CfnRuleset
- class aws_cdk.aws_databrew.CfnRuleset(scope, id, *, name, rules, target_arn, description=None, tags=None)
Bases:
CfnResourceA CloudFormation
AWS::DataBrew::Ruleset.Specifies a new ruleset that can be used in a profile job to validate the data quality of a dataset.
- CloudformationResource:
AWS::DataBrew::Ruleset
- Link:
http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-databrew-ruleset.html
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_databrew as databrew cfn_ruleset = databrew.CfnRuleset(self, "MyCfnRuleset", name="name", rules=[databrew.CfnRuleset.RuleProperty( check_expression="checkExpression", name="name", # the properties below are optional column_selectors=[databrew.CfnRuleset.ColumnSelectorProperty( name="name", regex="regex" )], disabled=False, substitution_map=[databrew.CfnRuleset.SubstitutionValueProperty( value="value", value_reference="valueReference" )], threshold=databrew.CfnRuleset.ThresholdProperty( value=123, # the properties below are optional type="type", unit="unit" ) )], target_arn="targetArn", # the properties below are optional description="description", tags=[CfnTag( key="key", value="value" )] )
Create a new
AWS::DataBrew::Ruleset.- Parameters:
scope (
Construct) –scope in which this resource is defined.
id (
str) –scoped id of the resource.
name (
str) – The name of the ruleset.rules (
Union[IResolvable,Sequence[Union[IResolvable,RuleProperty,Dict[str,Any]]]]) – Contains metadata about the ruleset.target_arn (
str) – The Amazon Resource Name (ARN) of a resource (dataset) that the ruleset is associated with.description (
Optional[str]) – The description of the ruleset.tags (
Optional[Sequence[Union[CfnTag,Dict[str,Any]]]]) – An array of key-value pairs to apply to this resource. For more information, see Tag .
Methods
- add_deletion_override(path)
Syntactic sugar for
addOverride(path, undefined).- Parameters:
path (
str) – The path of the value to delete.- Return type:
None
- add_depends_on(target)
Indicates that this resource depends on another resource and cannot be provisioned unless the other resource has been successfully provisioned.
This can be used for resources across stacks (or nested stack) boundaries and the dependency will automatically be transferred to the relevant scope.
- Parameters:
target (
CfnResource) –- Return type:
None
- add_metadata(key, value)
Add a value to the CloudFormation Resource Metadata.
- Parameters:
key (
str) –value (
Any) –
- See:
- Return type:
None
Note that this is a different set of metadata from CDK node metadata; this metadata ends up in the stack template under the resource, whereas CDK node metadata ends up in the Cloud Assembly.
- add_override(path, value)
Adds an override to the synthesized CloudFormation resource.
To add a property override, either use
addPropertyOverrideor prefixpathwith “Properties.” (i.e.Properties.TopicName).If the override is nested, separate each nested level using a dot (.) in the path parameter. If there is an array as part of the nesting, specify the index in the path.
To include a literal
.in the property name, prefix with a\. In most programming languages you will need to write this as"\\."because the\itself will need to be escaped.For example:
cfn_resource.add_override("Properties.GlobalSecondaryIndexes.0.Projection.NonKeyAttributes", ["myattribute"]) cfn_resource.add_override("Properties.GlobalSecondaryIndexes.1.ProjectionType", "INCLUDE")
would add the overrides Example:
"Properties": { "GlobalSecondaryIndexes": [ { "Projection": { "NonKeyAttributes": [ "myattribute" ] ... } ... }, { "ProjectionType": "INCLUDE" ... }, ] ... }
The
valueargument toaddOverridewill not be processed or translated in any way. Pass raw JSON values in here with the correct capitalization for CloudFormation. If you pass CDK classes or structs, they will be rendered with lowercased key names, and CloudFormation will reject the template.- Parameters:
path (
str) –The path of the property, you can use dot notation to override values in complex types. Any intermdediate keys will be created as needed.
value (
Any) –The value. Could be primitive or complex.
- Return type:
None
- add_property_deletion_override(property_path)
Adds an override that deletes the value of a property from the resource definition.
- Parameters:
property_path (
str) – The path to the property.- Return type:
None
- add_property_override(property_path, value)
Adds an override to a resource property.
Syntactic sugar for
addOverride("Properties.<...>", value).- Parameters:
property_path (
str) – The path of the property.value (
Any) – The value.
- Return type:
None
- apply_removal_policy(policy=None, *, apply_to_update_replace_policy=None, default=None)
Sets the deletion policy of the resource based on the removal policy specified.
The Removal Policy controls what happens to this resource when it stops being managed by CloudFormation, either because you’ve removed it from the CDK application or because you’ve made a change that requires the resource to be replaced.
The resource can be deleted (
RemovalPolicy.DESTROY), or left in your AWS account for data recovery and cleanup later (RemovalPolicy.RETAIN).- Parameters:
policy (
Optional[RemovalPolicy]) –apply_to_update_replace_policy (
Optional[bool]) – Apply the same deletion policy to the resource’s “UpdateReplacePolicy”. Default: truedefault (
Optional[RemovalPolicy]) – The default policy to apply in case the removal policy is not defined. Default: - Default value is resource specific. To determine the default value for a resoure, please consult that specific resource’s documentation.
- Return type:
None
- get_att(attribute_name)
Returns a token for an runtime attribute of this resource.
Ideally, use generated attribute accessors (e.g.
resource.arn), but this can be used for future compatibility in case there is no generated attribute.- Parameters:
attribute_name (
str) – The name of the attribute.- Return type:
- get_metadata(key)
Retrieve a value value from the CloudFormation Resource Metadata.
- Parameters:
key (
str) –- See:
- Return type:
Any
Note that this is a different set of metadata from CDK node metadata; this metadata ends up in the stack template under the resource, whereas CDK node metadata ends up in the Cloud Assembly.
- inspect(inspector)
Examines the CloudFormation resource and discloses attributes.
- Parameters:
inspector (
TreeInspector) –tree inspector to collect and process attributes.
- Return type:
None
- override_logical_id(new_logical_id)
Overrides the auto-generated logical ID with a specific ID.
- Parameters:
new_logical_id (
str) – The new logical ID to use for this stack element.- Return type:
None
- to_string()
Returns a string representation of this construct.
- Return type:
str- Returns:
a string representation of this resource
Attributes
- CFN_RESOURCE_TYPE_NAME = 'AWS::DataBrew::Ruleset'
- cfn_options
Options for this resource, such as condition, update policy etc.
- cfn_resource_type
AWS resource type.
- creation_stack
return:
the stack trace of the point where this Resource was created from, sourced from the +metadata+ entry typed +aws:cdk:logicalId+, and with the bottom-most node +internal+ entries filtered.
- description
The description of the ruleset.
- logical_id
The logical ID for this CloudFormation stack element.
The logical ID of the element is calculated from the path of the resource node in the construct tree.
To override this value, use
overrideLogicalId(newLogicalId).- Returns:
the logical ID as a stringified token. This value will only get resolved during synthesis.
- name
The name of the ruleset.
- node
The construct tree node associated with this construct.
- ref
Return a string that will be resolved to a CloudFormation
{ Ref }for this element.If, by any chance, the intrinsic reference of a resource is not a string, you could coerce it to an IResolvable through
Lazy.any({ produce: resource.ref }).
- rules
Contains metadata about the ruleset.
- stack
The stack in which this element is defined.
CfnElements must be defined within a stack scope (directly or indirectly).
- target_arn
The Amazon Resource Name (ARN) of a resource (dataset) that the ruleset is associated with.
Static Methods
- classmethod is_cfn_element(x)
Returns
trueif a construct is a stack element (i.e. part of the synthesized cloudformation template).Uses duck-typing instead of
instanceofto allow stack elements from different versions of this library to be included in the same stack.- Parameters:
x (
Any) –- Return type:
bool- Returns:
The construct as a stack element or undefined if it is not a stack element.
- classmethod is_cfn_resource(construct)
Check whether the given construct is a CfnResource.
- Parameters:
construct (
IConstruct) –- Return type:
bool
- classmethod is_construct(x)
Return whether the given object is a Construct.
- Parameters:
x (
Any) –- Return type:
bool
ColumnSelectorProperty
- class CfnRuleset.ColumnSelectorProperty(*, name=None, regex=None)
Bases:
objectSelector of a column from a dataset for profile job configuration.
One selector includes either a column name or a regular expression.
- Parameters:
name (
Optional[str]) – The name of a column from a dataset.regex (
Optional[str]) – A regular expression for selecting a column from a dataset.
- Link:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_databrew as databrew column_selector_property = databrew.CfnRuleset.ColumnSelectorProperty( name="name", regex="regex" )
Attributes
- name
The name of a column from a dataset.
- regex
A regular expression for selecting a column from a dataset.
RuleProperty
- class CfnRuleset.RuleProperty(*, check_expression, name, column_selectors=None, disabled=None, substitution_map=None, threshold=None)
Bases:
objectRepresents a single data quality requirement that should be validated in the scope of this dataset.
- Parameters:
check_expression (
str) – The expression which includes column references, condition names followed by variable references, possibly grouped and combined with other conditions. For example,(:col1 starts_with :prefix1 or :col1 starts_with :prefix2) and (:col1 ends_with :suffix1 or :col1 ends_with :suffix2). Column and value references are substitution variables that should start with the ‘:’ symbol. Depending on the context, substitution variables’ values can be either an actual value or a column name. These values are defined in the SubstitutionMap. If a CheckExpression starts with a column reference, then ColumnSelectors in the rule should be null. If ColumnSelectors has been defined, then there should be no columnn reference in the left side of a condition, for example,is_between :val1 and :val2.name (
str) – The name of the rule.column_selectors (
Union[IResolvable,Sequence[Union[IResolvable,ColumnSelectorProperty,Dict[str,Any]]],None]) – List of column selectors. Selectors can be used to select columns using a name or regular expression from the dataset. Rule will be applied to selected columns.disabled (
Union[bool,IResolvable,None]) – A value that specifies whether the rule is disabled. Once a rule is disabled, a profile job will not validate it during a job run. Default value is false.substitution_map (
Union[IResolvable,Sequence[Union[IResolvable,SubstitutionValueProperty,Dict[str,Any]]],None]) – The map of substitution variable names to their values used in a check expression. Variable names should start with a ‘:’ (colon). Variable values can either be actual values or column names. To differentiate between the two, column names should be enclosed in backticks, for example,":col1": "``Column A”.``threshold (
Union[IResolvable,ThresholdProperty,Dict[str,Any],None]) – The threshold used with a non-aggregate check expression. Non-aggregate check expressions will be applied to each row in a specific column, and the threshold will be used to determine whether the validation succeeds.
- Link:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_databrew as databrew rule_property = databrew.CfnRuleset.RuleProperty( check_expression="checkExpression", name="name", # the properties below are optional column_selectors=[databrew.CfnRuleset.ColumnSelectorProperty( name="name", regex="regex" )], disabled=False, substitution_map=[databrew.CfnRuleset.SubstitutionValueProperty( value="value", value_reference="valueReference" )], threshold=databrew.CfnRuleset.ThresholdProperty( value=123, # the properties below are optional type="type", unit="unit" ) )
Attributes
- check_expression
The expression which includes column references, condition names followed by variable references, possibly grouped and combined with other conditions.
For example,
(:col1 starts_with :prefix1 or :col1 starts_with :prefix2) and (:col1 ends_with :suffix1 or :col1 ends_with :suffix2). Column and value references are substitution variables that should start with the ‘:’ symbol. Depending on the context, substitution variables’ values can be either an actual value or a column name. These values are defined in the SubstitutionMap. If a CheckExpression starts with a column reference, then ColumnSelectors in the rule should be null. If ColumnSelectors has been defined, then there should be no columnn reference in the left side of a condition, for example,is_between :val1 and :val2.
- column_selectors
List of column selectors.
Selectors can be used to select columns using a name or regular expression from the dataset. Rule will be applied to selected columns.
- disabled
A value that specifies whether the rule is disabled.
Once a rule is disabled, a profile job will not validate it during a job run. Default value is false.
- name
The name of the rule.
- substitution_map
The map of substitution variable names to their values used in a check expression.
Variable names should start with a ‘:’ (colon). Variable values can either be actual values or column names. To differentiate between the two, column names should be enclosed in backticks, for example,
":col1": "``Column A”.``
- threshold
The threshold used with a non-aggregate check expression.
Non-aggregate check expressions will be applied to each row in a specific column, and the threshold will be used to determine whether the validation succeeds.
SubstitutionValueProperty
- class CfnRuleset.SubstitutionValueProperty(*, value, value_reference)
Bases:
objectA key-value pair to associate an expression’s substitution variable names with their values.
- Parameters:
value (
str) – Value or column name.value_reference (
str) – Variable name.
- Link:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_databrew as databrew substitution_value_property = databrew.CfnRuleset.SubstitutionValueProperty( value="value", value_reference="valueReference" )
Attributes
- value
Value or column name.
ThresholdProperty
- class CfnRuleset.ThresholdProperty(*, value, type=None, unit=None)
Bases:
objectThe threshold used with a non-aggregate check expression.
The non-aggregate check expression will be applied to each row in a specific column. Then the threshold will be used to determine whether the validation succeeds.
- Parameters:
value (
Union[int,float]) – The value of a threshold.type (
Optional[str]) – The type of a threshold. Used for comparison of an actual count of rows that satisfy the rule to the threshold value.unit (
Optional[str]) – Unit of threshold value. Can be either a COUNT or PERCENTAGE of the full sample size used for validation.
- Link:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_databrew as databrew threshold_property = databrew.CfnRuleset.ThresholdProperty( value=123, # the properties below are optional type="type", unit="unit" )
Attributes
- type
The type of a threshold.
Used for comparison of an actual count of rows that satisfy the rule to the threshold value.
- unit
Unit of threshold value.
Can be either a COUNT or PERCENTAGE of the full sample size used for validation.
- value
The value of a threshold.