def post(self, datasource_name):
# url /datasource/<string:user_schema_name>/<string:datasource_name> {
# "file_name": "cassava.csv",
# }
user_id = get_jwt_identity()
user_schema_name = 'u{}'.format(user_id)
user_table_name = datasource_name
data = NewDatasource.parser.parse_args()
datasource_description = data['datasource_description']
upload_file = data['upload_file']
file_extension = upload_file.filename.split('.')[1]
datasource = DatasourceModel(datasource_name, datasource_description,
user_schema_name, user_table_name,
user_id)
if datasource.find_by_name(datasource_name, user_id):
return {
'message': ERROR_DUPLICATE_NAME.format(datasource_name)
}, 500
upload = UploadModel(upload_file)
try:
file_id = str(upload.save_file_to_db())
except Exception as e:
return {'message': ERROR_CANNOT_UPLOAD_FILE}, 500
file = File(file_id, file_extension)
file.read_file_to_dataset()
dataset_dataframe = file.get_dataframe()
dataset_json = file.get_json()
datasource = DatasourceModel(datasource_name, datasource_description,
user_schema_name, user_table_name,
user_id)
try:
datasource.new_datasource(dataset_dataframe)
except Exception as e:
return {'message': ERROR_CANNOT_CONVERT_TO_DATAFRAME}, 500
try:
datasource.save_to_db(file_id)
except Exception as e:
return {'message': ERROR_CANNOT_INSERT_DB}, 500
return {'message': 'sucess', 'dataset': dataset_json}, 200
def post(self, datasource_name):
data = AddPrediction.parser.parse_args()
predicted_data = data['predicted_data']
datasource = DatasourceModel.find_by_name(datasource_name)
user_schema_name = datasource.user_schema_name
user_table_name = datasource.user_table_name
dataset = File.read_json(predicted_data)
try:
DatasourceModel.append_datasource(dataset, user_schema_name,
user_table_name)
except Exception as e:
return {'message': ERROR_CANNOT_INSERT_DB}, 500
return {
'message':
'This Dataset has append to datasource ({})'.format(
datasource_name)
}, 200