def generate_func(self, serialized_fn):
pandas_functions, variable_dict, user_defined_funcs = reduce(
lambda x, y: (
','.join([x[0], y[0]]),
dict(chain(x[1].items(), y[1].items())),
x[2] + y[2]),
[operation_utils.extract_user_defined_function(udf, True)
for udf in serialized_fn.udfs])
variable_dict['normalize_pandas_result'] = operation_utils.normalize_pandas_result
generate_func = eval('lambda value: normalize_pandas_result([%s])' %
pandas_functions, variable_dict)
return generate_func, user_defined_funcs
def generate_func(self, serialized_fn):
"""
Generates a lambda function based on udtfs.
:param serialized_fn: serialized function which contains the proto representation of
the Python :class:`TableFunction`
:return: the generated lambda function
"""
table_function, variable_dict, user_defined_funcs = \
operation_utils.extract_user_defined_function(serialized_fn.udfs[0])
variable_dict['normalize_table_function_result'] = \
operation_utils.normalize_table_function_result
generate_func = eval('lambda value: normalize_table_function_result(%s)' % table_function,
variable_dict)
return generate_func, user_defined_funcs
def generate_func(self, serialized_fn):
"""
Generates a lambda function based on udfs.
:param serialized_fn: serialized function which contains a list of the proto
representation of the Python :class:`ScalarFunction`
:return: the generated lambda function
"""
scalar_functions, variable_dict, user_defined_funcs = reduce(
lambda x, y: (
','.join([x[0], y[0]]),
dict(chain(x[1].items(), y[1].items())),
x[2] + y[2]),
[operation_utils.extract_user_defined_function(udf) for udf in serialized_fn.udfs])
generate_func = eval('lambda value: [%s]' % scalar_functions, variable_dict)
return generate_func, user_defined_funcs