def test_extraction_with_model_class(self) -> None:
"""
Test Extraction using model class
"""
config_dict = {
f'extractor.csv.{CsvExtractor.FILE_LOCATION}':
'example/sample_data/sample_table.csv',
f'extractor.csv.model_class':
'databuilder.models.table_metadata.TableMetadata',
}
self.conf = ConfigFactory.from_dict(config_dict)
extractor = CsvExtractor()
extractor.init(
Scoped.get_scoped_conf(conf=self.conf,
scope=extractor.get_scope()))
result = extractor.extract()
self.assertEqual(result.name, 'test_table1')
self.assertEqual(result.description.text, '1st test table')
self.assertEqual(result.database, 'hive')
self.assertEqual(result.cluster, 'gold')
self.assertEqual(result.schema, 'test_schema')
self.assertEqual(result.tags, ['tag1', 'tag2'])
self.assertEqual(result.is_view, 'false')
result2 = extractor.extract()
self.assertEqual(result2.name, 'test_table2')
self.assertEqual(result2.is_view, 'false')
result3 = extractor.extract()
self.assertEqual(result3.name, 'test_view1')
self.assertEqual(result3.is_view, 'true')
def create_dashboard_tables_job():
# loader saves data to these folders and publisher reads it from here
tmp_folder = '/var/tmp/amundsen/dashboard_table'
node_files_folder = '{tmp_folder}/nodes'.format(tmp_folder=tmp_folder)
relationship_files_folder = '{tmp_folder}/relationships'.format(
tmp_folder=tmp_folder)
csv_extractor = CsvExtractor()
loader = FSNeptuneCSVLoader()
publisher = NeptuneCSVPublisher()
generic_transformer = GenericTransformer()
dict_to_model_transformer = DictToModel()
transformer = ChainedTransformer(
transformers=[generic_transformer, dict_to_model_transformer],
is_init_transformers=True)
task = DefaultTask(extractor=csv_extractor,
loader=loader,
transformer=transformer)
job_config = ConfigFactory.from_dict({
csv_extractor.get_scope(): {
CsvExtractor.FILE_LOCATION:
'example/sample_data/sample_dashboard_table.csv'
},
transformer.get_scope(): {
generic_transformer.get_scope(): {
FIELD_NAME: 'table_ids',
CALLBACK_FUNCTION: _str_to_list
},
dict_to_model_transformer.get_scope(): {
MODEL_CLASS:
'databuilder.models.dashboard.dashboard_table.DashboardTable',
}
},
loader.get_scope(): {
FSNeptuneCSVLoader.NODE_DIR_PATH: node_files_folder,
FSNeptuneCSVLoader.RELATION_DIR_PATH: relationship_files_folder,
FSNeptuneCSVLoader.SHOULD_DELETE_CREATED_DIR: True,
FSNeptuneCSVLoader.JOB_PUBLISHER_TAG: 'unique_tag'
},
publisher.get_scope(): {
NeptuneCSVPublisher.NODE_FILES_DIR: node_files_folder,
NeptuneCSVPublisher.RELATION_FILES_DIR: relationship_files_folder,
NeptuneCSVPublisher.AWS_S3_BUCKET_NAME: S3_BUCKET_NAME,
NeptuneCSVPublisher.AWS_BASE_S3_DATA_PATH: S3_DATA_PATH,
NeptuneCSVPublisher.NEPTUNE_HOST: NEPTUNE_ENDPOINT,
NeptuneCSVPublisher.AWS_IAM_ROLE_NAME: neptune_iam_role_name,
NeptuneCSVPublisher.AWS_REGION: AWS_REGION,
NeptuneCSVPublisher.AWS_ACCESS_KEY: aws_access_key,
NeptuneCSVPublisher.AWS_SECRET_ACCESS_KEY: aws_access_secret,
NeptuneCSVPublisher.AWS_SESSION_TOKEN: aws_token
}
})
return DefaultJob(conf=job_config, task=task, publisher=publisher)
def create_dashboard_tables_job():
# loader saves data to these folders and publisher reads it from here
tmp_folder = '/var/tmp/amundsen/dashboard_table'
node_files_folder = '{tmp_folder}/nodes'.format(tmp_folder=tmp_folder)
relationship_files_folder = '{tmp_folder}/relationships'.format(
tmp_folder=tmp_folder)
csv_extractor = CsvExtractor()
csv_loader = FsNeo4jCSVLoader()
generic_transformer = GenericTransformer()
dict_to_model_transformer = DictToModel()
transformer = ChainedTransformer(
transformers=[generic_transformer, dict_to_model_transformer],
is_init_transformers=True)
task = DefaultTask(extractor=csv_extractor,
loader=csv_loader,
transformer=transformer)
publisher = Neo4jCsvPublisher()
job_config = ConfigFactory.from_dict({
'{}.file_location'.format(csv_extractor.get_scope()):
'example/sample_data/sample_dashboard_table.csv',
'{}.{}.{}'.format(transformer.get_scope(),
generic_transformer.get_scope(), FIELD_NAME):
'table_ids',
'{}.{}.{}'.format(transformer.get_scope(),
generic_transformer.get_scope(), CALLBACK_FUNCTION):
_str_to_list,
'{}.{}.{}'.format(transformer.get_scope(),
dict_to_model_transformer.get_scope(), MODEL_CLASS):
'databuilder.models.dashboard.dashboard_table.DashboardTable',
'{}.node_dir_path'.format(csv_loader.get_scope()):
node_files_folder,
'{}.relationship_dir_path'.format(csv_loader.get_scope()):
relationship_files_folder,
'{}.delete_created_directories'.format(csv_loader.get_scope()):
True,
'{}.node_files_directory'.format(publisher.get_scope()):
node_files_folder,
'{}.relation_files_directory'.format(publisher.get_scope()):
relationship_files_folder,
'{}.neo4j_endpoint'.format(publisher.get_scope()):
neo4j_endpoint,
'{}.neo4j_user'.format(publisher.get_scope()):
neo4j_user,
'{}.neo4j_password'.format(publisher.get_scope()):
neo4j_password,
'{}.neo4j_encrypted'.format(publisher.get_scope()):
False,
'{}.job_publish_tag'.format(publisher.get_scope()):
'unique_tag', # should use unique tag here like {ds}
})
return DefaultJob(conf=job_config, task=task, publisher=publisher)
def test_extraction_with_model_class(self) -> None:
"""
Test Extraction using model class
"""
extractor = CsvExtractor()
extractor.init(Scoped.get_scoped_conf(conf=self.conf,
scope=extractor.get_scope()))
result = extractor.extract()
self.assertEqual(result.name, 'test_table1')
self.assertEqual(result.description._text, '1st test table')
self.assertEqual(result.database, 'hive')
self.assertEqual(result.cluster, 'gold')
self.assertEqual(result.schema, 'test_schema')