runway.config.models.base module

Base models & other objects.

class runway.config.models.base.ConfigProperty[source]

Bases: runway.utils.BaseModel

Base class for Runway configuration properties.

class Config[source]

Bases: pydantic.config.BaseConfig

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 formatted str.

If skipkeys is true then dict keys that are not basic types (str, int, float, bool, None) will be skipped instead of raising a TypeError.

If ensure_ascii is false, then the return value can contain non-ASCII characters if they appear in strings contained in obj. 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 an RecursionError (or worse).

If allow_nan is false, then it will be a ValueError to serialize out of range float 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 is None 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 the cls kwarg; otherwise JSONEncoder 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 (a str, bytes or bytearray 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 (a dict). The return value of object_hook will be used instead of the dict. 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 of object_pairs_hook will be used instead of the dict. This feature can be used to implement custom decoders. If object_hook is also defined, the object_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 the cls kwarg; otherwise JSONDecoder is used.

classmethod prepare_field(field: ModelField) → None

Optional hook to check or modify fields during model creation.

__contains__(name: object) → bool

Implement evaluation of ‘in’ conditional.

Parameters

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

__getitem__(name: str) → Any

Implement evaluation of self[name].

Parameters

name – Attribute name to return the value for.

Returns

The value associated with the provided name/attribute name.

Raises

AttributeError – If attribute does not exist on this object.

__init__(**data: Any) → None

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

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

__iter__() → TupleGenerator

so dict(model) works

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

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

__repr_name__() → str

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

__rich_repr__() → RichReprResult

Get fields for Rich library

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

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

Parameters

  • name – Attribute name to set.

  • value – Value to assign to the attribute.

classmethod __try_update_forward_refs__(**localns: Any) → None

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

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

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

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

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

Parameters

  • include – fields to include in new model

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

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

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

Returns

new model instance

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

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

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

Safely get the value of an attribute.

Parameters

  • name – Attribute name to return the value for.

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

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

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

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

classmethod update_forward_refs(**localns: Any) → None

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