def parse_and_execute(self, parsed_args: Dict):
client = create_client_from_parsed_args(parsed_args)
df_handler = DataFrameHandler()
table_name = parsed_args['table-name']
in_file_path = parsed_args['input-file']
in_format = in_file_path.suffixes[0].replace('.', '') if parsed_args['file_format'] == 'infer' \
else parsed_args['file_format']
if in_format not in df_handler.allowed_format:
raise ParseError(
f'failed to infer file {in_file_path} format. '
f'Please give the exact file format instead of `infer`')
converted_tmp_file = tempfile.NamedTemporaryFile(mode='w',
suffix='.ndjson.gz',
delete=False)
convert_options = {
'read_input': in_file_path,
'write_output': converted_tmp_file.name,
'in_format': in_format,
'out_format': 'ndjson',
'convert_options': {
'compression': 'gzip'
},
'use_table_schema': api.get_table_schema(client, table_name)
}
df_handler = DataFrameHandler()
df_handler.convert_file(**convert_options)
converted_tmp_file.close()
with open(converted_tmp_file.name, 'rb') as in_f:
api.upload_binary_file(client=client,
table_name=table_name,
binary_file=in_f)
converted_tmp_file.close()
unlink(converted_tmp_file.name)
def parse_and_execute(self, parsed_args: Dict):
table_name = parsed_args['table-name']
client = create_client_from_parsed_args(parsed_args)
connection = create_sql_connecting_from_parsed_args(parsed_args)
result_df = connection.execute_query_and_save_result(
parsed_args['query'])
inferred_schema = AitoTableSchema.infer_from_pandas_data_frame(
result_df)
converted_tmp_file = tempfile.NamedTemporaryFile(mode='w',
suffix='.ndjson.gz',
delete=False)
DataFrameHandler().df_to_format(result_df, 'ndjson',
converted_tmp_file.name,
{'compression': 'gzip'})
converted_tmp_file.close()
api.create_table(client, table_name, inferred_schema)
with open(converted_tmp_file.name, 'rb') as in_f:
api.upload_binary_file(client=client,
table_name=table_name,
binary_file=in_f)
converted_tmp_file.close()
unlink(converted_tmp_file.name)
return 0
def parse_and_execute(self, parsed_args: Dict):
client = create_client_from_parsed_args(parsed_args)
table_name = parsed_args['table-name']
table_entries = load_json_from_parsed_input_arg(parsed_args['input'])
api.upload_entries(client,
table_name=table_name,
entries=table_entries)
return 0
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 parse_and_execute(self, parsed_args: Dict):
client = create_client_from_parsed_args(parsed_args)
table_name = parsed_args['table-name']
table_schema = load_json_from_parsed_input_arg(parsed_args['input'],
'table schema')
api.create_table(client=client,
table_name=table_name,
schema=table_schema)
return 0
def parse_and_execute(self, parsed_args: Dict):
in_f_path = parsed_args['input-file']
in_format = parsed_args.get('file_format')
table_name = parsed_args.get('table_name')
client = create_client_from_parsed_args(parsed_args)
api.quick_add_table(client=client,
input_file=in_f_path,
input_format=in_format,
table_name=table_name)
return 0
def parse_and_execute(self, parsed_args: Dict):
client = create_client_from_parsed_args(parsed_args)
query_str = parsed_args['query']
query = json.loads(query_str)
use_job = parsed_args['use_job']
client_method = getattr(api, self.api_method_name)
resp = client_method(client=client, query=query, use_job=use_job)
print(resp.to_json_string(indent=2))
return 0
def parse_and_execute(self, parsed_args: Dict):
from_table = parsed_args['from-table']
predicting_field = parsed_args['predicting-field']
client = create_client_from_parsed_args(parsed_args)
predict_query, evaluate_query = api.quick_predict_and_evaluate(
client=client,
from_table=from_table,
predicting_field=predicting_field)
print("[Predict Query Example]")
print(json.dumps(predict_query, indent=2))
if parsed_args['evaluate']:
evaluate_result = api.evaluate(client=client, query=evaluate_query)
print("[Evaluation Result]")
print(
f"- Train samples count: {evaluate_result.train_sample_count}")
print(f"- Test samples count: {evaluate_result.test_sample_count}")
print(f"- Accuracy: {evaluate_result.accuracy}")
return 0
def parse_and_execute(self, parsed_args: Dict):
client = create_client_from_parsed_args(parsed_args)
table_name = parsed_args['table-name']
api.optimize_table(client, table_name=table_name)
return 0
def parse_and_execute(self, parsed_args: Dict):
client = create_client_from_parsed_args(parsed_args)
if prompt_confirmation(
'Confirm delete the whole database? The action is irreversible',
False):
api.delete_database(client)
def parse_and_execute(self, parsed_args: Dict):
client = create_client_from_parsed_args(parsed_args)
print(api.get_database_schema(client).to_json_string(indent=2))
return 0
def parse_and_execute(self, parsed_args: Dict):
client = create_client_from_parsed_args(parsed_args)
tables = api.get_existing_tables(client)
print(*sorted(tables), sep='\n')
pass
def parse_and_execute(self, parsed_args: Dict):
client = create_client_from_parsed_args(parsed_args)
api.rename_table(client, parsed_args['old-name'],
parsed_args['new-name'], parsed_args['replace'])
return 0
def parse_and_execute(self, parsed_args: Dict):
client = create_client_from_parsed_args(parsed_args)
api.copy_table(client, parsed_args['table-name'],
parsed_args['copy-table-name'], parsed_args['replace'])
return 0
def parse_and_execute(self, parsed_args: Dict):
client = create_client_from_parsed_args(parsed_args)
table_name = parsed_args['table-name']
print(
api.get_table_schema(client, table_name).to_json_string(indent=2))
return 0
def parse_and_execute(self, parsed_args: Dict):
client = create_client_from_parsed_args(parsed_args)
database_schema = load_json_from_parsed_input_arg(
parsed_args['input'], 'database schema')
api.create_database(client=client, schema=database_schema)
return 0
