def build_numeric_metric_range_multi_batch_parameter_builder(
metric_name: str,
metric_value_kwargs: Optional[Union[str, dict]] = None,
json_serialize: Union[str, bool] = True,
) -> NumericMetricRangeMultiBatchParameterBuilder:
"""
This method instantiates "MetricMultiBatchParameterBuilder" class with specific arguments for given purpose.
"""
name: str = sanitize_parameter_name(name=f"{metric_name}.range")
return NumericMetricRangeMultiBatchParameterBuilder(
name=name,
metric_name=metric_name,
metric_domain_kwargs=
DOMAIN_KWARGS_PARAMETER_FULLY_QUALIFIED_NAME,
metric_value_kwargs=metric_value_kwargs,
enforce_numeric_metric=True,
replace_nan_with_zero=True,
reduce_scalar_metric=True,
false_positive_rate=f"{VARIABLES_KEY}false_positive_rate",
quantile_statistic_interpolation_method=
f"{VARIABLES_KEY}quantile_statistic_interpolation_method",
estimator=f"{VARIABLES_KEY}estimator",
n_resamples=f"{VARIABLES_KEY}n_resamples",
random_seed=f"{VARIABLES_KEY}random_seed",
include_estimator_samples_histogram_in_details=
f"{VARIABLES_KEY}include_estimator_samples_histogram_in_details",
truncate_values=f"{VARIABLES_KEY}truncate_values",
round_decimals=f"{VARIABLES_KEY}round_decimals",
evaluation_parameter_builder_configs=None,
json_serialize=json_serialize,
data_context=None,
)
def build_partition_parameter_builder(
name: str,
bucketize_data: Union[str, bool] = True,
) -> PartitionParameterBuilder:
"""
This method instantiates "PartitionParameterBuilder" class with specific arguments for given purpose.
"""
name: str = sanitize_parameter_name(name=f"{name}")
return PartitionParameterBuilder(
name=name,
bucketize_data=bucketize_data,
evaluation_parameter_builder_configs=None,
data_context=None,
)
def build_regex_pattern_string_parameter_builder(
name: str, ) -> RegexPatternStringParameterBuilder:
"""
This method instantiates "RegexPatternStringParameterBuilder" class with specific arguments for given purpose.
"""
name: str = sanitize_parameter_name(name=f"{name}")
return RegexPatternStringParameterBuilder(
name=name,
metric_domain_kwargs=
DOMAIN_KWARGS_PARAMETER_FULLY_QUALIFIED_NAME,
metric_value_kwargs=None,
threshold=1.0,
candidate_regexes=None,
evaluation_parameter_builder_configs=None,
data_context=None,
)
def get_table_columns_metric_multi_batch_parameter_builder(
) -> ParameterBuilder:
"""
This method instantiates one commonly used "MetricMultiBatchParameterBuilder" with specified directives.
"""
metric_name: str = "table.columns"
name: str = sanitize_parameter_name(name=metric_name)
return MetricMultiBatchParameterBuilder(
name=name,
metric_name=metric_name,
metric_domain_kwargs=
DOMAIN_KWARGS_PARAMETER_FULLY_QUALIFIED_NAME,
metric_value_kwargs=None,
enforce_numeric_metric=False,
replace_nan_with_zero=False,
reduce_scalar_metric=True,
evaluation_parameter_builder_configs=None,
data_context=None,
)
def build_numeric_metric_multi_batch_parameter_builder(
metric_name: str,
metric_domain_kwargs: Optional[Union[
str, dict]] = DOMAIN_KWARGS_PARAMETER_FULLY_QUALIFIED_NAME,
metric_value_kwargs: Optional[Union[str, dict]] = None,
) -> MetricMultiBatchParameterBuilder:
"""
This method instantiates "MetricMultiBatchParameterBuilder" class with specific arguments for given purpose.
"""
name: str = sanitize_parameter_name(name=metric_name)
return MetricMultiBatchParameterBuilder(
name=name,
metric_name=metric_name,
metric_domain_kwargs=metric_domain_kwargs,
metric_value_kwargs=metric_value_kwargs,
enforce_numeric_metric=True,
replace_nan_with_zero=True,
reduce_scalar_metric=True,
evaluation_parameter_builder_configs=None,
data_context=None,
)
