runway.config.models.runway package
Runway config models.
- class runway.config.models.runway.CfnLintRunwayTestArgs[source]
Bases:
runway.config.models.base.ConfigProperty
Model for the args of a cfn-lint test.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.Config
Model configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: str) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
obj
to a JSON formattedstr
.If
skipkeys
is true thendict
keys that are not basic types (str
,int
,float
,bool
,None
) will be skipped instead of raising aTypeError
.If
ensure_ascii
is false, then the return value can contain non-ASCII characters if they appear in strings contained inobj
. Otherwise, all such characters are escaped in JSON strings.If
check_circular
is false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError
(or worse).If
allow_nan
is false, then it will be aValueError
to serialize out of rangefloat
values (nan
,inf
,-inf
) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN
,Infinity
,-Infinity
).If
indent
is a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.None
is the most compact representation.If specified,
separators
should be an(item_separator, key_separator)
tuple. The default is(', ', ': ')
if indent isNone
and(',', ': ')
otherwise. To get the most compact JSON representation, you should specify(',', ':')
to eliminate whitespace.default(obj)
is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False
), then the output of dictionaries will be sorted by key.To use a custom
JSONEncoder
subclass (e.g. one that overrides the.default()
method to serialize additional types), specify it with thecls
kwarg; otherwiseJSONEncoder
is used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s
(astr
,bytes
orbytearray
instance containing a JSON document) to a Python object.object_hook
is an optional function that will be called with the result of any object literal decode (adict
). The return value ofobject_hook
will be used instead of thedict
. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hook
is an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hook
will be used instead of thedict
. This feature can be used to implement custom decoders. Ifobject_hook
is also defined, theobject_pairs_hook
takes priority.parse_float
, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int
, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant
, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecoder
subclass, specify it with thecls
kwarg; otherwiseJSONDecoder
is used.
- __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
- __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().
- class runway.config.models.runway.CfnLintRunwayTestDefinitionModel[source]
Bases:
runway.config.models.runway._builtin_tests.RunwayTestDefinitionModel
Model for a cfn-lint test definition.
- class Config[source]
Bases:
runway.config.models.runway._builtin_tests.RunwayTestDefinitionModel.Config
Model configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: str) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
obj
to a JSON formattedstr
.If
skipkeys
is true thendict
keys that are not basic types (str
,int
,float
,bool
,None
) will be skipped instead of raising aTypeError
.If
ensure_ascii
is false, then the return value can contain non-ASCII characters if they appear in strings contained inobj
. Otherwise, all such characters are escaped in JSON strings.If
check_circular
is false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError
(or worse).If
allow_nan
is false, then it will be aValueError
to serialize out of rangefloat
values (nan
,inf
,-inf
) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN
,Infinity
,-Infinity
).If
indent
is a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.None
is the most compact representation.If specified,
separators
should be an(item_separator, key_separator)
tuple. The default is(', ', ': ')
if indent isNone
and(',', ': ')
otherwise. To get the most compact JSON representation, you should specify(',', ':')
to eliminate whitespace.default(obj)
is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False
), then the output of dictionaries will be sorted by key.To use a custom
JSONEncoder
subclass (e.g. one that overrides the.default()
method to serialize additional types), specify it with thecls
kwarg; otherwiseJSONEncoder
is used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s
(astr
,bytes
orbytearray
instance containing a JSON document) to a Python object.object_hook
is an optional function that will be called with the result of any object literal decode (adict
). The return value ofobject_hook
will be used instead of thedict
. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hook
is an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hook
will be used instead of thedict
. This feature can be used to implement custom decoders. Ifobject_hook
is also defined, theobject_pairs_hook
takes priority.parse_float
, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int
, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant
, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecoder
subclass, specify it with thecls
kwarg; otherwiseJSONDecoder
is used.
- __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
- static __new__(cls, **kwargs: Any) runway.config.models.runway._builtin_tests.RunwayTestDefinitionModel
Create a new instance of a class.
- Returns
Correct subclass of RunwayTestDefinition for the given data.
- __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
- __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().
- class runway.config.models.runway.RunwayAssumeRoleDefinitionModel[source]
Bases:
runway.config.models.base.ConfigProperty
Model for a Runway assume role definition.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.Config
Model configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: str) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
obj
to a JSON formattedstr
.If
skipkeys
is true thendict
keys that are not basic types (str
,int
,float
,bool
,None
) will be skipped instead of raising aTypeError
.If
ensure_ascii
is false, then the return value can contain non-ASCII characters if they appear in strings contained inobj
. Otherwise, all such characters are escaped in JSON strings.If
check_circular
is false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError
(or worse).If
allow_nan
is false, then it will be aValueError
to serialize out of rangefloat
values (nan
,inf
,-inf
) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN
,Infinity
,-Infinity
).If
indent
is a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.None
is the most compact representation.If specified,
separators
should be an(item_separator, key_separator)
tuple. The default is(', ', ': ')
if indent isNone
and(',', ': ')
otherwise. To get the most compact JSON representation, you should specify(',', ':')
to eliminate whitespace.default(obj)
is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False
), then the output of dictionaries will be sorted by key.To use a custom
JSONEncoder
subclass (e.g. one that overrides the.default()
method to serialize additional types), specify it with thecls
kwarg; otherwiseJSONEncoder
is used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s
(astr
,bytes
orbytearray
instance containing a JSON document) to a Python object.object_hook
is an optional function that will be called with the result of any object literal decode (adict
). The return value ofobject_hook
will be used instead of thedict
. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hook
is an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hook
will be used instead of thedict
. This feature can be used to implement custom decoders. Ifobject_hook
is also defined, theobject_pairs_hook
takes priority.parse_float
, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int
, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant
, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecoder
subclass, specify it with thecls
kwarg; otherwiseJSONDecoder
is used.
- __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
- __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().
- class runway.config.models.runway.RunwayConfigDefinitionModel[source]
Bases:
runway.config.models.base.ConfigProperty
Runway configuration definition model.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.Config
Model configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: str) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
obj
to a JSON formattedstr
.If
skipkeys
is true thendict
keys that are not basic types (str
,int
,float
,bool
,None
) will be skipped instead of raising aTypeError
.If
ensure_ascii
is false, then the return value can contain non-ASCII characters if they appear in strings contained inobj
. Otherwise, all such characters are escaped in JSON strings.If
check_circular
is false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError
(or worse).If
allow_nan
is false, then it will be aValueError
to serialize out of rangefloat
values (nan
,inf
,-inf
) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN
,Infinity
,-Infinity
).If
indent
is a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.None
is the most compact representation.If specified,
separators
should be an(item_separator, key_separator)
tuple. The default is(', ', ': ')
if indent isNone
and(',', ': ')
otherwise. To get the most compact JSON representation, you should specify(',', ':')
to eliminate whitespace.default(obj)
is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False
), then the output of dictionaries will be sorted by key.To use a custom
JSONEncoder
subclass (e.g. one that overrides the.default()
method to serialize additional types), specify it with thecls
kwarg; otherwiseJSONEncoder
is used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s
(astr
,bytes
orbytearray
instance containing a JSON document) to a Python object.object_hook
is an optional function that will be called with the result of any object literal decode (adict
). The return value ofobject_hook
will be used instead of thedict
. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hook
is an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hook
will be used instead of thedict
. This feature can be used to implement custom decoders. Ifobject_hook
is also defined, theobject_pairs_hook
takes priority.parse_float
, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int
, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant
, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecoder
subclass, specify it with thecls
kwarg; otherwiseJSONDecoder
is used.
- classmethod parse_file(path: Union[str, Path], *, content_type: Optional[str] = None, encoding: str = 'utf8', proto: Optional[Protocol] = None, allow_pickle: bool = False) Model [source]
Parse a file.
- classmethod parse_raw(b: Union[bytes, str], *, content_type: Optional[str] = None, encoding: str = 'utf8', proto: Optional[Protocol] = None, allow_pickle: bool = False) Model [source]
Parse raw data.
- __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
- __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().
- class runway.config.models.runway.RunwayDeploymentDefinitionModel[source]
Bases:
runway.config.models.base.ConfigProperty
Model for a Runway deployment definition.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.Config
Model configuration.
- static schema_extra(schema: Dict[str, Any]) None [source]
Process the schema after it has been generated.
Schema is modified in place. Return value is ignored.
https://pydantic-docs.helpmanual.io/usage/schema/#schema-customization
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: str) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
obj
to a JSON formattedstr
.If
skipkeys
is true thendict
keys that are not basic types (str
,int
,float
,bool
,None
) will be skipped instead of raising aTypeError
.If
ensure_ascii
is false, then the return value can contain non-ASCII characters if they appear in strings contained inobj
. Otherwise, all such characters are escaped in JSON strings.If
check_circular
is false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError
(or worse).If
allow_nan
is false, then it will be aValueError
to serialize out of rangefloat
values (nan
,inf
,-inf
) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN
,Infinity
,-Infinity
).If
indent
is a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.None
is the most compact representation.If specified,
separators
should be an(item_separator, key_separator)
tuple. The default is(', ', ': ')
if indent isNone
and(',', ': ')
otherwise. To get the most compact JSON representation, you should specify(',', ':')
to eliminate whitespace.default(obj)
is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False
), then the output of dictionaries will be sorted by key.To use a custom
JSONEncoder
subclass (e.g. one that overrides the.default()
method to serialize additional types), specify it with thecls
kwarg; otherwiseJSONEncoder
is used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s
(astr
,bytes
orbytearray
instance containing a JSON document) to a Python object.object_hook
is an optional function that will be called with the result of any object literal decode (adict
). The return value ofobject_hook
will be used instead of thedict
. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hook
is an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hook
will be used instead of thedict
. This feature can be used to implement custom decoders. Ifobject_hook
is also defined, theobject_pairs_hook
takes priority.parse_float
, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int
, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant
, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecoder
subclass, specify it with thecls
kwarg; otherwiseJSONDecoder
is used.
- __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
- __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().
- class runway.config.models.runway.RunwayDeploymentRegionDefinitionModel[source]
Bases:
runway.config.models.base.ConfigProperty
Model for a Runway deployment region definition.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.Config
Model configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: str) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
obj
to a JSON formattedstr
.If
skipkeys
is true thendict
keys that are not basic types (str
,int
,float
,bool
,None
) will be skipped instead of raising aTypeError
.If
ensure_ascii
is false, then the return value can contain non-ASCII characters if they appear in strings contained inobj
. Otherwise, all such characters are escaped in JSON strings.If
check_circular
is false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError
(or worse).If
allow_nan
is false, then it will be aValueError
to serialize out of rangefloat
values (nan
,inf
,-inf
) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN
,Infinity
,-Infinity
).If
indent
is a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.None
is the most compact representation.If specified,
separators
should be an(item_separator, key_separator)
tuple. The default is(', ', ': ')
if indent isNone
and(',', ': ')
otherwise. To get the most compact JSON representation, you should specify(',', ':')
to eliminate whitespace.default(obj)
is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False
), then the output of dictionaries will be sorted by key.To use a custom
JSONEncoder
subclass (e.g. one that overrides the.default()
method to serialize additional types), specify it with thecls
kwarg; otherwiseJSONEncoder
is used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s
(astr
,bytes
orbytearray
instance containing a JSON document) to a Python object.object_hook
is an optional function that will be called with the result of any object literal decode (adict
). The return value ofobject_hook
will be used instead of thedict
. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hook
is an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hook
will be used instead of thedict
. This feature can be used to implement custom decoders. Ifobject_hook
is also defined, theobject_pairs_hook
takes priority.parse_float
, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int
, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant
, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecoder
subclass, specify it with thecls
kwarg; otherwiseJSONDecoder
is used.
- __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
- __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().
- class runway.config.models.runway.RunwayFutureDefinitionModel[source]
Bases:
runway.config.models.base.ConfigProperty
Model for the Runway future definition.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.Config
Model configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: str) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
obj
to a JSON formattedstr
.If
skipkeys
is true thendict
keys that are not basic types (str
,int
,float
,bool
,None
) will be skipped instead of raising aTypeError
.If
ensure_ascii
is false, then the return value can contain non-ASCII characters if they appear in strings contained inobj
. Otherwise, all such characters are escaped in JSON strings.If
check_circular
is false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError
(or worse).If
allow_nan
is false, then it will be aValueError
to serialize out of rangefloat
values (nan
,inf
,-inf
) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN
,Infinity
,-Infinity
).If
indent
is a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.None
is the most compact representation.If specified,
separators
should be an(item_separator, key_separator)
tuple. The default is(', ', ': ')
if indent isNone
and(',', ': ')
otherwise. To get the most compact JSON representation, you should specify(',', ':')
to eliminate whitespace.default(obj)
is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False
), then the output of dictionaries will be sorted by key.To use a custom
JSONEncoder
subclass (e.g. one that overrides the.default()
method to serialize additional types), specify it with thecls
kwarg; otherwiseJSONEncoder
is used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s
(astr
,bytes
orbytearray
instance containing a JSON document) to a Python object.object_hook
is an optional function that will be called with the result of any object literal decode (adict
). The return value ofobject_hook
will be used instead of thedict
. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hook
is an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hook
will be used instead of thedict
. This feature can be used to implement custom decoders. Ifobject_hook
is also defined, theobject_pairs_hook
takes priority.parse_float
, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int
, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant
, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecoder
subclass, specify it with thecls
kwarg; otherwiseJSONDecoder
is used.
- __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
- __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().
- class runway.config.models.runway.RunwayModuleDefinitionModel[source]
Bases:
runway.config.models.base.ConfigProperty
Model for a Runway module definition.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.Config
Model configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: str) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
obj
to a JSON formattedstr
.If
skipkeys
is true thendict
keys that are not basic types (str
,int
,float
,bool
,None
) will be skipped instead of raising aTypeError
.If
ensure_ascii
is false, then the return value can contain non-ASCII characters if they appear in strings contained inobj
. Otherwise, all such characters are escaped in JSON strings.If
check_circular
is false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError
(or worse).If
allow_nan
is false, then it will be aValueError
to serialize out of rangefloat
values (nan
,inf
,-inf
) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN
,Infinity
,-Infinity
).If
indent
is a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.None
is the most compact representation.If specified,
separators
should be an(item_separator, key_separator)
tuple. The default is(', ', ': ')
if indent isNone
and(',', ': ')
otherwise. To get the most compact JSON representation, you should specify(',', ':')
to eliminate whitespace.default(obj)
is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False
), then the output of dictionaries will be sorted by key.To use a custom
JSONEncoder
subclass (e.g. one that overrides the.default()
method to serialize additional types), specify it with thecls
kwarg; otherwiseJSONEncoder
is used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s
(astr
,bytes
orbytearray
instance containing a JSON document) to a Python object.object_hook
is an optional function that will be called with the result of any object literal decode (adict
). The return value ofobject_hook
will be used instead of thedict
. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hook
is an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hook
will be used instead of thedict
. This feature can be used to implement custom decoders. Ifobject_hook
is also defined, theobject_pairs_hook
takes priority.parse_float
, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int
, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant
, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecoder
subclass, specify it with thecls
kwarg; otherwiseJSONDecoder
is used.
- __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
- __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().
- class runway.config.models.runway.RunwayTestDefinitionModel[source]
Bases:
runway.config.models.base.ConfigProperty
Model for a Runway test definition.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.Config
Model configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: str) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
obj
to a JSON formattedstr
.If
skipkeys
is true thendict
keys that are not basic types (str
,int
,float
,bool
,None
) will be skipped instead of raising aTypeError
.If
ensure_ascii
is false, then the return value can contain non-ASCII characters if they appear in strings contained inobj
. Otherwise, all such characters are escaped in JSON strings.If
check_circular
is false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError
(or worse).If
allow_nan
is false, then it will be aValueError
to serialize out of rangefloat
values (nan
,inf
,-inf
) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN
,Infinity
,-Infinity
).If
indent
is a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.None
is the most compact representation.If specified,
separators
should be an(item_separator, key_separator)
tuple. The default is(', ', ': ')
if indent isNone
and(',', ': ')
otherwise. To get the most compact JSON representation, you should specify(',', ':')
to eliminate whitespace.default(obj)
is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False
), then the output of dictionaries will be sorted by key.To use a custom
JSONEncoder
subclass (e.g. one that overrides the.default()
method to serialize additional types), specify it with thecls
kwarg; otherwiseJSONEncoder
is used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s
(astr
,bytes
orbytearray
instance containing a JSON document) to a Python object.object_hook
is an optional function that will be called with the result of any object literal decode (adict
). The return value ofobject_hook
will be used instead of thedict
. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hook
is an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hook
will be used instead of thedict
. This feature can be used to implement custom decoders. Ifobject_hook
is also defined, theobject_pairs_hook
takes priority.parse_float
, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int
, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant
, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecoder
subclass, specify it with thecls
kwarg; otherwiseJSONDecoder
is used.
- static __new__(cls, **kwargs: Any) runway.config.models.runway._builtin_tests.RunwayTestDefinitionModel [source]
Create a new instance of a class.
- Returns
Correct subclass of RunwayTestDefinition for the given data.
- __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
- __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
- __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().
- class runway.config.models.runway.RunwayVariablesDefinitionModel[source]
Bases:
runway.config.models.base.ConfigProperty
Model for a Runway variable definition.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.Config
Model configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: str) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
obj
to a JSON formattedstr
.If
skipkeys
is true thendict
keys that are not basic types (str
,int
,float
,bool
,None
) will be skipped instead of raising aTypeError
.If
ensure_ascii
is false, then the return value can contain non-ASCII characters if they appear in strings contained inobj
. Otherwise, all such characters are escaped in JSON strings.If
check_circular
is false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError
(or worse).If
allow_nan
is false, then it will be aValueError
to serialize out of rangefloat
values (nan
,inf
,-inf
) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN
,Infinity
,-Infinity
).If
indent
is a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.None
is the most compact representation.If specified,
separators
should be an(item_separator, key_separator)
tuple. The default is(', ', ': ')
if indent isNone
and(',', ': ')
otherwise. To get the most compact JSON representation, you should specify(',', ':')
to eliminate whitespace.default(obj)
is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False
), then the output of dictionaries will be sorted by key.To use a custom
JSONEncoder
subclass (e.g. one that overrides the.default()
method to serialize additional types), specify it with thecls
kwarg; otherwiseJSONEncoder
is used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s
(astr
,bytes
orbytearray
instance containing a JSON document) to a Python object.object_hook
is an optional function that will be called with the result of any object literal decode (adict
). The return value ofobject_hook
will be used instead of thedict
. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hook
is an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hook
will be used instead of thedict
. This feature can be used to implement custom decoders. Ifobject_hook
is also defined, theobject_pairs_hook
takes priority.parse_float
, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int
, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant
, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecoder
subclass, specify it with thecls
kwarg; otherwiseJSONDecoder
is used.
- __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
- __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().
- class runway.config.models.runway.RunwayVersionField[source]
Bases:
packaging.specifiers.SpecifierSet
Extends packaging.specifiers.SpecifierSet for use with pydantic.
- classmethod __get_validators__() Generator[Callable[[...], Any], None, None] [source]
Yield one of more validators with will be called to validate the input.
Each validator will receive, as input, the value returned from the previous validator.
- classmethod __modify_schema__(field_schema: Dict[str, Any]) None [source]
Mutate the field schema in place.
This is only called when output JSON schema from a model.
- __and__(other: packaging.specifiers.SpecifierSet | str) packaging.specifiers.SpecifierSet
Return a SpecifierSet which is a combination of the two sets.
- Parameters
other – The other object to combine with.
>>> SpecifierSet(">=1.0.0,!=1.0.1") & '<=2.0.0,!=2.0.1' <SpecifierSet('!=1.0.1,!=2.0.1,<=2.0.0,>=1.0.0')> >>> SpecifierSet(">=1.0.0,!=1.0.1") & SpecifierSet('<=2.0.0,!=2.0.1') <SpecifierSet('!=1.0.1,!=2.0.1,<=2.0.0,>=1.0.0')>
- __contains__(item: Union[packaging.version.Version, str]) bool
Return whether or not the item is contained in this specifier.
- Parameters
item – The item to check for.
This is used for the
in
operator and behaves the same ascontains()
with noprereleases
argument passed.>>> "1.2.3" in SpecifierSet(">=1.0.0,!=1.0.1") True >>> Version("1.2.3") in SpecifierSet(">=1.0.0,!=1.0.1") True >>> "1.0.1" in SpecifierSet(">=1.0.0,!=1.0.1") False >>> "1.3.0a1" in SpecifierSet(">=1.0.0,!=1.0.1") False >>> "1.3.0a1" in SpecifierSet(">=1.0.0,!=1.0.1", prereleases=True) True
- __eq__(other: object) bool
Whether or not the two SpecifierSet-like objects are equal.
- Parameters
other – The other object to check against.
The value of
prereleases
is ignored.>>> SpecifierSet(">=1.0.0,!=1.0.1") == SpecifierSet(">=1.0.0,!=1.0.1") True >>> (SpecifierSet(">=1.0.0,!=1.0.1", prereleases=False) == ... SpecifierSet(">=1.0.0,!=1.0.1", prereleases=True)) True >>> SpecifierSet(">=1.0.0,!=1.0.1") == ">=1.0.0,!=1.0.1" True >>> SpecifierSet(">=1.0.0,!=1.0.1") == SpecifierSet(">=1.0.0") False >>> SpecifierSet(">=1.0.0,!=1.0.1") == SpecifierSet(">=1.0.0,!=1.0.2") False
- __init__(specifiers: str = '', prereleases: bool | None = None) None
Initialize a SpecifierSet instance.
- Parameters
specifiers – The string representation of a specifier or a comma-separated list of specifiers which will be parsed and normalized before use.
prereleases – This tells the SpecifierSet if it should accept prerelease versions if applicable or not. The default of
None
will autodetect it from the given specifiers.
- Raises
InvalidSpecifier – If the given
specifiers
are not parseable than this exception will be raised.
- __iter__() Iterator[packaging.specifiers.Specifier]
Returns an iterator over all the underlying
Specifier
instances in this specifier set.>>> sorted(SpecifierSet(">=1.0.0,!=1.0.1"), key=str) [<Specifier('!=1.0.1')>, <Specifier('>=1.0.0')>]
- __new__(**kwargs)
- __repr__() str
A representation of the specifier set that shows all internal state.
Note that the ordering of the individual specifiers within the set may not match the input string.
>>> SpecifierSet('>=1.0.0,!=2.0.0') <SpecifierSet('!=2.0.0,>=1.0.0')> >>> SpecifierSet('>=1.0.0,!=2.0.0', prereleases=False) <SpecifierSet('!=2.0.0,>=1.0.0', prereleases=False)> >>> SpecifierSet('>=1.0.0,!=2.0.0', prereleases=True) <SpecifierSet('!=2.0.0,>=1.0.0', prereleases=True)>
- __str__() str
A string representation of the specifier set that can be round-tripped.
Note that the ordering of the individual specifiers within the set may not match the input string.
>>> str(SpecifierSet(">=1.0.0,!=1.0.1")) '!=1.0.1,>=1.0.0' >>> str(SpecifierSet(">=1.0.0,!=1.0.1", prereleases=False)) '!=1.0.1,>=1.0.0'
- contains(item: Union[packaging.version.Version, str], prereleases: bool | None = None, installed: bool | None = None) bool
Return whether or not the item is contained in this SpecifierSet.
- Parameters
item – The item to check for, which can be a version string or a
Version
instance.prereleases – Whether or not to match prereleases with this SpecifierSet. If set to
None
(the default), it usesprereleases
to determine whether or not prereleases are allowed.
>>> SpecifierSet(">=1.0.0,!=1.0.1").contains("1.2.3") True >>> SpecifierSet(">=1.0.0,!=1.0.1").contains(Version("1.2.3")) True >>> SpecifierSet(">=1.0.0,!=1.0.1").contains("1.0.1") False >>> SpecifierSet(">=1.0.0,!=1.0.1").contains("1.3.0a1") False >>> SpecifierSet(">=1.0.0,!=1.0.1", prereleases=True).contains("1.3.0a1") True >>> SpecifierSet(">=1.0.0,!=1.0.1").contains("1.3.0a1", prereleases=True) True
- filter(iterable: Iterable[packaging.specifiers.UnparsedVersionVar], prereleases: bool | None = None) Iterator[packaging.specifiers.UnparsedVersionVar]
Filter items in the given iterable, that match the specifiers in this set.
- Parameters
iterable – An iterable that can contain version strings and
Version
instances. The items in the iterable will be filtered according to the specifier.prereleases – Whether or not to allow prereleases in the returned iterator. If set to
None
(the default), it will be intelligently decide whether to allow prereleases or not (based on theprereleases
attribute, and whether the only versions matching are prereleases).
This method is smarter than just
filter(SpecifierSet(...).contains, [...])
because it implements the rule from PEP 440 that a prerelease item SHOULD be accepted if no other versions match the given specifier.>>> list(SpecifierSet(">=1.2.3").filter(["1.2", "1.3", "1.5a1"])) ['1.3'] >>> list(SpecifierSet(">=1.2.3").filter(["1.2", "1.3", Version("1.4")])) ['1.3', <Version('1.4')>] >>> list(SpecifierSet(">=1.2.3").filter(["1.2", "1.5a1"])) [] >>> list(SpecifierSet(">=1.2.3").filter(["1.3", "1.5a1"], prereleases=True)) ['1.3', '1.5a1'] >>> list(SpecifierSet(">=1.2.3", prereleases=True).filter(["1.3", "1.5a1"])) ['1.3', '1.5a1']
An “empty” SpecifierSet will filter items based on the presence of prerelease versions in the set.
>>> list(SpecifierSet("").filter(["1.3", "1.5a1"])) ['1.3'] >>> list(SpecifierSet("").filter(["1.5a1"])) ['1.5a1'] >>> list(SpecifierSet("", prereleases=True).filter(["1.3", "1.5a1"])) ['1.3', '1.5a1'] >>> list(SpecifierSet("").filter(["1.3", "1.5a1"], prereleases=True)) ['1.3', '1.5a1']
- class runway.config.models.runway.ScriptRunwayTestArgs[source]
Bases:
runway.config.models.base.ConfigProperty
Model for the args of a script test.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.Config
Model configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: str) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
obj
to a JSON formattedstr
.If
skipkeys
is true thendict
keys that are not basic types (str
,int
,float
,bool
,None
) will be skipped instead of raising aTypeError
.If
ensure_ascii
is false, then the return value can contain non-ASCII characters if they appear in strings contained inobj
. Otherwise, all such characters are escaped in JSON strings.If
check_circular
is false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError
(or worse).If
allow_nan
is false, then it will be aValueError
to serialize out of rangefloat
values (nan
,inf
,-inf
) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN
,Infinity
,-Infinity
).If
indent
is a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.None
is the most compact representation.If specified,
separators
should be an(item_separator, key_separator)
tuple. The default is(', ', ': ')
if indent isNone
and(',', ': ')
otherwise. To get the most compact JSON representation, you should specify(',', ':')
to eliminate whitespace.default(obj)
is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False
), then the output of dictionaries will be sorted by key.To use a custom
JSONEncoder
subclass (e.g. one that overrides the.default()
method to serialize additional types), specify it with thecls
kwarg; otherwiseJSONEncoder
is used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s
(astr
,bytes
orbytearray
instance containing a JSON document) to a Python object.object_hook
is an optional function that will be called with the result of any object literal decode (adict
). The return value ofobject_hook
will be used instead of thedict
. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hook
is an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hook
will be used instead of thedict
. This feature can be used to implement custom decoders. Ifobject_hook
is also defined, theobject_pairs_hook
takes priority.parse_float
, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int
, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant
, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecoder
subclass, specify it with thecls
kwarg; otherwiseJSONDecoder
is used.
- __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
- __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().
- class runway.config.models.runway.ScriptRunwayTestDefinitionModel[source]
Bases:
runway.config.models.runway._builtin_tests.RunwayTestDefinitionModel
Model for a script test definition.
- class Config[source]
Bases:
runway.config.models.runway._builtin_tests.RunwayTestDefinitionModel.Config
Model configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: str) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
obj
to a JSON formattedstr
.If
skipkeys
is true thendict
keys that are not basic types (str
,int
,float
,bool
,None
) will be skipped instead of raising aTypeError
.If
ensure_ascii
is false, then the return value can contain non-ASCII characters if they appear in strings contained inobj
. Otherwise, all such characters are escaped in JSON strings.If
check_circular
is false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError
(or worse).If
allow_nan
is false, then it will be aValueError
to serialize out of rangefloat
values (nan
,inf
,-inf
) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN
,Infinity
,-Infinity
).If
indent
is a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.None
is the most compact representation.If specified,
separators
should be an(item_separator, key_separator)
tuple. The default is(', ', ': ')
if indent isNone
and(',', ': ')
otherwise. To get the most compact JSON representation, you should specify(',', ':')
to eliminate whitespace.default(obj)
is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False
), then the output of dictionaries will be sorted by key.To use a custom
JSONEncoder
subclass (e.g. one that overrides the.default()
method to serialize additional types), specify it with thecls
kwarg; otherwiseJSONEncoder
is used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s
(astr
,bytes
orbytearray
instance containing a JSON document) to a Python object.object_hook
is an optional function that will be called with the result of any object literal decode (adict
). The return value ofobject_hook
will be used instead of thedict
. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hook
is an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hook
will be used instead of thedict
. This feature can be used to implement custom decoders. Ifobject_hook
is also defined, theobject_pairs_hook
takes priority.parse_float
, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int
, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant
, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecoder
subclass, specify it with thecls
kwarg; otherwiseJSONDecoder
is used.
- __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
- static __new__(cls, **kwargs: Any) runway.config.models.runway._builtin_tests.RunwayTestDefinitionModel
Create a new instance of a class.
- Returns
Correct subclass of RunwayTestDefinition for the given data.
- __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
- __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().
- class runway.config.models.runway.YamlLintRunwayTestDefinitionModel[source]
Bases:
runway.config.models.runway._builtin_tests.RunwayTestDefinitionModel
Model for a yamllint test definition.
- class Config[source]
Bases:
runway.config.models.runway._builtin_tests.RunwayTestDefinitionModel.Config
Model configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: str) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
obj
to a JSON formattedstr
.If
skipkeys
is true thendict
keys that are not basic types (str
,int
,float
,bool
,None
) will be skipped instead of raising aTypeError
.If
ensure_ascii
is false, then the return value can contain non-ASCII characters if they appear in strings contained inobj
. Otherwise, all such characters are escaped in JSON strings.If
check_circular
is false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError
(or worse).If
allow_nan
is false, then it will be aValueError
to serialize out of rangefloat
values (nan
,inf
,-inf
) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN
,Infinity
,-Infinity
).If
indent
is a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.None
is the most compact representation.If specified,
separators
should be an(item_separator, key_separator)
tuple. The default is(', ', ': ')
if indent isNone
and(',', ': ')
otherwise. To get the most compact JSON representation, you should specify(',', ':')
to eliminate whitespace.default(obj)
is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False
), then the output of dictionaries will be sorted by key.To use a custom
JSONEncoder
subclass (e.g. one that overrides the.default()
method to serialize additional types), specify it with thecls
kwarg; otherwiseJSONEncoder
is used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s
(astr
,bytes
orbytearray
instance containing a JSON document) to a Python object.object_hook
is an optional function that will be called with the result of any object literal decode (adict
). The return value ofobject_hook
will be used instead of thedict
. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hook
is an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hook
will be used instead of thedict
. This feature can be used to implement custom decoders. Ifobject_hook
is also defined, theobject_pairs_hook
takes priority.parse_float
, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int
, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant
, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecoder
subclass, specify it with thecls
kwarg; otherwiseJSONDecoder
is used.
- __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
- static __new__(cls, **kwargs: Any) runway.config.models.runway._builtin_tests.RunwayTestDefinitionModel
Create a new instance of a class.
- Returns
Correct subclass of RunwayTestDefinition for the given data.
- __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
- __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().