_load_table_from_object_string.py

def _load_table_from_object_string(bucket_name, file_name, tableSchema, tableName):
  # ! we will convert body to a new line delimited JSON
  blob = CS.get_bucket(bucket_name).blob(file_name)
  blob = blob.download_as_string().decode()
  # Transform object string data into JSON outer array string:
  blob = json.dumps('[' + blob.replace('}{', '},{') + ']')
  # Load as JSON:
  body = json.loads(blob)
  # Create an array of string elements from JSON:
  jsonReady = [json.dumps(record) for record in json.loads(body)]
  # Now join them to create new line delimited JSON:
  data_str = u"\n".join(jsonReady)
  print('data_file :', data_str)
  # Create file to load into BigQuery:
  data_file = StringIO(data_str)

  table_id = BQ.dataset(BQ_DATASET).table(tableName)

  schema = create_schema_from_yaml(tableSchema) 
  job_config.schema = schema

  job_config.source_format = bigquery.SourceFormat.NEWLINE_DELIMITED_JSON,
  job_config.write_disposition = 'WRITE_APPEND',

  load_job = BQ.load_table_from_file(
       data_file,
       table_id,
       job_config=job_config,
       ) 

  load_job.result()  # Waits for table load to complete.
  print("Job finished.")