def _load_datasets(self):
"""
Load five persons data for each test hpo
"""
# expected_tables is for testing output
# it maps table name to list of expected records ex: "unioned_ehr_visit_occurrence" -> [{}, {}, ...]
expected_tables = dict()
running_jobs = []
for cdm_table in common.CDM_TABLES:
cdm_file_name = os.path.join(test_util.FIVE_PERSONS_PATH,
cdm_table + '.csv')
output_table = ehr_union.output_table_for(cdm_table)
expected_tables[output_table] = []
for hpo_id in self.hpo_ids:
# upload csv into hpo bucket
bucket = gcs_utils.get_hpo_bucket(hpo_id)
if os.path.exists(cdm_file_name):
test_util.write_cloud_file(bucket, cdm_file_name)
csv_rows = resources._csv_to_list(cdm_file_name)
else:
# results in empty table
test_util.write_cloud_str(bucket, cdm_table + '.csv',
'dummy\n')
csv_rows = []
# load table from csv
result = bq_utils.load_cdm_csv(hpo_id, cdm_table)
running_jobs.append(result['jobReference']['jobId'])
expected_tables[output_table] += list(csv_rows)
incomplete_jobs = bq_utils.wait_on_jobs(running_jobs)
if len(incomplete_jobs) > 0:
message = "Job id(s) %s failed to complete" % incomplete_jobs
raise RuntimeError(message)
self.expected_tables = expected_tables
def test_copy_five_persons(self, mock_check_cron):
folder_prefix = 'dummy-prefix-2018-03-22-v1/'
# upload all five_persons files
for cdm_file in test_util.FIVE_PERSONS_FILES:
test_util.write_cloud_file(self.hpo_bucket,
cdm_file,
prefix=folder_prefix)
test_util.write_cloud_file(self.hpo_bucket,
cdm_file,
prefix=folder_prefix + folder_prefix)
main.app.testing = True
with main.app.test_client() as c:
c.get(test_util.COPY_HPO_FILES_URL)
prefix = test_util.FAKE_HPO_ID + '/' + self.hpo_bucket + '/' + folder_prefix
expected_bucket_items = [
prefix + item.split(os.sep)[-1]
for item in test_util.FIVE_PERSONS_FILES
]
expected_bucket_items.extend([
prefix + folder_prefix + item.split(os.sep)[-1]
for item in test_util.FIVE_PERSONS_FILES
])
list_bucket_result = gcs_utils.list_bucket(
gcs_utils.get_drc_bucket())
actual_bucket_items = [item['name'] for item in list_bucket_result]
self.assertSetEqual(set(expected_bucket_items),
set(actual_bucket_items))
def _load_datasets(self):
load_jobs = []
self.expected_tables = dict()
for cdm_table in common.CDM_TABLES:
cdm_file_name = os.path.join(test_util.FIVE_PERSONS_PATH,
cdm_table + '.csv')
result_table = ehr_merge.result_table_for(cdm_table)
if os.path.exists(cdm_file_name):
# one copy for chs, the other for pitt
csv_rows = resources._csv_to_list(cdm_file_name)
self.expected_tables[result_table] = csv_rows + list(csv_rows)
test_util.write_cloud_file(self.chs_bucket, cdm_file_name)
test_util.write_cloud_file(self.pitt_bucket, cdm_file_name)
else:
self.expected_tables[result_table] = []
test_util.write_cloud_str(self.chs_bucket, cdm_table + '.csv',
'dummy\n')
test_util.write_cloud_str(self.pitt_bucket, cdm_table + '.csv',
'dummy\n')
chs_load_results = bq_utils.load_cdm_csv(CHS_HPO_ID, cdm_table)
pitt_load_results = bq_utils.load_cdm_csv(PITT_HPO_ID, cdm_table)
chs_load_job_id = chs_load_results['jobReference']['jobId']
pitt_load_job_id = pitt_load_results['jobReference']['jobId']
load_jobs.append(chs_load_job_id)
load_jobs.append(pitt_load_job_id)
incomplete_jobs = bq_utils.wait_on_jobs(load_jobs)
if len(incomplete_jobs) > 0:
raise RuntimeError('BigQuery jobs %s failed to complete' %
incomplete_jobs)
def _load_dataset(self):
for cdm_table in common.CDM_TABLES:
cdm_file_name = os.path.join(test_util.FIVE_PERSONS_PATH, cdm_table + '.csv')
if os.path.exists(cdm_file_name):
test_util.write_cloud_file(self.hpo_bucket, cdm_file_name)
else:
test_util.write_cloud_str(self.hpo_bucket, cdm_table + '.csv', 'dummy\n')
bq_utils.load_cdm_csv(FAKE_HPO_ID, cdm_table)
def test_validate_five_persons_success(self, mock_check_cron):
prefix = 'dummy-prefix-2018-03-22/'
expected_result_items = resources._csv_to_list(
test_util.FIVE_PERSONS_SUCCESS_RESULT_CSV)
json_export_files = self.get_json_export_files(test_util.FAKE_HPO_ID)
# upload all five_persons files
for cdm_file in test_util.FIVE_PERSONS_FILES:
test_util.write_cloud_file(self.hpo_bucket,
cdm_file,
prefix=prefix)
expected_tables = [
'person', 'visit_occurrence', 'condition_occurrence',
'procedure_occurrence', 'drug_exposure', 'measurement'
]
cdm_files = [table + '.csv' for table in expected_tables]
main.app.testing = True
with main.app.test_client() as c:
c.get(test_util.VALIDATE_HPO_FILES_URL)
# check the result file was put in bucket
expected_object_names = cdm_files + common.IGNORE_LIST + json_export_files
expected_objects = [
prefix + item for item in expected_object_names
]
list_bucket_result = gcs_utils.list_bucket(self.hpo_bucket)
actual_objects = [item['name'] for item in list_bucket_result]
self.assertSetEqual(set(expected_objects), set(actual_objects))
# result says file found, parsed, loaded
actual_result = test_util.read_cloud_file(
self.hpo_bucket, prefix + common.RESULT_CSV)
actual_result_file = StringIO.StringIO(actual_result)
actual_result_items = resources._csv_file_to_list(
actual_result_file)
expected_result_items.sort()
actual_result_items.sort()
self.assertListEqual(expected_result_items, actual_result_items)
self.assertTrue(
main.all_required_files_loaded(test_util.FAKE_HPO_ID,
folder_prefix=prefix))
# check tables exist and are clustered as expected
for table in expected_tables:
fields_file = os.path.join(resources.fields_path, table + '.json')
table_id = bq_utils.get_table_id(test_util.FAKE_HPO_ID, table)
table_info = bq_utils.get_table_info(table_id)
with open(fields_file, 'r') as fp:
fields = json.load(fp)
field_names = [field['name'] for field in fields]
if 'person_id' in field_names:
self.table_has_clustering(table_info)
def test_validate_five_persons_success(self, mock_check_cron):
prefix = 'dummy-prefix-2018-03-22/'
expected_result_items = resources._csv_to_list(
test_util.FIVE_PERSONS_SUCCESS_RESULT_CSV)
json_export_files = self.get_json_export_files(test_util.FAKE_HPO_ID)
# upload all five_persons files
for cdm_file in test_util.FIVE_PERSONS_FILES:
test_util.write_cloud_file(self.hpo_bucket,
cdm_file,
prefix=prefix)
main.app.testing = True
with main.app.test_client() as c:
c.get(test_util.VALIDATE_HPO_FILES_URL)
# check the result file was putin bucket
expected_bucket_items = common.REQUIRED_FILES + common.IGNORE_LIST + json_export_files
# want to keep this test the same. So adding all the old required files.
expected_bucket_items = expected_bucket_items + [
'measurement.csv', 'procedure_occurrence.csv',
'drug_exposure.csv', 'condition_occurrence.csv',
'visit_occurrence.csv'
]
expected_bucket_items = [
prefix + item for item in expected_bucket_items
]
list_bucket_result = gcs_utils.list_bucket(self.hpo_bucket)
actual_bucket_items = [item['name'] for item in list_bucket_result]
self.assertSetEqual(set(expected_bucket_items),
set(actual_bucket_items))
# result says file found, parsed, loaded
actual_result = test_util.read_cloud_file(
self.hpo_bucket, prefix + common.RESULT_CSV)
actual_result_file = StringIO.StringIO(actual_result)
actual_result_items = resources._csv_file_to_list(
actual_result_file)
expected_result_items.sort()
actual_result_items.sort()
self.assertListEqual(expected_result_items, actual_result_items)
self.assertTrue(
main.all_required_files_loaded(test_util.FAKE_HPO_ID,
folder_prefix=prefix))
def test_five_person_data_retraction(self):
folder_prefix = 'dummy-prefix-2018-03-22/'
pid = 17
expected_result = {}
for file_path in test_util.FIVE_PERSONS_FILES:
# generate results files
file_name = file_path.split('/')[-1]
expected_result[file_name] = []
with open(file_path) as f:
for line in f:
line = line.strip()
if (file_name in rd.PID_IN_COL1 and rd.get_integer(line.split(",")[0]) != pid) or \
(file_name in rd.PID_IN_COL2 and rd.get_integer(line.split(",")[1]) != pid):
expected_result[file_name].append(line)
# write file to cloud for testing
test_util.write_cloud_file(self.hpo_bucket,
file_path,
prefix=folder_prefix)
with mock.patch('__builtin__.raw_input',
return_value='Y') as _raw_input:
retract_result = rd.run_retraction(pid,
self.hpo_bucket,
folder=folder_prefix,
force=True)
actual_result = {}
for file_path in test_util.FIVE_PERSONS_FILES:
file_name = file_path.split('/')[-1]
actual_result_contents = test_util.read_cloud_file(
self.hpo_bucket, folder_prefix + file_name)
# convert to list and remove last list item since it is a newline
actual_result[file_name] = actual_result_contents.split('\n')[:-1]
for key in expected_result.keys():
self.assertListEqual(expected_result[key], actual_result[key])
# metadata for each updated file is returned
# TODO test that files lacking records for PID are not updated
self.assertEqual(len(retract_result[folder_prefix]),
len(expected_result.keys()))
def load_test_data(self, hpo_id=None):
"""
Load to bq test achilles heel results data from csv file
:param hpo_id: if specified, prefix to use on csv test file and bq table, otherwise no prefix is used
:return: contents of the file as list of objects
"""
schema_path = os.path.join(resources.fields_path,
common.ACHILLES_HEEL_RESULTS + '.json')
table_id = common.ACHILLES_HEEL_RESULTS
if hpo_id is not None:
table_id = bq_utils.get_table_id(hpo_id,
common.ACHILLES_HEEL_RESULTS)
test_file_name = table_id + '.csv'
test_file_path = os.path.join(test_util.TEST_DATA_PATH, test_file_name)
test_util.write_cloud_file(self.bucket, test_file_path)
gcs_path = 'gs://' + self.bucket + '/' + test_file_name
load_results = bq_utils.load_csv(schema_path, gcs_path, self.app_id,
self.dataset_id, table_id)
job_id = load_results['jobReference']['jobId']
bq_utils.wait_on_jobs([job_id])
return resources._csv_to_list(test_file_path)
def _load_datasets(self):
load_jobs = []
for cdm_table in common.CDM_TABLES:
cdm_file_name = os.path.join(test_util.FIVE_PERSONS_PATH,
cdm_table + '.csv')
if os.path.exists(cdm_file_name):
test_util.write_cloud_file(self.chs_bucket, cdm_file_name)
test_util.write_cloud_file(self.pitt_bucket, cdm_file_name)
else:
test_util.write_cloud_str(self.chs_bucket, cdm_table + '.csv',
'dummy\n')
test_util.write_cloud_str(self.pitt_bucket, cdm_table + '.csv',
'dummy\n')
chs_load_results = bq_utils.load_cdm_csv(CHS_HPO_ID, cdm_table)
pitt_load_results = bq_utils.load_cdm_csv(PITT_HPO_ID, cdm_table)
chs_load_job_id = chs_load_results['jobReference']['jobId']
pitt_load_job_id = pitt_load_results['jobReference']['jobId']
load_jobs.append(chs_load_job_id)
load_jobs.append(pitt_load_job_id)
incomplete_jobs = bq_utils.wait_on_jobs(load_jobs)
if len(incomplete_jobs) > 0:
raise RuntimeError('BigQuery jobs %s failed to complete' %
incomplete_jobs)
def test_pii_files_loaded(self, mock_check_cron):
# tests if pii files are loaded
folder_prefix = 'dummy-prefix-2018-03-22/'
expected_result_items = resources._csv_to_list(
test_util.PII_FILE_LOAD_RESULT_CSV)
test_util.write_cloud_file(self.hpo_bucket,
test_util.PII_NAME_FILE,
prefix=folder_prefix)
test_util.write_cloud_file(self.hpo_bucket,
test_util.PII_MRN_BAD_PERSON_ID_FILE,
prefix=folder_prefix)
main.app.testing = True
with main.app.test_client() as c:
c.get(test_util.VALIDATE_HPO_FILES_URL)
actual_result = test_util.read_cloud_file(
self.hpo_bucket, folder_prefix + common.RESULT_CSV)
actual_result_file = StringIO.StringIO(actual_result)
actual_result_items = resources._csv_file_to_list(
actual_result_file)
# sort in order to compare
expected_result_items.sort()
actual_result_items.sort()
self.assertListEqual(expected_result_items, actual_result_items)
