great_expectations.rule_based_profiler.util

Module Contents

Functions

get_validator(purpose: str, *, data_context: Optional[DataContext] = None, batch_request: Optional[Union[BatchRequest, dict, str]] = None, domain: Optional[Domain] = None, variables: Optional[ParameterContainer] = None, parameters: Optional[Dict[str, ParameterContainer]] = None)

get_batch_ids(data_context: Optional[DataContext] = None, batch_request: Optional[Union[BatchRequest, dict, str]] = None, domain: Optional[Domain] = None, variables: Optional[ParameterContainer] = None, parameters: Optional[Dict[str, ParameterContainer]] = None)

build_batch_request(batch_request: Optional[Union[dict, str]] = None, domain: Optional[Domain] = None, variables: Optional[ParameterContainer] = None, parameters: Optional[Dict[str, ParameterContainer]] = None)

build_metric_domain_kwargs(batch_id: Optional[str] = None, metric_domain_kwargs: Optional[Union[str, dict]] = None, domain: Optional[Domain] = None, variables: Optional[ParameterContainer] = None, parameters: Optional[Dict[str, ParameterContainer]] = None)

get_parameter_value_and_validate_return_type(domain: Optional[Domain] = None, parameter_reference: Optional[Union[Any, str]] = None, expected_return_type: Optional[Union[type, tuple]] = None, variables: Optional[ParameterContainer] = None, parameters: Optional[Dict[str, ParameterContainer]] = None)

This method allows for the parameter_reference to be specified as an object (literal, dict, any typed object, etc.)

get_parameter_value(domain: Optional[Domain] = None, parameter_reference: Optional[Union[Any, str]] = None, variables: Optional[ParameterContainer] = None, parameters: Optional[Dict[str, ParameterContainer]] = None)

This method allows for the parameter_reference to be specified as an object (literal, dict, any typed object, etc.)

compute_quantiles(metric_values: Union[np.ndarray, List[Number]], false_positive_rate: np.float64)

compute_bootstrap_quantiles(metric_values: np.ndarray, false_positive_rate: np.float64, n_resamples: int)

great_expectations.rule_based_profiler.util.NP_EPSILON :Union[Number, np.float64]
great_expectations.rule_based_profiler.util.get_validator(purpose: str, *, data_context: Optional[DataContext] = None, batch_request: Optional[Union[BatchRequest, dict, str]] = None, domain: Optional[Domain] = None, variables: Optional[ParameterContainer] = None, parameters: Optional[Dict[str, ParameterContainer]] = None) → Optional[Validator]
great_expectations.rule_based_profiler.util.get_batch_ids(data_context: Optional[DataContext] = None, batch_request: Optional[Union[BatchRequest, dict, str]] = None, domain: Optional[Domain] = None, variables: Optional[ParameterContainer] = None, parameters: Optional[Dict[str, ParameterContainer]] = None) → Optional[List[str]]
great_expectations.rule_based_profiler.util.build_batch_request(batch_request: Optional[Union[dict, str]] = None, domain: Optional[Domain] = None, variables: Optional[ParameterContainer] = None, parameters: Optional[Dict[str, ParameterContainer]] = None) → Optional[BatchRequest]
great_expectations.rule_based_profiler.util.build_metric_domain_kwargs(batch_id: Optional[str] = None, metric_domain_kwargs: Optional[Union[str, dict]] = None, domain: Optional[Domain] = None, variables: Optional[ParameterContainer] = None, parameters: Optional[Dict[str, ParameterContainer]] = None)
great_expectations.rule_based_profiler.util.get_parameter_value_and_validate_return_type(domain: Optional[Domain] = None, parameter_reference: Optional[Union[Any, str]] = None, expected_return_type: Optional[Union[type, tuple]] = None, variables: Optional[ParameterContainer] = None, parameters: Optional[Dict[str, ParameterContainer]] = None) → Optional[Any]

This method allows for the parameter_reference to be specified as an object (literal, dict, any typed object, etc.) or as a fully-qualified parameter name. In either case, it can optionally validate the type of the return value.

great_expectations.rule_based_profiler.util.get_parameter_value(domain: Optional[Domain] = None, parameter_reference: Optional[Union[Any, str]] = None, variables: Optional[ParameterContainer] = None, parameters: Optional[Dict[str, ParameterContainer]] = None) → Optional[Any]

This method allows for the parameter_reference to be specified as an object (literal, dict, any typed object, etc.) or as a fully-qualified parameter name. Moreover, if the parameter_reference argument is an object of type “dict”, it will recursively detect values using the fully-qualified parameter name format and evaluate them accordingly.

great_expectations.rule_based_profiler.util.compute_quantiles(metric_values: Union[np.ndarray, List[Number]], false_positive_rate: np.float64) → tuple
great_expectations.rule_based_profiler.util.compute_bootstrap_quantiles(metric_values: np.ndarray, false_positive_rate: np.float64, n_resamples: int) → tuple