django rest framework 数据的查找、过滤、排序的示例

(编辑:jimmy 日期: 2024/11/17 浏览:2)

对于管理系统,常常需要展示列表数据,我们对于列表内的数据常常需要查找、过滤、排序等操作,其中查找等操作大部分是在后台进行的。django rest framework可以轻松的实现数据的查找、过滤等操作。接下来我们将以实际的例子进行介绍。

示例代码github地址: https://github.com/jinjidejuren/drf_learn

例如cmdb系统,作为资产管理系统常常需要对数据进行过滤或查找,获取期望的信息。

实现model

1.在这个示例项目中,需要实现对物理服务器的条件过滤,物理服务器的model列表如下(apps/assets/models.py文件):

class Server(models.Model):
  """
  物理服务器
  """
  status_choice = (
    ('online', '上线'),
    ('offline', '下线'),
    ('normal', '正常'),
    ('abnormal', '异常')
  )

  server_name = models.CharField(verbose_name=u'服务器名称', max_length=128, blank=False, null=False)
  server_num = models.CharField(verbose_name=u'服务器编号', max_length=128, blank=True, null=True)
  brand = models.CharField(verbose_name=u'品牌', max_length=64, blank=True, null=True)
  model = models.CharField(verbose_name=u'型号', max_length=64, blank=True, null=True)
  cpus = models.IntegerField(verbose_name=u'cpu核数', default=0)
  ram = models.IntegerField(verbose_name=u'内存大小', default=0)
  disk = models.IntegerField(verbose_name=u'磁盘大小', default=0)
  product_date = models.DateTimeField(verbose_name=u'生产日期', auto_now_add=True)
  status = models.CharField(verbose_name=u'状态', max_length=16, choices=status_choice)

  created_time = models.DateTimeField(verbose_name=u'创建时间', auto_now_add=True)
  modified_time = models.DateTimeField(verbose_name=u'修改时间', auto_now_add=True)

  class Meta:
    verbose_name = u'服务器'
    verbose_name_plural = verbose_name

  def __str__(self):
    return self.server_name

实现serializer

接下来需要实现server这个model的序列化类,在apps/assets/serializers.py中编写:

class ServiceSerializer(serializers.ModelSerializer):
  """
  服务器序列化
  """

  class Meta:
    model = Server
    fields = ('id', 'server_name', 'server_num', 'brand', 'model', 'cpus',
         'ram', 'disk', 'product_date', 'status', 'created_time',
         'modified_time')

对于fields来说,可以使用 _ all _ 来代表所有的字段,除了model中定义的field外,序列化还可以指定其他的信息,比如嵌套信息或者自定义的信息。具体可以取决于业务逻辑。

实现modelviewset

对于modelviewset,我们可以围绕它对用户请求做相应的处理。常见的是对model进行增加、删除、查找、修改等。在这部分我们需要实现ServerViewSet:

class ServerViewSet(viewsets.ModelViewSet):
  """
  物理服务器视图
  """
  queryset = Server.objects.all().order_by('-created_time')
  serializer_class = ServerSerializer
  pagination_class = MyFormatResultsSetPagination

queryset指定返回列表的形式,所有的信息都返回,并且按照创建时间逆序排列,这样可以把最新的信息先返回,比较符合用户的操作习惯。

serializer_class定义了返回的序列化格式为ServerSerializer所指定的fields内容

pagination_class 指定了分页的类型,这个MyFormatResultsSetPagination是我们的自定义类型

实现router

如果用户想要访问server的信息,需要指定server的路由,这个和之前介绍的类似。需要的嗯一个一个router对象,并且将server的路由注册进去。

from rest_framework import routers

router = routers.DefaultRouter()
router.register(r'servers', views.ServerViewSet, base_name='servers')

urlpatterns = [
  url(r'^', include(router.urls))
]

对于servers的访问都由ServerViewSet进行处理。

尝试访问

http://127.0.0.1:8060/assets/v1/servers/ ,信息如下:

django rest framework 数据的查找、过滤、排序的示例

注:我们需要添加示例信息,作为后续的各种测试使用。

按照条件获取

在日常操作中,我们需要获取指定条件的数据,例如对于物理服务器,我们需要指定品牌、指定cpu核数、指定内存大小等。有时候我们需要按照cpu核数进行排序。这些都需要我们对ServerViewSet进行更多的拓展。

如果进行条件过滤,需要首先安装django-filter模块:

pip install django-filter

在配置文件settings/base.py中添加应用django_filters:

INSTALLED_APPS = [
  # 'django.contrib.admin',
  'django.contrib.auth',
  'django.contrib.contenttypes',
  'django.contrib.sessions',
  'django.contrib.messages',
  'django.contrib.staticfiles',
  'rest_framework',
  'django_filters',
  'apps.assets',
  'apps.rbac'
]

在apps/assets/views.py顶部包含如下包:

from django_filters.rest_framework import DjangoFilterBackend
from rest_framework import filters
from django_filters import rest_framework

ServerViewSet可以添加相应的过滤条件:

class ServerViewSet(viewsets.ModelViewSet):
  """
  物理服务器视图
  """
  queryset = Server.objects.all()
  serializer_class = ServerSerializer
  pagination_class = MyFormatResultsSetPagination
  filter_backends = (rest_framework.DjangoFilterBackend, filters.SearchFilter, filters.OrderingFilter, )
  filter_class = ServerFilter
  search_fields = ('server_name', '=brand', 'status', )
  ordering_fields = ('cpus', 'ram', 'disk', 'product_date', )
  ordering = ('-created_time', )

这里的filter_backends指定了过滤的类型,此处设定了DjangoFilterBackend(过滤)、SearchFilter(搜索)和OrderingFIlter(排序)。

1.过滤

过滤设定了过滤的配置类为ServerFilter,关于ServerFilter在apps/assets/filters.py文件中进行了定义:

import django_filters

from .models import *


class ServerFilter(django_filters.rest_framework.FilterSet):
  """
  物理服务器过滤器
  """

  server_name = django_filters.CharFilter(name='server_name', lookup_expr='icontains')
  brand = django_filters.CharFilter(name='brand', lookup_expr='icontains')
  cpus = django_filters.NumberFilter(name='cpus')
  ram = django_filters.NumberFilter(name='ram')
  disk = django_filters.NumberFilter(name='disk')

  class Meta:
    model = Server
    fields = ['server_name', 'brand', 'cpus', 'ram', 'disk', ]

也就是说可以通过'server_name', ‘brand', ‘cpus', ‘ram', ‘disk'对物理服务器的信息进行过滤,得到相应的序列化列表。

例如获取cpu为24核的物理服务器:

django rest framework 数据的查找、过滤、排序的示例

得到物理服务器列表中cpu都为24:

GET /assets/v1/servers/"results": [
    {
      "id": 9,
      "server_name": "data-server2",
      "server_num": "server-01-shanghai",
      "brand": "hp",
      "model": "HPE Apollo 4200 Gen9",
      "cpus": 24,
      "ram": 64,
      "disk": 2500,
      "product_date": "2018-06-23T13:51:09.641473Z",
      "status": "online",
      "created_time": "2018-06-23T13:51:09.642583Z",
      "modified_time": "2018-06-23T13:51:09.642764Z"
    },
    {
      "id": 8,
      "server_name": "data-server2",
      "server_num": "server-01-shanghai",
      "brand": "hp",
      "model": "HPE Apollo 4200 Gen9",
      "cpus": 24,
      "ram": 64,
      "disk": 5000,
      "product_date": "2018-06-23T13:51:02.466031Z",
      "status": "online",
      "created_time": "2018-06-23T13:51:02.467274Z",
      "modified_time": "2018-06-23T13:51:02.467471Z"
    },
    {
      "id": 7,
      "server_name": "data-server1",
      "server_num": "server-01-shanghai",
      "brand": "hp",
      "model": "HPE Apollo 4200 Gen9",
      "cpus": 24,
      "ram": 64,
      "disk": 5000,
      "product_date": "2018-06-23T13:50:55.622403Z",
      "status": "offline",
      "created_time": "2018-06-23T13:50:55.623315Z",
      "modified_time": "2018-06-23T13:50:55.623431Z"
    },
    {
      "id": 6,
      "server_name": "data-server",
      "server_num": "server-01-shanghai",
      "brand": "hp",
      "model": "HPE Apollo 4200 Gen9",
      "cpus": 24,
      "ram": 64,
      "disk": 5000,
      "product_date": "2018-06-23T13:50:48.088028Z",
      "status": "online",
      "created_time": "2018-06-23T13:50:48.089433Z",
      "modified_time": "2018-06-23T13:50:48.089703Z"
    },
    {
      "id": 5,
      "server_name": "harbor-server3",
      "server_num": "server-01-beijing",
      "brand": "dell",
      "model": "Rack",
      "cpus": 24,
      "ram": 128,
      "disk": 5000,
      "product_date": "2018-06-23T13:49:27.590015Z",
      "status": "offline",
      "created_time": "2018-06-23T13:49:27.590980Z",
      "modified_time": "2018-06-23T13:49:27.591097Z"
    },
    {
      "id": 4,
      "server_name": "harbor-server3",
      "server_num": "server-01-beijing",
      "brand": "dell",
      "model": "Rack",
      "cpus": 24,
      "ram": 128,
      "disk": 5000,
      "product_date": "2018-06-23T13:49:23.783337Z",
      "status": "abnormal",
      "created_time": "2018-06-23T13:49:23.784243Z",
      "modified_time": "2018-06-23T13:49:23.784500Z"
    },
    {
      "id": 3,
      "server_name": "harbor-server2",
      "server_num": "server-01-beijing",
      "brand": "dell",
      "model": "Rack",
      "cpus": 24,
      "ram": 128,
      "disk": 5000,
      "product_date": "2018-06-23T13:49:16.348672Z",
      "status": "online",
      "created_time": "2018-06-23T13:49:16.349555Z",
      "modified_time": "2018-06-23T13:49:16.349663Z"
    },
    {
      "id": 2,
      "server_name": "harbor-server1",
      "server_num": "server-02-beijing",
      "brand": "dell",
      "model": "Rack",
      "cpus": 24,
      "ram": 128,
      "disk": 5000,
      "product_date": "2018-06-23T13:48:57.853354Z",
      "status": "online",
      "created_time": "2018-06-23T13:48:57.853990Z",
      "modified_time": "2018-06-23T13:48:57.854098Z"
    },
    {
      "id": 1,
      "server_name": "harbor-server",
      "server_num": "server-01-beijing",
      "brand": "dell",
      "model": "Rack",
      "cpus": 24,
      "ram": 128,
      "disk": 5000,
      "product_date": "2018-06-23T13:48:48.777153Z",
      "status": "online",
      "created_time": "2018-06-23T13:48:48.778048Z",
      "modified_time": "2018-06-23T13:48:48.778166Z"
    }
  ],
  "pagination": 9,
  "page_size": 10,
  "page": 1
}

2.搜索

搜索需要指定 search 关键字需要查询的信息,例如搜索名称为‘test'开头的服务器:

http://127.0.0.1:8060/assets/v1/servers/"htmlcode">

HTTP 200 OK
Allow: GET, POST, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

{
  "results": [
    {
      "id": 14,
      "server_name": "test-server1",
      "server_num": "server-01-shanghai",
      "brand": "dell",
      "model": "Modular",
      "cpus": 32,
      "ram": 256,
      "disk": 500,
      "product_date": "2018-06-23T13:52:40.583743Z",
      "status": "offline",
      "created_time": "2018-06-23T13:52:40.584409Z",
      "modified_time": "2018-06-23T13:52:40.584512Z"
    },
    {
      "id": 13,
      "server_name": "test-server",
      "server_num": "server-01-shanghai",
      "brand": "dell",
      "model": "Modular",
      "cpus": 32,
      "ram": 256,
      "disk": 2500,
      "product_date": "2018-06-23T13:52:24.760819Z",
      "status": "normal",
      "created_time": "2018-06-23T13:52:24.761475Z",
      "modified_time": "2018-06-23T13:52:24.761578Z"
    }
  ],
  "pagination": 2,
  "page_size": 10,
  "page": 1
}

在search_fields中可以指定多种查找方式:

‘^name' 以name开头

‘=name' 精确匹配

‘@' 全局检索(只有mysql数据源支持)

‘$' 正则匹配

对应的search_fileds示例如下:

search_fields = ('^server_name', '=brand', 'status', )

3.排序

在ordering字段指定了默认排序方式(按照创建时间逆序排序):

ordering = ('-created_time', )

也可以使用如下方式指定:

queryset = Server.objects.all().order_by('-created_time')

如果要自定义排序字段,需要指定 ordering 字段的内容:

例如按照内存大小排列服务器:

http://127.0.0.1:8060/assets/v1/servers/"htmlcode">

HTTP 200 OK
Allow: GET, POST, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

{
  "results": [
    {
      "id": 6,
      "server_name": "data-server",
      "server_num": "server-01-shanghai",
      "brand": "hp",
      "model": "HPE Apollo 4200 Gen9",
      "cpus": 24,
      "ram": 64,
      "disk": 5000,
      "product_date": "2018-06-23T13:50:48.088028Z",
      "status": "online",
      "created_time": "2018-06-23T13:50:48.089433Z",
      "modified_time": "2018-06-23T13:50:48.089703Z"
    },
    {
      "id": 7,
      "server_name": "data-server1",
      "server_num": "server-01-shanghai",
      "brand": "hp",
      "model": "HPE Apollo 4200 Gen9",
      "cpus": 24,
      "ram": 64,
      "disk": 5000,
      "product_date": "2018-06-23T13:50:55.622403Z",
      "status": "offline",
      "created_time": "2018-06-23T13:50:55.623315Z",
      "modified_time": "2018-06-23T13:50:55.623431Z"
    },
    {
      "id": 8,
      "server_name": "data-server2",
      "server_num": "server-01-shanghai",
      "brand": "hp",
      "model": "HPE Apollo 4200 Gen9",
      "cpus": 24,
      "ram": 64,
      "disk": 5000,
      "product_date": "2018-06-23T13:51:02.466031Z",
      "status": "online",
      "created_time": "2018-06-23T13:51:02.467274Z",
      "modified_time": "2018-06-23T13:51:02.467471Z"
    },
    {
      "id": 9,
      "server_name": "data-server2",
      "server_num": "server-01-shanghai",
      "brand": "hp",
      "model": "HPE Apollo 4200 Gen9",
      "cpus": 24,
      "ram": 64,
      "disk": 2500,
      "product_date": "2018-06-23T13:51:09.641473Z",
      "status": "online",
      "created_time": "2018-06-23T13:51:09.642583Z",
      "modified_time": "2018-06-23T13:51:09.642764Z"
    },
    {
      "id": 1,
      "server_name": "harbor-server",
      "server_num": "server-01-beijing",
      "brand": "dell",
      "model": "Rack",
      "cpus": 24,
      "ram": 128,
      "disk": 5000,
      "product_date": "2018-06-23T13:48:48.777153Z",
      "status": "online",
      "created_time": "2018-06-23T13:48:48.778048Z",
      "modified_time": "2018-06-23T13:48:48.778166Z"
    },
    {
      "id": 2,
      "server_name": "harbor-server1",
      "server_num": "server-02-beijing",
      "brand": "dell",
      "model": "Rack",
      "cpus": 24,
      "ram": 128,
      "disk": 5000,
      "product_date": "2018-06-23T13:48:57.853354Z",
      "status": "online",
      "created_time": "2018-06-23T13:48:57.853990Z",
      "modified_time": "2018-06-23T13:48:57.854098Z"
    },
    {
      "id": 3,
      "server_name": "harbor-server2",
      "server_num": "server-01-beijing",
      "brand": "dell",
      "model": "Rack",
      "cpus": 24,
      "ram": 128,
      "disk": 5000,
      "product_date": "2018-06-23T13:49:16.348672Z",
      "status": "online",
      "created_time": "2018-06-23T13:49:16.349555Z",
      "modified_time": "2018-06-23T13:49:16.349663Z"
    },
    {
      "id": 4,
      "server_name": "harbor-server3",
      "server_num": "server-01-beijing",
      "brand": "dell",
      "model": "Rack",
      "cpus": 24,
      "ram": 128,
      "disk": 5000,
      "product_date": "2018-06-23T13:49:23.783337Z",
      "status": "abnormal",
      "created_time": "2018-06-23T13:49:23.784243Z",
      "modified_time": "2018-06-23T13:49:23.784500Z"
    },
    {
      "id": 5,
      "server_name": "harbor-server3",
      "server_num": "server-01-beijing",
      "brand": "dell",
      "model": "Rack",
      "cpus": 24,
      "ram": 128,
      "disk": 5000,
      "product_date": "2018-06-23T13:49:27.590015Z",
      "status": "offline",
      "created_time": "2018-06-23T13:49:27.590980Z",
      "modified_time": "2018-06-23T13:49:27.591097Z"
    },
    {
      "id": 10,
      "server_name": "data-server2",
      "server_num": "server-01-shanghai",
      "brand": "hp",
      "model": "HPE Apollo 4200 Gen9",
      "cpus": 32,
      "ram": 256,
      "disk": 2500,
      "product_date": "2018-06-23T13:51:30.706187Z",
      "status": "online",
      "created_time": "2018-06-23T13:51:30.707754Z",
      "modified_time": "2018-06-23T13:51:30.707878Z"
    }
  ],
  "pagination": 14,
  "page_size": 10,
  "page": 1
}

上述的排序、过滤等操作可以组合使用,一般为前端的列表搜索查询提供接口支持。

小结

本章小结的内容介绍了django rest framework如何进行model的定义、序列化、增删改查以及搜索、排序等功能,是书写后端接口必须掌握的技巧。

以上就是本文的全部内容,希望对大家的学习有所帮助,也希望大家多多支持。

一句话新闻

Windows上运行安卓你用过了吗
在去年的5月23日,借助Intel Bridge Technology以及Intel Celadon两项技术的驱动,Intel为PC用户带来了Android On Windows(AOW)平台,并携手国内软件公司腾讯共同推出了腾讯应用宝电脑版,将Windows与安卓两大生态进行了融合,PC的使用体验随即被带入到了一个全新的阶段。