1. 源码分析
注意:以下代码片段为方便理解已进行简化,只保留了与序列化功能相关的代码
序列化的源码中涉及到了元类的概念,我在这里简单说明一下:元类(metaclass)是一个高级概念,用于定义类的创建行为。简单来说,元类是创建类的类,它决定了类的创建方式和行为。
在 Python 中一切皆为对象,包括类。每个类都有一个元类,它定义了如何创建这个类。通常情况下 Python 会使用默认的元类 type 来创建类。但是,当我们需要对类的创建过程进行自定义时,就可以使用元类,举例:
python
class Mytype(type)
def __new__(cls,name,bases,attrs): # 类名,继承的父类 ,成员
# 此处可对要创建的类进行操作
del attrs["v1"]
attrs["name"] = "harry"
xx = super().__new__(cls,name,bases,attrs) # 调用type类创建对象(这个对象就是Bar类)
retyrn xx
class Bar(object, metaclass=Mytype) # metaclass指定自定义元类
v1 = 123
def func(self):
pass
由于元类中删除了v1属性,且增加了name属性,因此此时Bar中无v1属性,且多了name属性
另:父类 如果指定了元类metaclass,则其子类 都默认是用该元类来创建类
补充:实例化Bar类时,相当于是 type对象(),因此会触发type类的__call__方法,其中就调用了Bar的__new__和__init__,因此在实例化类时才会自动触发类的__new__和__init__方法。本质上是因为 对象() 而调用了type元类的call方法;
Serializers组件主要有两个功能:序列化和数据校验
- 序列化部分:
首先定义一个序列化类
python
class DepartSerializer(serializers.Serializer):
'''Serializer校验'''
# 内置校验
title = serializers.CharField(required=True, max_length=20, min_length=6)
order = serializers.IntegerField(required=False, max_value=100, min_value=10)
count = serializers.ChoiceField(choices=[(1, "高级"), (2, "中级")])
查看Serializer的父类,可知其是通过SerializerMetaclass元类创建的
python
Serializer(BaseSerializer, metaclass=SerializerMetaclass)
SerializerMetaclass元类源码:
python
class SerializerMetaclass(type):
@classmethod
def _get_declared_fields(cls, bases, attrs):
fields = [(field_name, attrs.pop(field_name)) # 通过循环获取field字段对象
for field_name, obj in list(attrs.items())
if isinstance(obj, Field)]
fields.sort(key=lambda x: x[1]._creation_counter)
known = set(attrs)
def visit(name):
known.add(name)
return name
base_fields = [
(visit(name), f)
for base in bases if hasattr(base, '_declared_fields')
for name, f in base._declared_fields.items() if name not in known
]
return OrderedDict(base_fields + fields)
def __new__(cls, name, bases, attrs):
attrs['_declared_fields'] = cls._get_declared_fields(bases, attrs) # 为类中增加了_declared_fields属性,其中封装了所有的Field字段名及对应的对象
return super().__new__(cls, name, bases, attrs)
通过serializer.data触发序列化流程:
python
@property
def data(self):
ret = super().data # 寻找其父类BaseSerializer的data方法
return ReturnDict(ret, serializer=self)
BaseSerializer的data方法源码:
python
@property
def data(self):
if hasattr(self, 'initial_data') and not hasattr(self, '_validated_data'):
msg = (
'When a serializer is passed a `data` keyword argument you '
'must call `.is_valid()` before attempting to access the '
'serialized `.data` representation.\n'
'You should either call `.is_valid()` first, '
'or access `.initial_data` instead.'
)
raise AssertionError(msg)
if not hasattr(self, '_data'):
if self.instance is not None and not getattr(self, '_errors', None):
self._data = self.to_representation(self.instance) # 执行to_representation方法获取序列化数据
elif hasattr(self, '_validated_data') and not getattr(self, '_errors', None):
self._data = self.to_representation(self.validated_data)
else:
self._data = self.get_initial()
return self._data
to_representation方法源码(核心):
python
def to_representation(self, instance):
ret = OrderedDict()
fields = self._readable_fields # 筛选出可读的字段对象(其内部对_declared_fields字段进行了深拷贝)
for field in fields:
try:
attribute = field.get_attribute(instance) # 循环字段对象列表,并执行get_attribute方法获取对应的值
except SkipField:
continue
check_for_none = attribute.pk if isinstance(attribute, PKOnlyObject) else attribute
if check_for_none is None:
ret[field.field_name] = None
else:
ret[field.field_name] = field.to_representation(attribute) # 执行to_representation转换格式,并将所有数据封装到ret字典中
return ret
get_attribute方法源码:
python
def get_attribute(self, instance):
return get_attribute(instance, self.source_attrs)
python
def get_attribute(instance, attrs): # attrs为source字段值 instance为模型对象
for attr in attrs:
try:
if isinstance(instance, Mapping):
instance = instance[attr]
else:
instance = getattr(instance, attr) # 循环获取模型对象最终的attr的值
except ObjectDoesNotExist:
return None
return instance # 返回该字段值
- 数据校验部分
使用is_valid方法校验数据,获取_errors数据,_errors存在则is_valid返回False。在执行该函数的过程中,触发了run_validation方法:
python
def is_valid(self, raise_exception=False):
if not hasattr(self, '_validated_data'):
try: # 触发了run_validation方法
self._validated_data = self.run_validation(self.initial_data)
except ValidationError as exc:
self._validated_data = {}
self._errors = exc.detail
else:
self._errors = {}
if self._errors and raise_exception:
raise ValidationError(self.errors)
return not bool(self._errors)****
run_validation方法,注意该方法是Serializer类下的方法,不是Field类的方法。在to_internal_value方法中调用字段内置校验,并执行钩子函数。
python
def run_validation(self, data=empty):
(is_empty_value, data) = self.validate_empty_values(data)
if is_empty_value:
return data
value = self.to_internal_value(data) # 调用字段内置校验,并执行钩子函数
try:
self.run_validators(value)
value = self.validate(value)
assert value is not None, '.validate() should return the validated data'
except (ValidationError, DjangoValidationError) as exc:
raise ValidationError(detail=as_serializer_error(exc))
return value
to_internal_value方法,fileds从_declared_fields中深拷贝而得到,且只包含了只写的字段对象
python
def to_internal_value(self, data):
if not isinstance(data, Mapping):
message = self.error_messages['invalid'].format(
datatype=type(data).__name__
)
raise ValidationError({
api_settings.NON_FIELD_ERRORS_KEY: [message]
}, code='invalid')
ret = OrderedDict()
errors = OrderedDict()
fields = self._writable_fields # 筛选只写的字段对象
for field in fields:
validate_method = getattr(self, 'validate_' + field.field_name, None)
primitive_value = field.get_value(data)
try:
validated_value = field.run_validation(primitive_value) # 执行内置校验
if validate_method is not None:
validated_value = validate_method(validated_value) # 执行钩子函数进行校验
except ValidationError as exc:
errors[field.field_name] = exc.detail
except DjangoValidationError as exc:
errors[field.field_name] = get_error_detail(exc)
except SkipField:
pass
else:
set_value(ret, field.source_attrs, validated_value)
if errors:
raise ValidationError(errors)
return ret
run_validation内置校验:
python
def run_validation(self, data=empty):
if data == '' or (self.trim_whitespace and str(data).strip() == ''):
if not self.allow_blank:
self.fail('blank')
return ''
return super().run_validation(data)
# 父类的run_validation方法
def run_validation(self, data=empty):
(is_empty_value, data) = self.validate_empty_values(data)
if is_empty_value:
return data
value = self.to_internal_value(data)
self.run_validators(value) # 调用字段定义的run_validators进行校验
return value
2、源码改编:
- 自定义钩子:让某字段既能支持前端传入,又能自定义序列化返回的值;(SerializerMethodField默认是只可读的,用户无法输入,而普通field又无法自定义复杂逻辑返回值)
思路:在调用ser.data开始序列化后的to_representation方法中判断有无自定义格式的钩子,如果有则替换掉该字段对象的值
python
def to_representation(self, instance):
ret = OrderedDict()
fields = self._readable_fields
for field in fields:
if hasattr(self, 'get_%s' % field.field_name): # 判断是否有"get_xxx"形式的函数,如则执行该方法并将instance传入
value = getattr(self, 'get_%s' % field.field_name)(instance)
ret[field.field_name] = value
else:
try:
attribute = field.get_attribute(instance)
except SkipField:
continue
check_for_none = attribute.pk if isinstance(attribute, PKOnlyObject) else attribute
if check_for_none is None:
ret[field.field_name] = None
else:
ret[field.field_name] = field.to_representation(attribute)
return ret
如果其他类中也需要使用该重写方法,可将该重新方法封装成类,其他类中继承该类后,即可不用每次都重写to_representation方法