rwskit.dataclasses

Attributes

log
D	A type intended to represent a dataclass.

Classes

DataclassRegistry	Initialize the registry.
FrozenDataclassMeta	Turn the class into a pydantic dataclass if it is not one already.
EnforceFrozenDataclassMeta	Requires that the class must be a standard or pydantic dataclass.

Functions

immutable_dataclass(cls)	A decorator to convert a class to a frozen keyword only pydantic dataclass.
is_frozen(→ bool)	Checks if a class is a frozen dataclass.
has_default_value(→ bool)	Checks if a field has a default value.
is_optional(→ bool)	Checks if a field is optional.
is_required(→ bool)	Checks if a field is required.
resolve_type_hints(→ dict[str, Any])	Try to resolve the type hints for a dataclass.
construct_dataclass(→ D)	Construct a dataclass from a mapping.

Module Contents

rwskit.dataclasses_.log

rwskit.dataclasses_.D

A type intended to represent a dataclass.

rwskit.dataclasses_.immutable_dataclass(cls: Type[D])

A decorator to convert a class to a frozen keyword only pydantic dataclass.

rwskit.dataclasses_.is_frozen(cls: Type) → bool

Checks if a class is a frozen dataclass.

This will return True if the input cls is both a dataclass (either dataclasses.dataclass or pydantic.dataclasses.dataclass) and it is frozen.

rwskit.dataclasses_.has_default_value(field: dataclasses.Field) → bool

Checks if a field has a default value.

Parameters:

field (Field) – The field to check.

Returns:

True if the field has a default value either directly or via a default factory.

Return type:

bool

rwskit.dataclasses_.is_optional(field: dataclasses.Field) → bool

Checks if a field is optional.

Parameters:

field (Field) – The field to check.

Returns:

True if the field is optional.

Return type:

bool

rwskit.dataclasses_.is_required(field: dataclasses.Field) → bool

Checks if a field is required.

A field is required if it is not optional and does not have a default value.

Parameters:

field (Field) – The field to check,

Returns:

True if the field is required.

Return type:

bool

rwskit.dataclasses_.resolve_type_hints(cls: Type[Any], type_map: dict[str, Type[Any]] | None = None, max_tries: int = 50) → dict[str, Any]

Try to resolve the type hints for a dataclass.

Sometimes func:typing.get_type_hints fails with a NameError when the type hint has not already been imported. This method will try to catch those errors and dynamically import the unresolved class.

Parameters:

• cls (Type[Any]) – The dataclass to resolve the type hints for.

• type_map (dict[str, Type[Any]], optional) – Additional mappings from string names to type classes, which can be used in addition to globals() for resolving type hint classes.

• max_tries (int) – The maximum number of times the method will try to resolve missing type hints.

Returns:

The dictionary containing the resolved type hints.

Return type:

dict[str, Any]

Raises:

icontract.ViolationError – If the input cls is not a dataclass.

rwskit.dataclasses_.construct_dataclass(data: Mapping[str, Any], dataclass_type: Type[D], type_map: dict[str, Any] | None = None) → D

Construct a dataclass from a mapping.

Try to construct a possibly nested dataclass of dataclass_type from a mapping provided by data. If the dataclass cannot be constructed from the data a TypeError will be raised.

Parameters:

• data (Mapping[str, Any]) – The dictionary (or other mapping) to try to convert.

• dataclass_type (Type[D]) – The dataclass type we will try to construct.

• type_map (dict[str, Any], optional) – By default this method will use globals() to try to resolve the type hints for the dataclass fields. You can specify any additional mappings with type_map which will be appended to the default.

Returns:

The dataclass object we have constructed.

Return type:

D

Raises:

• icontract.ViolationError – If the dataclass_type is not a dataclass.

• TypeError – If the dictionary cannot be converted to the dataclass type.

class rwskit.dataclasses_.DataclassRegistry

Initialize the registry.

registered_classes: set[Type[D]]

__iter__() → Iterator[Type[D]]

__len__() → int

register(*classes: Type[D])

Add a class to the registry.

Parameters:

classes (Type[D]) – The class or classes to add.

construct_registered_dataclass(data: Mapping[str, Any], type_map: dict[str, Any] | None = None) → D

Try to construct one of the registered dataclasses from the given data.

Parameters:

• data (Mapping[str, Any]) – The data to use for constructing a dataclass.

• type_map (dict[str, Any], optional) – Additional types that should be made available (imported) when resolving type hints for the registered dataclasses.

Returns:

An instance of a registered dataclass that is compatible with the given data.

Return type:

D

Raises:

• icontract.ViolationError – If data does not contain values for all required attributes of the dataclass (or any nested dataclass).

• icontract.ViolationError – If data is not a Mapping.

• ValueError – If a registered dataclass cannot be constructed from the data.

class rwskit.dataclasses_.FrozenDataclassMeta

Bases: type

Turn the class into a pydantic dataclass if it is not one already.

Note

Although this will turn any class that uses it into a pydantic dataclass, it will cause most linters (including PyCharm) to issue unresolved attribute warnings for all attributes.

class rwskit.dataclasses_.EnforceFrozenDataclassMeta

Bases: type

Requires that the class must be a standard or pydantic dataclass.

Any class using this metaclass is not a frozen dataclass will raise a TypeError exception.

Note

This is not particularly useful because the metaclass will be applied before any decorators, so even if a class is decorated with @dataclass it will still raise a TypeError here, because it has not been applied yet.