runway.cfngin.hooks.awslambda.models.responses module

Response data models.

class runway.cfngin.hooks.awslambda.models.responses.AwsLambdaHookDeployResponse[source]

Bases: runway.utils.BaseModel

Data model for AwsLambdaHook deploy response.

When returned by the hook as hook_data, this model is dumped to a standard Dict using the field’s aliases as the key in place of the attribute names. This is done so that the key is a direct match to a CloudFormation Property where the value should be used.

bucket_name: str

Name of the S3 Bucket where the deployment package is located. (alias S3Bucket)

code_sha256: str

SHA256 of the deployment package. This can be used by CloudFormation as the value of AWS::Lambda::Version.CodeSha256. (alias CodeSha256)

compatible_architectures: Optional[List[str]]

A list of compatible instruction set architectures. (https://docs.aws.amazon.com/lambda/latest/dg/foundation-arch.html) (alias CompatibleArchitectures)

compatible_runtimes: Optional[List[str]]

A list of compatible function runtimes. Used for filtering with ListLayers and ListLayerVersions. (alias CompatibleRuntimes)

license: Optional[str]

The layer’s software license (alias License). Can be any of the following:

  • A SPDX license identifier (e.g. MIT).

  • The URL of a license hosted on the internet (e.g. https://opensource.org/licenses/MIT).

  • The full text of the license.

object_key: str

Key (file path) of the deployment package S3 Object. (alias S3Key)

__contains__(name: object) → bool

Implement evaluation of ‘in’ conditional.

Parameters

name – The name to check for existence in the model.

__getitem__(name: str) → Any

Implement evaluation of self[name].

Parameters

name – Attribute name to return the value for.

Returns

The value associated with the provided name/attribute name.

Raises

AttributeError – If attribute does not exist on this object.

__init__(**data: Any) → None

Create a new model by parsing and validating input data from keyword arguments.

Raises ValidationError if the input data cannot be parsed to form a valid model.

__iter__() → TupleGenerator

so dict(model) works

__new__(**kwargs)
__pretty__(fmt: Callable[[Any], Any], **kwargs: Any) → Generator[Any, None, None]

Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects

__repr_name__() → str

Name of the instance’s class, used in __repr__.

__rich_repr__() → RichReprResult

Get fields for Rich library

__setitem__(name: str, value: Any) → None

Implement item assignment (e.g. self[name] = value).

Parameters

  • name – Attribute name to set.

  • value – Value to assign to the attribute.

classmethod __try_update_forward_refs__(**localns: Any) → None

Same as update_forward_refs but will not raise exception when forward references are not defined.

classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model

Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values

copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters

  • include – fields to include in new model

  • exclude – fields to exclude from new model, as with values this takes precedence over include

  • update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data

  • deep – set to True to make a deep copy of the model

Returns

new model instance

dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

get(name: str, default: Any = None) → Any

Safely get the value of an attribute.

Parameters

  • name – Attribute name to return the value for.

  • default – Value to return if attribute is not found.

json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → str

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

classmethod update_forward_refs(**localns: Any) → None

Try to update ForwardRefs on fields based on this Model, globalns and localns.

object_version_id: Optional[str]

The version ID of the deployment package S3 Object. This will only have a value if the S3 Bucket has versioning enabled. (alias S3ObjectVersion)

runtime: str

Runtime of the Lambda Function. (alias Runtime)

class Config[source]

Bases: object

Model configuration.

__init__()
__new__(**kwargs)