Restful 2 --DRF解析器,序列化组件使用(GET/POST接口设计)

DRF - 解析器

一、解析器的引出

  咱们知道,浏览器能够向django服务器发送json格式的数据,此时,django不会帮咱们进行解析,只是将发送的原数据保存在request.body中,只有post请求发送urlencoded格式的数据时,django会帮咱们将数据解析成字典放到reques.POST中,咱们可直接获取并使用,下面是django对数据解析的相关源码:html

def _load_post_and_files(self):
    if self.method != 'POST':
        self._post, self._files = QueryDict(encoding=self._encoding), MultiValueDict()
        return
    if self._read_started and not hasattr(self, '_body'):
        self._mark_post_parse_error()
        return
    if self.content_type == 'multipart/form-data':
        if hasattr(self, '_body'):
            data = BytesIO(self._body)
        else:
            data = self
        try:
            self._post, self._files = self.parse_file_upload(self.META, data)
        except MultiPartParserError:
            self._mark_post_parse_error()
            raise
    elif self.content_type == 'application/x-www-form-urlencoded':
        self._post, self._files = QueryDict(self.body, encoding=self._encoding), MultiValueDict()
    else:
        self._post, self._files = QueryDict(encoding=self._encoding), MultiValueDict()

  分析:有源码可见,django并无解析json数据的操做,那么咱们本身是否能够解析,固然能够,以下代码:前端

class LoginView(View):
    def get(self, request):
        return render(request, 'login.html')

    def post(self, request):
        print(request.body)  # b'{"name":"alex","password":123}'
        origin_data = request.body.decode('utf-8')
        parsed_data = json.loads(origin_data)
        print(parsed_data)  # {'name': 'alex', 'password': 123}
        print(type(parsed_data))  # <class 'dict'>
        return HttpResponse("Ok")

  分析:上面代码能够看出,咱们彻底能够拿到用户发送的数据,而后进行解码和反序列化,那么问题来了,咱们的项目中可能不止一次须要发送json格式数据,这是面临的问题就是拿到数据都要本身进行解析,有没有这样的一个工具能够为咱们解析用户发送的json格式数据,答案固然有,DRF的APIView就为咱们提供了这样的功能,看以下代码:python

from rest_framework.views import APIView
class LoginView(APIView):
    def get(self, request):
        return render(request, 'login.html')

    def post(self, request):
        # request是被drf封装的新对象,基于django的request
        # request.data是一个被property装饰的属性方法
        # request.data最后会找到self.parser_classes中的解析器 
        # 来实现对数据进行解析
        print(request.data)   # {'name': 'alex', 'password': 123}
        print(type(request.data))  # <class 'dict'>
        return HttpResponse("Ok")

  分析:上面代码能够看出,咱们经过使用APIView代替CBV中的View后,就能够经过request。data获取到通过解析后的用户发送的json格式数据。由此,咱们能够猜想,DRF中的APIView继承了View而且对它进行了功能的丰富。接下来咱们经过源码寻找答案。git

二、解析器源码解读

  APIView类中的dispatch方法实现View类中dispath的反射以外,还对request进行了封装,APIView类部分源码以下:web

class APIView(View):
   ...
   # api_settings是APISettings类的实例化对象,
   parser_classes = api_settings.DEFAULT_PARSER_CLASSES
   # APIView类加载时parser_classes已经有值,就是解析器,print(parser_classes)
   # 程序启动就能看见打印结果,结果以下
   # [<class 'rest_framework.parsers.JSONParser'>, 
   # <class 'rest_framework.parsers.FormParser'>, 
   # <class 'rest_framework.parsers.MultiPartParser'>]
   ...
    settings = api_settings
    schema = DefaultSchema()

    @classmethod
    def as_view(cls, **initkwargs):   # cls指LoginView
        if isinstance(getattr(cls, 'queryset', None), models.query.QuerySet):
            ...
     # 下面一句表示去执行APIView父类(即View类)中的as_view方法
        view = super(APIView, cls).as_view(**initkwargs)
        view.cls = cls
        view.initkwargs = initkwargs
        return csrf_exempt(view)

  def dispatch(self, request, *args, **kwargs):
        ...
        request = self.initialize_request(request, *args, **kwargs)
        self.request = request
        ...

        try:
            self.initial(request, *args, **kwargs)
            if request.method.lower() in self.http_method_names:
                handler = getattr(self, request.method.lower(),
                              self.http_method_not_allowed)
            else:
                handler = self.http_method_not_allowed
            response = handler(request, *args, **kwargs)
        except Exception as exc:
            response = self.handle_exception(exc)
        self.response = self.finalize_response(request, response, *args, **kwargs)
        return self.response

  使用initialize_request方法,对request进行加工,添加功能,APIView中initalize_request函数代码以下:算法

def initialize_request(self, request, *args, **kwargs):
    parser_context = self.get_parser_context(request)
    # 返回Request的实例化对象
    return Request(
        request,
        parsers=self.get_parsers(),  # 这里的self指LoginView实例对象
        authenticators=self.get_authenticators(),
        negotiator=self.get_content_negotiator(),
        parser_context=parser_context
    )

  APIView类所在文件views.py中导入了Request和api_settings,以下:数据库

  from rest_framework.request import Request
  from rest_framework.settings import api_settings

  Request类的部分代码以下:django

class Request(object):
    def __init__(self, request, parsers=None, authenticators=None,
                 negotiator=None, parser_context=None):
        assert isinstance(request, HttpRequest), (
            'The `request` argument must be an instance of '
            '`django.http.HttpRequest`, not `{}.{}`.'
            .format(request.__class__.__module__, request.__class__.__name__)
        )

        self._request = request
        self.parsers = parsers or ()
        self.authenticators = authenticators or ()
        self.negotiator = negotiator or self._default_negotiator()
        self.parser_context = parser_context
        self._data = Empty
        self._files = Empty
        self._full_data = Empty
        self._content_type = Empty
        self._stream = Empty

        if self.parser_context is None:
            self.parser_context = {}
        self.parser_context['request'] = self
        self.parser_context['encoding'] = request.encoding or settings.DEFAULT_CHARSET

        force_user = getattr(request, '_force_auth_user', None)
        force_token = getattr(request, '_force_auth_token', None)
        if force_user is not None or force_token is not None:
            forced_auth = ForcedAuthentication(force_user, force_token)
            self.authenticators = (forced_auth,)

  @property
  def data(self):
      if not _hasattr(self, '_full_data'):
          self._load_data_and_files()
      return self._full_data

  def _load_data_and_files(self):
      if not _hasattr(self, '_data'):
          # _parse()的执行结果是返回(parsed.data, parsed.files)
          self._data, self._files = self._parse()
          if self._files:
              self._full_data = self._data.copy()
              self._full_data.update(self._files)
          else:
              self._full_data = self._data 
           # 此时self._full_data就是parsed.data,即解析后的数据

          if is_form_media_type(self.content_type):
              self._request._post = self.POST
              self._request._files = self.FILES

  def _parse(self):
      media_type = self.content_type
      try:
          stream = self.stream
      except RawPostDataException:
          if not hasattr(self._request, '_post'):
              raise
          if self._supports_form_parsing():
              return (self._request.POST, self._request.FILES)
          stream = None

      if stream is None or media_type is None:
          if media_type and is_form_media_type(media_type):
              empty_data = QueryDict('', encoding=self._request._encoding)
          else:
              empty_data = {}
          empty_files = MultiValueDict()
          return (empty_data, empty_files)

      parser = self.negotiator.select_parser(self, self.parsers)    # 这里的self.parsers就是解析类

      if not parser:
          raise exceptions.UnsupportedMediaType(media_type)

      try:
          parsed = parser.parse(stream, media_type, self.parser_context)
      except Exception:
          self._data = QueryDict('', encoding=self._request._encoding)
          self._files = MultiValueDict()
          self._full_data = self._data
          raise

      try:
          return (parsed.data, parsed.files)
      except AttributeError:
          empty_files = MultiValueDict()
          return (parsed, empty_files)

  api_settings所在的settings.py中部分相关代码以下:json

DEFAULTS = {
    ...,
    'DEFAULT_PARSER_CLASSES': (
        'rest_framework.parsers.JSONParser',
        'rest_framework.parsers.FormParser',
        'rest_framework.parsers.MultiPartParser'
    ),
    ...
}

class APISettings(object):
    def __init__(self, user_settings=None, defaults=None, import_strings=None):
        if user_settings:
            self._user_settings = self.__check_user_settings(user_settings)
        self.defaults = defaults or DEFAULTS
        self.import_strings = import_strings or IMPORT_STRINGS
        self._cached_attrs = set()

        @property
  def user_settings(self):
      if not hasattr(self, '_user_settings'):
          self._user_settings = getattr(settings, 'REST_FRAMEWORK', {})
      return self._user_settings

  def __getattr__(self, attr):   # 形参attr对应实参是DEFAULT_PARSER_CLASSES
      if attr not in self.defaults:
          raise AttributeError("Invalid API setting: '%s'" % attr)

      try:
          val = self.user_settings[attr]
      except KeyError:
          val = self.defaults[attr]

      if attr in self.import_strings:
          val = perform_import(val, attr)  # 参考动态import理解

      self._cached_attrs.add(attr)
      setattr(self, attr, val)
      return val

      api_settings = APISettings(None, DEFAULTS, IMPORT_STRINGS)
     # 注意:api_settings是APISettings类的实例化对象,由于对象api_settings没有DEFAULT_PARSER_CLASSES属性,因此api_settings.DEFAULT_PARSER_CLASSES时,会执行APISettings类的__getattr__方法,而且将DEFAULT_PARSER_CLASSES做为参数传入。

三、本身指定解析数据类型

  知道了DRF的APIView封装了哪几个解析器类(JSONParser, FormParser,MultiPartParser)以后,咱们能够根据须要本身定义解析器,以下:api

from rest_framework.views import APIView
from rest_framework.parsers import JSONParser
class LoginView(APIView):
   parser_classes = [JSONParser]   # 只须要解析JSON数据
   # parser_classes = [] 则不能解析任何数据类型
    def get(self, request):
        return render(request, 'login.html')

    def post(self, request):
        request.data    # 解析后的数据
        return HttpResponse("Ok")

2、序列化组件的使用及接口设计

一、django原生serializer(序列化)的使用

from django.core.serializers import serialize    # 1.导入模块
class CourseView(APIView):
    def get(self, request):
        course_list = Course.objects.all()    # 2.获取queryset
         # 3.对queryset进行序列化
        serialized_data = serialize('json', course_list) 
         # 4.返回序列化后的数据
        return HttpResponse(serialized_data)

二、经过DRF的序列化组件进行接口设计

  1)参考图书管理系统的表结构,models.py以下:

from django.db import models
class Book(models.Model):
    nid = models.AutoField(primary_key=True)
    title = models.CharField(max_length=32)
    price = models.DecimalField(max_digits=5, decimal_places=2)
    publish = models.ForeignKey(to='Publish', related_name='book', on_delete=models.CASCADE)
    authors = models.ManyToManyField(to='Author')


class Publish(models.Model):
    nid = models.AutoField(primary_key=True)
    name = models.CharField(max_length=32)
    city = models.CharField(max_length=32)
    email = models.EmailField()

    def __str__(self):
        return self.name


class Author(models.Model):
    nid = models.AutoField(primary_key=True)
    name = models.CharField(max_length=32)
    age = models.IntegerField()

    def __str__(self):
        return self.name

  2)有以下几个接口

GET       127.0.0.1:8000/books/        # 获取全部数据,返回值: [{}, {}]
GET       127.0.0.1:8000/books/{id}    # 获取一条数据,返回值:{}
POST      127.0.0.1:8000/books/        # 新增一条数据,返回值:{}
PUT       127.0.0.1:8000/books/{id}    # 修改数据,返回值:{}
DELETE    127.0.0.1:8000/books/{id}    # 删除数据,返回空

  3)经过序列化组件进行get接口(获取全部数据)设计,序列化组建使用步骤以下:

    - 导入序列化组件 from rest_feanmework import serializers

    - 定义序列化类,继承serializers.Serializer(建议单首创建一个模块存放全部序列化类);

    - 定义须要返回的字(字段类型能够与model中类型不一致,参数也可调整),字段名称要与model中一致,若不一直则经过source参数指定原始的字段名;

    - 在GET接口逻辑中,获取queryset;

    -  开始序列化: 奖queryset做为第一个参数传给序列化类,many默认为false,若是返回的数据是一个含多个对象的queryset,须要改many=True;

    - 返回:将序列化对象的data属性返回便可;

  4)为了解耦,咱们新建一个名为app_serializers.py的模块,将全部的序列化的使用集中在这个模块中:

from rest_framework import serializers  #  导入序列化模块

from .models import Book

# 建立序列化类
class BookSerializer(serializers.Serializer):
    nid = serializers.CharField(max_length=32)
    title = serializers.CharField(max_length=128)
    price  = serializers.DecimalField(max_digits=5, decimal_places=2)
    publish = serializers.CharField(max_length=32)
    authors = serializers.CharField(max_length=32)

  5)视图代码以下:

from rest_framework.views import APIView
from rest_framework.response import Response
from .app_serializers import BookSerializer
from .models import Book, Publish, Author

class BookView(APIView):
    def get(self, request):
        origin_data = Book.objects.all()  # 获取queryset
        # 开始序列化(参数many=True表示有多条数据,默认为False)
        serialized_data = BookSerializer(origin_data, many=True)
        # 将序列化对象的data属性返回
        return Response(serialized_data.data)

  上面的接口逻辑中,咱们使用了Response对象,它是drf从新封装的响应对象,该对象在返回响应数据时会判断客户端类型(浏览器或者postman),若是是浏览器,它会以web页面的形式返回,若是时postman这类工具,就直接返回json类型的数据。

  下面是经过postman请求该接口后的返回数据,能够看到,除了ManyToManyField字段不是咱们想要的的外,其余都没有问题:

[
    {
        "nid": "1",
        "title": "python初级",
        "price": "188.00",
        "publish": "清华大学出版社",
        "authors": "serializer.Author.None"
    },
    {
        "nid": "2", 
        "title": "python中级",
        "price": "78.00",
        "publish": "清华大学出版社",
        "authors": "serializer.Author.None"
    },
]

  那么,多对多来讲怎么处理呢?若是将source参数定义为“authors.all”,那么取出来的结果将是要给QuerySet,对于前端来讲,这样的数据并非特别友好,咱们可使用以下方式:

from rest_framework import serializers  # 导入序列化模块
# 建立序列化类
class BookSerializer(serializers.Serializer):
    nid = serializers.CharField(max_length=32)
    title = serializers.CharField(max_length=128)
    price  = serializers.DecimalField(max_digits=5, decimal_places=2)
    publish = serializers.CharField(max_length=32)
    authors = serializers.SerializerMethodField()

    def get_authors(self, author_object):
        authors = list()

        for author in author_object.authors.all():
            authors.append(author.name)

        return authors

  注意:get_必须与字段字段名称一致,不然报错。

  6)经过序列化组件进行post接口(提交一条数据)设计,步骤以下:

    - 定义post方法:在视图类中定义post方法;

    - 开始序列化:经过上面定义的序列化类,建立一个序列化对象,传入参数data=request.data(application/json)数据;

    - 校验数据:经过实例对象的is_valid()方法,对请求数据的合法性进行校验;

    - 保存数据:调用save()方法,将数据插入数据库;

    - 插入数据到多对多关系表:若是有多对多字段,手动插入数据到多对多关系表;

    - 返回:将插入的对象返回;

  注意:由于多对多关系字段是咱们自定义的,并且必须这样定义,返回的数据才有意义,而用户插入数据的时候,没法找到这个字段类型SerializerMethodField,因此,序列化类不能帮咱们插入数据到多对多表,咱们必须手动插入数据,所以序列化类要作以下修改:

from rest_framework import serializers  # 1.导入序列化模块

from .models import Book

# 2.建立序列化类
class BookSerializer(serializers.Serializer):
    # nid字段只须要传给客户端,用户提交不须要id,因此read_only=True
    nid = serializers.CharField(read_only=True, max_length=32)
    title = serializers.CharField(max_length=128)
    price  = serializers.DecimalField(max_digits=5, decimal_places=2)
    publish = serializers.CharField(max_length=32)
    # SerializerMethodField默认read_only=True
    authors = serializers.SerializerMethodField()

    def get_authors(self, author_object):
        authors = list()
        for author in author_object.authors.all():
            authors.append(author.name)
        print(authors)

        return authors

    # 必须手动插入数据,所以post方法提交数据必须有create方法
    def create(self, validated_data):
        print(validated_data) # validated_data为过滤以后的数据
            # {'title': '手册', 'price': Decimal('123.00'), 'publish': '3'}
            validated_data['publish_id'] = validated_data.pop('publish')
            book = Book.objects.create(**validated_data)

            return book

  根据接口规范,咱们不须要新增url,只须要在上面视图类中定义一个post方法便可,代码以下:

from rest_framework.views import APIView
from rest_framework.response import Response
from .app_serializers import BookSerializer
from .models import Book, Publish, Author

class BookView(APIView):
    def get(self, request):
        origin_data = Book.objects.all()
        serialized_data = BookSerializer(origin_data, many=True)
        return Response(serialized_data.data)

    def post(self, request):
        verfied_data = BookSerializer(data=request.data)

        if verfied_data.is_valid():
            book = verfied_data.save()
         # 手动绑定多对多关系,也能够放到create方法中去
            authors = Author.objects.filter(nid__in=request.data['authors'])
            book.authors.add(*authors)
            return Response(verfied_data.data)
        else:
            return Response(verfied_data.errors)

 分析:上面这种方法有两个问题:一个是须要手动插入数据(写序列化类中写create方法),另外一个是若是字段不少,写序列化类的字段也会变成一种负担,那么有没有更简单的方式呢?固然,那就是用ModelSerializer。

  7)使用ModelSerializer序列化组件写上面的get和post接口,修改app_serializers.py代码以下:

from rest_framework import serializers  
        from .models import Book

class BookSerializer(serializers.ModelSerializer):
    class Meta:
        model = Book
        fields = (
            'title',
            'price',
            'publish',
            'authors',
            'author_list',
            'pubName',
            'pubCity'
        )
        extra_kwargs = {
            'publish':{'write_only':True},
            'authors':{'write_only':True}
        }

    pubName = serializers.CharField(max_length=32, read_only=True, source='publish.name')
    pubCity = serializers.CharField(max_length=32, read_only=True, source='publish.city')

    # 多对多字段
    author_list = serializers.SerializerMethodField()

    def get_author_list(self, book_obj):
        authors = list()

        for author in book_obj.authors.all():
            authors.append(author.name)

        return authors

3、补充知识点

一、访问对象一个不存在的属性会执行类的__getattr__方法,以下:

class Person(object):
    def __init__(self, name, age): 
        self.name = name
        self.age = age

    def __getattr__(self, item):
        print(item)

jihong = Person("jihong", 20)
print(jihong.name)  # jihong
jihong.hobby   # hobby

二、动态import

# foo.py文件
def foo():
    print('this is foo')

# test.py文件
import importlib
module_path = input('请输入要导入的模块')  # 输入 foo
module = importlib.import_module(module_path)
print(module)
# <module 'foo' from 'D:\\@Lily\\drfserver\\classbasedview\\foo.py'>
module.foo()   # 执行foo.py模块中的foo函数
# this is foo

三、多继承(参考面向对象的对继承C3算法)

class A(object):
    def foo(self):
        print('A.foo')

class B(A):
    def foo(self):
        print('B.foo')
        super().foo()

class C(A):
    def foo(self):
        print('C.foo')
        super().foo()

class D(B, C):
    def foo(self):
        print('D.foo')
        super().foo()

d = D()
d.foo()

 执行结果以下:

  D.foo

  B.foo

  C.foo

  A.foo

四、Django settings文件查找顺序

  咱们在使用django的时候,常常会使用到它的settings文件,经过在settings文件中定义变量,

  咱们能够在程序的任何地方使用这个变量,好比,假设在settings里边定义了一个变量NAME='Lily',虽然能够在项目的任何地方使用:

1
2
>>>  from  drf_server  import  settings
>>>  print (settings.NAME)    # Lily

  可是,这种方式并非被推荐和建议的,由于除了项目自己的settings文件以外,django程序自己也有许多配置信息,都存在django/conf/global_settings.py模块里面,包括缓存、数据库、密钥等,若是咱们写from drf_server import settings,只是导入了项目自己的配置信息,当须要用到django默认的配置信息的时候,还须要再次导入,即from django.conf import settings,因此建议的导入方式是:

1
2
>>>  from  django.conf  import  settings
>>>  print (setting.NAME)

  使用上面的方式,咱们除了可使用自定义的配置信息(NAME)外,还可使用global_settings中的配置信息,不须要重复导入,django查找变量的顺序是先从用户的settings中查找,而后在global_settings中查找,若是用户的settings中找到了,则不会继续查找global_settings中的配置信息,假设我在用户的settings里面定义了NAME='Lily',在global_settings中定义了NAME='Alex',则请看下面的打印结果:

>>> from django.conf import settings
>>> print(settings.NAME)   # Lily

  可见,这种方式更加灵活高效,建议使用。

五、序列化类中的字段名能够与model中的不一致,可是须要使用source参数来告诉组件原始的字段名,以下:

from rest_framework import serializers  # 导入序列化模块

# 建立序列化类
class BookSerializer(serializers.Serializer):
    nid = serializers.CharField(max_length=32)
    bookTitle = serializers.CharField(max_length=128, source='title')
    price  = serializers.DecimalField(max_digits=5, decimal_places=2)
    # source也能够用于ForeignKey字段
    pubName = serializers.CharField(max_length=32, source='publish.name')
    pubCity = serializers.CharField(max_length=32, source='publish.city')
    # 多对多字段source参数为“authors.all”,则取出来的结果是QuerySet,不推荐
    authors = serializers.CharField(source='authors.all')
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