# -*- coding: utf-8 -*-
"""The :class:`Schema` class, including its metaclass and options (class Meta)."""
from __future__ import absolute_import, unicode_literals
from collections import defaultdict, Mapping
import copy
import datetime as dt
import decimal
import inspect
import json
import uuid
import warnings
from collections import namedtuple
import functools
from marshmallow import base, fields, utils, class_registry, marshalling
from marshmallow.compat import (with_metaclass, iteritems, text_type,
binary_type, OrderedDict)
from marshmallow.exceptions import ValidationError
from marshmallow.orderedset import OrderedSet
from marshmallow.decorators import (PRE_DUMP, POST_DUMP, PRE_LOAD, POST_LOAD,
VALIDATES, VALIDATES_SCHEMA)
#: Return type of :meth:`Schema.dump` including serialized data and errors
MarshalResult = namedtuple('MarshalResult', ['data', 'errors'])
#: Return type of :meth:`Schema.load`, including deserialized data and errors
UnmarshalResult = namedtuple('UnmarshalResult', ['data', 'errors'])
def _get_fields(attrs, field_class, pop=False, ordered=False):
"""Get fields from a class. If ordered=True, fields will sorted by creation index.
:param attrs: Mapping of class attributes
:param type field_class: Base field class
:param bool pop: Remove matching fields
"""
getter = getattr(attrs, 'pop' if pop else 'get')
fields = [
(field_name, getter(field_name))
for field_name, field_value in list(iteritems(attrs))
if utils.is_instance_or_subclass(field_value, field_class)
]
if ordered:
return sorted(
fields,
key=lambda pair: pair[1]._creation_index,
)
else:
return fields
# This function allows Schemas to inherit from non-Schema classes and ensures
# inheritance according to the MRO
def _get_fields_by_mro(klass, field_class, ordered=False):
"""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
:param type field_class: Base field class
"""
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__),
field_class,
ordered=ordered
)
for base in mro[:0:-1]
),
[],
)
class SchemaMeta(type):
"""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, base.FieldABC, pop=True, ordered=ordered)
klass = super(SchemaMeta, mcs).__new__(mcs, name, bases, attrs)
inherited_fields = _get_fields_by_mro(klass, base.FieldABC)
# Use getattr rather than attrs['Meta'] so that we get inheritance for free
meta = getattr(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)
# Add fields specifid in the `include` class Meta option
cls_fields += list(klass.opts.include.items())
dict_cls = OrderedDict if ordered else dict
# 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_cls
)
return klass
@classmethod
def get_declared_fields(mcs, klass, cls_fields, inherited_fields, dict_cls):
"""Returns a dictionary of field_name => `Field` pairs declard on the class.
This is exposed mainly so that plugins can add additional fields, e.g. fields
computed from class Meta options.
:param type klass: The class object.
:param dict cls_fields: The fields declared on the class, including those added
by the ``include`` class Meta option.
:param dict inherited_fileds: Inherited fields.
:param type dict_class: Either `dict` or `OrderedDict`, depending on the whether
the user specified `ordered=True`.
"""
return dict_cls(inherited_fields + cls_fields)
# NOTE: self is the class object
def __init__(self, name, bases, attrs):
super(SchemaMeta, self).__init__(name, bases, attrs)
if name:
class_registry.register(name, self)
self._resolve_processors()
def _resolve_processors(self):
"""Add in the decorated processors
By doing this after constructing the class, we let standard inheritance
do all the hard work.
"""
mro = inspect.getmro(self)
self.__processors__ = defaultdict(list)
for attr_name in dir(self):
# 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:
processor_tags = attr.__marshmallow_tags__
except AttributeError:
continue
for tag in processor_tags:
# Use name here so we can get the bound method later, in case
# the processor was a descriptor or something.
self.__processors__[tag].append(attr_name)
class SchemaOpts(object):
"""class Meta options for the :class:`Schema`. Defines defaults."""
def __init__(self, meta):
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.strict = getattr(meta, 'strict', False)
self.dateformat = getattr(meta, 'dateformat', None)
self.json_module = getattr(meta, 'json_module', json)
if hasattr(meta, 'skip_missing'):
warnings.warn(
'The skip_missing option is no longer necessary. Missing inputs passed to '
'Schema.dump will be excluded from the serialized output by default.',
UserWarning
)
self.ordered = getattr(meta, 'ordered', False)
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', ())
class BaseSchema(base.SchemaABC):
"""Base schema class with which to define custom schemas.
Example usage:
.. code-block:: python
import datetime as dt
from marshmallow import Schema, fields
class Album(object):
def __init__(self, title, release_date):
self.title = title
self.release_date = release_date
class AlbumSchema(Schema):
title = fields.Str()
release_date = fields.Date()
# Or, equivalently
class AlbumSchema2(Schema):
class Meta:
fields = ("title", "release_date")
album = Album("Beggars Banquet", dt.date(1968, 12, 6))
schema = AlbumSchema()
data, errors = schema.dump(album)
data # {'release_date': '1968-12-06', 'title': 'Beggars Banquet'}
:param dict extra: A dict of extra attributes to bind to the serialized result.
:param tuple only: A list or tuple of fields to serialize. If `None`, all
fields will be serialized. Nested fields can be represented with dot delimiters.
:param tuple exclude: A list or tuple of fields to exclude from the
serialized result. Nested fields can be represented with dot delimiters.
:param str prefix: Optional prefix that will be prepended to all the
serialized field names.
:param bool strict: If `True`, raise errors if invalid data are passed in
instead of failing silently and storing the errors.
:param bool many: Should be set to `True` if ``obj`` is a collection
so that the object will be serialized to a list.
:param dict context: Optional context passed to :class:`fields.Method` and
:class:`fields.Function` fields.
:param tuple load_only: A list or tuple of fields to skip during serialization
:param tuple dump_only: A list or tuple of fields to skip during
deserialization, read-only fields
:param bool|tuple partial: Whether to ignore missing fields. If its value
is an iterable, only missing fields listed in that iterable will be
ignored.
.. 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 = {
text_type: fields.String,
binary_type: fields.String,
dt.datetime: fields.DateTime,
float: fields.Float,
bool: fields.Boolean,
tuple: fields.Raw,
list: fields.Raw,
set: fields.Raw,
int: fields.Integer,
uuid.UUID: fields.UUID,
dt.time: fields.Time,
dt.date: fields.Date,
dt.timedelta: fields.TimeDelta,
decimal.Decimal: fields.Decimal,
}
OPTIONS_CLASS = SchemaOpts
#: DEPRECATED: Custom error handler function. May be `None`.
__error_handler__ = None
#: DEPRECATED: Function used to get values of an object.
__accessor__ = None
class Meta(object):
"""Options object for a Schema.
Example usage: ::
class Meta:
fields = ("id", "email", "date_created")
exclude = ("password", "secret_attribute")
Available options:
- ``fields``: Tuple or list of fields to include in the serialized result.
- ``additional``: Tuple or list of fields to include *in addition* to the
explicitly declared fields. ``additional`` and ``fields`` are
mutually-exclusive options.
- ``include``: Dictionary of additional fields to include in the schema. It is
usually better to define fields as class variables, but you may need to
use this option, e.g., if your fields are Python keywords. May be an
`OrderedDict`.
- ``exclude``: Tuple or list of fields to exclude in the serialized result.
Nested fields can be represented with dot delimiters.
- ``dateformat``: Date format for all DateTime fields that do not have their
date format explicitly specified.
- ``strict``: If `True`, raise errors during marshalling rather than
storing them.
- ``json_module``: JSON module to use for `loads` and `dumps`.
Defaults to the ``json`` module in the stdlib.
- ``ordered``: If `True`, order serialization output according to the
order in which fields were declared. Output of `Schema.dump` will be a
`collections.OrderedDict`.
- ``index_errors``: If `True`, errors dictionaries will include the index
of invalid items in a collection.
- ``load_only``: Tuple or list of fields to exclude from serialized results.
- ``dump_only``: Tuple or list of fields to exclude from deserialization
"""
pass
def __init__(self, extra=None, only=(), exclude=(), prefix='', strict=False,
many=False, context=None, load_only=(), dump_only=(),
partial=False):
# copy declared fields from metaclass
self.declared_fields = copy.deepcopy(self._declared_fields)
self.many = many
self.only = only
self.exclude = exclude
self.prefix = prefix
self.strict = strict or self.opts.strict
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
#: Dictionary mapping field_names -> :class:`Field` objects
self.fields = self.dict_class()
#: Callable marshalling object
self._marshal = marshalling.Marshaller(
prefix=self.prefix
)
#: Callable unmarshalling object
self._unmarshal = marshalling.Unmarshaller()
if extra:
warnings.warn(
'The `extra` argument is deprecated. Use a post_dump '
'method to add additional data instead.',
DeprecationWarning
)
self.extra = extra
self.context = context or {}
self._normalize_nested_options()
self._update_fields(many=many)
def __repr__(self):
return '<{ClassName}(many={self.many}, strict={self.strict})>'.format(
ClassName=self.__class__.__name__, self=self
)
def _postprocess(self, data, many, obj):
if self.extra:
if many:
for each in data:
each.update(self.extra)
else:
data.update(self.extra)
if self._marshal.errors:
# TODO: Remove self.__error_handler__ in a later release
error_handler = self.handle_error or self.__error_handler__
if callable(error_handler):
error_handler(self._marshal.errors, obj)
return data
@property
def dict_class(self):
return OrderedDict if self.ordered else dict
@property
def set_class(self):
return OrderedSet if self.ordered else set
##### Override-able methods #####
def handle_error(self, error, data):
"""Custom error handler function for the schema.
:param ValidationError error: The `ValidationError` raised during (de)serialization.
:param data: The original input data.
.. versionadded:: 2.0.0
"""
pass
def get_attribute(self, attr, obj, default):
"""Defines how to pull values from an object to serialize.
.. versionadded:: 2.0.0
"""
return utils.get_value(attr, obj, default)
##### Handler decorators (deprecated) #####
@classmethod
def error_handler(cls, func):
"""Decorator that registers an error handler function for the schema.
The function receives the :class:`Schema` instance, a dictionary of errors,
and the serialized object (if serializing data) or data dictionary (if
deserializing data) as arguments.
Example: ::
class UserSchema(Schema):
email = fields.Email()
@UserSchema.error_handler
def handle_errors(schema, errors, obj):
raise ValueError('An error occurred while marshalling {}'.format(obj))
user = User(email='invalid')
UserSchema().dump(user) # => raises ValueError
UserSchema().load({'email': 'bademail'}) # raises ValueError
.. versionadded:: 0.7.0
.. deprecated:: 2.0.0
Set the ``error_handler`` class Meta option instead.
"""
warnings.warn(
'Schema.error_handler is deprecated. Set the error_handler class Meta option '
'instead.', category=DeprecationWarning
)
cls.__error_handler__ = func
return func
@classmethod
def accessor(cls, func):
"""Decorator that registers a function for pulling values from an object
to serialize. The function receives the :class:`Schema` instance, the
``key`` of the value to get, the ``obj`` to serialize, and an optional
``default`` value.
.. deprecated:: 2.0.0
Set the ``error_handler`` class Meta option instead.
"""
warnings.warn(
'Schema.accessor is deprecated. Set the accessor class Meta option '
'instead.', category=DeprecationWarning
)
cls.__accessor__ = func
return func
##### Serialization/Deserialization API #####
def dump(self, obj, many=None, update_fields=True, **kwargs):
"""Serialize an object to native Python data types according to this
Schema's fields.
:param obj: The object to serialize.
:param bool many: Whether to serialize `obj` as a collection. If `None`, the value
for `self.many` is used.
:param bool update_fields: Whether to update the schema's field classes. Typically
set to `True`, but may be `False` when serializing a homogenous collection.
This parameter is used by `fields.Nested` to avoid multiple updates.
:return: A tuple of the form (``data``, ``errors``)
:rtype: `MarshalResult`, a `collections.namedtuple`
.. versionadded:: 1.0.0
"""
many = self.many if many is None else bool(many)
if not many and utils.is_collection(obj) and not utils.is_keyed_tuple(obj):
warnings.warn('Implicit collection handling is deprecated. Set '
'many=True to serialize a collection.',
category=DeprecationWarning)
if many and utils.is_iterable_but_not_string(obj):
obj = list(obj)
processed_obj = self._invoke_dump_processors(PRE_DUMP, obj, many, original_data=obj)
if update_fields:
self._update_fields(processed_obj, many=many)
try:
preresult = self._marshal(
processed_obj,
self.fields,
many=many,
# TODO: Remove self.__accessor__ in a later release
accessor=self.get_attribute or self.__accessor__,
dict_class=self.dict_class,
index_errors=self.opts.index_errors,
**kwargs
)
except ValidationError as error:
errors = self._marshal.errors
preresult = error.data
if self.strict:
raise error
else:
errors = {}
result = self._postprocess(preresult, many, obj=obj)
result = self._invoke_dump_processors(POST_DUMP, result, many, original_data=obj)
return MarshalResult(result, errors)
def dumps(self, obj, many=None, update_fields=True, *args, **kwargs):
"""Same as :meth:`dump`, except return a JSON-encoded string.
:param obj: The object to serialize.
:param bool many: Whether to serialize `obj` as a collection. If `None`, the value
for `self.many` is used.
:param bool update_fields: Whether to update the schema's field classes. Typically
set to `True`, but may be `False` when serializing a homogenous collection.
This parameter is used by `fields.Nested` to avoid multiple updates.
:return: A tuple of the form (``data``, ``errors``)
:rtype: `MarshalResult`, a `collections.namedtuple`
.. versionadded:: 1.0.0
"""
deserialized, errors = self.dump(obj, many=many, update_fields=update_fields)
ret = self.opts.json_module.dumps(deserialized, *args, **kwargs)
return MarshalResult(ret, errors)
def load(self, data, many=None, partial=None):
"""Deserialize a data structure to an object defined by this Schema's
fields and :meth:`make_object`.
:param dict data: The data to deserialize.
:param bool many: Whether to deserialize `data` as a collection. If `None`, the
value for `self.many` is used.
:param bool|tuple partial: Whether to ignore missing fields. If `None`,
the value for `self.partial` is used. If its value is an iterable,
only missing fields listed in that iterable will be ignored.
:return: A tuple of the form (``data``, ``errors``)
:rtype: `UnmarshalResult`, a `collections.namedtuple`
.. versionadded:: 1.0.0
"""
result, errors = self._do_load(data, many, partial=partial, postprocess=True)
return UnmarshalResult(data=result, errors=errors)
def loads(self, json_data, many=None, *args, **kwargs):
"""Same as :meth:`load`, except it takes a JSON string as input.
:param str json_data: A JSON string of the data to deserialize.
:param bool many: Whether to deserialize `obj` as a collection. If `None`, the
value for `self.many` is used.
:param bool|tuple partial: Whether to ignore missing fields. If `None`,
the value for `self.partial` is used. If its value is an iterable,
:return: A tuple of the form (``data``, ``errors``)
:rtype: `UnmarshalResult`, a `collections.namedtuple`
.. versionadded:: 1.0.0
"""
# TODO: This avoids breaking backward compatibility if people were
# passing in positional args after `many` for use by `json.loads`, but
# ideally we shouldn't have to do this.
partial = kwargs.pop('partial', None)
data = self.opts.json_module.loads(json_data, *args, **kwargs)
return self.load(data, many=many, partial=partial)
def validate(self, data, many=None, partial=None):
"""Validate `data` against the schema, returning a dictionary of
validation errors.
:param dict data: The data to validate.
:param bool many: Whether to validate `data` as a collection. If `None`, the
value for `self.many` is used.
:return: A dictionary of validation errors.
:rtype: dict
.. versionadded:: 1.1.0
"""
_, errors = self._do_load(data, many, partial=partial, postprocess=False)
return errors
##### Private Helpers #####
def _do_load(self, data, many=None, partial=None, postprocess=True):
"""Deserialize `data`, returning the deserialized result and a dictonary of
validation errors.
:param data: The data to deserialize.
:param bool many: Whether to deserialize `data` as a collection. If `None`, the
value for `self.many` is used.
:param bool|tuple 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 bool postprocess: Whether to run post_load methods..
:return: A tuple of the form (`data`, `errors`)
"""
many = self.many if many is None else bool(many)
if partial is None:
partial = self.partial
processed_data = self._invoke_load_processors(PRE_LOAD, data, many, original_data=data)
try:
result = self._unmarshal(
processed_data,
self.fields,
many=many,
partial=partial,
dict_class=self.dict_class,
index_errors=self.opts.index_errors,
)
except ValidationError as error:
result = error.data
else:
errors = {}
self._invoke_field_validators(data=result, many=many)
errors = self._unmarshal.errors
field_errors = bool(errors)
# Run schema-level migration
try:
self._invoke_validators(pass_many=True, data=result, original_data=data, many=many,
field_errors=field_errors)
except ValidationError as err:
errors.update(err.messages)
try:
self._invoke_validators(pass_many=False, data=result, original_data=data, many=many,
field_errors=field_errors)
except ValidationError as err:
errors.update(err.messages)
if errors:
# TODO: Remove self.__error_handler__ in a later release
if self.__error_handler__ and callable(self.__error_handler__):
self.__error_handler__(errors, data)
exc = ValidationError(
errors,
field_names=self._unmarshal.error_field_names,
fields=self._unmarshal.error_fields,
data=data,
**self._unmarshal.error_kwargs
)
self.handle_error(exc, data)
if self.strict:
raise exc
if not errors and postprocess:
result = self._invoke_load_processors(POST_LOAD, result, many, original_data=data)
return result, errors
def _normalize_nested_options(self):
"""Apply then flatten nested schema options"""
if self.only:
# Apply the only option to nested fields.
self.__apply_nested_option('only', self.only)
# Remove the child field names from the only option.
self.only = self.set_class(
[field.split('.', 1)[0] for field in self.only])
excludes = set(self.opts.exclude) | set(self.exclude)
if excludes:
# Apply the exclude option to nested fields.
self.__apply_nested_option('exclude', excludes)
if self.exclude:
# Remove the parent field names from the exclude option.
self.exclude = self.set_class(
[field for field in self.exclude if '.' not in field])
if self.opts.exclude:
# Remove the parent field names from the meta exclude option.
self.opts.exclude = self.set_class(
[field for field in self.opts.exclude if '.' not in field])
def __apply_nested_option(self, option_name, field_names):
"""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)
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()):
setattr(self.declared_fields[key], option_name, self.set_class(options))
def _update_fields(self, obj=None, many=False):
"""Update fields based on the passed in object."""
if self.only:
# Return only fields specified in only option
if self.opts.fields:
field_names = self.set_class(self.opts.fields) & self.set_class(self.only)
else:
field_names = self.set_class(self.only)
elif self.opts.fields:
# Return fields specified in fields option
field_names = self.set_class(self.opts.fields)
elif self.opts.additional:
# Return declared fields + additional fields
field_names = (self.set_class(self.declared_fields.keys()) |
self.set_class(self.opts.additional))
else:
field_names = self.set_class(self.declared_fields.keys())
# If "exclude" option or param is specified, remove those fields
excludes = set(self.opts.exclude) | set(self.exclude)
if excludes:
field_names = field_names - excludes
ret = self.__filter_fields(field_names, obj, many=many)
# Set parents
self.__set_field_attrs(ret)
self.fields = ret
return self.fields
def on_bind_field(self, field_name, field_obj):
"""Hook to modify a field when it is bound to the `Schema`. No-op by default."""
return None
def __set_field_attrs(self, fields_dict):
"""Bind fields to the schema, setting any necessary attributes
on the fields (e.g. parent and name).
Also set field load_only and dump_only values if field_name was
specified in ``class Meta``.
"""
for field_name, field_obj in iteritems(fields_dict):
try:
if field_name in self.load_only:
field_obj.load_only = True
if field_name in self.dump_only:
field_obj.dump_only = True
field_obj._add_to_schema(field_name, self)
self.on_bind_field(field_name, field_obj)
except TypeError:
# field declared as a class, not an instance
if (isinstance(field_obj, type) and
issubclass(field_obj, base.FieldABC)):
msg = ('Field for "{0}" must be declared as a '
'Field instance, not a class. '
'Did you mean "fields.{1}()"?'
.format(field_name, field_obj.__name__))
raise TypeError(msg)
return fields_dict
def __filter_fields(self, field_names, obj, many=False):
"""Return only those field_name:field_obj pairs specified by
``field_names``.
:param set field_names: Field names to include in the final
return dictionary.
:returns: An dict of field_name:field_obj pairs.
"""
if obj and many:
try: # Homogeneous collection
# Prefer getitem over iter to prevent breaking serialization
# of objects for which iter will modify position in the collection
# e.g. Pymongo cursors
if hasattr(obj, '__getitem__') and callable(getattr(obj, '__getitem__')):
obj_prototype = obj[0]
else:
obj_prototype = next(iter(obj))
except (StopIteration, IndexError): # Nothing to serialize
return self.declared_fields
obj = obj_prototype
ret = self.dict_class()
for key in field_names:
if key in self.declared_fields:
ret[key] = self.declared_fields[key]
else: # Implicit field creation (class Meta 'fields' or 'additional')
if obj:
attribute_type = None
try:
if isinstance(obj, Mapping):
attribute_type = type(obj[key])
else:
attribute_type = type(getattr(obj, key))
except (AttributeError, KeyError) as err:
err_type = type(err)
raise err_type(
'"{0}" is not a valid field for {1}.'.format(key, obj))
field_obj = self.TYPE_MAPPING.get(attribute_type, fields.Field)()
else: # Object is None
field_obj = fields.Field()
# map key -> field (default to Raw)
ret[key] = field_obj
return ret
def _invoke_dump_processors(self, tag_name, data, many, 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_name, pass_many=False,
data=data, many=many, original_data=original_data)
data = self._invoke_processors(tag_name, pass_many=True,
data=data, many=many, original_data=original_data)
return data
def _invoke_load_processors(self, tag_name, data, many, original_data=None):
# This has to invert the order of the dump processors, so run the pass_many
# processors first.
data = self._invoke_processors(tag_name, pass_many=True,
data=data, many=many, original_data=original_data)
data = self._invoke_processors(tag_name, pass_many=False,
data=data, many=many, original_data=original_data)
return data
def _invoke_field_validators(self, data, many):
for attr_name in self.__processors__[(VALIDATES, False)]:
validator = getattr(self, attr_name)
validator_kwargs = validator.__marshmallow_kwargs__[(VALIDATES, False)]
field_name = validator_kwargs['field_name']
try:
field_obj = self.fields[field_name]
except KeyError:
if field_name in self.declared_fields:
continue
raise ValueError('"{0}" field does not exist.'.format(field_name))
if many:
for idx, item in enumerate(data):
try:
value = item[field_obj.attribute or field_name]
except KeyError:
pass
else:
self._unmarshal.call_and_store(
getter_func=validator,
data=value,
field_name=field_name,
field_obj=field_obj,
index=(idx if self.opts.index_errors else None)
)
else:
try:
value = data[field_obj.attribute or field_name]
except KeyError:
pass
else:
self._unmarshal.call_and_store(
getter_func=validator,
data=value,
field_name=field_name,
field_obj=field_obj
)
def _invoke_validators(self, pass_many, data, original_data, many, field_errors=False):
errors = {}
for attr_name in self.__processors__[(VALIDATES_SCHEMA, pass_many)]:
validator = getattr(self, attr_name)
validator_kwargs = validator.__marshmallow_kwargs__[(VALIDATES_SCHEMA, pass_many)]
pass_original = validator_kwargs.get('pass_original', False)
skip_on_field_errors = validator_kwargs['skip_on_field_errors']
if skip_on_field_errors and field_errors:
continue
if pass_many:
validator = functools.partial(validator, many=many)
if many and not pass_many:
for idx, item in enumerate(data):
try:
self._unmarshal.run_validator(validator,
item, original_data, self.fields, many=many,
index=idx, pass_original=pass_original)
except ValidationError as err:
errors.update(err.messages)
else:
try:
self._unmarshal.run_validator(validator,
data, original_data, self.fields, many=many,
pass_original=pass_original)
except ValidationError as err:
errors.update(err.messages)
if errors:
raise ValidationError(errors)
return None
def _invoke_processors(self, tag_name, pass_many, data, many, original_data=None):
for attr_name in self.__processors__[(tag_name, pass_many)]:
# This will be a bound method.
processor = getattr(self, attr_name)
processor_kwargs = processor.__marshmallow_kwargs__[(tag_name, pass_many)]
pass_original = processor_kwargs.get('pass_original', False)
if pass_many:
if pass_original:
data = utils.if_none(processor(data, many, original_data), data)
else:
data = utils.if_none(processor(data, many), data)
elif many:
if pass_original:
data = [utils.if_none(processor(item, original_data), item)
for item in data]
else:
data = [utils.if_none(processor(item), item) for item in data]
else:
if pass_original:
data = utils.if_none(processor(data, original_data), data)
else:
data = utils.if_none(processor(data), data)
return data
class Schema(with_metaclass(SchemaMeta, BaseSchema)):
__doc__ = BaseSchema.__doc__
