def handle_cli(self, args, func):
parser = argparse.ArgumentParser()
parser.add_argument("--input", required=True)
parser.add_argument("-o",
"--output",
default="str",
choices=["str", "json"])
parser.add_argument(
"--orient",
default=self.orient,
choices=PANDAS_DATAFRAME_TO_DICT_ORIENT_OPTIONS,
)
parser.add_argument(
"--output_orient",
default=self.output_orient,
choices=PANDAS_DATAFRAME_TO_DICT_ORIENT_OPTIONS,
)
parsed_args = parser.parse_args(args)
orient = parsed_args.orient
output_orient = parsed_args.output_orient
cli_input = parsed_args.input
if os.path.isfile(cli_input) or is_s3_url(cli_input) or is_url(
cli_input):
if cli_input.endswith(".csv"):
df = pd.read_csv(cli_input)
elif cli_input.endswith(".json"):
df = pd.read_json(cli_input,
orient=orient,
typ=self.typ,
dtype=False)
else:
raise BadInput(
"Input file format not supported, BentoML cli only accepts .json "
"and .csv file")
else:
# Assuming input string is JSON format
try:
df = pd.read_json(cli_input,
orient=orient,
typ=self.typ,
dtype=False)
except ValueError as e:
raise BadInput(
"Unexpected input format, BentoML DataframeHandler expects json "
"string as input: {}".format(e))
if self.typ == "frame" and self.input_dtypes is not None:
_check_dataframe_column_contains(self.input_dtypes, df)
result = func(df)
if parsed_args.output == 'json':
result = api_func_result_to_json(
result, pandas_dataframe_orient=output_orient)
else:
result = str(result)
print(result)
def handle_cli(self, args, func):
parser = argparse.ArgumentParser()
parser.add_argument('--input', required=True)
parser.add_argument('-o',
'--output',
default="str",
choices=['str', 'json', 'yaml'])
parser.add_argument('--orient', default=self.orient)
parser.add_argument('--output_orient', default=self.output_orient)
parsed_args = parser.parse_args(args)
orient = parsed_args.orient
output_orient = parsed_args.output_orient
cli_input = parsed_args.input
if os.path.isfile(cli_input) or is_s3_url(cli_input) or is_url(
cli_input):
if cli_input.endswith('.csv'):
df = pd.read_csv(cli_input)
elif cli_input.endswith('.json'):
df = pd.read_json(cli_input,
orient=orient,
typ=self.typ,
dtype=False)
else:
raise ValueError(
"Input file format not supported, BentoML cli only accepts .json and .csv file"
)
else:
# Assuming input string is JSON format
try:
df = pd.read_json(cli_input,
orient=orient,
typ=self.typ,
dtype=False)
except ValueError as e:
raise ValueError(
"Unexpected input format, BentoML DataframeHandler expects json string as"
"input: {}".format(e))
if self.typ == 'frame' and self.input_columns is not None:
check_dataframe_column_contains(self.input_columns, df)
result = func(df)
result = get_output_str(result, parsed_args.output, output_orient)
print(result)
def handle_cli(self, args, func):
parser = argparse.ArgumentParser()
parser.add_argument("--input", required=True)
parser.add_argument(
"--orient",
default=self.orient,
choices=PANDAS_DATAFRAME_TO_JSON_ORIENT_OPTIONS,
)
parsed_args, unknown_args = parser.parse_known_args(args)
orient = parsed_args.orient
cli_input = parsed_args.input
if os.path.isfile(cli_input) or is_s3_url(cli_input) or is_url(cli_input):
if cli_input.endswith(".csv"):
df = pd.read_csv(cli_input)
elif cli_input.endswith(".json"):
df = pd.read_json(cli_input, orient=orient, typ=self.typ)
else:
raise BadInput(
"Input file format not supported, BentoML cli only accepts .json "
"and .csv file"
)
else:
# Assuming input string is JSON format
try:
df = pd.read_json(cli_input, orient=orient, typ=self.typ)
except ValueError as e:
raise BadInput(
"Unexpected input format, BentoML DataframeInput expects json "
"string as input: {}".format(e)
)
if self.typ == "frame" and self.input_dtypes is not None:
check_dataframe_column_contains(self.input_dtypes, df)
result = func(df)
self.output_adapter.to_cli(result, unknown_args)
