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='mick@stones.org')
user_data = user_schema.dump(user).data
# {'user': {'email': 'mick@stones.org', 'name': 'Mick'}}
users = [User('Keith', email='keith@stones.org'),
User('Charlie', email='charlie@stones.org')]
users_data = user_schema.dump(users, many=True).data
# {'users': [{'email': 'keith@stones.org', 'name': 'Keith'},
# {'email': 'charlie@stones.org', 'name': 'Charlie'}]}
user_objs = user_schema.load(users_data, many=True).data
# [<User(name='Keith Richards')>, <User(name='Charlie Watts')>]
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:
- @pre_load(pass_many=True) methods
- @pre_load(pass_many=False) methods
- load(in_data, many) (validation and deserialization)
- @post_load(pass_many=True) methods
- @post_load(pass_many=False) methods
序列化的处理流程(注意pass_many
的区别):
- @pre_dump(pass_many=False) methods
- @pre_dump(pass_many=True) methods
- dump(obj, many) (serialization)
- @post_dump(pass_many=False) methods
- @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='keith@stones.com')
result = ser.dump(user)
result.data # {"user": {"name": "Keith", "email": "keith@stones.com"}}
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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