dataclass_wizard.v1 package

Submodules

dataclass_wizard.v1.decorators module

dataclass_wizard.v1.decorators.process_patterned_date_time(func)[source]

Decorator for processing patterned date and time data.

If the ‘pattern’ key exists in the extras dictionary, it updates the base and origin of the type information and processes the pattern before calling the original function.

Supports both class methods and static methods.

Return type:

Callable

Parameters:

func (Callable)

Args:

func (Callable): The function to decorate, either a class method or static method.

Returns:

Callable: The wrapped function with pattern processing applied.

dataclass_wizard.v1.decorators.setup_recursive_safe_function(func=None, *, fn_name=None, is_generic=False, add_cls=True)[source]

A decorator to ensure recursion safety and facilitate dynamic function generation with FunctionBuilder, supporting both generic and non-generic types.

The decorated function can define the logic for dynamically generated functions. If fn_name is provided, the decorator assumes that the function generation context (e.g., with fn_gen.function(…)) has already been handled externally and will not apply it again.

Parameters:
  • func (Callable, optional) – The function to decorate. If None, the decorator is applied with arguments.

  • fn_name (str, optional) – A format string for dynamically generating function names, or None.

  • is_generic (bool, optional) – Whether the function deals with generic types.

  • add_cls (bool, optional) – Whether the class should be added to the function locals for FunctionBuilder.

Returns:

The decorated function with recursion safety and dynamic function generation.

Return type:

Callable

dataclass_wizard.v1.decorators.setup_recursive_safe_function_for_generic(func)[source]

A helper decorator to handle generic types using setup_recursive_safe_function.

Return type:

Callable

Parameters:

func (Callable)

Parameters

funcCallable

The function to be decorated, responsible for returning the generated function name.

Returns

Callable

A wrapped function ensuring recursion safety for generic types.

dataclass_wizard.v1.enums module

class dataclass_wizard.v1.enums.KeyAction(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]

Bases: Enum

Specifies how to handle unknown keys encountered during deserialization.

Actions: - IGNORE: Skip unknown keys silently. - RAISE: Raise an exception upon encountering the first unknown key. - WARN: Log a warning for each unknown key.

For capturing unknown keys (e.g., including them in a dataclass), use the CatchAll field. More details: https://dataclass-wizard.readthedocs.io/en/latest/common_use_cases/handling_unknown_json_keys.html#capturing-unknown-keys-with-catchall

IGNORE = 0
RAISE = 1
WARN = 2
class dataclass_wizard.v1.enums.KeyCase(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]

Bases: Enum

Defines transformations for string keys, commonly used for mapping JSON keys to dataclass fields.

Key transformations:

  • CAMEL: Converts snake_case to camelCase. Example: my_field_name -> myFieldName

  • PASCAL: Converts snake_case to PascalCase (UpperCamelCase). Example: my_field_name -> MyFieldName

  • KEBAB: Converts camelCase or snake_case to kebab-case. Example: myFieldName -> my-field-name

  • SNAKE: Converts camelCase to snake_case. Example: myFieldName -> my_field_name

  • AUTO: Automatically maps JSON keys to dataclass fields by

    attempting all valid key casing transforms at runtime.

    Example: My-Field-Name -> my_field_name (cached for future lookups)

By default, no transformation is applied:
  • Example: MY_FIELD_NAME -> MY_FIELD_NAME

A = None
AUTO = None
C = <dataclass_wizard.utils.wrappers.FuncWrapper object>
CAMEL = <dataclass_wizard.utils.wrappers.FuncWrapper object>
K = <dataclass_wizard.utils.wrappers.FuncWrapper object>
KEBAB = <dataclass_wizard.utils.wrappers.FuncWrapper object>
P = <dataclass_wizard.utils.wrappers.FuncWrapper object>
PASCAL = <dataclass_wizard.utils.wrappers.FuncWrapper object>
S = <dataclass_wizard.utils.wrappers.FuncWrapper object>
SNAKE = <dataclass_wizard.utils.wrappers.FuncWrapper object>

dataclass_wizard.v1.loaders module

class dataclass_wizard.v1.loaders.LoadMixin[source]

Bases: AbstractLoaderGenerator, BaseLoadHook

This Mixin class derives its name from the eponymous json.loads function. Essentially it contains helper methods to convert JSON strings (or a Python dictionary object) to a dataclass which can often contain complex types such as lists, dicts, or even other dataclasses nested within it.

Refer to the AbstractLoader class for documentation on any of the implemented methods.

static default_load_to(tp, extras)[source]

Generate code for the default load function if no other types match. Generally, this will be a stub load method.

Parameters:
classmethod get_string_for_annotation(tp, extras)[source]

Generate code to get the parser (dispatcher) for a given annotation type.

base_cls is the original class object, useful when the annotated type is a typing.ForwardRef object.

static load_to_bool(tp, extras)[source]

Generate code to load a value into a boolean field. Adds a helper function as_bool to the local context.

Parameters:
classmethod load_to_bytearray(tp, extras)[source]

Generate code to load a value into a bytearray field.

Parameters:
static load_to_bytes(tp, extras)[source]

Generate code to load a value into a bytes field.

Parameters:
static load_to_dataclass(tp, extras)[source]

Generate code to load a value into a dataclass type field.

Parameters:
classmethod load_to_date(cls, tp, extras)[source]

Generate code to load a value into a date field.

Parameters:
classmethod load_to_datetime(cls, tp, extras)[source]

Generate code to load a value into a datetime field.

Parameters:
static load_to_decimal(tp, extras)[source]

Generate code to load a value into a Decimal field.

Parameters:
classmethod load_to_defaultdict(tp, extras)[source]

Generate code to load a value into a defaultdict field.

Parameters:
classmethod load_to_dict(tp, extras)[source]

Generate code to load a value into a dictionary field.

Parameters:
static load_to_enum(tp, extras)[source]

Generate code to load a value into an Enum field.

Parameters:
static load_to_float(tp, extras)[source]

Generate code to load a value into a float field.

Parameters:
static load_to_int(tp, extras)[source]

Generate code to load a value into an integer field.

Current logic to parse (an annotated) int returns:
  • v –> v is an int or similarly annotated type.

  • int(v) –> v is a str value of either a decimal

    integer (e.g. '123') or a non-fractional float value (e.g. 42.0).

  • as_int(v) –> v is a non-fractional float, or in case

    of “less common” types / scenarios. Note that empty strings and None (e.g. null values) are not supported.

Parameters:
classmethod load_to_iterable(tp, extras)[source]

Generate code to load a value into an iterable field (list, set, etc.).

Parameters:
static load_to_literal(tp, extras)[source]

Generate code to confirm a value is equivalent to one of the provided literals.

Parameters:
classmethod load_to_named_tuple(cls, tp, extras)[source]

Generate code to load a value into a named tuple field.

Parameters:
classmethod load_to_named_tuple_untyped(tp, extras)[source]

Generate code to load a value into an untyped named tuple.

Parameters:
static load_to_none(tp, extras)[source]

Generate code to load a value into a None.

Parameters:
static load_to_path(tp, extras)[source]

Generate code to load a value into a Decimal field.

Parameters:
static load_to_str(tp, extras)[source]

Generate code to load a value into a string field.

Parameters:
static load_to_time(tp, extras)[source]

Generate code to load a value into a time field.

Parameters:
static load_to_timedelta(tp, extras)[source]

Generate code to load a value into a timedelta field.

Parameters:
classmethod load_to_tuple(tp, extras)[source]

Generate code to load a value into a tuple field.

Parameters:
classmethod load_to_typed_dict(cls, tp, extras)[source]

Generate code to load a value into a typed dictionary field.

Parameters:
classmethod load_to_union(cls, tp, extras)[source]

Generate code to load a value into a Union[X, Y, …] (one of [X, Y, …] possible types)

Parameters:
static load_to_uuid(tp, extras)[source]

Generate code to load a value into a UUID field.

Parameters:
transform_json_field = None
dataclass_wizard.v1.loaders.check_and_raise_missing_fields(_locals, o, cls, fields)[source]
Parameters:

fields (tuple[Field, ...] | None)

dataclass_wizard.v1.loaders.generate_field_code(cls_loader, extras, field, field_i)[source]
Return type:

str | TypeInfo

Parameters:
dataclass_wizard.v1.loaders.load_func_for_dataclass(cls, extras=None, loader_cls=<class 'dataclass_wizard.v1.loaders.LoadMixin'>, base_meta_cls=<class 'dataclass_wizard.bases.AbstractMeta'>)[source]
Return type:

Optional[Callable[[dict[str, Any]], TypeVar(T)]]

Parameters:
  • cls (type)

  • extras (Extras | None)

  • base_meta_cls (type)

dataclass_wizard.v1.loaders.re_raise(e, cls, o, fields, field, value)[source]
dataclass_wizard.v1.loaders.setup_default_loader(cls=<class 'dataclass_wizard.v1.loaders.LoadMixin'>)[source]

Set up the default type hooks to use when converting str (json) or a Python dict object to a dataclass instance.

Note: cls must be LoadMixIn or a subclass of it.

dataclass_wizard.v1.models module

dataclass_wizard.v1.models.Alias(*all, load=None, dump=None, skip=False, default=<dataclasses._MISSING_TYPE object>, default_factory=<dataclasses._MISSING_TYPE object>, init=True, repr=True, hash=None, compare=True, metadata=None, kw_only=False)[source]

Maps one or more JSON key names to a dataclass field.

This function acts as an alias for dataclasses.field(...), with additional support for associating a field with one or more JSON keys. It customizes serialization and deserialization behavior, including handling keys with varying cases or alternative names.

The mapping is case-sensitive; JSON keys must match exactly (e.g., myField will not match myfield). If multiple keys are provided, the first one is used as the default for serialization.

Parameters:
  • all (str) – One or more JSON key names to associate with the dataclass field.

  • load (str | Sequence[str] | None) – Key(s) to use for deserialization. Defaults to all if not specified.

  • dump (str | None) – Key to use for serialization. Defaults to the first key in all.

  • skip (bool) – If True, the field is excluded during serialization. Defaults to False.

  • default (Any) – Default value for the field. Cannot be used with default_factory.

  • default_factory (Callable[[], Any]) – Callable to generate the default value. Cannot be used with default.

  • init (bool) – Whether the field is included in the generated __init__ method. Defaults to True.

  • repr (bool) – Whether the field appears in the __repr__ output. Defaults to True.

  • hash (bool) – Whether the field is included in the __hash__ method. Defaults to None.

  • compare (bool) – Whether the field is included in comparison methods. Defaults to True.

  • metadata (dict) – Additional metadata for the field. Defaults to None.

  • kw_only (bool) – If True, the field is keyword-only. Defaults to False.

Returns:

A dataclass field with additional mappings to one or more JSON keys.

Return type:

Field

Examples

Example 1 – Mapping multiple key names to a field:

from dataclasses import dataclass

from dataclass_wizard import LoadMeta, fromdict
from dataclass_wizard.v1 import Alias

@dataclass
class Example:
    my_field: str = Alias('key1', 'key2', default="default_value")

LoadMeta(v1=True).bind_to(Example)

print(fromdict(Example, {'key2': 'a value!'}))
#> Example(my_field='a value!')

Example 2 – Skipping a field during serialization:

from dataclasses import dataclass

from dataclass_wizard import JSONPyWizard
from dataclass_wizard.v1 import Alias

@dataclass
class Example(JSONPyWizard):
    class _(JSONPyWizard.Meta):
        v1 = True

    my_field: str = Alias('key', skip=True)

ex = Example.from_dict({'key': 'some value'})
print(ex)                  #> Example(my_field='a value!')
assert ex.to_dict() == {}  #> True
dataclass_wizard.v1.models.AliasPath(*all, load=None, dump=None, skip=False, default=<dataclasses._MISSING_TYPE object>, default_factory=<dataclasses._MISSING_TYPE object>, init=True, repr=True, hash=None, compare=True, metadata=None, kw_only=False)[source]

Creates a dataclass field mapped to one or more nested JSON paths.

This function acts as an alias for dataclasses.field(...), with additional functionality to associate a field with one or more nested JSON paths, including complex or deeply nested structures.

The mapping is case-sensitive, meaning that JSON keys must match exactly (e.g., “myField” will not match “myfield”). Nested paths can include dot notations or bracketed syntax for accessing specific indices or keys.

Parameters:
  • all (PathType | str) – One or more nested JSON paths to associate with the dataclass field (e.g., a.b.c or a["nested"]["key"]).

  • load (PathType | str | None) – Path(s) to use for deserialization. Defaults to all if not specified.

  • dump (PathType | str | None) – Path(s) to use for serialization. Defaults to all if not specified.

  • skip (bool) – If True, the field is excluded during serialization. Defaults to False.

  • default (Any) – Default value for the field. Cannot be used with default_factory.

  • default_factory (Callable[[], Any]) – A callable to generate the default value. Cannot be used with default.

  • init (bool) – Whether the field is included in the generated __init__ method. Defaults to True.

  • repr (bool) – Whether the field appears in the __repr__ output. Defaults to True.

  • hash (bool) – Whether the field is included in the __hash__ method. Defaults to None.

  • compare (bool) – Whether the field is included in comparison methods. Defaults to True.

  • metadata (dict) – Additional metadata for the field. Defaults to None.

  • kw_only (bool) – If True, the field is keyword-only. Defaults to False.

Returns:

A dataclass field with additional mapping to one or more nested JSON paths.

Return type:

Field

Examples

Example 1 – Mapping multiple nested paths to a field:

from dataclasses import dataclass

from dataclass_wizard import fromdict, LoadMeta
from dataclass_wizard.v1 import AliasPath

@dataclass
class Example:
    my_str: str = AliasPath('a.b.c.1', 'x.y["-1"].z', default="default_value")

LoadMeta(v1=True).bind_to(Example)

# Maps nested paths ('a', 'b', 'c', 1) and ('x', 'y', '-1', 'z')
# to the `my_str` attribute. '-1' is treated as a literal string key,
# not an index, for the second path.

print(fromdict(Example, {'x': {'y': {'-1': {'z': 'some_value'}}}}))
#> Example(my_str='some_value')

Example 2 – Using Annotated:

from dataclasses import dataclass
from typing import Annotated

from dataclass_wizard import JSONPyWizard
from dataclass_wizard.v1 import AliasPath

@dataclass
class Example(JSONPyWizard):
    class _(JSONPyWizard.Meta):
        v1 = True

    my_str: Annotated[str, AliasPath('my."7".nested.path.-321')]


ex = Example.from_dict({'my': {'7': {'nested': {'path': {-321: 'Test'}}}}})
print(ex)  #> Example(my_str='Test')
class dataclass_wizard.v1.models.Extras[source]

Bases: TypedDict

“Extra” config that can be used in the load / dump process.

cls: type
cls_name: str
config: Type[TypeVar(META_, bound= AbstractMeta)]
fn_gen: FunctionBuilder
locals: dict[str, Any]
pattern: NotRequired[PatternBase]
recursion_guard: dict[type, str]
class dataclass_wizard.v1.models.Field(load_alias, dump_alias, skip, path, default, default_factory, init, repr, hash, compare, metadata, kw_only)[source]

Bases: Field

Alias to a dataclasses.Field, but one which also represents a mapping of one or more JSON key names to a dataclass field.

See the docs on the Alias() and AliasPath() for more info.

dump_alias
load_alias
path
skip
class dataclass_wizard.v1.models.PatternBase(base, patterns=None, tz_info=None)[source]

Bases: object

base
load_to_pattern(tp, extras)[source]
Parameters:
patterns
tz_info
with_tz(tz_info)[source]
Parameters:

tz_info (tzinfo)

class dataclass_wizard.v1.models.TypeInfo(origin, args=None, name=None, i=1, field_i=1, prefix='v', index=None)[source]

Bases: object

args
static ensure_in_locals(extras, *tps, **name_to_tp)[source]
field_i
i
property in_optional
index
multi_wrap(extras, prefix='', *result, force=False)[source]
name
origin
prefix
replace(**changes)[source]
type_name(extras, bound=None)[source]

Return type name as string (useful for Union type checks)

v()[source]
v_and_next()[source]
v_and_next_k_v()[source]
wrap(result, extras, force=False, prefix='', bound=None)[source]
Parameters:

result (str)

wrap_builtin(bound, result, extras)[source]
wrap_dd(default_factory, result, extras)[source]
Parameters:
  • default_factory (Callable[[], T])

  • result (str)

Module contents

dataclass_wizard.v1.Alias(*all, load=None, dump=None, skip=False, default=<dataclasses._MISSING_TYPE object>, default_factory=<dataclasses._MISSING_TYPE object>, init=True, repr=True, hash=None, compare=True, metadata=None, kw_only=False)[source]

Maps one or more JSON key names to a dataclass field.

This function acts as an alias for dataclasses.field(...), with additional support for associating a field with one or more JSON keys. It customizes serialization and deserialization behavior, including handling keys with varying cases or alternative names.

The mapping is case-sensitive; JSON keys must match exactly (e.g., myField will not match myfield). If multiple keys are provided, the first one is used as the default for serialization.

Parameters:
  • all (str) – One or more JSON key names to associate with the dataclass field.

  • load (str | Sequence[str] | None) – Key(s) to use for deserialization. Defaults to all if not specified.

  • dump (str | None) – Key to use for serialization. Defaults to the first key in all.

  • skip (bool) – If True, the field is excluded during serialization. Defaults to False.

  • default (Any) – Default value for the field. Cannot be used with default_factory.

  • default_factory (Callable[[], Any]) – Callable to generate the default value. Cannot be used with default.

  • init (bool) – Whether the field is included in the generated __init__ method. Defaults to True.

  • repr (bool) – Whether the field appears in the __repr__ output. Defaults to True.

  • hash (bool) – Whether the field is included in the __hash__ method. Defaults to None.

  • compare (bool) – Whether the field is included in comparison methods. Defaults to True.

  • metadata (dict) – Additional metadata for the field. Defaults to None.

  • kw_only (bool) – If True, the field is keyword-only. Defaults to False.

Returns:

A dataclass field with additional mappings to one or more JSON keys.

Return type:

Field

Examples

Example 1 – Mapping multiple key names to a field:

from dataclasses import dataclass

from dataclass_wizard import LoadMeta, fromdict
from dataclass_wizard.v1 import Alias

@dataclass
class Example:
    my_field: str = Alias('key1', 'key2', default="default_value")

LoadMeta(v1=True).bind_to(Example)

print(fromdict(Example, {'key2': 'a value!'}))
#> Example(my_field='a value!')

Example 2 – Skipping a field during serialization:

from dataclasses import dataclass

from dataclass_wizard import JSONPyWizard
from dataclass_wizard.v1 import Alias

@dataclass
class Example(JSONPyWizard):
    class _(JSONPyWizard.Meta):
        v1 = True

    my_field: str = Alias('key', skip=True)

ex = Example.from_dict({'key': 'some value'})
print(ex)                  #> Example(my_field='a value!')
assert ex.to_dict() == {}  #> True
dataclass_wizard.v1.AliasPath(*all, load=None, dump=None, skip=False, default=<dataclasses._MISSING_TYPE object>, default_factory=<dataclasses._MISSING_TYPE object>, init=True, repr=True, hash=None, compare=True, metadata=None, kw_only=False)[source]

Creates a dataclass field mapped to one or more nested JSON paths.

This function acts as an alias for dataclasses.field(...), with additional functionality to associate a field with one or more nested JSON paths, including complex or deeply nested structures.

The mapping is case-sensitive, meaning that JSON keys must match exactly (e.g., “myField” will not match “myfield”). Nested paths can include dot notations or bracketed syntax for accessing specific indices or keys.

Parameters:
  • all (PathType | str) – One or more nested JSON paths to associate with the dataclass field (e.g., a.b.c or a["nested"]["key"]).

  • load (PathType | str | None) – Path(s) to use for deserialization. Defaults to all if not specified.

  • dump (PathType | str | None) – Path(s) to use for serialization. Defaults to all if not specified.

  • skip (bool) – If True, the field is excluded during serialization. Defaults to False.

  • default (Any) – Default value for the field. Cannot be used with default_factory.

  • default_factory (Callable[[], Any]) – A callable to generate the default value. Cannot be used with default.

  • init (bool) – Whether the field is included in the generated __init__ method. Defaults to True.

  • repr (bool) – Whether the field appears in the __repr__ output. Defaults to True.

  • hash (bool) – Whether the field is included in the __hash__ method. Defaults to None.

  • compare (bool) – Whether the field is included in comparison methods. Defaults to True.

  • metadata (dict) – Additional metadata for the field. Defaults to None.

  • kw_only (bool) – If True, the field is keyword-only. Defaults to False.

Returns:

A dataclass field with additional mapping to one or more nested JSON paths.

Return type:

Field

Examples

Example 1 – Mapping multiple nested paths to a field:

from dataclasses import dataclass

from dataclass_wizard import fromdict, LoadMeta
from dataclass_wizard.v1 import AliasPath

@dataclass
class Example:
    my_str: str = AliasPath('a.b.c.1', 'x.y["-1"].z', default="default_value")

LoadMeta(v1=True).bind_to(Example)

# Maps nested paths ('a', 'b', 'c', 1) and ('x', 'y', '-1', 'z')
# to the `my_str` attribute. '-1' is treated as a literal string key,
# not an index, for the second path.

print(fromdict(Example, {'x': {'y': {'-1': {'z': 'some_value'}}}}))
#> Example(my_str='some_value')

Example 2 – Using Annotated:

from dataclasses import dataclass
from typing import Annotated

from dataclass_wizard import JSONPyWizard
from dataclass_wizard.v1 import AliasPath

@dataclass
class Example(JSONPyWizard):
    class _(JSONPyWizard.Meta):
        v1 = True

    my_str: Annotated[str, AliasPath('my."7".nested.path.-321')]


ex = Example.from_dict({'my': {'7': {'nested': {'path': {-321: 'Test'}}}}})
print(ex)  #> Example(my_str='Test')