marshmallow之Schema延伸功能

预处理和后处理方法

数据的预处理和后处理方法通过pre_load, post_load, pre_dump和post_dump装饰器注册：

from marshmallow import Schema, fields, pre_load

class UserSchema(Schema):
    name = fields.Str()
    slug = fields.Str()

    @pre_load
    def slugify_name(self, in_data):
        in_data['slug'] = in_data['slug'].lower().strip().replace(' ', '-')
        return in_data

schema = UserSchema()
result, errors = schema.load({'name': 'Steve', 'slug': 'Steve Loria '})
result['slug']  # => 'steve-loria'

预处理和后处理的many参数

预处理和后处理方法默认一次接收一个对象/数据，在运行时处理传递给schema对象的many参数。

创建schema实例时如果传递了many=True，表示需要接收输入数据集合，装饰器注册预处理和后处理方法时需要传递参数pass_many=True。预处理和后处理方法接收输入数据(可能是单个数据或数据集合)和布尔类型的many参数：

from marshmallow import Schema, fields, pre_load, post_load, post_dump

class BaseSchema(Schema):
    # Custom options
    __envelope__ = {
        'single': None,
        'many': None
    }
    __model__ = User

    def get_envelope_key(self, many):
        """Helper to get the envelope key."""
        key = self.__envelope__['many'] if many else self.__envelope__['single']
        assert key is not None, "Envelope key undefined"
        return key

    @pre_load(pass_many=True)
    def unwrap_envelope(self, data, many):
        key = self.get_envelope_key(many)
        return data[key]

    @post_dump(pass_many=True)
    def wrap_with_envelope(self, data, many):
        key = self.get_envelope_key(many)
        return {key: data}

    @post_load
    def make_object(self, data):
        return self.__model__(**data)

class UserSchema(BaseSchema):
    __envelope__ = {
        'single': 'user',
        'many': 'users',
    }
    __model__ = User
    name = fields.Str()
    email = fields.Email()

user_schema = UserSchema()

user = User('Mick', email='[email protected]')
user_data = user_schema.dump(user).data
# {'user': {'email': '[email protected]', 'name': 'Mick'}}

users = [User('Keith', email='[email protected]'),
        User('Charlie', email='[email protected]')]
users_data = user_schema.dump(users, many=True).data
# {'users': [{'email': '[email protected]', 'name': 'Keith'},
#            {'email': '[email protected]', 'name': 'Charlie'}]}

user_objs = user_schema.load(users_data, many=True).data
# [, ]

在预处理和后处理方法中抛出异常

字段验证产生的错误字典的_schema键包含了ValidationError异常的信息：

from marshmallow import Schema, fields, ValidationError, pre_load

class BandSchema(Schema):
    name = fields.Str()

    @pre_load
    def unwrap_envelope(self, data):
        if 'data' not in data:
            raise ValidationError('Input data must have a "data" key.')
        return data['data']

sch = BandSchema()
sch.load({'name': 'The Band'}).errors
# {'_schema': ['Input data must have a "data" key.']}

如果不想存储在_schema键中，可以指定新的键名传递给ValidationError的第二个参数：

from marshmallow import Schema, fields, ValidationError, pre_load

class BandSchema(Schema):
    name = fields.Str()

    @pre_load
    def unwrap_envelope(self, data):
        if 'data' not in data:
            raise ValidationError('Input data must have a "data" key.', '_preprocessing')
        return data['data']

sch = BandSchema()
sch.load({'name': 'The Band'}).errors
# {'_preprocessing': ['Input data must have a "data" key.']}

预处理和后处理方法的调用顺序

反序列化的处理流程：

1. @pre_load(pass_many=True) methods
2. @pre_load(pass_many=False) methods
3. load(in_data, many) (validation and deserialization)
4. @post_load(pass_many=True) methods
5. @post_load(pass_many=False) methods

序列化的处理流程(注意pass_many的区别)：

1. @pre_dump(pass_many=False) methods
2. @pre_dump(pass_many=True) methods
3. dump(obj, many) (serialization)
4. @post_dump(pass_many=False) methods
5. @post_dump(pass_many=True) methods

不保证相同装饰器和pass_many参数装饰的方法的调用顺序

错误处理

重写schema的handle_error方法来自定义错误处理功能。handle_error接收一个ValidationError异常实例，一个原始对象(序列化)或输入数据(反序列化)：

import logging
from marshmallow import Schema, fields

class AppError(Exception):
    pass

class UserSchema(Schema):
    email = fields.Email()

    def handle_error(self, exc, data):
        """Log and raise our custom exception when (de)serialization fails."""
        logging.error(exc.messages)
        raise AppError('An error occurred with input: {0}'.format(data))

schema = UserSchema()
schema.load({'email': 'invalid-email'})  # raises AppError

Schema级别的验证

使用marshmallow.validates_schema装饰器可以为Schema注册一个schema级别的验证函数，其异常信息保存在错误字典的_schema键中：

from marshmallow import Schema, fields, validates_schema, ValidationError

class NumberSchema(Schema):
    field_a = fields.Integer()
    field_b = fields.Integer()

    @validates_schema
    def validate_numbers(self, data):
        if data['field_b'] >= data['field_a']:
            raise ValidationError('field_a must be greater than field_b')

schema = NumberSchema()
result, errors = schema.load({'field_a': 1, 'field_b': 2})
errors['_schema'] # => ["field_a must be greater than field_b"]

验证原始输入数据

通常验证器会忽略未声明的field的数据输入。如果要访问原始输入数据(例如如果发送了未知字段视为验证失败)，可以给validates_schema装饰器传递一个pass_original=True参数：

from marshmallow import Schema, fields, validates_schema, ValidationError

class MySchema(Schema):
    foo = fields.Int()
    bar = fields.Int()

    @validates_schema(pass_original=True)
    def check_unknown_fields(self, data, original_data):
        unknown = set(original_data) - set(self.fields)
        if unknown:
            raise ValidationError('Unknown field', unknown)

schema = MySchema()
errors = schema.load({'foo': 1, 'bar': 2, 'baz': 3, 'bu': 4}).errors
# {'baz': 'Unknown field', 'bu': 'Unknown field'}

存储特定field的错误

如果要在指定field上保存schema级别的验证错误，可以给ValidationError的第二个参数传递field名称(列表)：

class NumberSchema(Schema):
    field_a = fields.Integer()
    field_b = fields.Integer()

    @validates_schema
    def validate_numbers(self, data):
        if data['field_b'] >= data['field_a']:
            raise ValidationError(
                'field_a must be greater than field_b',
                'field_a'
            )

schema = NumberSchema()
result, errors = schema.load({'field_a': 1, 'field_b': 2})
errors['field_a'] # => ["field_a must be greater than field_b"]

重写属性访问的方式

marshmallow默认使用utils.get_value函数获取各种类型的对象的属性以进行序列化。

通过重写get_attribute方法可以重写对象属性的访问方式：

class UserDictSchema(Schema):
    name = fields.Str()
    email = fields.Email()

    # If we know we're only serializing dictionaries, we can
    # use dict.get for all input objects
    def get_attribute(self, key, obj, default):
        return obj.get(key, default)

自定义class Meta选项

class Meta是配置和修改Schema行为的一种方式。通过继承自SchemaOpts可以添加自定义class Meta选项(Schema.Meta API docs查看原生选项)。

下面的代码通过自定义class Meta选项实现了预处理和后处理的many参数这一节中例子的功能。

首先通过继承SchemaOpts类添加了两个选项，name和plural_name：

from marshmallow import Schema, SchemaOpts

class NamespaceOpts(SchemaOpts):
    """Same as the default class Meta options, but adds "name" and
    "plural_name" options for enveloping.
    """
    def __init__(self, meta):
        SchemaOpts.__init__(self, meta)
        self.name = getattr(meta, 'name', None)
        self.plural_name = getattr(meta, 'plural_name', self.name)

然后创建NamespacedSchema类并使用刚才创建的NamespaceOpts：

class NamespacedSchema(Schema):
    OPTIONS_CLASS = NamespaceOpts

    @pre_load(pass_many=True)
    def unwrap_envelope(self, data, many):
        key = self.opts.plural_name if many else self.opts.name
        return data[key]

    @post_dump(pass_many=True)
    def wrap_with_envelope(self, data, many):
        key = self.opts.plural_name if many else self.opts.name
        return {key: data}

现在我们处理序列化和反序列化的自定义schema再继承自NamespacedSchema：

class UserSchema(NamespacedSchema):
    name = fields.String()
    email = fields.Email()

    class Meta:
        name = 'user'
        plural_name = 'users'

ser = UserSchema()
user = User('Keith', email='[email protected]')
result = ser.dump(user)
result.data  # {"user": {"name": "Keith", "email": "[email protected]"}}

使用上下文

Schema的context属性存储序列化及反序列化可能要用到的额外信息。

schema = UserSchema()
# Make current HTTP request available to
# custom fields, schema methods, schema validators, etc.
schema.context['request'] = request
schema.dump(user)

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