def test_instantiation_partition_parameter_builder(
alice_columnar_table_single_batch_context,
):
data_context: DataContext = alice_columnar_table_single_batch_context
# noinspection PyUnusedLocal
parameter_builder_0: ParameterBuilder = PartitionParameterBuilder(
name="my_name_0",
bucketize_data=True,
data_context=data_context,
)
# noinspection PyUnusedLocal
parameter_builder_1: ParameterBuilder = PartitionParameterBuilder(
name="my_name_1",
bucketize_data=False,
data_context=data_context,
)
# noinspection PyUnusedLocal
parameter_builder_2: ParameterBuilder = PartitionParameterBuilder(
name="my_name_2",
bucketize_data="$variables.bucketize_data",
data_context=data_context,
)
def test_partition_parameter_builder_alice_continuous_check_serialized_keys(
alice_columnar_table_single_batch_context,
):
data_context: DataContext = alice_columnar_table_single_batch_context
parameter_builder: ParameterBuilder = PartitionParameterBuilder(
name="my_name",
bucketize_data=True,
data_context=data_context,
)
# Note: "evaluation_parameter_builder_configs" is not one of "ParameterBuilder" formal property attributes.
assert set(parameter_builder.to_json_dict().keys()) == {
"class_name",
"module_name",
"name",
"bucketize_data",
"metric_name",
"metric_domain_kwargs",
"metric_value_kwargs",
"enforce_numeric_metric",
"replace_nan_with_zero",
"reduce_scalar_metric",
"evaluation_parameter_builder_configs",
"json_serialize",
}
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 test_partition_parameter_builder_alice_continuous_check_serialized_keys(
alice_columnar_table_single_batch_context, ):
data_context: DataContext = alice_columnar_table_single_batch_context
parameter_builder: ParameterBuilder = PartitionParameterBuilder(
name="my_name",
bucketize_data=True,
evaluation_parameter_builder_configs=None,
data_context=data_context,
)
# Note: "evaluation_parameter_builder_configs" is not one of "ParameterBuilder" formal property attributes.
assert set(parameter_builder.to_json_dict().keys()) == {
"class_name",
"module_name",
"name",
"bucketize_data",
"evaluation_parameter_builder_configs",
}
def test_partition_parameter_builder_alice_continuous(
alice_columnar_table_single_batch_context, ):
data_context: DataContext = alice_columnar_table_single_batch_context
batch_request: dict = {
"datasource_name": "alice_columnar_table_single_batch_datasource",
"data_connector_name":
"alice_columnar_table_single_batch_data_connector",
"data_asset_name": "alice_columnar_table_single_batch_data_asset",
}
parameter_builder: ParameterBuilder = PartitionParameterBuilder(
name="my_name",
bucketize_data=True,
evaluation_parameter_builder_configs=None,
data_context=data_context,
)
metric_domain_kwargs: dict = {"column": "user_id"}
domain: Domain = Domain(
domain_type=MetricDomainTypes.COLUMN,
domain_kwargs=metric_domain_kwargs,
rule_name="my_rule",
)
parameter_container: ParameterContainer = ParameterContainer(
parameter_nodes=None)
parameters: Dict[str, ParameterContainer] = {
domain.id: parameter_container,
}
assert parameter_container.parameter_nodes is None
variables: Optional[ParameterContainer] = None
parameter_builder.build_parameters(
domain=domain,
variables=variables,
parameters=parameters,
batch_request=batch_request,
)
expected_parameter_value: dict = {
"value": {
"bins": [397433.0, 4942918.5, 9488404.0],
"weights": [0.6666666666666666, 0.3333333333333333],
"tail_weights": [0.0, 0.0],
},
"details": {
"metric_configuration": {
"metric_name": "column.histogram",
"domain_kwargs": {
"column": "user_id"
},
"metric_value_kwargs": {
"bins": [397433.0, 4942918.5, 9488404.0]
},
"metric_dependencies": None,
},
"num_batches": 1,
},
}
parameter_node: ParameterNode = get_parameter_value_and_validate_return_type(
domain=domain,
parameter_reference=parameter_builder.
json_serialized_fully_qualified_parameter_name,
expected_return_type=None,
variables=variables,
parameters=parameters,
)
assert parameter_node == expected_parameter_value
def test_partition_parameter_builder_alice_continuous_changed_to_categorical(
alice_columnar_table_single_batch_context, ):
data_context: DataContext = alice_columnar_table_single_batch_context
batch_request: dict = {
"datasource_name": "alice_columnar_table_single_batch_datasource",
"data_connector_name":
"alice_columnar_table_single_batch_data_connector",
"data_asset_name": "alice_columnar_table_single_batch_data_asset",
}
parameter_builder: ParameterBuilder = PartitionParameterBuilder(
name="my_name",
bucketize_data=True,
evaluation_parameter_builder_configs=None,
data_context=data_context,
)
metric_domain_kwargs: dict = {"column": "event_ts"}
domain: Domain = Domain(
domain_type=MetricDomainTypes.COLUMN,
domain_kwargs=metric_domain_kwargs,
rule_name="my_rule",
)
parameter_container: ParameterContainer = ParameterContainer(
parameter_nodes=None)
parameters: Dict[str, ParameterContainer] = {
domain.id: parameter_container,
}
assert parameter_container.parameter_nodes is None
variables: Optional[ParameterContainer] = None
parameter_builder.build_parameters(
domain=domain,
variables=variables,
parameters=parameters,
batch_request=batch_request,
)
expected_parameter_value: dict = {
"value": {
"values": [
"2004-10-19 10:23:54",
"2004-10-19 10:23:55",
"2004-10-19 11:05:20",
],
"weights":
[0.3333333333333333, 0.3333333333333333, 0.3333333333333333],
},
"details": {
"metric_configuration": {
"metric_name": "column.value_counts",
"domain_kwargs": {
"column": "event_ts"
},
"metric_value_kwargs": {
"sort": "value"
},
"metric_dependencies": None,
},
"num_batches": 1,
},
}
parameter_node: ParameterNode = get_parameter_value_and_validate_return_type(
domain=domain,
parameter_reference=parameter_builder.
json_serialized_fully_qualified_parameter_name,
expected_return_type=None,
variables=variables,
parameters=parameters,
)
assert parameter_node == expected_parameter_value