EventBridge (events)

Primary Models

Primary models are models that you can act on directly. They are the models that represent resources in the AWS service, and are acted on by the managers.

pydantic model botocraft.services.events.EventBus

Bases: PrimaryBoto3Model

An event bus receives events from a source, uses rules to evaluate them, applies any configured input transformation, and routes them to the appropriate target(s).

Your account’s default event bus receives events from Amazon Web Services services. A custom event bus can receive events from your custom applications and services. A partner event bus receives events from an event source created by an SaaS partner. These events come from the partners services or applications.

Show JSON schema

{
   "title": "EventBus",
   "description": "An event bus receives events from a source, uses rules to evaluate them, applies any\nconfigured input transformation, and routes them to the appropriate target(s).\n\nYour account's default event bus receives events from Amazon Web Services services.\nA custom event bus can receive events from your custom applications and services. A\npartner event bus receives events from an event source created by an SaaS partner.\nThese events come from the partners services or applications.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "Name": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Name"
      },
      "Arn": {
         "default": null,
         "title": "Arn",
         "type": "string"
      },
      "Description": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Description"
      },
      "Policy": {
         "default": null,
         "title": "Policy",
         "type": "string"
      },
      "CreationTime": {
         "default": null,
         "format": "date-time",
         "title": "Creationtime",
         "type": "string"
      },
      "LastModifiedTime": {
         "default": null,
         "format": "date-time",
         "title": "Lastmodifiedtime",
         "type": "string"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• Arn (str)

• CreationTime (datetime.datetime)

• Description (str | None)

• LastModifiedTime (datetime.datetime)

• Name (str | None)

• Policy (str)

• session (Any | None)

field Arn: str = None

The ARN of the event bus.

field CreationTime: datetime = None

The time the event bus was created.

field Description: str | None = None

The event bus description.

field LastModifiedTime: datetime = None

The time the event bus was last modified.

field Name: str | None = None

The name of the event bus.

field Policy: str = None

The permissions policy of the event bus, describing which other Amazon Web Services accounts can write events to this event bus.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

manager_class

alias of EventBusManager

delete()

Delete the model.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

put_events(Entries: list[botocraft.services.events.PutEventsRequestEntry], EndpointId: str | None = None) → PutEventsResponse

Put events to this event bus.

Parameters:

Entries – The entry that defines an event in your system. You can specify several parameters for the entry such as the source and type of the event, resources associated with the event, and so on.

Keyword Arguments:

EndpointId – The URL subdomain of the endpoint. For example, if the URL for Endpoint is https://abcde.veo.endpoints.event.amazonaws.com, then the EndpointId is abcde.veo.

rules() → list[botocraft.services.events.EventRule]

Return the rules that are associated with this event bus.

save(**kwargs)

Save the model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

property arn: str | None

Return the ARN of the model. This is the value of the Arn attribute.

Returns:

The ARN of the model instance.

property name: str | None

Return the name of the model. This is the value of the Name attribute.

Returns:

The name of the model instance.

objects: ClassVar[classproperty]

Get the manager for this model, and set it as a class property

property pk: str | None

Return the primary key of the model. This is the value of the Name attribute.

Returns:

The primary key of the model instance.

pydantic model botocraft.services.events.EventRule

Bases: PrimaryBoto3Model

Contains information about a rule in Amazon EventBridge.

Show JSON schema

{
   "title": "EventRule",
   "description": "Contains information about a rule in Amazon EventBridge.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "Name": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Name"
      },
      "Arn": {
         "default": null,
         "title": "Arn",
         "type": "string"
      },
      "EventPattern": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Eventpattern"
      },
      "State": {
         "anyOf": [
            {
               "enum": [
                  "ENABLED",
                  "DISABLED",
                  "ENABLED_WITH_ALL_CLOUDTRAIL_MANAGEMENT_EVENTS"
               ],
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "State"
      },
      "Description": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Description"
      },
      "ScheduleExpression": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Scheduleexpression"
      },
      "RoleArn": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Rolearn"
      },
      "ManagedBy": {
         "default": null,
         "title": "Managedby",
         "type": "string"
      },
      "EventBusName": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Eventbusname"
      },
      "CreatedBy": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Createdby"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• Arn (str)

• CreatedBy (str | None)

• Description (str | None)

• EventBusName (str | None)

• EventPattern (str | None)

• ManagedBy (str)

• Name (str | None)

• RoleArn (str | None)

• ScheduleExpression (str | None)

• State (Literal['ENABLED', 'DISABLED', 'ENABLED_WITH_ALL_CLOUDTRAIL_MANAGEMENT_EVENTS'] | None)

• session (Any | None)

field Arn: str = None

The Amazon Resource Name (ARN) of the rule.

field CreatedBy: str | None = None

field Description: str | None = None

The description of the rule.

field EventBusName: str | None = None

The name or ARN of the event bus associated with the rule.

If you omit this, the default event bus is used.

field EventPattern: str | None = None

The event pattern of the rule.

For more information, see Events and Event Patterns in the Amazon EventBridge User Guide .

field ManagedBy: str = None

If the rule was created on behalf of your account by an Amazon Web Services service, this field displays the principal name of the service that created the rule.

field Name: str | None = None

The name of the rule.

field RoleArn: str | None = None

The Amazon Resource Name (ARN) of the role that is used for target invocation.

field ScheduleExpression: str | None = None

The scheduling expression.

For example, “cron(0 20 * * ? *)”, “rate(5 minutes)”. For more information, see Creating an Amazon EventBridge rule that runs on a schedule.

field State: Literal['ENABLED', 'DISABLED', 'ENABLED_WITH_ALL_CLOUDTRAIL_MANAGEMENT_EVENTS'] | None = None

The state of the rule.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

manager_class

alias of EventRuleManager

delete()

Delete the model.

disable() → None

Disable the rule.

enable() → None

Enable the rule.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

save(**kwargs)

Save the model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

property arn: str | None

Return the ARN of the model. This is the value of the Arn attribute.

Returns:

The ARN of the model instance.

property name: str | None

Return the name of the model. This is the value of the Name attribute.

Returns:

The name of the model instance.

objects: ClassVar[classproperty]

Get the manager for this model, and set it as a class property

property pk: str | None

Return the primary key of the model. This is the value of the Name attribute.

Returns:

The primary key of the model instance.

property targets: list[botocraft.services.events.EventTarget] | None

Return the targets that are associated with this rule, if any.

Note

The output of this property is cached on the model instance, so calling this multiple times will not result in multiple calls to the AWS API. If you need a fresh copy of the data, you can re-get the model instance from the manager.

pydantic model botocraft.services.events.EventTarget

Bases: PrimaryBoto3Model

Targets are the resources to be invoked when a rule is triggered. For a complete list of services and resources that can be set as a target, see PutTargets.

If you are setting the event bus of another account as the target, and that account granted permission to your account through an organization instead of directly by the account ID, then you must specify a RoleArn with proper permissions in the Target structure. For more information, see Sending and Receiving Events Between Amazon Web Services Accounts in the Amazon EventBridge User Guide.

Show JSON schema

{
   "title": "EventTarget",
   "description": "Targets are the resources to be invoked when a rule is triggered. For a complete list of services and resources that can\nbe set as a target, see `PutTargets <https://docs.aws.amazon.com/eventbridge/latest/APIReference/API_PutTargets.html>`_.\n\nIf you are setting the event bus of another account as the target, and that account granted permission to your account\nthrough an organization instead of directly by the account ID, then you must specify a ``RoleArn`` with proper\npermissions in the ``Target`` structure. For more information, see `Sending and Receiving Events Between Amazon Web\nServices Accounts <https://docs.aws.amazon.com/eventbridge/latest/userguide/eventbridge-cross-account-event-\ndelivery.html>`_ in the *Amazon EventBridge User Guide*.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "Id": {
         "title": "Id",
         "type": "string"
      },
      "Arn": {
         "title": "Arn",
         "type": "string"
      },
      "RoleArn": {
         "default": null,
         "title": "Rolearn",
         "type": "string"
      },
      "Input": {
         "default": null,
         "title": "Input",
         "type": "string"
      },
      "InputPath": {
         "default": null,
         "title": "Inputpath",
         "type": "string"
      },
      "InputTransformer": {
         "$ref": "#/$defs/EventsInputTransformer",
         "default": null
      },
      "KinesisParameters": {
         "$ref": "#/$defs/EventsKinesisParameters",
         "default": null
      },
      "RunCommandParameters": {
         "$ref": "#/$defs/EventsRunCommandParameters",
         "default": null
      },
      "EcsParameters": {
         "$ref": "#/$defs/EventsEcsParameters",
         "default": null
      },
      "BatchParameters": {
         "$ref": "#/$defs/EventsBatchParameters",
         "default": null
      },
      "SqsParameters": {
         "$ref": "#/$defs/EventsSqsParameters",
         "default": null
      },
      "HttpParameters": {
         "$ref": "#/$defs/EventsHttpParameters",
         "default": null
      },
      "RedshiftDataParameters": {
         "$ref": "#/$defs/EventsRedshiftDataParameters",
         "default": null
      },
      "SageMakerPipelineParameters": {
         "$ref": "#/$defs/EventsSageMakerPipelineParameters",
         "default": null
      },
      "DeadLetterConfig": {
         "$ref": "#/$defs/EventsDeadLetterConfig",
         "default": null
      },
      "RetryPolicy": {
         "$ref": "#/$defs/EventsRetryPolicy",
         "default": null
      },
      "AppSyncParameters": {
         "$ref": "#/$defs/EventsAppSyncParameters",
         "default": null
      }
   },
   "$defs": {
      "BatchArrayProperties": {
         "description": "The array properties for the submitted job, such as the size of the array.\n\nThe array size can be between 2 and 10,000. If you specify array properties for a\njob, it becomes an array job. This parameter is used only if the target is an Batch\njob.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "Size": {
               "anyOf": [
                  {
                     "type": "integer"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Size"
            }
         },
         "title": "BatchArrayProperties",
         "type": "object"
      },
      "BatchRetryStrategy": {
         "description": "The retry strategy to use for failed jobs, if the target is an Batch job.\n\nIf you specify a retry strategy here, it overrides the retry strategy defined in the\njob definition.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "Attempts": {
               "anyOf": [
                  {
                     "type": "integer"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Attempts"
            }
         },
         "title": "BatchRetryStrategy",
         "type": "object"
      },
      "EventsAppSyncParameters": {
         "description": "Contains the GraphQL operation to be parsed and executed, if the event target is an\nAppSync API.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "GraphQLOperation": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Graphqloperation"
            }
         },
         "title": "EventsAppSyncParameters",
         "type": "object"
      },
      "EventsAwsVpcConfiguration": {
         "description": "This structure specifies the VPC subnets and security groups for the task, and\nwhether a public IP address is to be used.\n\nThis structure is relevant only for ECS tasks that use the ``awsvpc`` network mode.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "Subnets": {
               "items": {
                  "type": "string"
               },
               "title": "Subnets",
               "type": "array"
            },
            "SecurityGroups": {
               "anyOf": [
                  {
                     "items": {
                        "type": "string"
                     },
                     "type": "array"
                  },
                  {
                     "type": "null"
                  }
               ],
               "title": "Securitygroups"
            },
            "AssignPublicIp": {
               "anyOf": [
                  {
                     "enum": [
                        "ENABLED",
                        "DISABLED"
                     ],
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Assignpublicip"
            }
         },
         "required": [
            "Subnets"
         ],
         "title": "EventsAwsVpcConfiguration",
         "type": "object"
      },
      "EventsBatchParameters": {
         "description": "The custom parameters to be used when the target is an Batch job.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "JobDefinition": {
               "title": "Jobdefinition",
               "type": "string"
            },
            "JobName": {
               "title": "Jobname",
               "type": "string"
            },
            "ArrayProperties": {
               "anyOf": [
                  {
                     "$ref": "#/$defs/BatchArrayProperties"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null
            },
            "RetryStrategy": {
               "anyOf": [
                  {
                     "$ref": "#/$defs/BatchRetryStrategy"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null
            }
         },
         "required": [
            "JobDefinition",
            "JobName"
         ],
         "title": "EventsBatchParameters",
         "type": "object"
      },
      "EventsCapacityProviderStrategyItem": {
         "description": "The details of a capacity provider strategy.\n\nTo learn more, see `CapacityProviderStrategyItem <https://docs.aws.amazon.c\nom/AmazonECS/latest/APIReference/API_CapacityProviderStrategyItem.html>`_ in the Amazon ECS API Reference.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "capacityProvider": {
               "title": "Capacityprovider",
               "type": "string"
            },
            "weight": {
               "anyOf": [
                  {
                     "type": "integer"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Weight"
            },
            "base": {
               "anyOf": [
                  {
                     "type": "integer"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Base"
            }
         },
         "required": [
            "capacityProvider"
         ],
         "title": "EventsCapacityProviderStrategyItem",
         "type": "object"
      },
      "EventsDeadLetterConfig": {
         "description": "Configuration details of the Amazon SQS queue for EventBridge to use as a dead-\nletter queue (DLQ).\n\nFor more information, see `Using dead-letter queues to process undelivered\nevents <https://docs.aws.amazon.com/eventbridge/latest/userguide/eb-rule-event-delivery.html#eb-rule-dlq>`_ in the\n*EventBridge User Guide*.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "Arn": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Arn"
            }
         },
         "title": "EventsDeadLetterConfig",
         "type": "object"
      },
      "EventsEcsParameters": {
         "description": "The custom parameters to be used when the target is an Amazon ECS task.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "TaskDefinitionArn": {
               "title": "Taskdefinitionarn",
               "type": "string"
            },
            "TaskCount": {
               "anyOf": [
                  {
                     "type": "integer"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Taskcount"
            },
            "LaunchType": {
               "anyOf": [
                  {
                     "enum": [
                        "EC2",
                        "FARGATE",
                        "EXTERNAL"
                     ],
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Launchtype"
            },
            "NetworkConfiguration": {
               "anyOf": [
                  {
                     "$ref": "#/$defs/EventsNetworkConfiguration"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null
            },
            "PlatformVersion": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Platformversion"
            },
            "Group": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Group"
            },
            "CapacityProviderStrategy": {
               "anyOf": [
                  {
                     "items": {
                        "$ref": "#/$defs/EventsCapacityProviderStrategyItem"
                     },
                     "type": "array"
                  },
                  {
                     "type": "null"
                  }
               ],
               "title": "Capacityproviderstrategy"
            },
            "EnableECSManagedTags": {
               "anyOf": [
                  {
                     "type": "boolean"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Enableecsmanagedtags"
            },
            "EnableExecuteCommand": {
               "anyOf": [
                  {
                     "type": "boolean"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Enableexecutecommand"
            },
            "PlacementConstraints": {
               "anyOf": [
                  {
                     "items": {
                        "$ref": "#/$defs/EventsPlacementConstraint"
                     },
                     "type": "array"
                  },
                  {
                     "type": "null"
                  }
               ],
               "title": "Placementconstraints"
            },
            "PlacementStrategy": {
               "anyOf": [
                  {
                     "items": {
                        "$ref": "#/$defs/EventsPlacementStrategy"
                     },
                     "type": "array"
                  },
                  {
                     "type": "null"
                  }
               ],
               "title": "Placementstrategy"
            },
            "PropagateTags": {
               "anyOf": [
                  {
                     "const": "TASK_DEFINITION",
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Propagatetags"
            },
            "ReferenceId": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Referenceid"
            },
            "Tags": {
               "anyOf": [
                  {
                     "items": {
                        "$ref": "#/$defs/Tag"
                     },
                     "type": "array"
                  },
                  {
                     "type": "null"
                  }
               ],
               "title": "Tags"
            }
         },
         "required": [
            "TaskDefinitionArn"
         ],
         "title": "EventsEcsParameters",
         "type": "object"
      },
      "EventsHttpParameters": {
         "description": "These are custom parameter to be used when the target is an API Gateway APIs or\nEventBridge ApiDestinations.\n\nIn the latter case, these are merged with any InvocationParameters specified on the\nConnection, with any values from the Connection taking precedence.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "PathParameterValues": {
               "anyOf": [
                  {
                     "items": {
                        "type": "string"
                     },
                     "type": "array"
                  },
                  {
                     "type": "null"
                  }
               ],
               "title": "Pathparametervalues"
            },
            "HeaderParameters": {
               "anyOf": [
                  {
                     "additionalProperties": {
                        "type": "string"
                     },
                     "type": "object"
                  },
                  {
                     "type": "null"
                  }
               ],
               "title": "Headerparameters"
            },
            "QueryStringParameters": {
               "anyOf": [
                  {
                     "additionalProperties": {
                        "type": "string"
                     },
                     "type": "object"
                  },
                  {
                     "type": "null"
                  }
               ],
               "title": "Querystringparameters"
            }
         },
         "title": "EventsHttpParameters",
         "type": "object"
      },
      "EventsInputTransformer": {
         "description": "Contains the parameters needed for you to provide custom input to a target based on\none or more pieces of data extracted from the event.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "InputPathsMap": {
               "anyOf": [
                  {
                     "additionalProperties": {
                        "type": "string"
                     },
                     "type": "object"
                  },
                  {
                     "type": "null"
                  }
               ],
               "title": "Inputpathsmap"
            },
            "InputTemplate": {
               "title": "Inputtemplate",
               "type": "string"
            }
         },
         "required": [
            "InputTemplate"
         ],
         "title": "EventsInputTransformer",
         "type": "object"
      },
      "EventsKinesisParameters": {
         "description": "This object enables you to specify a JSON path to extract from the event and use as\nthe partition key for the Amazon Kinesis data stream, so that you can control the\nshard to which the event goes.\n\nIf you do not include this parameter,\nthe default is to use the ``eventId`` as the partition key.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "PartitionKeyPath": {
               "title": "Partitionkeypath",
               "type": "string"
            }
         },
         "required": [
            "PartitionKeyPath"
         ],
         "title": "EventsKinesisParameters",
         "type": "object"
      },
      "EventsNetworkConfiguration": {
         "description": "This structure specifies the network configuration for an ECS task.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "awsvpcConfiguration": {
               "anyOf": [
                  {
                     "$ref": "#/$defs/EventsAwsVpcConfiguration"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null
            }
         },
         "title": "EventsNetworkConfiguration",
         "type": "object"
      },
      "EventsPlacementConstraint": {
         "description": "An object representing a constraint on task placement.\n\nTo learn more, see\n`Task Placement Constraints <https://docs.aws.amazon.com/AmazonECS/latest/developerguide/task-placement-constraints.html>`_\nin the Amazon\nElastic Container Service Developer Guide.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "type": {
               "anyOf": [
                  {
                     "enum": [
                        "distinctInstance",
                        "memberOf"
                     ],
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Type"
            },
            "expression": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Expression"
            }
         },
         "title": "EventsPlacementConstraint",
         "type": "object"
      },
      "EventsPlacementStrategy": {
         "description": "The task placement strategy for a task or service.\n\nTo learn more, see\n`Task Placement Strategies <https://docs.aws.amazon.com/AmazonECS/latest/developerguide/task-placement-strategies.html>`_\nin the Amazon\nElastic Container Service Service Developer Guide.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "type": {
               "anyOf": [
                  {
                     "enum": [
                        "random",
                        "spread",
                        "binpack"
                     ],
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Type"
            },
            "field": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Field"
            }
         },
         "title": "EventsPlacementStrategy",
         "type": "object"
      },
      "EventsRedshiftDataParameters": {
         "description": "These are custom parameters to be used when the target is a Amazon Redshift cluster\nto invoke the Amazon Redshift Data API ExecuteStatement based on EventBridge events.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "SecretManagerArn": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Secretmanagerarn"
            },
            "Database": {
               "title": "Database",
               "type": "string"
            },
            "DbUser": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Dbuser"
            },
            "Sql": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Sql"
            },
            "StatementName": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Statementname"
            },
            "WithEvent": {
               "anyOf": [
                  {
                     "type": "boolean"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Withevent"
            },
            "Sqls": {
               "anyOf": [
                  {
                     "items": {
                        "type": "string"
                     },
                     "type": "array"
                  },
                  {
                     "type": "null"
                  }
               ],
               "title": "Sqls"
            }
         },
         "required": [
            "Database"
         ],
         "title": "EventsRedshiftDataParameters",
         "type": "object"
      },
      "EventsRetryPolicy": {
         "description": "A ``RetryPolicy`` object that includes information about the retry policy settings.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "MaximumRetryAttempts": {
               "anyOf": [
                  {
                     "type": "integer"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Maximumretryattempts"
            },
            "MaximumEventAgeInSeconds": {
               "anyOf": [
                  {
                     "type": "integer"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Maximumeventageinseconds"
            }
         },
         "title": "EventsRetryPolicy",
         "type": "object"
      },
      "EventsRunCommandParameters": {
         "description": "This parameter contains the criteria (either InstanceIds or a tag) used to specify\nwhich EC2 instances are to be sent the command.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "RunCommandTargets": {
               "items": {
                  "$ref": "#/$defs/RunCommandTarget"
               },
               "title": "Runcommandtargets",
               "type": "array"
            }
         },
         "required": [
            "RunCommandTargets"
         ],
         "title": "EventsRunCommandParameters",
         "type": "object"
      },
      "EventsSageMakerPipelineParameters": {
         "description": "These are custom parameters to use when the target is a SageMaker AI Model Building\nPipeline that starts based on EventBridge events.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "PipelineParameterList": {
               "anyOf": [
                  {
                     "items": {
                        "$ref": "#/$defs/SageMakerPipelineParameter"
                     },
                     "type": "array"
                  },
                  {
                     "type": "null"
                  }
               ],
               "title": "Pipelineparameterlist"
            }
         },
         "title": "EventsSageMakerPipelineParameters",
         "type": "object"
      },
      "EventsSqsParameters": {
         "description": "This structure includes the custom parameter to be used when the target is an SQS\nFIFO queue.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "MessageGroupId": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Messagegroupid"
            }
         },
         "title": "EventsSqsParameters",
         "type": "object"
      },
      "RunCommandTarget": {
         "description": "Information about the EC2 instances that are to be sent the command, specified as\nkey-value pairs.\n\nEach\n``RunCommandTarget`` block can include only one key, but this key may specify multiple values.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "Key": {
               "title": "Key",
               "type": "string"
            },
            "Values": {
               "items": {
                  "type": "string"
               },
               "title": "Values",
               "type": "array"
            }
         },
         "required": [
            "Key",
            "Values"
         ],
         "title": "RunCommandTarget",
         "type": "object"
      },
      "SageMakerPipelineParameter": {
         "description": "Name/Value pair of a parameter to start execution of a SageMaker AI Model Building\nPipeline.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "Name": {
               "title": "Name",
               "type": "string"
            },
            "Value": {
               "title": "Value",
               "type": "string"
            }
         },
         "required": [
            "Name",
            "Value"
         ],
         "title": "SageMakerPipelineParameter",
         "type": "object"
      },
      "Tag": {
         "description": "The metadata that you apply to a resource to help you categorize and\norganize them. Each tag consists of a key and an optional value. You define\nthem.\n\nThe following basic restrictions apply to tags:\n\n* Maximum number of tags per resource - 50\n* For each resource, each tag key must be unique, and each tag key can have\n  only one value.\n* Maximum key length - 128 Unicode characters in UTF-8\n* Maximum value length - 256 Unicode characters in UTF-8\n* If your tagging schema is used across multiple services and resources,\n  remember that other services may have restrictions on allowed characters.\n  Generally allowed characters are: letters, numbers, and spaces representable in\n  UTF-8, and the following characters: + - = . _ : / @.\n* Tag keys and values are case-sensitive.\n* Do not use ``aws:``, ``AWS:``, or any upper or lowercase combination of such\n  as a prefix for either keys or values as it is reserved for Amazon Web Services\n  use. You cannot edit or delete tag keys or values with this prefix. Tags with\n  this prefix do not count against your tags per resource limit.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "Key": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Key"
            },
            "Value": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Value"
            }
         },
         "title": "Tag",
         "type": "object"
      }
   },
   "required": [
      "Id",
      "Arn"
   ]
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• AppSyncParameters (botocraft.services.events.EventsAppSyncParameters)

• Arn (str)

• BatchParameters (botocraft.services.events.EventsBatchParameters)

• DeadLetterConfig (botocraft.services.events.EventsDeadLetterConfig)

• EcsParameters (botocraft.services.events.EventsEcsParameters)

• HttpParameters (botocraft.services.events.EventsHttpParameters)

• Id (str)

• Input (str)

• InputPath (str)

• InputTransformer (botocraft.services.events.EventsInputTransformer)

• KinesisParameters (botocraft.services.events.EventsKinesisParameters)

• RedshiftDataParameters (botocraft.services.events.EventsRedshiftDataParameters)

• RetryPolicy (botocraft.services.events.EventsRetryPolicy)

• RoleArn (str)

• RunCommandParameters (botocraft.services.events.EventsRunCommandParameters)

• SageMakerPipelineParameters (botocraft.services.events.EventsSageMakerPipelineParameters)

• SqsParameters (botocraft.services.events.EventsSqsParameters)

• session (Any | None)

field AppSyncParameters: EventsAppSyncParameters = None

Contains the GraphQL operation to be parsed and executed, if the event target is an AppSync API.

field Arn: str [Required]

The Amazon Resource Name (ARN) of the target.

field BatchParameters: EventsBatchParameters = None

If the event target is an Batch job, this contains the job definition, job name, and other parameters.

For more information, see Jobs in the Batch User Guide.

field DeadLetterConfig: EventsDeadLetterConfig = None

The DeadLetterConfig that defines the target queue to send dead-letter queue events to.

field EcsParameters: EventsEcsParameters = None

Contains the Amazon ECS task definition and task count to be used, if the event target is an Amazon ECS task.

For more information about Amazon ECS tasks, see Task Definitions in the Amazon EC2 Container Service Developer Guide.

field HttpParameters: EventsHttpParameters = None

Contains the HTTP parameters to use when the target is a API Gateway endpoint or EventBridge ApiDestination.

field Id: str [Required]

The ID of the target within the specified rule.

Use this ID to reference the target when updating the rule. We recommend using a memorable and unique string.

field Input: str = None

Valid JSON text passed to the target.

In this case, nothing from the event itself is passed to the target. For more information, see The JavaScript Object Notation (JSON) Data Interchange Format.

field InputPath: str = None

The value of the JSONPath that is used for extracting part of the matched event when passing it to the target.

You may use JSON dot notation or bracket notation. For more information about JSON paths, see JSONPath.

field InputTransformer: EventsInputTransformer = None

Settings to enable you to provide custom input to a target based on certain event data.

You can extract one or more key- value pairs from the event and then use that data to send customized input to the target.

field KinesisParameters: EventsKinesisParameters = None

The custom parameter you can use to control the shard assignment, when the target is a Kinesis data stream.

If you do not include this parameter, the default is to use the eventId as the partition key.

field RedshiftDataParameters: EventsRedshiftDataParameters = None

Contains the Amazon Redshift Data API parameters to use when the target is a Amazon Redshift cluster.

field RetryPolicy: EventsRetryPolicy = None

The retry policy configuration to use for the dead-letter queue.

field RoleArn: str = None

The Amazon Resource Name (ARN) of the IAM role to be used for this target when the rule is triggered.

If one rule triggers multiple targets, you can use a different IAM role for each target.

field RunCommandParameters: EventsRunCommandParameters = None

Parameters used when you are using the rule to invoke Amazon EC2 Run Command.

field SageMakerPipelineParameters: EventsSageMakerPipelineParameters = None

Contains the SageMaker AI Model Building Pipeline parameters to start execution of a SageMaker AI Model Building Pipeline.

field SqsParameters: EventsSqsParameters = None

Contains the message group ID to use when the target is a FIFO queue.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

manager_class

alias of EventTargetManager

delete()

Delete the model.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

save(**kwargs)

Save the model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

property arn: str | None

Return the ARN of the model. This is the value of the Arn attribute.

Returns:

The ARN of the model instance.

property name: str | None

Return the name of the model. This is the value of the Id attribute.

Returns:

The name of the model instance.

objects: ClassVar[classproperty]

Get the manager for this model, and set it as a class property

property pk: str | None

Return the primary key of the model. This is the value of the Id attribute.

Returns:

The primary key of the model instance.

property rules: EventRule | None

Return the Rule object that this target belongs to.

Note

The output of this property is cached on the model instance, so calling this multiple times will not result in multiple calls to the AWS API. If you need a fresh copy of the data, you can re-get the model instance from the manager.

Managers

Managers work with the primary models to provide a high-level interface to the AWS service. They are responsible for creating, updating, and deleting the resources in the service, as well as any additional operations that are available for those models.

class botocraft.services.events.EventBusManager

Bases: Boto3ModelManager

create(model: EventBus, EventSourceName: str | None = None, KmsKeyIdentifier: str | None = None, DeadLetterConfig: EventsDeadLetterConfig | None = None, LogConfig: EventsLogConfig | None = None, Tags: list[botocraft.services.common.Tag] | None = None) → CreateEventBusResponse

Creates a new event bus within your account. This can be a custom event bus which you can use to receive events from your custom applications and services, or it can be a partner event bus which can be matched to a partner event source.

Parameters:

model – The EventBus to create.

Keyword Arguments:

• EventSourceName – If you are creating a partner event bus, this specifies the partner event source that the new event bus will be matched with.

• KmsKeyIdentifier – The identifier of the KMS customer managed key for EventBridge to use, if you choose to use a customer managed key to encrypt events on this event bus. The identifier can be the key Amazon Resource Name (ARN), KeyId, key alias, or key alias ARN.

• DeadLetterConfig – Configuration details of the Amazon SQS queue for EventBridge to use as a dead-letter queue (DLQ).

• LogConfig – The logging configuration settings for the event bus.

• Tags – Tags to associate with the event bus.

delete(Name: str) → None

Deletes the specified custom event bus or partner event bus. All rules associated with this event bus need to be deleted. You can’t delete your account’s default event bus.

Parameters:

Name – The name of the event bus to delete.

get(*, Name: str | None = None) → EventBus | None

Displays details about an event bus in your account. This can include the external Amazon Web Services accounts that are permitted to write events to your default event bus, and the associated policy. For custom event buses and partner event buses, it displays the name, ARN, policy, state, and creation time.

Keyword Arguments:

Name – The name or ARN of the event bus to show details for. If you omit this, the default event bus is displayed.

list(*, NamePrefix: str | None = None, NextToken: str | None = None, Limit: int | None = None) → PrimaryBoto3ModelQuerySet

Lists all the event buses in your account, including the default event bus, custom event buses, and partner event buses.

Keyword Arguments:

• NamePrefix – Specifying this limits the results to only those event buses with names that start with the specified prefix.

• NextToken – The token returned by a previous call, which you can use to retrieve the next set of results.

• Limit – Specifying this limits the number of results returned by this operation. The operation also returns a NextToken which you can use in a subsequent operation to retrieve the next set of results.

list_rules(*, NamePrefix: str | None = None, EventBusName: str | None = None, Limit: int | None = None) → list[botocraft.services.events.EventRule]

Lists your Amazon EventBridge rules. You can either list all the rules or you can provide a prefix to match to the rule names.

Keyword Arguments:

• NamePrefix – The prefix matching the rule name.

• EventBusName – The name or ARN of the event bus to list the rules for. If you omit this, the default event bus is used.

• Limit – The maximum number of results to return.

put_events(Entries: list[botocraft.services.events.PutEventsRequestEntry], *, EndpointId: str | None = None) → PutEventsResponse

Sends custom events to Amazon EventBridge so that they can be matched to rules.

Parameters:

Entries – The entry that defines an event in your system. You can specify several parameters for the entry such as the source and type of the event, resources associated with the event, and so on.

Keyword Arguments:

EndpointId – The URL subdomain of the endpoint. For example, if the URL for Endpoint is https://abcde.veo.endpoints.event.amazonaws.com, then the EndpointId is abcde.veo.

update(model: EventBus, KmsKeyIdentifier: str | None = None, DeadLetterConfig: EventsDeadLetterConfig | None = None, LogConfig: EventsLogConfig | None = None) → UpdateEventBusResponse

Updates the specified event bus.

Parameters:

model – The EventBus to update.

Keyword Arguments:

• KmsKeyIdentifier – The identifier of the KMS customer managed key for EventBridge to use, if you choose to use a customer managed key to encrypt events on this event bus. The identifier can be the key Amazon Resource Name (ARN), KeyId, key alias, or key alias ARN.

• DeadLetterConfig – Configuration details of the Amazon SQS queue for EventBridge to use as a dead-letter queue (DLQ).

• LogConfig – The logging configuration settings for the event bus.

service_name: str = 'events'

ec2, s3, etc.

Type:

The name of the boto3 service. Example

class botocraft.services.events.EventRuleManager

Bases: Boto3ModelManager

create(model: EventRule, Tags: list[botocraft.services.common.Tag] | None = None) → str

Creates or updates the specified rule. Rules are enabled by default, or based on value of the state. You can disable a rule using DisableRule.

Parameters:

model – The Rule to create.

Keyword Arguments:

Tags – The list of key-value pairs to associate with the rule.

delete(Name: str, *, EventBusName: str | None = None, Force: bool = True) → None

Deletes the specified rule.

Parameters:

Name – The name of the rule.

Keyword Arguments:

• EventBusName – The name or ARN of the event bus associated with the rule. If you omit this, the default event bus is used.

• Force – If this is a managed rule, created by an Amazon Web Services service on your behalf, you must specify Force as True to delete the rule. This parameter is ignored for rules that are not managed rules. You can check whether a rule is a managed rule by using DescribeRule or ListRules and checking the ManagedBy field of the response.

disable(Name: str, *, EventBusName: str | None = None) → None

Disables the specified rule. A disabled rule won’t match any events, and won’t self-trigger if it has a schedule expression.

Parameters:

Name – The name of the rule.

Keyword Arguments:

EventBusName – The name or ARN of the event bus associated with the rule. If you omit this, the default event bus is used.

enable(Name: str, *, EventBusName: str | None = None) → None

Enables the specified rule. If the rule does not exist, the operation fails.

Parameters:

Name – The name of the rule.

Keyword Arguments:

EventBusName – The name or ARN of the event bus associated with the rule. If you omit this, the default event bus is used.

get(Name: str, *, EventBusName: str | None = None) → DescribeRuleResponse | None

Describes the specified rule.

Parameters:

Name – The name of the rule.

Keyword Arguments:

EventBusName – The name or ARN of the event bus associated with the rule. If you omit this, the default event bus is used.

list(*, NamePrefix: str | None = None, EventBusName: str | None = None, Limit: int | None = None) → PrimaryBoto3ModelQuerySet

Lists your Amazon EventBridge rules. You can either list all the rules or you can provide a prefix to match to the rule names.

Keyword Arguments:

• NamePrefix – The prefix matching the rule name.

• EventBusName – The name or ARN of the event bus to list the rules for. If you omit this, the default event bus is used.

• Limit – The maximum number of results to return.

list_by_target(TargetArn: str, *, EventBusName: str | None = None, Limit: int | None = None) → list[str]

Lists the rules for the specified target. You can see which of the rules in Amazon EventBridge can invoke a specific target in your account.

Parameters:

TargetArn – The Amazon Resource Name (ARN) of the target resource.

Keyword Arguments:

• EventBusName – The name or ARN of the event bus to list rules for. If you omit this, the default event bus is used.

• Limit – The maximum number of results to return.

list_targets(Rule: str, *, EventBusName: str | None = None, Limit: int | None = None) → list[botocraft.services.events.EventTarget]

Lists the targets assigned to the specified rule.

Parameters:

Rule – The name of the rule.

Keyword Arguments:

• EventBusName – The name or ARN of the event bus associated with the rule. If you omit this, the default event bus is used.

• Limit – The maximum number of results to return.

update(model: EventRule, Tags: list[botocraft.services.common.Tag] | None = None) → str

Creates or updates the specified rule. Rules are enabled by default, or based on value of the state. You can disable a rule using DisableRule.

Parameters:

model – The Rule to update.

Keyword Arguments:

Tags – The list of key-value pairs to associate with the rule.

service_name: str = 'events'

ec2, s3, etc.

Type:

The name of the boto3 service. Example

class botocraft.services.events.EventTargetManager

Bases: Boto3ModelManager

create(model: EventTarget, EventBusName: str | None = None) → PutTargetsResponse

Adds the specified targets to the specified rule, or updates the targets if they are already associated with the rule.

Parameters:

model – The Target to create.

Keyword Arguments:

EventBusName – The name or ARN of the event bus associated with the rule. If you omit this, the default event bus is used.

delete(Rule: str, Ids: list[str], *, EventBusName: str | None = None, Force: bool | None = None) → EventTarget

Removes the specified targets from the specified rule. When the rule is triggered, those targets are no longer be invoked.

Parameters:

• Rule – The name of the rule.

• Ids – The IDs of the targets to remove from the rule.

Keyword Arguments:

• EventBusName – The name or ARN of the event bus associated with the rule. If you omit this, the default event bus is used.

• Force – If this is a managed rule, created by an Amazon Web Services service on your behalf, you must specify Force as True to remove targets. This parameter is ignored for rules that are not managed rules. You can check whether a rule is a managed rule by using DescribeRule or ListRules and checking the ManagedBy field of the response.

list(Rule: str, *, EventBusName: str | None = None, Limit: int | None = None) → PrimaryBoto3ModelQuerySet

Lists the targets assigned to the specified rule.

Parameters:

Rule – The name of the rule.

Keyword Arguments:

• EventBusName – The name or ARN of the event bus associated with the rule. If you omit this, the default event bus is used.

• Limit – The maximum number of results to return.

list_rules(TargetArn: str, *, EventBusName: str | None = None, Limit: int | None = None) → list[str]

Lists the rules for the specified target. You can see which of the rules in Amazon EventBridge can invoke a specific target in your account.

Parameters:

TargetArn – The Amazon Resource Name (ARN) of the target resource.

Keyword Arguments:

• EventBusName – The name or ARN of the event bus to list rules for. If you omit this, the default event bus is used.

• Limit – The maximum number of results to return.

update(model: EventTarget, EventBusName: str | None = None) → PutTargetsResponse

Adds the specified targets to the specified rule, or updates the targets if they are already associated with the rule.

Parameters:

model – The Target to update.

Keyword Arguments:

EventBusName – The name or ARN of the event bus associated with the rule. If you omit this, the default event bus is used.

service_name: str = 'events'

ec2, s3, etc.

Type:

The name of the boto3 service. Example

Secondary Models

Secondary models are models that are used by the primary models to organize their data. They are not acted on directly, but are used to describe the structure of the fields in the primary models or other secondary models.

pydantic model botocraft.services.events.BatchArrayProperties

Bases: Boto3Model

The array properties for the submitted job, such as the size of the array.

The array size can be between 2 and 10,000. If you specify array properties for a job, it becomes an array job. This parameter is used only if the target is an Batch job.

Show JSON schema

{
   "title": "BatchArrayProperties",
   "description": "The array properties for the submitted job, such as the size of the array.\n\nThe array size can be between 2 and 10,000. If you specify array properties for a\njob, it becomes an array job. This parameter is used only if the target is an Batch\njob.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "Size": {
         "anyOf": [
            {
               "type": "integer"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Size"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• Size (int | None)

• session (Any | None)

field Size: int | None = None

The size of the array, if this is an array batch job.

Valid values are integers between 2 and 10,000.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.BatchRetryStrategy

Bases: Boto3Model

The retry strategy to use for failed jobs, if the target is an Batch job.

If you specify a retry strategy here, it overrides the retry strategy defined in the job definition.

Show JSON schema

{
   "title": "BatchRetryStrategy",
   "description": "The retry strategy to use for failed jobs, if the target is an Batch job.\n\nIf you specify a retry strategy here, it overrides the retry strategy defined in the\njob definition.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "Attempts": {
         "anyOf": [
            {
               "type": "integer"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Attempts"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• Attempts (int | None)

• session (Any | None)

field Attempts: int | None = None

The number of times to attempt to retry, if the job fails.

Valid values are 1-10.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.EventsAppSyncParameters

Bases: Boto3Model

Contains the GraphQL operation to be parsed and executed, if the event target is an AppSync API.

Show JSON schema

{
   "title": "EventsAppSyncParameters",
   "description": "Contains the GraphQL operation to be parsed and executed, if the event target is an\nAppSync API.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "GraphQLOperation": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Graphqloperation"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• GraphQLOperation (str | None)

• session (Any | None)

field GraphQLOperation: str | None = None

The GraphQL operation; that is, the query, mutation, or subscription to be parsed and executed by the GraphQL service.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.EventsAwsVpcConfiguration

Bases: Boto3Model

This structure specifies the VPC subnets and security groups for the task, and whether a public IP address is to be used.

This structure is relevant only for ECS tasks that use the awsvpc network mode.

Show JSON schema

{
   "title": "EventsAwsVpcConfiguration",
   "description": "This structure specifies the VPC subnets and security groups for the task, and\nwhether a public IP address is to be used.\n\nThis structure is relevant only for ECS tasks that use the ``awsvpc`` network mode.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "Subnets": {
         "items": {
            "type": "string"
         },
         "title": "Subnets",
         "type": "array"
      },
      "SecurityGroups": {
         "anyOf": [
            {
               "items": {
                  "type": "string"
               },
               "type": "array"
            },
            {
               "type": "null"
            }
         ],
         "title": "Securitygroups"
      },
      "AssignPublicIp": {
         "anyOf": [
            {
               "enum": [
                  "ENABLED",
                  "DISABLED"
               ],
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Assignpublicip"
      }
   },
   "required": [
      "Subnets"
   ]
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• AssignPublicIp (Literal['ENABLED', 'DISABLED'] | None)

• SecurityGroups (list[str] | None)

• Subnets (list[str])

• session (Any | None)

field AssignPublicIp: Literal['ENABLED', 'DISABLED'] | None = None

Specifies whether the task’s elastic network interface receives a public IP address.

You can specify ENABLED only when LaunchType in EcsParameters is set to FARGATE.

field SecurityGroups: builtins.list[str] | None [Optional]

Specifies the security groups associated with the task.

These security groups must all be in the same VPC. You can specify as many as five security groups. If you do not specify a security group, the default security group for the VPC is used.

field Subnets: builtins.list[str] [Required]

Specifies the subnets associated with the task.

These subnets must all be in the same VPC. You can specify as many as 16 subnets.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.EventsBatchParameters

Bases: Boto3Model

The custom parameters to be used when the target is an Batch job.

Show JSON schema

{
   "title": "EventsBatchParameters",
   "description": "The custom parameters to be used when the target is an Batch job.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "JobDefinition": {
         "title": "Jobdefinition",
         "type": "string"
      },
      "JobName": {
         "title": "Jobname",
         "type": "string"
      },
      "ArrayProperties": {
         "anyOf": [
            {
               "$ref": "#/$defs/BatchArrayProperties"
            },
            {
               "type": "null"
            }
         ],
         "default": null
      },
      "RetryStrategy": {
         "anyOf": [
            {
               "$ref": "#/$defs/BatchRetryStrategy"
            },
            {
               "type": "null"
            }
         ],
         "default": null
      }
   },
   "$defs": {
      "BatchArrayProperties": {
         "description": "The array properties for the submitted job, such as the size of the array.\n\nThe array size can be between 2 and 10,000. If you specify array properties for a\njob, it becomes an array job. This parameter is used only if the target is an Batch\njob.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "Size": {
               "anyOf": [
                  {
                     "type": "integer"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Size"
            }
         },
         "title": "BatchArrayProperties",
         "type": "object"
      },
      "BatchRetryStrategy": {
         "description": "The retry strategy to use for failed jobs, if the target is an Batch job.\n\nIf you specify a retry strategy here, it overrides the retry strategy defined in the\njob definition.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "Attempts": {
               "anyOf": [
                  {
                     "type": "integer"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Attempts"
            }
         },
         "title": "BatchRetryStrategy",
         "type": "object"
      }
   },
   "required": [
      "JobDefinition",
      "JobName"
   ]
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• ArrayProperties (botocraft.services.events.BatchArrayProperties | None)

• JobDefinition (str)

• JobName (str)

• RetryStrategy (botocraft.services.events.BatchRetryStrategy | None)

• session (Any | None)

field ArrayProperties: BatchArrayProperties | None = None

The array properties for the submitted job, such as the size of the array.

The array size can be between 2 and 10,000. If you specify array properties for a job, it becomes an array job. This parameter is used only if the target is an Batch job.

field JobDefinition: str [Required]

The ARN or name of the job definition to use if the event target is an Batch job.

This job definition must already exist.

field JobName: str [Required]

The name to use for this execution of the job, if the target is an Batch job.

field RetryStrategy: BatchRetryStrategy | None = None

The retry strategy to use for failed jobs, if the target is an Batch job.

The retry strategy is the number of times to retry the failed job execution. Valid values are 1-10. When you specify a retry strategy here, it overrides the retry strategy defined in the job definition.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.EventsCapacityProviderStrategyItem

Bases: Boto3Model

The details of a capacity provider strategy.

To learn more, see CapacityProviderStrategyItem in the Amazon ECS API Reference.

Show JSON schema

{
   "title": "EventsCapacityProviderStrategyItem",
   "description": "The details of a capacity provider strategy.\n\nTo learn more, see `CapacityProviderStrategyItem <https://docs.aws.amazon.c\nom/AmazonECS/latest/APIReference/API_CapacityProviderStrategyItem.html>`_ in the Amazon ECS API Reference.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "capacityProvider": {
         "title": "Capacityprovider",
         "type": "string"
      },
      "weight": {
         "anyOf": [
            {
               "type": "integer"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Weight"
      },
      "base": {
         "anyOf": [
            {
               "type": "integer"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Base"
      }
   },
   "required": [
      "capacityProvider"
   ]
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• base (int | None)

• capacityProvider (str)

• session (Any | None)

• weight (int | None)

field base: int | None = None

The base value designates how many tasks, at a minimum, to run on the specified capacity provider.

Only one capacity provider in a capacity provider strategy can have a base defined. If no value is specified, the default value of 0 is used.

field capacityProvider: str [Required]

The short name of the capacity provider.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

field weight: int | None = None

The weight value designates the relative percentage of the total number of tasks launched that should use the specified capacity provider.

The weight value is taken into consideration after the base value, if defined, is satisfied.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.EventsDeadLetterConfig

Bases: Boto3Model

Configuration details of the Amazon SQS queue for EventBridge to use as a dead- letter queue (DLQ).

For more information, see Using dead-letter queues to process undelivered events in the EventBridge User Guide.

Show JSON schema

{
   "title": "EventsDeadLetterConfig",
   "description": "Configuration details of the Amazon SQS queue for EventBridge to use as a dead-\nletter queue (DLQ).\n\nFor more information, see `Using dead-letter queues to process undelivered\nevents <https://docs.aws.amazon.com/eventbridge/latest/userguide/eb-rule-event-delivery.html#eb-rule-dlq>`_ in the\n*EventBridge User Guide*.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "Arn": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Arn"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• Arn (str | None)

• session (Any | None)

field Arn: str | None = None

The ARN of the SQS queue specified as the target for the dead-letter queue.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.EventsEcsParameters

Bases: TagsDictMixin, Boto3Model

The custom parameters to be used when the target is an Amazon ECS task.

Show JSON schema

{
   "title": "EventsEcsParameters",
   "description": "The custom parameters to be used when the target is an Amazon ECS task.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "TaskDefinitionArn": {
         "title": "Taskdefinitionarn",
         "type": "string"
      },
      "TaskCount": {
         "anyOf": [
            {
               "type": "integer"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Taskcount"
      },
      "LaunchType": {
         "anyOf": [
            {
               "enum": [
                  "EC2",
                  "FARGATE",
                  "EXTERNAL"
               ],
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Launchtype"
      },
      "NetworkConfiguration": {
         "anyOf": [
            {
               "$ref": "#/$defs/EventsNetworkConfiguration"
            },
            {
               "type": "null"
            }
         ],
         "default": null
      },
      "PlatformVersion": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Platformversion"
      },
      "Group": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Group"
      },
      "CapacityProviderStrategy": {
         "anyOf": [
            {
               "items": {
                  "$ref": "#/$defs/EventsCapacityProviderStrategyItem"
               },
               "type": "array"
            },
            {
               "type": "null"
            }
         ],
         "title": "Capacityproviderstrategy"
      },
      "EnableECSManagedTags": {
         "anyOf": [
            {
               "type": "boolean"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Enableecsmanagedtags"
      },
      "EnableExecuteCommand": {
         "anyOf": [
            {
               "type": "boolean"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Enableexecutecommand"
      },
      "PlacementConstraints": {
         "anyOf": [
            {
               "items": {
                  "$ref": "#/$defs/EventsPlacementConstraint"
               },
               "type": "array"
            },
            {
               "type": "null"
            }
         ],
         "title": "Placementconstraints"
      },
      "PlacementStrategy": {
         "anyOf": [
            {
               "items": {
                  "$ref": "#/$defs/EventsPlacementStrategy"
               },
               "type": "array"
            },
            {
               "type": "null"
            }
         ],
         "title": "Placementstrategy"
      },
      "PropagateTags": {
         "anyOf": [
            {
               "const": "TASK_DEFINITION",
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Propagatetags"
      },
      "ReferenceId": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Referenceid"
      },
      "Tags": {
         "anyOf": [
            {
               "items": {
                  "$ref": "#/$defs/Tag"
               },
               "type": "array"
            },
            {
               "type": "null"
            }
         ],
         "title": "Tags"
      }
   },
   "$defs": {
      "EventsAwsVpcConfiguration": {
         "description": "This structure specifies the VPC subnets and security groups for the task, and\nwhether a public IP address is to be used.\n\nThis structure is relevant only for ECS tasks that use the ``awsvpc`` network mode.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "Subnets": {
               "items": {
                  "type": "string"
               },
               "title": "Subnets",
               "type": "array"
            },
            "SecurityGroups": {
               "anyOf": [
                  {
                     "items": {
                        "type": "string"
                     },
                     "type": "array"
                  },
                  {
                     "type": "null"
                  }
               ],
               "title": "Securitygroups"
            },
            "AssignPublicIp": {
               "anyOf": [
                  {
                     "enum": [
                        "ENABLED",
                        "DISABLED"
                     ],
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Assignpublicip"
            }
         },
         "required": [
            "Subnets"
         ],
         "title": "EventsAwsVpcConfiguration",
         "type": "object"
      },
      "EventsCapacityProviderStrategyItem": {
         "description": "The details of a capacity provider strategy.\n\nTo learn more, see `CapacityProviderStrategyItem <https://docs.aws.amazon.c\nom/AmazonECS/latest/APIReference/API_CapacityProviderStrategyItem.html>`_ in the Amazon ECS API Reference.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "capacityProvider": {
               "title": "Capacityprovider",
               "type": "string"
            },
            "weight": {
               "anyOf": [
                  {
                     "type": "integer"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Weight"
            },
            "base": {
               "anyOf": [
                  {
                     "type": "integer"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Base"
            }
         },
         "required": [
            "capacityProvider"
         ],
         "title": "EventsCapacityProviderStrategyItem",
         "type": "object"
      },
      "EventsNetworkConfiguration": {
         "description": "This structure specifies the network configuration for an ECS task.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "awsvpcConfiguration": {
               "anyOf": [
                  {
                     "$ref": "#/$defs/EventsAwsVpcConfiguration"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null
            }
         },
         "title": "EventsNetworkConfiguration",
         "type": "object"
      },
      "EventsPlacementConstraint": {
         "description": "An object representing a constraint on task placement.\n\nTo learn more, see\n`Task Placement Constraints <https://docs.aws.amazon.com/AmazonECS/latest/developerguide/task-placement-constraints.html>`_\nin the Amazon\nElastic Container Service Developer Guide.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "type": {
               "anyOf": [
                  {
                     "enum": [
                        "distinctInstance",
                        "memberOf"
                     ],
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Type"
            },
            "expression": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Expression"
            }
         },
         "title": "EventsPlacementConstraint",
         "type": "object"
      },
      "EventsPlacementStrategy": {
         "description": "The task placement strategy for a task or service.\n\nTo learn more, see\n`Task Placement Strategies <https://docs.aws.amazon.com/AmazonECS/latest/developerguide/task-placement-strategies.html>`_\nin the Amazon\nElastic Container Service Service Developer Guide.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "type": {
               "anyOf": [
                  {
                     "enum": [
                        "random",
                        "spread",
                        "binpack"
                     ],
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Type"
            },
            "field": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Field"
            }
         },
         "title": "EventsPlacementStrategy",
         "type": "object"
      },
      "Tag": {
         "description": "The metadata that you apply to a resource to help you categorize and\norganize them. Each tag consists of a key and an optional value. You define\nthem.\n\nThe following basic restrictions apply to tags:\n\n* Maximum number of tags per resource - 50\n* For each resource, each tag key must be unique, and each tag key can have\n  only one value.\n* Maximum key length - 128 Unicode characters in UTF-8\n* Maximum value length - 256 Unicode characters in UTF-8\n* If your tagging schema is used across multiple services and resources,\n  remember that other services may have restrictions on allowed characters.\n  Generally allowed characters are: letters, numbers, and spaces representable in\n  UTF-8, and the following characters: + - = . _ : / @.\n* Tag keys and values are case-sensitive.\n* Do not use ``aws:``, ``AWS:``, or any upper or lowercase combination of such\n  as a prefix for either keys or values as it is reserved for Amazon Web Services\n  use. You cannot edit or delete tag keys or values with this prefix. Tags with\n  this prefix do not count against your tags per resource limit.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "Key": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Key"
            },
            "Value": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Value"
            }
         },
         "title": "Tag",
         "type": "object"
      }
   },
   "required": [
      "TaskDefinitionArn"
   ]
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• CapacityProviderStrategy (list[botocraft.services.events.EventsCapacityProviderStrategyItem] | None)

• EnableECSManagedTags (bool | None)

• EnableExecuteCommand (bool | None)

• Group (str | None)

• LaunchType (Literal['EC2', 'FARGATE', 'EXTERNAL'] | None)

• NetworkConfiguration (botocraft.services.events.EventsNetworkConfiguration | None)

• PlacementConstraints (list[botocraft.services.events.EventsPlacementConstraint] | None)

• PlacementStrategy (list[botocraft.services.events.EventsPlacementStrategy] | None)

• PlatformVersion (str | None)

• PropagateTags (Literal['TASK_DEFINITION'] | None)

• ReferenceId (str | None)

• Tags (list[botocraft.services.common.Tag] | None)

• TaskCount (int | None)

• TaskDefinitionArn (str)

• session (Any | None)

field CapacityProviderStrategy: builtins.list[EventsCapacityProviderStrategyItem] | None [Optional]

The capacity provider strategy to use for the task.

field EnableECSManagedTags: bool | None = None

Specifies whether to enable Amazon ECS managed tags for the task.

For more information, see Tagging Your Amazon ECS Resources in the Amazon Elastic Container Service Developer Guide.

field EnableExecuteCommand: bool | None = None

Whether or not to enable the execute command functionality for the containers in this task.

If true, this enables execute command functionality on all containers in the task.

field Group: str | None = None

Specifies an ECS task group for the task.

The maximum length is 255 characters.

field LaunchType: Literal['EC2', 'FARGATE', 'EXTERNAL'] | None = None

Specifies the launch type on which your task is running.

The launch type that you specify here must match one of the launch type (compatibilities) of the target task. The FARGATE value is supported only in the Regions where Fargate with Amazon ECS is supported. For more information, see Fargate on Amazon ECS in the Amazon Elastic Container Service Developer Guide.

field NetworkConfiguration: EventsNetworkConfiguration | None = None

Use this structure if the Amazon ECS task uses the awsvpc network mode.

This structure specifies the VPC subnets and security groups associated with the task, and whether a public IP address is to be used. This structure is required if LaunchType is FARGATE because the awsvpc mode is required for Fargate tasks.

field PlacementConstraints: builtins.list[EventsPlacementConstraint] | None [Optional]

An array of placement constraint objects to use for the task.

You can specify up to 10 constraints per task (including constraints in the task definition and those specified at runtime).

field PlacementStrategy: builtins.list[EventsPlacementStrategy] | None [Optional]

The placement strategy objects to use for the task.

You can specify a maximum of five strategy rules per task.

field PlatformVersion: str | None = None

Specifies the platform version for the task.

Specify only the numeric portion of the platform version, such as 1.1.0.

field PropagateTags: Literal['TASK_DEFINITION'] | None = None

Specifies whether to propagate the tags from the task definition to the task.

If no value is specified, the tags are not propagated. Tags can only be propagated to the task during task creation. To add tags to a task after task creation, use the TagResource API action.

field ReferenceId: str | None = None

The reference ID to use for the task.

field Tags: builtins.list[Tag] | None [Optional]

The metadata that you apply to the task to help you categorize and organize them.

Each tag consists of a key and an optional value, both of which you define. To learn more, see RunTask in the Amazon ECS API Reference.

field TaskCount: int | None = None

The number of tasks to create based on TaskDefinition.

The default is 1.

field TaskDefinitionArn: str [Required]

The ARN of the task definition to use if the event target is an Amazon ECS task.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

tag_class

alias of Tag

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

property tags: TagsDict

Get the tags for the model instance.

Returns:

The tags for the model instance.

pydantic model botocraft.services.events.EventsHttpParameters

Bases: Boto3Model

These are custom parameter to be used when the target is an API Gateway APIs or EventBridge ApiDestinations.

In the latter case, these are merged with any InvocationParameters specified on the Connection, with any values from the Connection taking precedence.

Show JSON schema

{
   "title": "EventsHttpParameters",
   "description": "These are custom parameter to be used when the target is an API Gateway APIs or\nEventBridge ApiDestinations.\n\nIn the latter case, these are merged with any InvocationParameters specified on the\nConnection, with any values from the Connection taking precedence.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "PathParameterValues": {
         "anyOf": [
            {
               "items": {
                  "type": "string"
               },
               "type": "array"
            },
            {
               "type": "null"
            }
         ],
         "title": "Pathparametervalues"
      },
      "HeaderParameters": {
         "anyOf": [
            {
               "additionalProperties": {
                  "type": "string"
               },
               "type": "object"
            },
            {
               "type": "null"
            }
         ],
         "title": "Headerparameters"
      },
      "QueryStringParameters": {
         "anyOf": [
            {
               "additionalProperties": {
                  "type": "string"
               },
               "type": "object"
            },
            {
               "type": "null"
            }
         ],
         "title": "Querystringparameters"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• HeaderParameters (dict[str, str] | None)

• PathParameterValues (list[str] | None)

• QueryStringParameters (dict[str, str] | None)

• session (Any | None)

field HeaderParameters: dict[str, str] | None [Optional]

The headers that need to be sent as part of request invoking the API Gateway API or EventBridge ApiDestination.

field PathParameterValues: builtins.list[str] | None [Optional]

The path parameter values to be used to populate API Gateway API or EventBridge ApiDestination path wildcards (“*”).

field QueryStringParameters: dict[str, str] | None [Optional]

The query string keys/values that need to be sent as part of request invoking the API Gateway API or EventBridge ApiDestination.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.EventsInputTransformer

Bases: Boto3Model

Contains the parameters needed for you to provide custom input to a target based on one or more pieces of data extracted from the event.

Show JSON schema

{
   "title": "EventsInputTransformer",
   "description": "Contains the parameters needed for you to provide custom input to a target based on\none or more pieces of data extracted from the event.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "InputPathsMap": {
         "anyOf": [
            {
               "additionalProperties": {
                  "type": "string"
               },
               "type": "object"
            },
            {
               "type": "null"
            }
         ],
         "title": "Inputpathsmap"
      },
      "InputTemplate": {
         "title": "Inputtemplate",
         "type": "string"
      }
   },
   "required": [
      "InputTemplate"
   ]
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• InputPathsMap (dict[str, str] | None)

• InputTemplate (str)

• session (Any | None)

field InputPathsMap: dict[str, str] | None [Optional]

Map of JSON paths to be extracted from the event.

You can then insert these in the template in InputTemplate to produce the output you want to be sent to the target.

field InputTemplate: str [Required]

Input template where you specify placeholders that will be filled with the values of the keys from InputPathsMap to customize the data sent to the target.

Enclose each InputPathsMaps value in brackets: <value>

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.EventsKinesisParameters

Bases: Boto3Model

This object enables you to specify a JSON path to extract from the event and use as the partition key for the Amazon Kinesis data stream, so that you can control the shard to which the event goes.

If you do not include this parameter, the default is to use the eventId as the partition key.

Show JSON schema

{
   "title": "EventsKinesisParameters",
   "description": "This object enables you to specify a JSON path to extract from the event and use as\nthe partition key for the Amazon Kinesis data stream, so that you can control the\nshard to which the event goes.\n\nIf you do not include this parameter,\nthe default is to use the ``eventId`` as the partition key.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "PartitionKeyPath": {
         "title": "Partitionkeypath",
         "type": "string"
      }
   },
   "required": [
      "PartitionKeyPath"
   ]
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• PartitionKeyPath (str)

• session (Any | None)

field PartitionKeyPath: str [Required]

The JSON path to be extracted from the event and used as the partition key.

For more information, see Amazon Kinesis Streams Key Concepts in the Amazon Kinesis Streams Developer Guide.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.EventsNetworkConfiguration

Bases: Boto3Model

This structure specifies the network configuration for an ECS task.

Show JSON schema

{
   "title": "EventsNetworkConfiguration",
   "description": "This structure specifies the network configuration for an ECS task.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "awsvpcConfiguration": {
         "anyOf": [
            {
               "$ref": "#/$defs/EventsAwsVpcConfiguration"
            },
            {
               "type": "null"
            }
         ],
         "default": null
      }
   },
   "$defs": {
      "EventsAwsVpcConfiguration": {
         "description": "This structure specifies the VPC subnets and security groups for the task, and\nwhether a public IP address is to be used.\n\nThis structure is relevant only for ECS tasks that use the ``awsvpc`` network mode.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "Subnets": {
               "items": {
                  "type": "string"
               },
               "title": "Subnets",
               "type": "array"
            },
            "SecurityGroups": {
               "anyOf": [
                  {
                     "items": {
                        "type": "string"
                     },
                     "type": "array"
                  },
                  {
                     "type": "null"
                  }
               ],
               "title": "Securitygroups"
            },
            "AssignPublicIp": {
               "anyOf": [
                  {
                     "enum": [
                        "ENABLED",
                        "DISABLED"
                     ],
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Assignpublicip"
            }
         },
         "required": [
            "Subnets"
         ],
         "title": "EventsAwsVpcConfiguration",
         "type": "object"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• awsvpcConfiguration (botocraft.services.events.EventsAwsVpcConfiguration | None)

• session (Any | None)

field awsvpcConfiguration: EventsAwsVpcConfiguration | None = None

Use this structure to specify the VPC subnets and security groups for the task, and whether a public IP address is to be used.

This structure is relevant only for ECS tasks that use the awsvpc network mode.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.EventsPlacementConstraint

Bases: Boto3Model

An object representing a constraint on task placement.

To learn more, see Task Placement Constraints in the Amazon Elastic Container Service Developer Guide.

Show JSON schema

{
   "title": "EventsPlacementConstraint",
   "description": "An object representing a constraint on task placement.\n\nTo learn more, see\n`Task Placement Constraints <https://docs.aws.amazon.com/AmazonECS/latest/developerguide/task-placement-constraints.html>`_\nin the Amazon\nElastic Container Service Developer Guide.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "type": {
         "anyOf": [
            {
               "enum": [
                  "distinctInstance",
                  "memberOf"
               ],
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Type"
      },
      "expression": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Expression"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• expression (str | None)

• session (Any | None)

• type (Literal['distinctInstance', 'memberOf'] | None)

field expression: str | None = None

A cluster query language expression to apply to the constraint.

You cannot specify an expression if the constraint type is distinctInstance. To learn more, see Cluster Query Language in the Amazon Elastic Container Service Developer Guide.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

field type: Literal['distinctInstance', 'memberOf'] | None = None

The type of constraint.

Use distinctInstance to ensure that each task in a particular group is running on a different container instance. Use memberOf to restrict the selection to a group of valid candidates.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.EventsPlacementStrategy

Bases: Boto3Model

The task placement strategy for a task or service.

To learn more, see Task Placement Strategies in the Amazon Elastic Container Service Service Developer Guide.

Show JSON schema

{
   "title": "EventsPlacementStrategy",
   "description": "The task placement strategy for a task or service.\n\nTo learn more, see\n`Task Placement Strategies <https://docs.aws.amazon.com/AmazonECS/latest/developerguide/task-placement-strategies.html>`_\nin the Amazon\nElastic Container Service Service Developer Guide.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "type": {
         "anyOf": [
            {
               "enum": [
                  "random",
                  "spread",
                  "binpack"
               ],
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Type"
      },
      "field": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Field"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• field (str | None)

• session (Any | None)

• type (Literal['random', 'spread', 'binpack'] | None)

field field: str | None = None

The field to apply the placement strategy against.

For the spread placement strategy, valid values are instanceId (or host, which has the same effect), or any platform or custom attribute that is applied to a container instance, such as attribute:ecs.availability-zone. For the binpack placement strategy, valid values are cpu and memory. For the random placement strategy, this field is not used.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

field type: Literal['random', 'spread', 'binpack'] | None = None

The type of placement strategy.

The random placement strategy randomly places tasks on available candidates. The spread placement strategy spreads placement across available candidates evenly based on the field parameter. The binpack strategy places tasks on available candidates that have the least available amount of the resource that is specified with the field parameter. For example, if you binpack on memory, a task is placed on the instance with the least amount of remaining memory (but still enough to run the task).

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.EventsRedshiftDataParameters

Bases: Boto3Model

These are custom parameters to be used when the target is a Amazon Redshift cluster to invoke the Amazon Redshift Data API ExecuteStatement based on EventBridge events.

Show JSON schema

{
   "title": "EventsRedshiftDataParameters",
   "description": "These are custom parameters to be used when the target is a Amazon Redshift cluster\nto invoke the Amazon Redshift Data API ExecuteStatement based on EventBridge events.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "SecretManagerArn": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Secretmanagerarn"
      },
      "Database": {
         "title": "Database",
         "type": "string"
      },
      "DbUser": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Dbuser"
      },
      "Sql": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Sql"
      },
      "StatementName": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Statementname"
      },
      "WithEvent": {
         "anyOf": [
            {
               "type": "boolean"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Withevent"
      },
      "Sqls": {
         "anyOf": [
            {
               "items": {
                  "type": "string"
               },
               "type": "array"
            },
            {
               "type": "null"
            }
         ],
         "title": "Sqls"
      }
   },
   "required": [
      "Database"
   ]
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• Database (str)

• DbUser (str | None)

• SecretManagerArn (str | None)

• Sql (str | None)

• Sqls (list[str] | None)

• StatementName (str | None)

• WithEvent (bool | None)

• session (Any | None)

field Database: str [Required]

The name of the database.

Required when authenticating using temporary credentials.

field DbUser: str | None = None

The database user name.

Required when authenticating using temporary credentials.

field SecretManagerArn: str | None = None

The name or ARN of the secret that enables access to the database.

Required when authenticating using Amazon Web Services Secrets Manager.

field Sql: str | None = None

The SQL statement text to run.

field Sqls: builtins.list[str] | None [Optional]

One or more SQL statements to run.

The SQL statements are run as a single transaction. They run serially in the order of the array. Subsequent SQL statements don’t start until the previous statement in the array completes. If any SQL statement fails, then because they are run as one transaction, all work is rolled back.

field StatementName: str | None = None

The name of the SQL statement.

You can name the SQL statement when you create it to identify the query.

field WithEvent: bool | None = None

Indicates whether to send an event back to EventBridge after the SQL statement runs.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.EventsRetryPolicy

Bases: Boto3Model

A RetryPolicy object that includes information about the retry policy settings.

Show JSON schema

{
   "title": "EventsRetryPolicy",
   "description": "A ``RetryPolicy`` object that includes information about the retry policy settings.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "MaximumRetryAttempts": {
         "anyOf": [
            {
               "type": "integer"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Maximumretryattempts"
      },
      "MaximumEventAgeInSeconds": {
         "anyOf": [
            {
               "type": "integer"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Maximumeventageinseconds"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• MaximumEventAgeInSeconds (int | None)

• MaximumRetryAttempts (int | None)

• session (Any | None)

field MaximumEventAgeInSeconds: int | None = None

The maximum amount of time, in seconds, to continue to make retry attempts.

field MaximumRetryAttempts: int | None = None

The maximum number of retry attempts to make before the request fails.

Retry attempts continue until either the maximum number of attempts is made or until the duration of the MaximumEventAgeInSeconds is met.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.EventsRunCommandParameters

Bases: Boto3Model

This parameter contains the criteria (either InstanceIds or a tag) used to specify which EC2 instances are to be sent the command.

Show JSON schema

{
   "title": "EventsRunCommandParameters",
   "description": "This parameter contains the criteria (either InstanceIds or a tag) used to specify\nwhich EC2 instances are to be sent the command.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "RunCommandTargets": {
         "items": {
            "$ref": "#/$defs/RunCommandTarget"
         },
         "title": "Runcommandtargets",
         "type": "array"
      }
   },
   "$defs": {
      "RunCommandTarget": {
         "description": "Information about the EC2 instances that are to be sent the command, specified as\nkey-value pairs.\n\nEach\n``RunCommandTarget`` block can include only one key, but this key may specify multiple values.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "Key": {
               "title": "Key",
               "type": "string"
            },
            "Values": {
               "items": {
                  "type": "string"
               },
               "title": "Values",
               "type": "array"
            }
         },
         "required": [
            "Key",
            "Values"
         ],
         "title": "RunCommandTarget",
         "type": "object"
      }
   },
   "required": [
      "RunCommandTargets"
   ]
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• RunCommandTargets (list[botocraft.services.events.RunCommandTarget])

• session (Any | None)

field RunCommandTargets: builtins.list[RunCommandTarget] [Required]

Currently, we support including only one RunCommandTarget block, which specifies either an array of InstanceIds or a tag.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.EventsSageMakerPipelineParameters

Bases: Boto3Model

These are custom parameters to use when the target is a SageMaker AI Model Building Pipeline that starts based on EventBridge events.

Show JSON schema

{
   "title": "EventsSageMakerPipelineParameters",
   "description": "These are custom parameters to use when the target is a SageMaker AI Model Building\nPipeline that starts based on EventBridge events.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "PipelineParameterList": {
         "anyOf": [
            {
               "items": {
                  "$ref": "#/$defs/SageMakerPipelineParameter"
               },
               "type": "array"
            },
            {
               "type": "null"
            }
         ],
         "title": "Pipelineparameterlist"
      }
   },
   "$defs": {
      "SageMakerPipelineParameter": {
         "description": "Name/Value pair of a parameter to start execution of a SageMaker AI Model Building\nPipeline.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "Name": {
               "title": "Name",
               "type": "string"
            },
            "Value": {
               "title": "Value",
               "type": "string"
            }
         },
         "required": [
            "Name",
            "Value"
         ],
         "title": "SageMakerPipelineParameter",
         "type": "object"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• PipelineParameterList (list[botocraft.services.events.SageMakerPipelineParameter] | None)

• session (Any | None)

field PipelineParameterList: builtins.list[SageMakerPipelineParameter] | None [Optional]

List of Parameter names and values for SageMaker AI Model Building Pipeline execution.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.EventsSqsParameters

Bases: Boto3Model

This structure includes the custom parameter to be used when the target is an SQS FIFO queue.

Show JSON schema

{
   "title": "EventsSqsParameters",
   "description": "This structure includes the custom parameter to be used when the target is an SQS\nFIFO queue.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "MessageGroupId": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Messagegroupid"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• MessageGroupId (str | None)

• session (Any | None)

field MessageGroupId: str | None = None

The FIFO message group ID to use as the target.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.PutEventsRequestEntry

Bases: Boto3Model

Represents an event to be submitted.

Show JSON schema

{
   "title": "PutEventsRequestEntry",
   "description": "Represents an event to be submitted.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "Time": {
         "anyOf": [
            {
               "format": "date-time",
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Time"
      },
      "Source": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Source"
      },
      "Resources": {
         "anyOf": [
            {
               "items": {
                  "type": "string"
               },
               "type": "array"
            },
            {
               "type": "null"
            }
         ],
         "title": "Resources"
      },
      "DetailType": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Detailtype"
      },
      "Detail": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Detail"
      },
      "EventBusName": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Eventbusname"
      },
      "TraceHeader": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Traceheader"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• Detail (str | None)

• DetailType (str | None)

• EventBusName (str | None)

• Resources (list[str] | None)

• Source (str | None)

• Time (datetime.datetime | None)

• TraceHeader (str | None)

• session (Any | None)

field Detail: str | None = None

A valid JSON object.

There is no other schema imposed. The JSON object may contain fields and nested sub- objects.

field DetailType: str | None = None

Free-form string, with a maximum of 128 characters, used to decide what fields to expect in the event detail.

field EventBusName: str | None = None

The name or ARN of the event bus to receive the event.

Only the rules that are associated with this event bus are used to match the event. If you omit this, the default event bus is used.

field Resources: builtins.list[str] | None [Optional]

Amazon Web Services resources, identified by Amazon Resource Name (ARN), which the event primarily concerns.

Any number, including zero, may be present.

field Source: str | None = None

The source of the event.

field Time: datetime | None = None

The time stamp of the event, per RFC3339. If no time stamp is provided, the time stamp of the PutEvents call is used.

field TraceHeader: str | None = None

An X-Ray trace header, which is an http header (X-Amzn-Trace-Id) that contains the trace-id associated with the event.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.RunCommandTarget

Bases: Boto3Model

Information about the EC2 instances that are to be sent the command, specified as key-value pairs.

Each RunCommandTarget block can include only one key, but this key may specify multiple values.

Show JSON schema

{
   "title": "RunCommandTarget",
   "description": "Information about the EC2 instances that are to be sent the command, specified as\nkey-value pairs.\n\nEach\n``RunCommandTarget`` block can include only one key, but this key may specify multiple values.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "Key": {
         "title": "Key",
         "type": "string"
      },
      "Values": {
         "items": {
            "type": "string"
         },
         "title": "Values",
         "type": "array"
      }
   },
   "required": [
      "Key",
      "Values"
   ]
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• Key (str)

• Values (list[str])

• session (Any | None)

field Key: str [Required]

Can be either tag: tag-key or InstanceIds.

field Values: builtins.list[str] [Required]

If Key is tag: tag-key, Values is a list of tag values.

If Key is InstanceIds, Values is a list of Amazon EC2 instance IDs.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.SageMakerPipelineParameter

Bases: Boto3Model

Name/Value pair of a parameter to start execution of a SageMaker AI Model Building Pipeline.

Show JSON schema

{
   "title": "SageMakerPipelineParameter",
   "description": "Name/Value pair of a parameter to start execution of a SageMaker AI Model Building\nPipeline.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "Name": {
         "title": "Name",
         "type": "string"
      },
      "Value": {
         "title": "Value",
         "type": "string"
      }
   },
   "required": [
      "Name",
      "Value"
   ]
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• Name (str)

• Value (str)

• session (Any | None)

field Name: str [Required]

Name of parameter to start execution of a SageMaker AI Model Building Pipeline.

field Value: str [Required]

Value of parameter to start execution of a SageMaker AI Model Building Pipeline.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

Request/Response Models

Request/response models are models that are used to describe the structure of the data that is sent to and received from the AWS service. They are used by the managers to send requests to the service and to parse the responses that are received.

You will not often use them directly – typically they are used by the managers internally to send requests and parse responses – but they are included here for completeness, and because occasionally we return them directly to you because they have some useful additional information.

pydantic model botocraft.services.events.CreateEventBusResponse

Bases: Boto3Model

Show JSON schema

{
   "title": "CreateEventBusResponse",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "EventBusArn": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Eventbusarn"
      },
      "Description": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Description"
      },
      "KmsKeyIdentifier": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Kmskeyidentifier"
      },
      "DeadLetterConfig": {
         "anyOf": [
            {
               "$ref": "#/$defs/EventsDeadLetterConfig"
            },
            {
               "type": "null"
            }
         ],
         "default": null
      },
      "LogConfig": {
         "anyOf": [
            {
               "$ref": "#/$defs/EventsLogConfig"
            },
            {
               "type": "null"
            }
         ],
         "default": null
      }
   },
   "$defs": {
      "EventsDeadLetterConfig": {
         "description": "Configuration details of the Amazon SQS queue for EventBridge to use as a dead-\nletter queue (DLQ).\n\nFor more information, see `Using dead-letter queues to process undelivered\nevents <https://docs.aws.amazon.com/eventbridge/latest/userguide/eb-rule-event-delivery.html#eb-rule-dlq>`_ in the\n*EventBridge User Guide*.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "Arn": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Arn"
            }
         },
         "title": "EventsDeadLetterConfig",
         "type": "object"
      },
      "EventsLogConfig": {
         "description": "The logging configuration settings for the event bus.\n\nFor more information, see\n`Configuring logs for event buses <https://docs.aws.amazon.com/eb-event-bus-logs.html>`_\nin the\n*EventBridge User Guide*.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "IncludeDetail": {
               "anyOf": [
                  {
                     "enum": [
                        "NONE",
                        "FULL"
                     ],
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Includedetail"
            },
            "Level": {
               "anyOf": [
                  {
                     "enum": [
                        "OFF",
                        "ERROR",
                        "INFO",
                        "TRACE"
                     ],
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Level"
            }
         },
         "title": "EventsLogConfig",
         "type": "object"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• DeadLetterConfig (botocraft.services.events.EventsDeadLetterConfig | None)

• Description (str | None)

• EventBusArn (str | None)

• KmsKeyIdentifier (str | None)

• LogConfig (botocraft.services.events.EventsLogConfig | None)

• session (Any | None)

field DeadLetterConfig: EventsDeadLetterConfig | None = None

Configuration details of the Amazon SQS queue for EventBridge to use as a dead- letter queue (DLQ).

field Description: str | None = None

The event bus description.

field EventBusArn: str | None = None

The ARN of the new event bus.

field KmsKeyIdentifier: str | None = None

The identifier of the KMS customer managed key for EventBridge to use to encrypt events on this event bus, if one has been specified.

field LogConfig: EventsLogConfig | None = None

The logging configuration settings for the event bus.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.DescribeRuleResponse

Bases: Boto3Model

Show JSON schema

{
   "title": "DescribeRuleResponse",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "Name": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Name"
      },
      "Arn": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Arn"
      },
      "EventPattern": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Eventpattern"
      },
      "ScheduleExpression": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Scheduleexpression"
      },
      "State": {
         "anyOf": [
            {
               "enum": [
                  "ENABLED",
                  "DISABLED",
                  "ENABLED_WITH_ALL_CLOUDTRAIL_MANAGEMENT_EVENTS"
               ],
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "State"
      },
      "Description": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Description"
      },
      "RoleArn": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Rolearn"
      },
      "ManagedBy": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Managedby"
      },
      "EventBusName": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Eventbusname"
      },
      "CreatedBy": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Createdby"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• Arn (str | None)

• CreatedBy (str | None)

• Description (str | None)

• EventBusName (str | None)

• EventPattern (str | None)

• ManagedBy (str | None)

• Name (str | None)

• RoleArn (str | None)

• ScheduleExpression (str | None)

• State (Literal['ENABLED', 'DISABLED', 'ENABLED_WITH_ALL_CLOUDTRAIL_MANAGEMENT_EVENTS'] | None)

• session (Any | None)

field Arn: str | None = None

The Amazon Resource Name (ARN) of the rule.

field CreatedBy: str | None = None

The account ID of the user that created the rule.

If you use PutRule to put a rule on an event bus in another account, the other account is the owner of the rule, and the rule ARN includes the account ID for that account. However, the value for CreatedBy is the account ID as the account that created the rule in the other account.

field Description: str | None = None

The description of the rule.

field EventBusName: str | None = None

The name of the event bus associated with the rule.

field EventPattern: str | None = None

The event pattern.

For more information, see Events and Event Patterns in the Amazon EventBridge User Guide .

field ManagedBy: str | None = None

If this is a managed rule, created by an Amazon Web Services service on your behalf, this field displays the principal name of the Amazon Web Services service that created the rule.

field Name: str | None = None

The name of the rule.

field RoleArn: str | None = None

The Amazon Resource Name (ARN) of the IAM role associated with the rule.

field ScheduleExpression: str | None = None

The scheduling expression.

For example, “cron(0 20 * * ? *)”, “rate(5 minutes)”.

field State: Literal['ENABLED', 'DISABLED', 'ENABLED_WITH_ALL_CLOUDTRAIL_MANAGEMENT_EVENTS'] | None = None

Specifies whether the rule is enabled or disabled.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.EventsLogConfig

Bases: Boto3Model

The logging configuration settings for the event bus.

For more information, see Configuring logs for event buses in the EventBridge User Guide.

Show JSON schema

{
   "title": "EventsLogConfig",
   "description": "The logging configuration settings for the event bus.\n\nFor more information, see\n`Configuring logs for event buses <https://docs.aws.amazon.com/eb-event-bus-logs.html>`_\nin the\n*EventBridge User Guide*.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "IncludeDetail": {
         "anyOf": [
            {
               "enum": [
                  "NONE",
                  "FULL"
               ],
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Includedetail"
      },
      "Level": {
         "anyOf": [
            {
               "enum": [
                  "OFF",
                  "ERROR",
                  "INFO",
                  "TRACE"
               ],
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Level"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• IncludeDetail (Literal['NONE', 'FULL'] | None)

• Level (Literal['OFF', 'ERROR', 'INFO', 'TRACE'] | None)

• session (Any | None)

field IncludeDetail: Literal['NONE', 'FULL'] | None = None

Whether EventBridge include detailed event information in the records it generates.

Detailed data can be useful for troubleshooting and debugging. This information includes details of the event itself, as well as target details.

field Level: Literal['OFF', 'ERROR', 'INFO', 'TRACE'] | None = None

The level of logging detail to include.

This applies to all log destinations for the event bus.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.ListEventBusesResponse

Bases: Boto3Model

Show JSON schema

{
   "title": "ListEventBusesResponse",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "EventBuses": {
         "anyOf": [
            {
               "items": {
                  "$ref": "#/$defs/EventBus"
               },
               "type": "array"
            },
            {
               "type": "null"
            }
         ],
         "title": "Eventbuses"
      },
      "NextToken": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Nexttoken"
      }
   },
   "$defs": {
      "EventBus": {
         "description": "An event bus receives events from a source, uses rules to evaluate them, applies any\nconfigured input transformation, and routes them to the appropriate target(s).\n\nYour account's default event bus receives events from Amazon Web Services services.\nA custom event bus can receive events from your custom applications and services. A\npartner event bus receives events from an event source created by an SaaS partner.\nThese events come from the partners services or applications.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "Name": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Name"
            },
            "Arn": {
               "default": null,
               "title": "Arn",
               "type": "string"
            },
            "Description": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Description"
            },
            "Policy": {
               "default": null,
               "title": "Policy",
               "type": "string"
            },
            "CreationTime": {
               "default": null,
               "format": "date-time",
               "title": "Creationtime",
               "type": "string"
            },
            "LastModifiedTime": {
               "default": null,
               "format": "date-time",
               "title": "Lastmodifiedtime",
               "type": "string"
            }
         },
         "title": "EventBus",
         "type": "object"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• EventBuses (list[botocraft.services.events.EventBus] | None)

• NextToken (str | None)

• session (Any | None)

field EventBuses: builtins.list[EventBus] | None [Optional]

This list of event buses.

field NextToken: str | None = None

A token indicating there are more results available.

If there are no more results, no token is included in the response.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.ListRuleNamesByTargetResponse

Bases: Boto3Model

Show JSON schema

{
   "title": "ListRuleNamesByTargetResponse",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "RuleNames": {
         "anyOf": [
            {
               "items": {
                  "type": "string"
               },
               "type": "array"
            },
            {
               "type": "null"
            }
         ],
         "title": "Rulenames"
      },
      "NextToken": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Nexttoken"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• NextToken (str | None)

• RuleNames (list[str] | None)

• session (Any | None)

field NextToken: str | None = None

A token indicating there are more results available.

If there are no more results, no token is included in the response.

field RuleNames: builtins.list[str] | None [Optional]

The names of the rules that can invoke the given target.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.ListRulesResponse

Bases: Boto3Model

Show JSON schema

{
   "title": "ListRulesResponse",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "Rules": {
         "anyOf": [
            {
               "items": {
                  "$ref": "#/$defs/EventRule"
               },
               "type": "array"
            },
            {
               "type": "null"
            }
         ],
         "title": "Rules"
      },
      "NextToken": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Nexttoken"
      }
   },
   "$defs": {
      "EventRule": {
         "description": "Contains information about a rule in Amazon EventBridge.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "Name": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Name"
            },
            "Arn": {
               "default": null,
               "title": "Arn",
               "type": "string"
            },
            "EventPattern": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Eventpattern"
            },
            "State": {
               "anyOf": [
                  {
                     "enum": [
                        "ENABLED",
                        "DISABLED",
                        "ENABLED_WITH_ALL_CLOUDTRAIL_MANAGEMENT_EVENTS"
                     ],
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "State"
            },
            "Description": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Description"
            },
            "ScheduleExpression": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Scheduleexpression"
            },
            "RoleArn": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Rolearn"
            },
            "ManagedBy": {
               "default": null,
               "title": "Managedby",
               "type": "string"
            },
            "EventBusName": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Eventbusname"
            },
            "CreatedBy": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Createdby"
            }
         },
         "title": "EventRule",
         "type": "object"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• NextToken (str | None)

• Rules (list[botocraft.services.events.EventRule] | None)

• session (Any | None)

field NextToken: str | None = None

A token indicating there are more results available.

If there are no more results, no token is included in the response.

field Rules: builtins.list[EventRule] | None [Optional]

The rules that match the specified criteria.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.ListTargetsByRuleResponse

Bases: Boto3Model

Show JSON schema

{
   "title": "ListTargetsByRuleResponse",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "Targets": {
         "anyOf": [
            {
               "items": {
                  "$ref": "#/$defs/EventTarget"
               },
               "type": "array"
            },
            {
               "type": "null"
            }
         ],
         "title": "Targets"
      },
      "NextToken": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Nexttoken"
      }
   },
   "$defs": {
      "BatchArrayProperties": {
         "description": "The array properties for the submitted job, such as the size of the array.\n\nThe array size can be between 2 and 10,000. If you specify array properties for a\njob, it becomes an array job. This parameter is used only if the target is an Batch\njob.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "Size": {
               "anyOf": [
                  {
                     "type": "integer"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Size"
            }
         },
         "title": "BatchArrayProperties",
         "type": "object"
      },
      "BatchRetryStrategy": {
         "description": "The retry strategy to use for failed jobs, if the target is an Batch job.\n\nIf you specify a retry strategy here, it overrides the retry strategy defined in the\njob definition.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "Attempts": {
               "anyOf": [
                  {
                     "type": "integer"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Attempts"
            }
         },
         "title": "BatchRetryStrategy",
         "type": "object"
      },
      "EventTarget": {
         "description": "Targets are the resources to be invoked when a rule is triggered. For a complete list of services and resources that can\nbe set as a target, see `PutTargets <https://docs.aws.amazon.com/eventbridge/latest/APIReference/API_PutTargets.html>`_.\n\nIf you are setting the event bus of another account as the target, and that account granted permission to your account\nthrough an organization instead of directly by the account ID, then you must specify a ``RoleArn`` with proper\npermissions in the ``Target`` structure. For more information, see `Sending and Receiving Events Between Amazon Web\nServices Accounts <https://docs.aws.amazon.com/eventbridge/latest/userguide/eventbridge-cross-account-event-\ndelivery.html>`_ in the *Amazon EventBridge User Guide*.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "Id": {
               "title": "Id",
               "type": "string"
            },
            "Arn": {
               "title": "Arn",
               "type": "string"
            },
            "RoleArn": {
               "default": null,
               "title": "Rolearn",
               "type": "string"
            },
            "Input": {
               "default": null,
               "title": "Input",
               "type": "string"
            },
            "InputPath": {
               "default": null,
               "title": "Inputpath",
               "type": "string"
            },
            "InputTransformer": {
               "$ref": "#/$defs/EventsInputTransformer",
               "default": null
            },
            "KinesisParameters": {
               "$ref": "#/$defs/EventsKinesisParameters",
               "default": null
            },
            "RunCommandParameters": {
               "$ref": "#/$defs/EventsRunCommandParameters",
               "default": null
            },
            "EcsParameters": {
               "$ref": "#/$defs/EventsEcsParameters",
               "default": null
            },
            "BatchParameters": {
               "$ref": "#/$defs/EventsBatchParameters",
               "default": null
            },
            "SqsParameters": {
               "$ref": "#/$defs/EventsSqsParameters",
               "default": null
            },
            "HttpParameters": {
               "$ref": "#/$defs/EventsHttpParameters",
               "default": null
            },
            "RedshiftDataParameters": {
               "$ref": "#/$defs/EventsRedshiftDataParameters",
               "default": null
            },
            "SageMakerPipelineParameters": {
               "$ref": "#/$defs/EventsSageMakerPipelineParameters",
               "default": null
            },
            "DeadLetterConfig": {
               "$ref": "#/$defs/EventsDeadLetterConfig",
               "default": null
            },
            "RetryPolicy": {
               "$ref": "#/$defs/EventsRetryPolicy",
               "default": null
            },
            "AppSyncParameters": {
               "$ref": "#/$defs/EventsAppSyncParameters",
               "default": null
            }
         },
         "required": [
            "Id",
            "Arn"
         ],
         "title": "EventTarget",
         "type": "object"
      },
      "EventsAppSyncParameters": {
         "description": "Contains the GraphQL operation to be parsed and executed, if the event target is an\nAppSync API.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "GraphQLOperation": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Graphqloperation"
            }
         },
         "title": "EventsAppSyncParameters",
         "type": "object"
      },
      "EventsAwsVpcConfiguration": {
         "description": "This structure specifies the VPC subnets and security groups for the task, and\nwhether a public IP address is to be used.\n\nThis structure is relevant only for ECS tasks that use the ``awsvpc`` network mode.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "Subnets": {
               "items": {
                  "type": "string"
               },
               "title": "Subnets",
               "type": "array"
            },
            "SecurityGroups": {
               "anyOf": [
                  {
                     "items": {
                        "type": "string"
                     },
                     "type": "array"
                  },
                  {
                     "type": "null"
                  }
               ],
               "title": "Securitygroups"
            },
            "AssignPublicIp": {
               "anyOf": [
                  {
                     "enum": [
                        "ENABLED",
                        "DISABLED"
                     ],
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Assignpublicip"
            }
         },
         "required": [
            "Subnets"
         ],
         "title": "EventsAwsVpcConfiguration",
         "type": "object"
      },
      "EventsBatchParameters": {
         "description": "The custom parameters to be used when the target is an Batch job.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "JobDefinition": {
               "title": "Jobdefinition",
               "type": "string"
            },
            "JobName": {
               "title": "Jobname",
               "type": "string"
            },
            "ArrayProperties": {
               "anyOf": [
                  {
                     "$ref": "#/$defs/BatchArrayProperties"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null
            },
            "RetryStrategy": {
               "anyOf": [
                  {
                     "$ref": "#/$defs/BatchRetryStrategy"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null
            }
         },
         "required": [
            "JobDefinition",
            "JobName"
         ],
         "title": "EventsBatchParameters",
         "type": "object"
      },
      "EventsCapacityProviderStrategyItem": {
         "description": "The details of a capacity provider strategy.\n\nTo learn more, see `CapacityProviderStrategyItem <https://docs.aws.amazon.c\nom/AmazonECS/latest/APIReference/API_CapacityProviderStrategyItem.html>`_ in the Amazon ECS API Reference.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "capacityProvider": {
               "title": "Capacityprovider",
               "type": "string"
            },
            "weight": {
               "anyOf": [
                  {
                     "type": "integer"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Weight"
            },
            "base": {
               "anyOf": [
                  {
                     "type": "integer"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Base"
            }
         },
         "required": [
            "capacityProvider"
         ],
         "title": "EventsCapacityProviderStrategyItem",
         "type": "object"
      },
      "EventsDeadLetterConfig": {
         "description": "Configuration details of the Amazon SQS queue for EventBridge to use as a dead-\nletter queue (DLQ).\n\nFor more information, see `Using dead-letter queues to process undelivered\nevents <https://docs.aws.amazon.com/eventbridge/latest/userguide/eb-rule-event-delivery.html#eb-rule-dlq>`_ in the\n*EventBridge User Guide*.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "Arn": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Arn"
            }
         },
         "title": "EventsDeadLetterConfig",
         "type": "object"
      },
      "EventsEcsParameters": {
         "description": "The custom parameters to be used when the target is an Amazon ECS task.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "TaskDefinitionArn": {
               "title": "Taskdefinitionarn",
               "type": "string"
            },
            "TaskCount": {
               "anyOf": [
                  {
                     "type": "integer"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Taskcount"
            },
            "LaunchType": {
               "anyOf": [
                  {
                     "enum": [
                        "EC2",
                        "FARGATE",
                        "EXTERNAL"
                     ],
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Launchtype"
            },
            "NetworkConfiguration": {
               "anyOf": [
                  {
                     "$ref": "#/$defs/EventsNetworkConfiguration"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null
            },
            "PlatformVersion": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Platformversion"
            },
            "Group": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Group"
            },
            "CapacityProviderStrategy": {
               "anyOf": [
                  {
                     "items": {
                        "$ref": "#/$defs/EventsCapacityProviderStrategyItem"
                     },
                     "type": "array"
                  },
                  {
                     "type": "null"
                  }
               ],
               "title": "Capacityproviderstrategy"
            },
            "EnableECSManagedTags": {
               "anyOf": [
                  {
                     "type": "boolean"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Enableecsmanagedtags"
            },
            "EnableExecuteCommand": {
               "anyOf": [
                  {
                     "type": "boolean"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Enableexecutecommand"
            },
            "PlacementConstraints": {
               "anyOf": [
                  {
                     "items": {
                        "$ref": "#/$defs/EventsPlacementConstraint"
                     },
                     "type": "array"
                  },
                  {
                     "type": "null"
                  }
               ],
               "title": "Placementconstraints"
            },
            "PlacementStrategy": {
               "anyOf": [
                  {
                     "items": {
                        "$ref": "#/$defs/EventsPlacementStrategy"
                     },
                     "type": "array"
                  },
                  {
                     "type": "null"
                  }
               ],
               "title": "Placementstrategy"
            },
            "PropagateTags": {
               "anyOf": [
                  {
                     "const": "TASK_DEFINITION",
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Propagatetags"
            },
            "ReferenceId": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Referenceid"
            },
            "Tags": {
               "anyOf": [
                  {
                     "items": {
                        "$ref": "#/$defs/Tag"
                     },
                     "type": "array"
                  },
                  {
                     "type": "null"
                  }
               ],
               "title": "Tags"
            }
         },
         "required": [
            "TaskDefinitionArn"
         ],
         "title": "EventsEcsParameters",
         "type": "object"
      },
      "EventsHttpParameters": {
         "description": "These are custom parameter to be used when the target is an API Gateway APIs or\nEventBridge ApiDestinations.\n\nIn the latter case, these are merged with any InvocationParameters specified on the\nConnection, with any values from the Connection taking precedence.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "PathParameterValues": {
               "anyOf": [
                  {
                     "items": {
                        "type": "string"
                     },
                     "type": "array"
                  },
                  {
                     "type": "null"
                  }
               ],
               "title": "Pathparametervalues"
            },
            "HeaderParameters": {
               "anyOf": [
                  {
                     "additionalProperties": {
                        "type": "string"
                     },
                     "type": "object"
                  },
                  {
                     "type": "null"
                  }
               ],
               "title": "Headerparameters"
            },
            "QueryStringParameters": {
               "anyOf": [
                  {
                     "additionalProperties": {
                        "type": "string"
                     },
                     "type": "object"
                  },
                  {
                     "type": "null"
                  }
               ],
               "title": "Querystringparameters"
            }
         },
         "title": "EventsHttpParameters",
         "type": "object"
      },
      "EventsInputTransformer": {
         "description": "Contains the parameters needed for you to provide custom input to a target based on\none or more pieces of data extracted from the event.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "InputPathsMap": {
               "anyOf": [
                  {
                     "additionalProperties": {
                        "type": "string"
                     },
                     "type": "object"
                  },
                  {
                     "type": "null"
                  }
               ],
               "title": "Inputpathsmap"
            },
            "InputTemplate": {
               "title": "Inputtemplate",
               "type": "string"
            }
         },
         "required": [
            "InputTemplate"
         ],
         "title": "EventsInputTransformer",
         "type": "object"
      },
      "EventsKinesisParameters": {
         "description": "This object enables you to specify a JSON path to extract from the event and use as\nthe partition key for the Amazon Kinesis data stream, so that you can control the\nshard to which the event goes.\n\nIf you do not include this parameter,\nthe default is to use the ``eventId`` as the partition key.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "PartitionKeyPath": {
               "title": "Partitionkeypath",
               "type": "string"
            }
         },
         "required": [
            "PartitionKeyPath"
         ],
         "title": "EventsKinesisParameters",
         "type": "object"
      },
      "EventsNetworkConfiguration": {
         "description": "This structure specifies the network configuration for an ECS task.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "awsvpcConfiguration": {
               "anyOf": [
                  {
                     "$ref": "#/$defs/EventsAwsVpcConfiguration"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null
            }
         },
         "title": "EventsNetworkConfiguration",
         "type": "object"
      },
      "EventsPlacementConstraint": {
         "description": "An object representing a constraint on task placement.\n\nTo learn more, see\n`Task Placement Constraints <https://docs.aws.amazon.com/AmazonECS/latest/developerguide/task-placement-constraints.html>`_\nin the Amazon\nElastic Container Service Developer Guide.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "type": {
               "anyOf": [
                  {
                     "enum": [
                        "distinctInstance",
                        "memberOf"
                     ],
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Type"
            },
            "expression": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Expression"
            }
         },
         "title": "EventsPlacementConstraint",
         "type": "object"
      },
      "EventsPlacementStrategy": {
         "description": "The task placement strategy for a task or service.\n\nTo learn more, see\n`Task Placement Strategies <https://docs.aws.amazon.com/AmazonECS/latest/developerguide/task-placement-strategies.html>`_\nin the Amazon\nElastic Container Service Service Developer Guide.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "type": {
               "anyOf": [
                  {
                     "enum": [
                        "random",
                        "spread",
                        "binpack"
                     ],
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Type"
            },
            "field": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Field"
            }
         },
         "title": "EventsPlacementStrategy",
         "type": "object"
      },
      "EventsRedshiftDataParameters": {
         "description": "These are custom parameters to be used when the target is a Amazon Redshift cluster\nto invoke the Amazon Redshift Data API ExecuteStatement based on EventBridge events.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "SecretManagerArn": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Secretmanagerarn"
            },
            "Database": {
               "title": "Database",
               "type": "string"
            },
            "DbUser": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Dbuser"
            },
            "Sql": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Sql"
            },
            "StatementName": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Statementname"
            },
            "WithEvent": {
               "anyOf": [
                  {
                     "type": "boolean"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Withevent"
            },
            "Sqls": {
               "anyOf": [
                  {
                     "items": {
                        "type": "string"
                     },
                     "type": "array"
                  },
                  {
                     "type": "null"
                  }
               ],
               "title": "Sqls"
            }
         },
         "required": [
            "Database"
         ],
         "title": "EventsRedshiftDataParameters",
         "type": "object"
      },
      "EventsRetryPolicy": {
         "description": "A ``RetryPolicy`` object that includes information about the retry policy settings.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "MaximumRetryAttempts": {
               "anyOf": [
                  {
                     "type": "integer"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Maximumretryattempts"
            },
            "MaximumEventAgeInSeconds": {
               "anyOf": [
                  {
                     "type": "integer"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Maximumeventageinseconds"
            }
         },
         "title": "EventsRetryPolicy",
         "type": "object"
      },
      "EventsRunCommandParameters": {
         "description": "This parameter contains the criteria (either InstanceIds or a tag) used to specify\nwhich EC2 instances are to be sent the command.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "RunCommandTargets": {
               "items": {
                  "$ref": "#/$defs/RunCommandTarget"
               },
               "title": "Runcommandtargets",
               "type": "array"
            }
         },
         "required": [
            "RunCommandTargets"
         ],
         "title": "EventsRunCommandParameters",
         "type": "object"
      },
      "EventsSageMakerPipelineParameters": {
         "description": "These are custom parameters to use when the target is a SageMaker AI Model Building\nPipeline that starts based on EventBridge events.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "PipelineParameterList": {
               "anyOf": [
                  {
                     "items": {
                        "$ref": "#/$defs/SageMakerPipelineParameter"
                     },
                     "type": "array"
                  },
                  {
                     "type": "null"
                  }
               ],
               "title": "Pipelineparameterlist"
            }
         },
         "title": "EventsSageMakerPipelineParameters",
         "type": "object"
      },
      "EventsSqsParameters": {
         "description": "This structure includes the custom parameter to be used when the target is an SQS\nFIFO queue.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "MessageGroupId": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Messagegroupid"
            }
         },
         "title": "EventsSqsParameters",
         "type": "object"
      },
      "RunCommandTarget": {
         "description": "Information about the EC2 instances that are to be sent the command, specified as\nkey-value pairs.\n\nEach\n``RunCommandTarget`` block can include only one key, but this key may specify multiple values.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "Key": {
               "title": "Key",
               "type": "string"
            },
            "Values": {
               "items": {
                  "type": "string"
               },
               "title": "Values",
               "type": "array"
            }
         },
         "required": [
            "Key",
            "Values"
         ],
         "title": "RunCommandTarget",
         "type": "object"
      },
      "SageMakerPipelineParameter": {
         "description": "Name/Value pair of a parameter to start execution of a SageMaker AI Model Building\nPipeline.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "Name": {
               "title": "Name",
               "type": "string"
            },
            "Value": {
               "title": "Value",
               "type": "string"
            }
         },
         "required": [
            "Name",
            "Value"
         ],
         "title": "SageMakerPipelineParameter",
         "type": "object"
      },
      "Tag": {
         "description": "The metadata that you apply to a resource to help you categorize and\norganize them. Each tag consists of a key and an optional value. You define\nthem.\n\nThe following basic restrictions apply to tags:\n\n* Maximum number of tags per resource - 50\n* For each resource, each tag key must be unique, and each tag key can have\n  only one value.\n* Maximum key length - 128 Unicode characters in UTF-8\n* Maximum value length - 256 Unicode characters in UTF-8\n* If your tagging schema is used across multiple services and resources,\n  remember that other services may have restrictions on allowed characters.\n  Generally allowed characters are: letters, numbers, and spaces representable in\n  UTF-8, and the following characters: + - = . _ : / @.\n* Tag keys and values are case-sensitive.\n* Do not use ``aws:``, ``AWS:``, or any upper or lowercase combination of such\n  as a prefix for either keys or values as it is reserved for Amazon Web Services\n  use. You cannot edit or delete tag keys or values with this prefix. Tags with\n  this prefix do not count against your tags per resource limit.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "Key": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Key"
            },
            "Value": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Value"
            }
         },
         "title": "Tag",
         "type": "object"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• NextToken (str | None)

• Targets (list[botocraft.services.events.EventTarget] | None)

• session (Any | None)

field NextToken: str | None = None

A token indicating there are more results available.

If there are no more results, no token is included in the response.

field Targets: builtins.list[EventTarget] | None [Optional]

The targets assigned to the rule.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.PutEventsResponse

Bases: Boto3Model

Show JSON schema

{
   "title": "PutEventsResponse",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "FailedEntryCount": {
         "anyOf": [
            {
               "type": "integer"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Failedentrycount"
      },
      "Entries": {
         "anyOf": [
            {
               "items": {
                  "$ref": "#/$defs/PutEventsResultEntry"
               },
               "type": "array"
            },
            {
               "type": "null"
            }
         ],
         "title": "Entries"
      }
   },
   "$defs": {
      "PutEventsResultEntry": {
         "description": "Represents the results of an event submitted to an event bus.\n\nIf the submission was successful, the entry has the event ID in it. Otherwise, you\ncan use the error code and error message to identify the problem with the entry.\n\nFor information about the errors that are common to all actions, see\n`Common Errors <https://docs.aws.amazon.com/eventbridge/latest/APIReference/CommonErrors.html>`_.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "EventId": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Eventid"
            },
            "ErrorCode": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Errorcode"
            },
            "ErrorMessage": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Errormessage"
            }
         },
         "title": "PutEventsResultEntry",
         "type": "object"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• Entries (list[botocraft.services.events.PutEventsResultEntry] | None)

• FailedEntryCount (int | None)

• session (Any | None)

field Entries: builtins.list[PutEventsResultEntry] | None [Optional]

The successfully and unsuccessfully ingested events results.

If the ingestion was successful, the entry has the event ID in it. Otherwise, you can use the error code and error message to identify the problem with the entry.

field FailedEntryCount: int | None = None

The number of failed entries.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.PutEventsResultEntry

Bases: Boto3Model

Represents the results of an event submitted to an event bus.

If the submission was successful, the entry has the event ID in it. Otherwise, you can use the error code and error message to identify the problem with the entry.

For information about the errors that are common to all actions, see Common Errors.

Show JSON schema

{
   "title": "PutEventsResultEntry",
   "description": "Represents the results of an event submitted to an event bus.\n\nIf the submission was successful, the entry has the event ID in it. Otherwise, you\ncan use the error code and error message to identify the problem with the entry.\n\nFor information about the errors that are common to all actions, see\n`Common Errors <https://docs.aws.amazon.com/eventbridge/latest/APIReference/CommonErrors.html>`_.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "EventId": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Eventid"
      },
      "ErrorCode": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Errorcode"
      },
      "ErrorMessage": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Errormessage"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• ErrorCode (str | None)

• ErrorMessage (str | None)

• EventId (str | None)

• session (Any | None)

field ErrorCode: str | None = None

The error code that indicates why the event submission failed.

field ErrorMessage: str | None = None

The error message that explains why the event submission failed.

field EventId: str | None = None

The ID of the event.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.PutRuleResponse

Bases: Boto3Model

Show JSON schema

{
   "title": "PutRuleResponse",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "RuleArn": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Rulearn"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• RuleArn (str | None)

• session (Any | None)

field RuleArn: str | None = None

The Amazon Resource Name (ARN) of the rule.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.PutTargetsResponse

Bases: Boto3Model

Show JSON schema

{
   "title": "PutTargetsResponse",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "FailedEntryCount": {
         "anyOf": [
            {
               "type": "integer"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Failedentrycount"
      },
      "FailedEntries": {
         "anyOf": [
            {
               "items": {
                  "$ref": "#/$defs/PutTargetsResultEntry"
               },
               "type": "array"
            },
            {
               "type": "null"
            }
         ],
         "title": "Failedentries"
      }
   },
   "$defs": {
      "PutTargetsResultEntry": {
         "description": "Represents a target that failed to be added to a rule.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "TargetId": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Targetid"
            },
            "ErrorCode": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Errorcode"
            },
            "ErrorMessage": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Errormessage"
            }
         },
         "title": "PutTargetsResultEntry",
         "type": "object"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• FailedEntries (list[botocraft.services.events.PutTargetsResultEntry] | None)

• FailedEntryCount (int | None)

• session (Any | None)

field FailedEntries: builtins.list[PutTargetsResultEntry] | None [Optional]

The failed target entries.

field FailedEntryCount: int | None = None

The number of failed entries.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.PutTargetsResultEntry

Bases: Boto3Model

Represents a target that failed to be added to a rule.

Show JSON schema

{
   "title": "PutTargetsResultEntry",
   "description": "Represents a target that failed to be added to a rule.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "TargetId": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Targetid"
      },
      "ErrorCode": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Errorcode"
      },
      "ErrorMessage": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Errormessage"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• ErrorCode (str | None)

• ErrorMessage (str | None)

• TargetId (str | None)

• session (Any | None)

field ErrorCode: str | None = None

The error code that indicates why the target addition failed.

If the value is ConcurrentModificationException, too many requests were made at the same time.

field ErrorMessage: str | None = None

The error message that explains why the target addition failed.

field TargetId: str | None = None

The ID of the target.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.RemoveTargetsResponse

Bases: Boto3Model

Show JSON schema

{
   "title": "RemoveTargetsResponse",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "FailedEntryCount": {
         "anyOf": [
            {
               "type": "integer"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Failedentrycount"
      },
      "FailedEntries": {
         "anyOf": [
            {
               "items": {
                  "$ref": "#/$defs/RemoveTargetsResultEntry"
               },
               "type": "array"
            },
            {
               "type": "null"
            }
         ],
         "title": "Failedentries"
      }
   },
   "$defs": {
      "RemoveTargetsResultEntry": {
         "description": "Represents a target that failed to be removed from a rule.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "TargetId": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Targetid"
            },
            "ErrorCode": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Errorcode"
            },
            "ErrorMessage": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Errormessage"
            }
         },
         "title": "RemoveTargetsResultEntry",
         "type": "object"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• FailedEntries (list[botocraft.services.events.RemoveTargetsResultEntry] | None)

• FailedEntryCount (int | None)

• session (Any | None)

field FailedEntries: builtins.list[RemoveTargetsResultEntry] | None [Optional]

The failed target entries.

field FailedEntryCount: int | None = None

The number of failed entries.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.RemoveTargetsResultEntry

Bases: Boto3Model

Represents a target that failed to be removed from a rule.

Show JSON schema

{
   "title": "RemoveTargetsResultEntry",
   "description": "Represents a target that failed to be removed from a rule.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "TargetId": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Targetid"
      },
      "ErrorCode": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Errorcode"
      },
      "ErrorMessage": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Errormessage"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• ErrorCode (str | None)

• ErrorMessage (str | None)

• TargetId (str | None)

• session (Any | None)

field ErrorCode: str | None = None

The error code that indicates why the target removal failed.

If the value is ConcurrentModificationException, too many requests were made at the same time.

field ErrorMessage: str | None = None

The error message that explains why the target removal failed.

field TargetId: str | None = None

The ID of the target.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.events.UpdateEventBusResponse

Bases: Boto3Model

Show JSON schema

{
   "title": "UpdateEventBusResponse",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "Arn": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Arn"
      },
      "Name": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Name"
      },
      "KmsKeyIdentifier": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Kmskeyidentifier"
      },
      "Description": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Description"
      },
      "DeadLetterConfig": {
         "anyOf": [
            {
               "$ref": "#/$defs/EventsDeadLetterConfig"
            },
            {
               "type": "null"
            }
         ],
         "default": null
      },
      "LogConfig": {
         "anyOf": [
            {
               "$ref": "#/$defs/EventsLogConfig"
            },
            {
               "type": "null"
            }
         ],
         "default": null
      }
   },
   "$defs": {
      "EventsDeadLetterConfig": {
         "description": "Configuration details of the Amazon SQS queue for EventBridge to use as a dead-\nletter queue (DLQ).\n\nFor more information, see `Using dead-letter queues to process undelivered\nevents <https://docs.aws.amazon.com/eventbridge/latest/userguide/eb-rule-event-delivery.html#eb-rule-dlq>`_ in the\n*EventBridge User Guide*.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "Arn": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Arn"
            }
         },
         "title": "EventsDeadLetterConfig",
         "type": "object"
      },
      "EventsLogConfig": {
         "description": "The logging configuration settings for the event bus.\n\nFor more information, see\n`Configuring logs for event buses <https://docs.aws.amazon.com/eb-event-bus-logs.html>`_\nin the\n*EventBridge User Guide*.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "IncludeDetail": {
               "anyOf": [
                  {
                     "enum": [
                        "NONE",
                        "FULL"
                     ],
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Includedetail"
            },
            "Level": {
               "anyOf": [
                  {
                     "enum": [
                        "OFF",
                        "ERROR",
                        "INFO",
                        "TRACE"
                     ],
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Level"
            }
         },
         "title": "EventsLogConfig",
         "type": "object"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• Arn (str | None)

• DeadLetterConfig (botocraft.services.events.EventsDeadLetterConfig | None)

• Description (str | None)

• KmsKeyIdentifier (str | None)

• LogConfig (botocraft.services.events.EventsLogConfig | None)

• Name (str | None)

• session (Any | None)

field Arn: str | None = None

The event bus Amazon Resource Name (ARN).

field DeadLetterConfig: EventsDeadLetterConfig | None = None

Configuration details of the Amazon SQS queue for EventBridge to use as a dead- letter queue (DLQ).

field Description: str | None = None

The event bus description.

field KmsKeyIdentifier: str | None = None

The identifier of the KMS customer managed key for EventBridge to use to encrypt events on this event bus, if one has been specified.

field LogConfig: EventsLogConfig | None = None

The logging configuration settings for the event bus.

field Name: str | None = None

The event bus name.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.