def parse_and_execute(self, parsed_args: Dict): client = create_client_from_parsed_args(parsed_args) table_name = parsed_args['table-name'] if prompt_confirmation( f'Confirm delete table `{table_name}`? The action is irreversible', False): api.delete_table(client, table_name) return 0
def clean_up(): delete_table(self.client, rename_table_name)
def _default_clean_up(): try: delete_table(self.client, self.default_table_name) except Exception as e: self.logger.error(f"failed to delete table in cleanup: {e}")
def clean_up(): delete_table(self.client, copy_table_name)
def tearDown(self): super().tearDown() delete_table(self.client, self.default_table_name)
import json # 1. load the data df = pandas.read_csv("../datasets/invoice-automation/invoice_data.csv") print("loaded the invoice data.") # 2. load the database schema with open("schema.json") as f: schema = json.load(f) print("loaded the invoice schema from schema.json.") # 3. create the Aito table aito_instance_url = os.environ.get('AITO_INSTANCE_URL') aito_api_key = os.environ.get('AITO_API_KEY') aito_client = AitoClient(instance_url=aito_instance_url, api_key=aito_api_key) delete_table(client=aito_client, table_name='invoice_data') create_table(client=aito_client, table_name='invoice_data', schema=schema) print("created the aito database table.") # 4. convert the dataframe to have correct types entries = DataFrameHandler().convert_df_using_aito_table_schema( df=df, table_schema=schema ).to_dict(orient="records") print("converted the dataframe.") # 5. upload the entries upload_entries(aito_client, table_name='invoice_data', entries=entries) print("uploaded the entries.")
def delete_default_table_and_check(self): api.delete_table(self.client, self.default_table_name) self.assertFalse(api.check_table_exists(self.client, self.default_table_name))
def clean_up(): api.delete_table(self.client, self.default_table_name) api.delete_table(self.client, copy_table_name) api.delete_table(self.client, rename_table_name)