def test_estimator_persistance_without_factory(self):
m = Estimator(estimator='new string', description='another object')
assert m.object_file.storage.exists(m.object_file.path) == False
assert m.is_file_persisted == False
m.save()
assert m.object_file.storage.exists(m.object_file.path) == True
assert m.is_file_persisted == True
def test_update_estimator_fail(self):
m = Estimator(estimator='uneditable_object')
m.estimator = 'object_edited_before_persistance'
m.save()
m.estimator = 'object_edited_after_persistance'
with pytest.raises(ValidationError):
m.save()
def persist_results(self, er):
er._estimator_proxy = Estimator.get_or_create(
er._estimator_proxy.estimator)
er._X_test_proxy = DataSet.get_or_create(er._X_test_proxy.data)
er._y_test_proxy = DataSet.get_or_create(er._y_test_proxy.data)
er._y_predicted_proxy = DataSet.get_or_create(
er._y_predicted_proxy.data)
er.save()
def test_create_from_file_with_factory(self):
obj = "{'key': 'value'}"
m = EstimatorFactory(estimator=obj)
object_hash = m.object_hash
file_path = m.object_file.name
del m
m = Estimator.create_from_file(file_path)
assert m.estimator == obj
assert m.object_hash == object_hash
assert m.is_file_persisted == True
def test_object_hash_with_factory(self):
m = EstimatorFactory(estimator=object)
assert m.estimator == object
del m
n = Estimator.objects.filter(estimator=object).first()
# sklearn hash of a object = 'd9c9f286391652b89978a6961b52b674'
assert n.object_hash == 'd9c9f286391652b89978a6961b52b674'
# assert loaded after calling n.estimator
assert n.estimator == object
assert Estimator._compute_hash(
object) == 'd9c9f286391652b89978a6961b52b674'
def test_load_records(self):
with self.settings(MEDIA_ROOT=self.tmp_dir.name):
kept = Estimator(estimator='object to be kept3')
kept.save()
no_obj = Estimator(estimator='object to be deleted3')
no_obj.save()
no_file = Estimator(estimator='file to be deleted3')
no_file.save()
filename = no_obj.object_file.name
no_obj.delete()
del no_obj
os.remove(
os.path.join(
self.tmp_dir.name,
no_file.object_file.name))
del no_file
# run tests
unreferenced_files = Estimator.objects.unreferenced_files()
total_count = Estimator.objects.count()
self.assertEqual(unreferenced_files, {filename})
num = Estimator.load_unreferenced_files()
self.assertEqual(num, 1)
new_unreferenced_files = Estimator.objects.unreferenced_files()
new_total_count = Estimator.objects.count()
self.assertEqual(new_total_count, total_count + 1)
# Note this does not reflect the original file. Instead it makes a
# duplicate file.
self.assertEqual(len(unreferenced_files),
len(new_unreferenced_files))
def test_empty_records(self):
with self.settings(MEDIA_ROOT=self.tmp_dir.name):
kept = Estimator(estimator='object to be kept2')
kept.save()
no_obj = Estimator(estimator='object to be deleted2')
no_obj.save()
no_file = Estimator(estimator='file to be deleted2')
no_file.save()
no_obj.delete()
del no_obj
os.remove(
os.path.join(
self.tmp_dir.name,
no_file.object_file.name))
# run tests
all_estimators = Estimator.objects.empty_records()
self.assertEqual(
all_estimators[0].object_hash, no_file.object_hash)
deletion = Estimator.delete_empty_records()
self.assertEqual(deletion[0], 1)
all_estimators = Estimator.objects.empty_records()
self.assertEqual(len(all_estimators), 0)
def test_unreferenced_files(self):
with self.settings(MEDIA_ROOT=self.tmp_dir.name):
kept = Estimator(estimator='object to be kept1')
kept.save()
no_obj = Estimator(estimator='object to be deleted1')
no_obj.save()
no_file = Estimator(estimator='file to be deleted1')
no_file.save()
filename = no_obj.object_file.name
no_obj.delete()
del no_obj
os.remove(
os.path.join(
self.tmp_dir.name,
no_file.object_file.name))
del no_file
# run tests
all_files = Estimator.objects.unreferenced_files()
self.assertEqual(all_files, {filename})
num = Estimator.delete_unreferenced_files()
self.assertEqual(num, 1)
all_files = Estimator.objects.unreferenced_files()
self.assertEqual(len(all_files), 0)
def test_wrong_hash_fail(self):
m = Estimator(estimator='unique_object')
m.object_hash = 'randomly set hash'
with pytest.raises(ValidationError):
m.save()
def test_hash_without_estimator_fail(self):
m = Estimator()
m.object_hash = 'randomly set hash'
with pytest.raises(ValidationError):
m.save()
def test_hashing_func(self):
object_hash = Estimator._compute_hash('abcd')
assert object_hash == '3062a9e3345c129799bd2c1603c2e966'