"""The :class:`Schema` class, including its metaclass and options (class Meta)."""
from __future__ import annotations
import copy
import datetime as dt
import decimal
import inspect
import json
import typing
import uuid
import warnings
from abc import ABCMeta
from collections import OrderedDict, defaultdict
from collections.abc import Mapping
from functools import lru_cache
from marshmallow import base, class_registry, types
from marshmallow import fields as ma_fields
from marshmallow.decorators import (
POST_DUMP,
POST_LOAD,
PRE_DUMP,
PRE_LOAD,
VALIDATES,
VALIDATES_SCHEMA,
)
from marshmallow.error_store import ErrorStore
from marshmallow.exceptions import StringNotCollectionError, ValidationError
from marshmallow.orderedset import OrderedSet
from marshmallow.utils import (
EXCLUDE,
INCLUDE,
RAISE,
get_value,
is_collection,
is_instance_or_subclass,
missing,
set_value,
validate_unknown_parameter_value,
)
from marshmallow.warnings import RemovedInMarshmallow4Warning
_T = typing.TypeVar("_T")
def _get_fields(attrs):
"""Get fields from a class
:param attrs: Mapping of class attributes
"""
return [
(field_name, field_value)
for field_name, field_value in attrs.items()
if is_instance_or_subclass(field_value, base.FieldABC)
]
# This function allows Schemas to inherit from non-Schema classes and ensures
# inheritance according to the MRO
def _get_fields_by_mro(klass):
"""Collect fields from a class, following its method resolution order. The
class itself is excluded from the search; only its parents are checked. Get
fields from ``_declared_fields`` if available, else use ``__dict__``.
:param type klass: Class whose fields to retrieve
"""
mro = inspect.getmro(klass)
# Loop over mro in reverse to maintain correct order of fields
return sum(
(
_get_fields(
getattr(base, "_declared_fields", base.__dict__),
)
for base in mro[:0:-1]
),
[],
)
class SchemaMeta(ABCMeta):
"""Metaclass for the Schema class. Binds the declared fields to
a ``_declared_fields`` attribute, which is a dictionary mapping attribute
names to field objects. Also sets the ``opts`` class attribute, which is
the Schema class's ``class Meta`` options.
"""
def __new__(mcs, name, bases, attrs):
meta = attrs.get("Meta")
ordered = getattr(meta, "ordered", False)
if not ordered:
# Inherit 'ordered' option
# Warning: We loop through bases instead of MRO because we don't
# yet have access to the class object
# (i.e. can't call super before we have fields)
for base_ in bases:
if hasattr(base_, "Meta") and hasattr(base_.Meta, "ordered"):
ordered = base_.Meta.ordered
break
else:
ordered = False
cls_fields = _get_fields(attrs)
# Remove fields from list of class attributes to avoid shadowing
# Schema attributes/methods in case of name conflict
for field_name, _ in cls_fields:
del attrs[field_name]
klass = super().__new__(mcs, name, bases, attrs)
inherited_fields = _get_fields_by_mro(klass)
meta = klass.Meta
# Set klass.opts in __new__ rather than __init__ so that it is accessible in
# get_declared_fields
klass.opts = klass.OPTIONS_CLASS(meta, ordered=ordered)
# Add fields specified in the `include` class Meta option
cls_fields += list(klass.opts.include.items())
# Assign _declared_fields on class
klass._declared_fields = mcs.get_declared_fields(
klass=klass,
cls_fields=cls_fields,
inherited_fields=inherited_fields,
dict_cls=dict,
)
return klass
@classmethod
def get_declared_fields(
mcs,
klass: type,
cls_fields: list,
inherited_fields: list,
dict_cls: type = dict,
):
"""Returns a dictionary of field_name => `Field` pairs declared on the class.
This is exposed mainly so that plugins can add additional fields, e.g. fields
computed from class Meta options.
:param klass: The class object.
:param cls_fields: The fields declared on the class, including those added
by the ``include`` class Meta option.
:param inherited_fields: Inherited fields.
:param dict_cls: dict-like class to use for dict output Default to ``dict``.
"""
return dict_cls(inherited_fields + cls_fields)
def __init__(cls, name, bases, attrs):
super().__init__(name, bases, attrs)
if name and cls.opts.register:
class_registry.register(name, cls)
cls._hooks = cls.resolve_hooks()
def resolve_hooks(cls) -> dict[types.Tag, list[str]]:
"""Add in the decorated processors
By doing this after constructing the class, we let standard inheritance
do all the hard work.
"""
mro = inspect.getmro(cls)
hooks = defaultdict(list) # type: typing.Dict[types.Tag, typing.List[str]]
for attr_name in dir(cls):
# Need to look up the actual descriptor, not whatever might be
# bound to the class. This needs to come from the __dict__ of the
# declaring class.
for parent in mro:
try:
attr = parent.__dict__[attr_name]
except KeyError:
continue
else:
break
else:
# In case we didn't find the attribute and didn't break above.
# We should never hit this - it's just here for completeness
# to exclude the possibility of attr being undefined.
continue
try:
hook_config = attr.__marshmallow_hook__
except AttributeError:
pass
else:
for key in hook_config.keys():
# Use name here so we can get the bound method later, in
# case the processor was a descriptor or something.
hooks[key].append(attr_name)
return hooks
[docs]
class SchemaOpts:
"""class Meta options for the :class:`Schema`. Defines defaults."""
def __init__(self, meta, ordered: bool = False):
self.fields = getattr(meta, "fields", ())
if not isinstance(self.fields, (list, tuple)):
raise ValueError("`fields` option must be a list or tuple.")
self.additional = getattr(meta, "additional", ())
if not isinstance(self.additional, (list, tuple)):
raise ValueError("`additional` option must be a list or tuple.")
if self.fields and self.additional:
raise ValueError(
"Cannot set both `fields` and `additional` options"
" for the same Schema."
)
self.exclude = getattr(meta, "exclude", ())
if not isinstance(self.exclude, (list, tuple)):
raise ValueError("`exclude` must be a list or tuple.")
self.dateformat = getattr(meta, "dateformat", None)
self.datetimeformat = getattr(meta, "datetimeformat", None)
self.timeformat = getattr(meta, "timeformat", None)
if hasattr(meta, "json_module"):
warnings.warn(
"The json_module class Meta option is deprecated. Use render_module instead.",
RemovedInMarshmallow4Warning,
stacklevel=2,
)
render_module = getattr(meta, "json_module", json)
else:
render_module = json
self.render_module = getattr(meta, "render_module", render_module)
self.ordered = getattr(meta, "ordered", ordered)
self.index_errors = getattr(meta, "index_errors", True)
self.include = getattr(meta, "include", {})
self.load_only = getattr(meta, "load_only", ())
self.dump_only = getattr(meta, "dump_only", ())
self.unknown = validate_unknown_parameter_value(getattr(meta, "unknown", RAISE))
self.register = getattr(meta, "register", True)
[docs]
class Schema(base.SchemaABC, metaclass=SchemaMeta):
"""Base schema class with which to define custom schemas.
Example usage:
.. code-block:: python
import datetime as dt
from dataclasses import dataclass
from marshmallow import Schema, fields
@dataclass
class Album:
title: str
release_date: dt.date
class AlbumSchema(Schema):
title = fields.Str()
release_date = fields.Date()
album = Album("Beggars Banquet", dt.date(1968, 12, 6))
schema = AlbumSchema()
data = schema.dump(album)
data # {'release_date': '1968-12-06', 'title': 'Beggars Banquet'}
:param only: Whitelist of the declared fields to select when
instantiating the Schema. If None, all fields are used. Nested fields
can be represented with dot delimiters.
:param exclude: Blacklist of the declared fields to exclude
when instantiating the Schema. If a field appears in both `only` and
`exclude`, it is not used. Nested fields can be represented with dot
delimiters.
:param many: Should be set to `True` if ``obj`` is a collection
so that the object will be serialized to a list.
:param context: Optional context passed to :class:`fields.Method` and
:class:`fields.Function` fields.
:param load_only: Fields to skip during serialization (write-only fields)
:param dump_only: Fields to skip during deserialization (read-only fields)
:param partial: Whether to ignore missing fields and not require
any fields declared. Propagates down to ``Nested`` fields as well. If
its value is an iterable, only missing fields listed in that iterable
will be ignored. Use dot delimiters to specify nested fields.
:param unknown: Whether to exclude, include, or raise an error for unknown
fields in the data. Use `EXCLUDE`, `INCLUDE` or `RAISE`.
.. versionchanged:: 3.0.0
`prefix` parameter removed.
.. versionchanged:: 2.0.0
`__validators__`, `__preprocessors__`, and `__data_handlers__` are removed in favor of
`marshmallow.decorators.validates_schema`,
`marshmallow.decorators.pre_load` and `marshmallow.decorators.post_dump`.
`__accessor__` and `__error_handler__` are deprecated. Implement the
`handle_error` and `get_attribute` methods instead.
"""
TYPE_MAPPING = {
str: ma_fields.String,
bytes: ma_fields.String,
dt.datetime: ma_fields.DateTime,
float: ma_fields.Float,
bool: ma_fields.Boolean,
tuple: ma_fields.Raw,
list: ma_fields.Raw,
set: ma_fields.Raw,
int: ma_fields.Integer,
uuid.UUID: ma_fields.UUID,
dt.time: ma_fields.Time,
dt.date: ma_fields.Date,
dt.timedelta: ma_fields.TimeDelta,
decimal.Decimal: ma_fields.Decimal,
} # type: typing.Dict[type, typing.Type[ma_fields.Field]]
#: Overrides for default schema-level error messages
error_messages = {} # type: typing.Dict[str, str]
_default_error_messages = {
"type": "Invalid input type.",
"unknown": "Unknown field.",
} # type: typing.Dict[str, str]
OPTIONS_CLASS = SchemaOpts # type: type
set_class = OrderedSet
# These get set by SchemaMeta
opts = None # type: SchemaOpts
_declared_fields = {} # type: typing.Dict[str, ma_fields.Field]
_hooks = {} # type: typing.Dict[types.Tag, typing.List[str]]
def __init__(
self,
*,
only: types.StrSequenceOrSet | None = None,
exclude: types.StrSequenceOrSet = (),
many: bool = False,
context: dict | None = None,
load_only: types.StrSequenceOrSet = (),
dump_only: types.StrSequenceOrSet = (),
partial: bool | types.StrSequenceOrSet | None = None,
unknown: str | None = None,
):
# Raise error if only or exclude is passed as string, not list of strings
if only is not None and not is_collection(only):
raise StringNotCollectionError('"only" should be a list of strings')
if not is_collection(exclude):
raise StringNotCollectionError('"exclude" should be a list of strings')
# copy declared fields from metaclass
self.declared_fields = copy.deepcopy(self._declared_fields)
self.many = many
self.only = only
self.exclude: set[typing.Any] | typing.MutableSet[typing.Any] = set(
self.opts.exclude
) | set(exclude)
self.ordered = self.opts.ordered
self.load_only = set(load_only) or set(self.opts.load_only)
self.dump_only = set(dump_only) or set(self.opts.dump_only)
self.partial = partial
self.unknown = (
self.opts.unknown
if unknown is None
else validate_unknown_parameter_value(unknown)
)
self.context = context or {}
self._normalize_nested_options()
#: Dictionary mapping field_names -> :class:`Field` objects
self.fields = {} # type: typing.Dict[str, ma_fields.Field]
self.load_fields = {} # type: typing.Dict[str, ma_fields.Field]
self.dump_fields = {} # type: typing.Dict[str, ma_fields.Field]
self._init_fields()
messages = {}
messages.update(self._default_error_messages)
for cls in reversed(self.__class__.__mro__):
messages.update(getattr(cls, "error_messages", {}))
messages.update(self.error_messages or {})
self.error_messages = messages
def __repr__(self) -> str:
return f"<{self.__class__.__name__}(many={self.many})>"
@property
def dict_class(self) -> type:
return OrderedDict if self.ordered else dict
[docs]
@classmethod
def from_dict(
cls,
fields: dict[str, ma_fields.Field | type],
*,
name: str = "GeneratedSchema",
) -> type:
"""Generate a `Schema` class given a dictionary of fields.
.. code-block:: python
from marshmallow import Schema, fields
PersonSchema = Schema.from_dict({"name": fields.Str()})
print(PersonSchema().load({"name": "David"})) # => {'name': 'David'}
Generated schemas are not added to the class registry and therefore cannot
be referred to by name in `Nested` fields.
:param dict fields: Dictionary mapping field names to field instances.
:param str name: Optional name for the class, which will appear in
the ``repr`` for the class.
.. versionadded:: 3.0.0
"""
attrs = fields.copy()
attrs["Meta"] = type(
"GeneratedMeta", (getattr(cls, "Meta", object),), {"register": False}
)
schema_cls = type(name, (cls,), attrs)
return schema_cls
##### Override-able methods #####
[docs]
def handle_error(
self, error: ValidationError, data: typing.Any, *, many: bool, **kwargs
):
"""Custom error handler function for the schema.
:param error: The `ValidationError` raised during (de)serialization.
:param data: The original input data.
:param many: Value of ``many`` on dump or load.
:param partial: Value of ``partial`` on load.
.. versionadded:: 2.0.0
.. versionchanged:: 3.0.0rc9
Receives `many` and `partial` (on deserialization) as keyword arguments.
"""
pass
[docs]
def get_attribute(self, obj: typing.Any, attr: str, default: typing.Any):
"""Defines how to pull values from an object to serialize.
.. versionadded:: 2.0.0
.. versionchanged:: 3.0.0a1
Changed position of ``obj`` and ``attr``.
"""
return get_value(obj, attr, default)
##### Serialization/Deserialization API #####
@staticmethod
def _call_and_store(getter_func, data, *, field_name, error_store, index=None):
"""Call ``getter_func`` with ``data`` as its argument, and store any `ValidationErrors`.
:param callable getter_func: Function for getting the serialized/deserialized
value from ``data``.
:param data: The data passed to ``getter_func``.
:param str field_name: Field name.
:param int index: Index of the item being validated, if validating a collection,
otherwise `None`.
"""
try:
value = getter_func(data)
except ValidationError as error:
error_store.store_error(error.messages, field_name, index=index)
# When a Nested field fails validation, the marshalled data is stored
# on the ValidationError's valid_data attribute
return error.valid_data or missing
return value
def _serialize(self, obj: _T | typing.Iterable[_T], *, many: bool = False):
"""Serialize ``obj``.
:param obj: The object(s) to serialize.
:param bool many: `True` if ``data`` should be serialized as a collection.
:return: A dictionary of the serialized data
.. versionchanged:: 1.0.0
Renamed from ``marshal``.
"""
if many and obj is not None:
return [
self._serialize(d, many=False)
for d in typing.cast(typing.Iterable[_T], obj)
]
ret = self.dict_class()
for attr_name, field_obj in self.dump_fields.items():
value = field_obj.serialize(attr_name, obj, accessor=self.get_attribute)
if value is missing:
continue
key = field_obj.data_key if field_obj.data_key is not None else attr_name
ret[key] = value
return ret
[docs]
def dump(self, obj: typing.Any, *, many: bool | None = None):
"""Serialize an object to native Python data types according to this
Schema's fields.
:param obj: The object to serialize.
:param many: Whether to serialize `obj` as a collection. If `None`, the value
for `self.many` is used.
:return: Serialized data
.. versionadded:: 1.0.0
.. versionchanged:: 3.0.0b7
This method returns the serialized data rather than a ``(data, errors)`` duple.
A :exc:`ValidationError <marshmallow.exceptions.ValidationError>` is raised
if ``obj`` is invalid.
.. versionchanged:: 3.0.0rc9
Validation no longer occurs upon serialization.
"""
many = self.many if many is None else bool(many)
if self._has_processors(PRE_DUMP):
processed_obj = self._invoke_dump_processors(
PRE_DUMP, obj, many=many, original_data=obj
)
else:
processed_obj = obj
result = self._serialize(processed_obj, many=many)
if self._has_processors(POST_DUMP):
result = self._invoke_dump_processors(
POST_DUMP, result, many=many, original_data=obj
)
return result
[docs]
def dumps(self, obj: typing.Any, *args, many: bool | None = None, **kwargs):
"""Same as :meth:`dump`, except return a JSON-encoded string.
:param obj: The object to serialize.
:param many: Whether to serialize `obj` as a collection. If `None`, the value
for `self.many` is used.
:return: A ``json`` string
.. versionadded:: 1.0.0
.. versionchanged:: 3.0.0b7
This method returns the serialized data rather than a ``(data, errors)`` duple.
A :exc:`ValidationError <marshmallow.exceptions.ValidationError>` is raised
if ``obj`` is invalid.
"""
serialized = self.dump(obj, many=many)
return self.opts.render_module.dumps(serialized, *args, **kwargs)
def _deserialize(
self,
data: (
typing.Mapping[str, typing.Any]
| typing.Iterable[typing.Mapping[str, typing.Any]]
),
*,
error_store: ErrorStore,
many: bool = False,
partial=None,
unknown=RAISE,
index=None,
) -> _T | list[_T]:
"""Deserialize ``data``.
:param dict data: The data to deserialize.
:param ErrorStore error_store: Structure to store errors.
:param bool many: `True` if ``data`` should be deserialized as a collection.
:param bool|tuple partial: Whether to ignore missing fields and not require
any fields declared. Propagates down to ``Nested`` fields as well. If
its value is an iterable, only missing fields listed in that iterable
will be ignored. Use dot delimiters to specify nested fields.
:param unknown: Whether to exclude, include, or raise an error for unknown
fields in the data. Use `EXCLUDE`, `INCLUDE` or `RAISE`.
:param int index: Index of the item being serialized (for storing errors) if
serializing a collection, otherwise `None`.
:return: A dictionary of the deserialized data.
"""
index_errors = self.opts.index_errors
index = index if index_errors else None
if many:
if not is_collection(data):
error_store.store_error([self.error_messages["type"]], index=index)
ret_l = [] # type: typing.List[_T]
else:
ret_l = [
typing.cast(
_T,
self._deserialize(
typing.cast(typing.Mapping[str, typing.Any], d),
error_store=error_store,
many=False,
partial=partial,
unknown=unknown,
index=idx,
),
)
for idx, d in enumerate(data)
]
return ret_l
ret_d = self.dict_class()
# Check data is a dict
if not isinstance(data, Mapping):
error_store.store_error([self.error_messages["type"]], index=index)
else:
partial_is_collection = is_collection(partial)
for attr_name, field_obj in self.load_fields.items():
field_name = (
field_obj.data_key if field_obj.data_key is not None else attr_name
)
raw_value = data.get(field_name, missing)
if raw_value is missing:
# Ignore missing field if we're allowed to.
if partial is True or (
partial_is_collection and attr_name in partial
):
continue
d_kwargs = {}
# Allow partial loading of nested schemas.
if partial_is_collection:
prefix = field_name + "."
len_prefix = len(prefix)
sub_partial = [
f[len_prefix:] for f in partial if f.startswith(prefix)
]
d_kwargs["partial"] = sub_partial
elif partial is not None:
d_kwargs["partial"] = partial
def getter(
val, field_obj=field_obj, field_name=field_name, d_kwargs=d_kwargs
):
return field_obj.deserialize(
val,
field_name,
data,
**d_kwargs,
)
value = self._call_and_store(
getter_func=getter,
data=raw_value,
field_name=field_name,
error_store=error_store,
index=index,
)
if value is not missing:
key = field_obj.attribute or attr_name
set_value(ret_d, key, value)
if unknown != EXCLUDE:
fields = {
field_obj.data_key if field_obj.data_key is not None else field_name
for field_name, field_obj in self.load_fields.items()
}
for key in set(data) - fields:
value = data[key]
if unknown == INCLUDE:
ret_d[key] = value
elif unknown == RAISE:
error_store.store_error(
[self.error_messages["unknown"]],
key,
(index if index_errors else None),
)
return ret_d
[docs]
def load(
self,
data: (
typing.Mapping[str, typing.Any]
| typing.Iterable[typing.Mapping[str, typing.Any]]
),
*,
many: bool | None = None,
partial: bool | types.StrSequenceOrSet | None = None,
unknown: str | None = None,
):
"""Deserialize a data structure to an object defined by this Schema's fields.
:param data: The data to deserialize.
:param many: Whether to deserialize `data` as a collection. If `None`, the
value for `self.many` is used.
:param partial: Whether to ignore missing fields and not require
any fields declared. Propagates down to ``Nested`` fields as well. If
its value is an iterable, only missing fields listed in that iterable
will be ignored. Use dot delimiters to specify nested fields.
:param unknown: Whether to exclude, include, or raise an error for unknown
fields in the data. Use `EXCLUDE`, `INCLUDE` or `RAISE`.
If `None`, the value for `self.unknown` is used.
:return: Deserialized data
.. versionadded:: 1.0.0
.. versionchanged:: 3.0.0b7
This method returns the deserialized data rather than a ``(data, errors)`` duple.
A :exc:`ValidationError <marshmallow.exceptions.ValidationError>` is raised
if invalid data are passed.
"""
return self._do_load(
data, many=many, partial=partial, unknown=unknown, postprocess=True
)
[docs]
def loads(
self,
json_data: str,
*,
many: bool | None = None,
partial: bool | types.StrSequenceOrSet | None = None,
unknown: str | None = None,
**kwargs,
):
"""Same as :meth:`load`, except it takes a JSON string as input.
:param json_data: A JSON string of the data to deserialize.
:param many: Whether to deserialize `obj` as a collection. If `None`, the
value for `self.many` is used.
:param partial: Whether to ignore missing fields and not require
any fields declared. Propagates down to ``Nested`` fields as well. If
its value is an iterable, only missing fields listed in that iterable
will be ignored. Use dot delimiters to specify nested fields.
:param unknown: Whether to exclude, include, or raise an error for unknown
fields in the data. Use `EXCLUDE`, `INCLUDE` or `RAISE`.
If `None`, the value for `self.unknown` is used.
:return: Deserialized data
.. versionadded:: 1.0.0
.. versionchanged:: 3.0.0b7
This method returns the deserialized data rather than a ``(data, errors)`` duple.
A :exc:`ValidationError <marshmallow.exceptions.ValidationError>` is raised
if invalid data are passed.
"""
data = self.opts.render_module.loads(json_data, **kwargs)
return self.load(data, many=many, partial=partial, unknown=unknown)
def _run_validator(
self,
validator_func,
output,
*,
original_data,
error_store,
many,
partial,
pass_original,
index=None,
):
try:
if pass_original: # Pass original, raw data (before unmarshalling)
validator_func(output, original_data, partial=partial, many=many)
else:
validator_func(output, partial=partial, many=many)
except ValidationError as err:
error_store.store_error(err.messages, err.field_name, index=index)
[docs]
def validate(
self,
data: (
typing.Mapping[str, typing.Any]
| typing.Iterable[typing.Mapping[str, typing.Any]]
),
*,
many: bool | None = None,
partial: bool | types.StrSequenceOrSet | None = None,
) -> dict[str, list[str]]:
"""Validate `data` against the schema, returning a dictionary of
validation errors.
:param data: The data to validate.
:param many: Whether to validate `data` as a collection. If `None`, the
value for `self.many` is used.
:param partial: Whether to ignore missing fields and not require
any fields declared. Propagates down to ``Nested`` fields as well. If
its value is an iterable, only missing fields listed in that iterable
will be ignored. Use dot delimiters to specify nested fields.
:return: A dictionary of validation errors.
.. versionadded:: 1.1.0
"""
try:
self._do_load(data, many=many, partial=partial, postprocess=False)
except ValidationError as exc:
return typing.cast(typing.Dict[str, typing.List[str]], exc.messages)
return {}
##### Private Helpers #####
def _do_load(
self,
data: (
typing.Mapping[str, typing.Any]
| typing.Iterable[typing.Mapping[str, typing.Any]]
),
*,
many: bool | None = None,
partial: bool | types.StrSequenceOrSet | None = None,
unknown: str | None = None,
postprocess: bool = True,
):
"""Deserialize `data`, returning the deserialized result.
This method is private API.
:param data: The data to deserialize.
:param many: Whether to deserialize `data` as a collection. If `None`, the
value for `self.many` is used.
:param partial: Whether to validate required fields. If its
value is an iterable, only fields listed in that iterable will be
ignored will be allowed missing. If `True`, all fields will be allowed missing.
If `None`, the value for `self.partial` is used.
:param unknown: Whether to exclude, include, or raise an error for unknown
fields in the data. Use `EXCLUDE`, `INCLUDE` or `RAISE`.
If `None`, the value for `self.unknown` is used.
:param postprocess: Whether to run post_load methods..
:return: Deserialized data
"""
error_store = ErrorStore()
errors = {} # type: dict[str, list[str]]
many = self.many if many is None else bool(many)
unknown = (
self.unknown
if unknown is None
else validate_unknown_parameter_value(unknown)
)
if partial is None:
partial = self.partial
# Run preprocessors
if self._has_processors(PRE_LOAD):
try:
processed_data = self._invoke_load_processors(
PRE_LOAD, data, many=many, original_data=data, partial=partial
)
except ValidationError as err:
errors = err.normalized_messages()
result = None # type: list | dict | None
else:
processed_data = data
if not errors:
# Deserialize data
result = self._deserialize(
processed_data,
error_store=error_store,
many=many,
partial=partial,
unknown=unknown,
)
# Run field-level validation
self._invoke_field_validators(
error_store=error_store, data=result, many=many
)
# Run schema-level validation
if self._has_processors(VALIDATES_SCHEMA):
field_errors = bool(error_store.errors)
self._invoke_schema_validators(
error_store=error_store,
pass_many=True,
data=result,
original_data=data,
many=many,
partial=partial,
field_errors=field_errors,
)
self._invoke_schema_validators(
error_store=error_store,
pass_many=False,
data=result,
original_data=data,
many=many,
partial=partial,
field_errors=field_errors,
)
errors = error_store.errors
# Run post processors
if not errors and postprocess and self._has_processors(POST_LOAD):
try:
result = self._invoke_load_processors(
POST_LOAD,
result,
many=many,
original_data=data,
partial=partial,
)
except ValidationError as err:
errors = err.normalized_messages()
if errors:
exc = ValidationError(errors, data=data, valid_data=result)
self.handle_error(exc, data, many=many, partial=partial)
raise exc
return result
def _normalize_nested_options(self) -> None:
"""Apply then flatten nested schema options.
This method is private API.
"""
if self.only is not None:
# Apply the only option to nested fields.
self.__apply_nested_option("only", self.only, "intersection")
# Remove the child field names from the only option.
self.only = self.set_class([field.split(".", 1)[0] for field in self.only])
if self.exclude:
# Apply the exclude option to nested fields.
self.__apply_nested_option("exclude", self.exclude, "union")
# Remove the parent field names from the exclude option.
self.exclude = self.set_class(
[field for field in self.exclude if "." not in field]
)
def __apply_nested_option(self, option_name, field_names, set_operation) -> None:
"""Apply nested options to nested fields"""
# Split nested field names on the first dot.
nested_fields = [name.split(".", 1) for name in field_names if "." in name]
# Partition the nested field names by parent field.
nested_options = defaultdict(list) # type: defaultdict
for parent, nested_names in nested_fields:
nested_options[parent].append(nested_names)
# Apply the nested field options.
for key, options in iter(nested_options.items()):
new_options = self.set_class(options)
original_options = getattr(self.declared_fields[key], option_name, ())
if original_options:
if set_operation == "union":
new_options |= self.set_class(original_options)
if set_operation == "intersection":
new_options &= self.set_class(original_options)
setattr(self.declared_fields[key], option_name, new_options)
def _init_fields(self) -> None:
"""Update self.fields, self.load_fields, and self.dump_fields based on schema options.
This method is private API.
"""
if self.opts.fields:
available_field_names = self.set_class(self.opts.fields)
else:
available_field_names = self.set_class(self.declared_fields.keys())
if self.opts.additional:
available_field_names |= self.set_class(self.opts.additional)
invalid_fields = self.set_class()
if self.only is not None:
# Return only fields specified in only option
field_names: typing.AbstractSet[typing.Any] = self.set_class(self.only)
invalid_fields |= field_names - available_field_names
else:
field_names = available_field_names
# If "exclude" option or param is specified, remove those fields.
if self.exclude:
# Note that this isn't available_field_names, since we want to
# apply "only" for the actual calculation.
field_names = field_names - self.exclude
invalid_fields |= self.exclude - available_field_names
if invalid_fields:
message = f"Invalid fields for {self}: {invalid_fields}."
raise ValueError(message)
fields_dict = self.dict_class()
for field_name in field_names:
field_obj = self.declared_fields.get(field_name, ma_fields.Inferred())
self._bind_field(field_name, field_obj)
fields_dict[field_name] = field_obj
load_fields, dump_fields = self.dict_class(), self.dict_class()
for field_name, field_obj in fields_dict.items():
if not field_obj.dump_only:
load_fields[field_name] = field_obj
if not field_obj.load_only:
dump_fields[field_name] = field_obj
dump_data_keys = [
field_obj.data_key if field_obj.data_key is not None else name
for name, field_obj in dump_fields.items()
]
if len(dump_data_keys) != len(set(dump_data_keys)):
data_keys_duplicates = {
x for x in dump_data_keys if dump_data_keys.count(x) > 1
}
raise ValueError(
"The data_key argument for one or more fields collides "
"with another field's name or data_key argument. "
"Check the following field names and "
f"data_key arguments: {list(data_keys_duplicates)}"
)
load_attributes = [obj.attribute or name for name, obj in load_fields.items()]
if len(load_attributes) != len(set(load_attributes)):
attributes_duplicates = {
x for x in load_attributes if load_attributes.count(x) > 1
}
raise ValueError(
"The attribute argument for one or more fields collides "
"with another field's name or attribute argument. "
"Check the following field names and "
f"attribute arguments: {list(attributes_duplicates)}"
)
self.fields = fields_dict
self.dump_fields = dump_fields
self.load_fields = load_fields
[docs]
def on_bind_field(self, field_name: str, field_obj: ma_fields.Field) -> None:
"""Hook to modify a field when it is bound to the `Schema`.
No-op by default.
"""
return None
def _bind_field(self, field_name: str, field_obj: ma_fields.Field) -> None:
"""Bind field to the schema, setting any necessary attributes on the
field (e.g. parent and name).
Also set field load_only and dump_only values if field_name was
specified in ``class Meta``.
"""
if field_name in self.load_only:
field_obj.load_only = True
if field_name in self.dump_only:
field_obj.dump_only = True
try:
field_obj._bind_to_schema(field_name, self)
except TypeError as error:
# Field declared as a class, not an instance. Ignore type checking because
# we handle unsupported arg types, i.e. this is dead code from
# the type checker's perspective.
if isinstance(field_obj, type) and issubclass(field_obj, base.FieldABC):
msg = (
f'Field for "{field_name}" must be declared as a '
"Field instance, not a class. "
f'Did you mean "fields.{field_obj.__name__}()"?' # type: ignore
)
raise TypeError(msg) from error
raise error
self.on_bind_field(field_name, field_obj)
@lru_cache(maxsize=8) # noqa (https://github.com/PyCQA/flake8-bugbear/issues/310)
def _has_processors(self, tag) -> bool:
return bool(self._hooks[(tag, True)] or self._hooks[(tag, False)])
def _invoke_dump_processors(
self, tag: str, data, *, many: bool, original_data=None
):
# The pass_many post-dump processors may do things like add an envelope, so
# invoke those after invoking the non-pass_many processors which will expect
# to get a list of items.
data = self._invoke_processors(
tag, pass_many=False, data=data, many=many, original_data=original_data
)
data = self._invoke_processors(
tag, pass_many=True, data=data, many=many, original_data=original_data
)
return data
def _invoke_load_processors(
self,
tag: str,
data,
*,
many: bool,
original_data,
partial: bool | types.StrSequenceOrSet | None,
):
# This has to invert the order of the dump processors, so run the pass_many
# processors first.
data = self._invoke_processors(
tag,
pass_many=True,
data=data,
many=many,
original_data=original_data,
partial=partial,
)
data = self._invoke_processors(
tag,
pass_many=False,
data=data,
many=many,
original_data=original_data,
partial=partial,
)
return data
def _invoke_field_validators(self, *, error_store: ErrorStore, data, many: bool):
for attr_name in self._hooks[VALIDATES]:
validator = getattr(self, attr_name)
validator_kwargs = validator.__marshmallow_hook__[VALIDATES]
field_name = validator_kwargs["field_name"]
try:
field_obj = self.fields[field_name]
except KeyError as error:
if field_name in self.declared_fields:
continue
raise ValueError(f'"{field_name}" field does not exist.') from error
data_key = (
field_obj.data_key if field_obj.data_key is not None else field_name
)
if many:
for idx, item in enumerate(data):
try:
value = item[field_obj.attribute or field_name]
except KeyError:
pass
else:
validated_value = self._call_and_store(
getter_func=validator,
data=value,
field_name=data_key,
error_store=error_store,
index=(idx if self.opts.index_errors else None),
)
if validated_value is missing:
data[idx].pop(field_name, None)
else:
try:
value = data[field_obj.attribute or field_name]
except KeyError:
pass
else:
validated_value = self._call_and_store(
getter_func=validator,
data=value,
field_name=data_key,
error_store=error_store,
)
if validated_value is missing:
data.pop(field_name, None)
def _invoke_schema_validators(
self,
*,
error_store: ErrorStore,
pass_many: bool,
data,
original_data,
many: bool,
partial: bool | types.StrSequenceOrSet | None,
field_errors: bool = False,
):
for attr_name in self._hooks[(VALIDATES_SCHEMA, pass_many)]:
validator = getattr(self, attr_name)
validator_kwargs = validator.__marshmallow_hook__[
(VALIDATES_SCHEMA, pass_many)
]
if field_errors and validator_kwargs["skip_on_field_errors"]:
continue
pass_original = validator_kwargs.get("pass_original", False)
if many and not pass_many:
for idx, (item, orig) in enumerate(zip(data, original_data)):
self._run_validator(
validator,
item,
original_data=orig,
error_store=error_store,
many=many,
partial=partial,
index=idx,
pass_original=pass_original,
)
else:
self._run_validator(
validator,
data,
original_data=original_data,
error_store=error_store,
many=many,
pass_original=pass_original,
partial=partial,
)
def _invoke_processors(
self,
tag: str,
*,
pass_many: bool,
data,
many: bool,
original_data=None,
**kwargs,
):
key = (tag, pass_many)
for attr_name in self._hooks[key]:
# This will be a bound method.
processor = getattr(self, attr_name)
processor_kwargs = processor.__marshmallow_hook__[key]
pass_original = processor_kwargs.get("pass_original", False)
if many and not pass_many:
if pass_original:
data = [
processor(item, original, many=many, **kwargs)
for item, original in zip(data, original_data)
]
else:
data = [processor(item, many=many, **kwargs) for item in data]
else:
if pass_original:
data = processor(data, original_data, many=many, **kwargs)
else:
data = processor(data, many=many, **kwargs)
return data
BaseSchema = Schema # for backwards compatibility
