recommendation_validity(
recommended_dependency_set)
self.assertTrue(count == 2)
recommended_dependency_set = set(['A', 'W', 'C', 'D'])
count = obj.check_alternate_recommendation_validity(
recommended_dependency_set)
self.assertTrue(count == 0)
def __init__(self):
"""Initialize this class."""
super(CompanionOutlierAccuracy, self).__init__()
self.user_eco_kronos_dict = load_user_eco_to_kronos_model_dict_s3(
bucket_name=AWS_BUCKET_NAME, additional_path=KRONOS_MODEL_PATH)
self.package_frequency_dict = load_package_frequency_dict_s3(
bucket_name=AWS_BUCKET_NAME, additional_path=KRONOS_MODEL_PATH)
self.all_package_list_obj = RecommendationValidator.load_package_list_s3(
input_bucket_name=AWS_BUCKET_NAME, additional_path=KRONOS_MODEL_PATH)
self.test_set = set()
self.unique_items_len = 0
def test_check_companion_recommendation(self):
obj = RecommendationValidator.load_package_list_local(
self.input_folder_name, self.additional_path, self.input_ecosystem)
input_list = ['A', 'B', 'C', 'D']
companion_packages = [{
"cooccurrence_probability": 0.49942501008907109,
"package_name": "E",
"topic_list": ["some_topic"]
}, {
"cooccurrence_probability": 0.42699967636612329,
"package_name": "F",
"topic_list": ["some_topic"]
}, {
"cooccurrence_probability": 0.42699967636612329,
"package_name": "G",
"topic_list": ["some_topic"]
}]
result_companion_list = obj.check_companion_recommendation(
input_list, companion_packages)
self.assertTrue(len(result_companion_list) == 2)
comp_name = [c.get('package_name') for c in result_companion_list]
self.assertTrue(set(comp_name) == set(['E', 'F']))
global user_eco_kronos_dict
global eco_to_kronos_dependency_dict
global scoring_status
global all_package_list_obj
hash_dict = dict()
if KRONOS_SCORING_REGION != "":
app.user_eco_kronos_dict = load_user_eco_to_kronos_model_dict_s3(
bucket_name=AWS_BUCKET_NAME, additional_path=KRONOS_MODEL_PATH)
app.eco_to_kronos_dependency_dict = load_eco_to_kronos_dependency_dict_s3(
bucket_name=AWS_BUCKET_NAME, additional_path=KRONOS_MODEL_PATH)
app.all_package_list_obj = RecommendationValidator.load_package_list_s3(
AWS_BUCKET_NAME, KRONOS_MODEL_PATH)
app.package_frequency_dict = load_package_frequency_dict_s3(
bucket_name=AWS_BUCKET_NAME, additional_path=KRONOS_MODEL_PATH)
app.scoring_status = True
app.logger.info("The total manifest file for this ecosystem are: %d" %
app.all_package_list_obj.get_all_list_package_length())
else:
app.scoring_status = False
@app.before_request
def before_request():
g.request_start = datetime.datetime.utcnow()
def test_load_manifest_file(self):
obj = RecommendationValidator.load_package_list_local(
self.input_folder_name, self.additional_path)
self.assertTrue(obj is not None)
self.assertTrue(isinstance(obj, RecommendationValidator))
self.assertTrue(obj.manifest_len == 4)