marshmallow-recipe 0.0.83

Bake marshmallow schemas based on dataclasses

marshmallow-recipe

Library for convenient serialization/deserialization of Python dataclasses using marshmallow.

Originally developed as an abstraction layer over marshmallow to facilitate migration from v2 to v3 for codebases with extensive dataclass usage, this library has evolved into a powerful tool offering a more concise approach to serialization. It can be seamlessly integrated into any codebase, providing the following benefits:

1. Automatic schema generation: Marshmallow schemas are generated and cached automatically, while still being accessible when needed
2. Comprehensive Generics support with full nesting and inheritance capabilities
3. Nested cyclic references support
4. Flexible field configuration through dataclass.field(meta) or Annotated[T, meta]
5. Customizable case formatting support, including built-in camelCase and CamelCase, via dataclass decorators
6. Configurable None value handling through dataclass decorators
7. PATCH operation support via mr.MISSING value

Supported Types

Simple types: str, bool, int, float, decimal.Decimal, datetime.datetime, datetime.date, datetime.time, uuid.UUID, enum.StrEnum, enum.IntEnum, typing.Any

Collections: list[T], set[T], frozenset[T], tuple[T, ...], dict[K, V], Sequence[T], Set[T], Mapping[K, V]

Advanced: T | None, Optional[T], Generic[T], Annotated[T, ...], NewType('Name', T)

Features: Nested dataclasses, cyclic references, generics with full inheritance

Examples

Base scenario

import dataclasses
import datetime
import uuid

import marshmallow_recipe as mr

@dataclasses.dataclass(frozen=True)
class Entity:
    id: uuid.UUID
    created_at: datetime.datetime
    comment: str | None

entity = Entity(
    id=uuid.uuid4(),
    created_at=datetime.datetime.now(tz=datetime.UTC),
    comment=None,
 )

# dumps the dataclass instance to a dict
serialized = mr.dump(entity) 

# deserializes a dict to the dataclass instance
loaded = mr.load(Entity, serialized)

assert loaded == entity

# provides a generated marshmallow schema for the dataclass
marshmallow_schema = mr.schema(Entity)

Configuration

import dataclasses
import datetime
import decimal

import marshmallow_recipe as mr

from typing import Annotated


@dataclasses.dataclass(frozen=True)
class ConfiguredFields:
    with_custom_name: str = dataclasses.field(metadata=mr.meta(name="alias"))
    strip_whitespaces: str = dataclasses.field(metadata=mr.str_meta(strip_whitespaces=True))
    with_post_load: str = dataclasses.field(metadata=mr.str_meta(post_load=lambda x: x.replace("-", "")))
    with_validation: decimal.Decimal = dataclasses.field(metadata=mr.meta(validate=lambda x: x != 0))
    decimal_two_places_by_default: decimal.Decimal  # Note: 2 decimal places by default
    decimal_any_places: decimal.Decimal = dataclasses.field(metadata=mr.decimal_metadata(places=None))
    decimal_three_places: decimal.Decimal = dataclasses.field(metadata=mr.decimal_metadata(places=3))
    decimal_with_rounding: decimal.Decimal = dataclasses.field(metadata=mr.decimal_metadata(places=2, rounding=decimal.ROUND_UP))
    nullable_with_custom_format: datetime.date | None = dataclasses.field(metadata=mr.datetime_meta(format="%Y%m%d"), default=None)
    with_default_factory: str = dataclasses.field(default_factory=lambda: "42")


@dataclasses.dataclass(frozen=True)
class AnnotatedFields:
    with_post_load: Annotated[str, mr.str_meta(post_load=lambda x: x.replace("-", ""))]
    decimal_three_places: Annotated[decimal.Decimal, mr.decimal_metadata(places=3)]


@dataclasses.dataclass(frozen=True)
class AnnotatedListItem:
    nullable_value: list[Annotated[str, mr.str_meta(strip_whitespaces=True)]] | None
    value_with_nullable_item: list[Annotated[str | None, mr.str_meta(strip_whitespaces=True)]]


@dataclasses.dataclass(frozen=True)
@mr.options(none_value_handling=mr.NoneValueHandling.INCLUDE)
class NoneValueFieldIncluded:
    nullable_value: str | None

    
@dataclasses.dataclass(frozen=True)
@mr.options(none_value_handling=mr.NoneValueHandling.IGNORE)
class NoneValueFieldExcluded:
    nullable_value: str | None

    
@dataclasses.dataclass(frozen=True)
@mr.options(naming_case=mr.CAPITAL_CAMEL_CASE)
class UpperCamelCaseExcluded:
    naming_case_applied: str  # serialized to `NamingCaseApplied`
    naming_case_ignored: str = dataclasses.field(metadata=mr.meta(name="alias"))  # serialized to `alias`

    
@dataclasses.dataclass(frozen=True)
@mr.options(naming_case=mr.CAMEL_CASE)
class LowerCamelCaseExcluded:
    naming_case_applied: str  # serialized to `namingCaseApplied`


@dataclasses.dataclass(frozen=True, slots=True, kw_only=True)
class DataClass:
    str_field: str

data = dict(StrField="foobar")
loaded = mr.load(DataClass, data, naming_case=mr.CAPITAL_CAMEL_CASE)
dumped = mr.dump(loaded, naming_case=mr.CAPITAL_CAMEL_CASE)

Update API

import decimal
import dataclasses

import marshmallow_recipe as mr

@dataclasses.dataclass(frozen=True)
@mr.options(none_value_handling=mr.NoneValueHandling.INCLUDE)
class CompanyUpdateData:
    name: str = mr.MISSING
    annual_turnover: decimal.Decimal | None = mr.MISSING

company_update_data = CompanyUpdateData(name="updated name")
dumped = mr.dump(company_update_data)
assert dumped == {"name": "updated name"}  # Note: no "annual_turnover" here

loaded = mr.load(CompanyUpdateData, {"name": "updated name"})
assert loaded.name == "updated name"
assert loaded.annual_turnover is mr.MISSING

loaded = mr.load(CompanyUpdateData, {"annual_turnover": None})
assert loaded.name is mr.MISSING
assert loaded.annual_turnover is None

Generics

Everything works automatically, except for one case. Dump operation of a generic dataclass with frozen=True or/and slots=True requires an explicitly specified subscripted generic type as first cls argument of dump and dump_many methods.

import dataclasses
from typing import Generic, TypeVar

import marshmallow_recipe as mr

T = TypeVar("T")


@dataclasses.dataclass()
class RegularGeneric(Generic[T]):
    value: T

mr.dump(RegularGeneric[int](value=123))  # it works without explicit cls specification


@dataclasses.dataclass(slots=True)
class SlotsGeneric(Generic[T]):
    value: T

mr.dump(SlotsGeneric[int], SlotsGeneric[int](value=123))  # cls required for slots=True generic

@dataclasses.dataclass(frozen=True)
class FrozenGeneric(Generic[T]):
    value: T

mr.dump(FrozenGeneric[int], FrozenGeneric[int](value=123))  # cls required for frozen=True generic


@dataclasses.dataclass(slots=True, frozen=True)
class SlotsFrozenNonGeneric(FrozenGeneric[int]):
    pass

mr.dump(SlotsFrozenNonGeneric(value=123))  # cls not required for non-generic

More Examples

The examples/ directory contains comprehensive examples covering all library features:

• 01_basic_usage.md - Basic types, load/dump, schema, NewType
• 02_nested_and_collections.md - Nested dataclasses, collections, collections.abc types
• 03_field_customization.md - Custom field names, string transforms, decimal precision, datetime formats
• 04_validation.md - Field validation, regex, mr.validate(), collection item validation
• 05_naming_case_conversion.md - camelCase, PascalCase, UPPER_SNAKE_CASE conversion
• 06_patch_operations.md - PATCH operations with mr.MISSING
• 07_generics.md - Generic[T] types
• 08_global_overrides.md - Runtime parameter overrides (naming_case, none_value_handling, decimal_places)
• 09_per_dataclass_overrides.md - Per-dataclass overrides with @mr.options decorator
• 10_cyclic_references.md - Cyclic and self-referencing structures
• 11_pre_load_hooks.md - @mr.pre_load hooks, add_pre_load()
• 12_validation_errors.md - get_validation_field_errors(), error handling