Django之model操作

一、表結構設計

from django.db import models

class Book(models.Model):
    title=models.CharField(max_length=32)
    price=models.IntegerField()
    pub_date=models.DateField(null=True,blank=True)
    publish=models.ForeignKey("Publish",on_delete=models.CASCADE)
    authors=models.ManyToManyField("Author")
    def __str__(self):
        return self.title

class Publish(models.Model):
    name=models.CharField(max_length=32)
    email=models.EmailField()
    def __str__(self):
        return self.name

class Author(models.Model):
    name=models.CharField(max_length=32)
    age=models.IntegerField()
    def __str__(self):
        return self.name

上述包含書籍、出版社、作者模型表，其中出版社和書籍是一對多的關系，作者和書籍是多對多的關系。

二、表操作

（一）一對一操作

以Book表為例，對其進行增、刪、改、查：

1、增加操作

• create方式

#方式一:   
Book.objects.create(title='Python',price=12,pub_date='2017-12-10',publish='天津出版社') #其中publish為外鍵對象，或者寫publish_id=2

#方式二:
Book.objects.create(**{'title':'Python','price':12,'pub_date':'2017-12-10','publish':'天津出版社')

• save方式

#方式一：
book = Book(title='Python',price=12,pub_date='2017-12-10',publish='天津出版社') #其中publish為外鍵對象，或者寫publish_id=2
book.save()

#方式二：
book = Book()
book.title = 'Python'
book.price = 12
book.pub_date = '2017-12-10'
book.publish = '天津出版社' #或者book.publish_id=2
book.save

2、刪除操作

book = Book.objects.filter(id=1).delete()

3、修改操作

#方式一：
Book.objects.filter(id=2).update(title='Java')

#方式二：
book = Book.objects.get(id=2)
book.title= 'Java'
book.save()

注意：get()方法獲取的內容更新的是所有的，效率較低，並且只能獲取一個對象，而filter()獲取的是queryset對象的集合。建議更新用update()方法。

4、查詢操作

 Book.objects.all().values('title').distinct()#對於某一個字段去重
 Book.objects.filter(title='Python').values('title','publish','pub_date')#根據具體條件查找

（二）一對多操作

Publish和Book是一對多的關系，所以以它們為例進行增、刪、改、查操作：

1、增加操作

#方式一： 直接給外鍵的數據庫字段賦值
    Book.objects.create(title='linux',price=15,pub_date='2017-12-10',publish_id=2)

#方式二：對象方法添加
    publish_obj = Publish.objects.filter(name='機械出版社')[0]
    Book.objects.create(title='php',price=15,pub_date='2017-12-10',publish=publish_obj)

2、刪除操作

• 對象方式

#外鍵在的表-主表  對象調用外鍵publish
    Book.objects.filter(title='linux')[0].publish.delete()

#主表-外鍵在的表  對象調用book_set
    Publish.objects.filter(id=1)[0].book_set.all().delete()

• 雙下划線方式

#外鍵在的表-主表
    Book.objects.filter(publish__name='機械出版社').delete()

#主表-外鍵在的表
    Publish.objects.filter(book__name='python').delete()

3、修改操作

#主表-外鍵在的表
    Publish.objects.filter(book__title='python').update(name='北京出版社')

# 外鍵在的表-主表
    Book.objects.filter(publish__name='北京出版社').update(title='python')

4、查詢操作

• 對象方法

#外鍵所在的表-主表
    ret = Book.objects.filter(publish=Publish.objects.filter(name='北京出版社')[0]).values('title','price')
    print(ret)

#主表—外鍵所在的表
    ret =Publish.objects.filter(name='北京出版社')[0].book_set.values('title','price')
    print('Book表內容',ret)

上述外鍵反向使用的是book_set，另一種方法是利用related_name='a'屬性

    Publish.objects.filter(name='北京出版社).values('a')
　  Publish.objects.filter(name='北京出版社').values('a_title','a_price')#用於反向跨表

• 雙下划線

#外鍵在的表-主表
    ret = Book.objects.filter(publish__name='北京出版社').values('title','price')
    print(ret)

#主表-外鍵在的表
    ret = Publish.objects.filter(book__title='php').values('name','book__pub_date')
    print(ret)

（三）多對多操作

Book和Author是多對多關系，所以Book和Author表會生成第三張表，在第三張表中保存了這兩張表的關系，所以以這兩張表為實例進行增、刪、改、查操作：

1、增加操作

• 對象方式

#構建第三張表中的關系

#ManyToMany字段在的表-主表
    author1 = Author.objects.get(id=1)
    author2 = Author.objects.filter(id=2)[0]
    book1 = Book.objects.get(id=2)
    book1.authors.add(author1,author2)#等同於boo1.authors.add(*[author1.author2])

# 主表-ManyToMany字段在的表
    author1 = Author.objects.get(id=2)
    book1 = Book.objects.get(id=3)
    author1.book_set.add(book1) #也可以添加多個和上面相同

• 添加id的方式

   book1 = Book.objects.get(id=2)
   book1.authors.add(2) #其中authors是ManytoMany字段，2是Author表中的id
   book1.authors.add(*[2,3])

2、刪除操作

#ManyToMany字段在的表-主表
    author1 = Author.objects.get(id=1)
    author2 = Author.objects.filter(id=2)[0]
    book1 = Book.objects.get(id=2)
    book1.authors.remove(author1, author2)  # 等同於boo1.authors.remove(*[author1.author2])


#主表-ManyToMany字段在的表
    author1 = Author.objects.get(id=2)
    book1 = Book.objects.get(id=3)
    author1.book_set.remove(book1)

 刪除操作可以使用clear方法，刪除操作也就是j將第三張表中的關系清除掉：

 book1.authors.clear() #將與book1對象相關的關系在第三張表所有清空

3、修改操作

    book1 = Book.objects.get(id=2)
    author = Author.objects.filter(id__gt=2)[0]
    book1.authors.clear() #clear先將第三張表清空
    book1.authors.add(author) #這里實際就是增加操作了，可以增加一個或者多個

修改也可以使用set方法：

   book.authors.set([2,3,4]) #重置，如果存在就不管，不存在就設置，如果不符合條件的刪除，重新建立。第三張表id從最后一個開始往上加

4、查找操作

• 對象方式

#子表-主表
    ret = Book.objects.filter(authors = Author.objects.filter(name='aaa')[0]).values('title')
    print(ret)

#主表-子表
    ret = Author.objects.filter(name='aaa')[0].book_set.all().values('title')
    print(ret)

• 雙下划線方式

#子表-主表
    ret = Book.objects.filter(authors__name='aaa').values('title')

#主表-子表
    ret = Author.objects.filter(book__title='python').values('name')
    print(ret)

 5、總結

多對多操作使用到了以下方法：

add()  #添加方法，可添加對象或者id。並且可以以列表的形式添加多個
remove() #刪除，實際上就是移除掉與指定對象在第三張表中的關系
clear()  #也可用於刪除，但是它不需要傳遞任何參數，清空掉所有調用它的對象在第三張表中的關系
set()#修改方法，傳入需要修改對象的id列表

三、QuerySet中的API

Django的ORM操作主要就是對queryset類型進行操作：

（一）查詢API

1、普通方法

• filter(*args,**kwargs)： 它包含了與所給篩選條件相匹配的對象

def filter(self, *args, **kwargs)
    # 條件查詢
    # 條件可以是：參數，字典，Q

• all()： 查詢所有結果

def all(self)
    # 獲取所有的數據對象

• get(*args,**kwargs)：返回與所給篩選條件相匹配的對象，返回結果有且只有一個，如果符合篩選條件的對象超過一個或者沒有都會拋出錯誤。

def get(self, *args, **kwargs):
    #返回一個匹配的對象  

• values(*field)：返回一個ValueQuerySet——一個特殊的QuerySet，運行后得到的並不是一系列 model的實例化對象，而是一個可迭代的字典序列。

def values(self, *fields):
    # 獲取每行數據為字典格式

• exclude(*args,**kwargs)： 它包含了與所給篩選條件不匹配的對象。

def exclude(self, *args, **kwargs)
    # 條件查詢
    # 條件可以是：參數，字典，Q

# 用於取反
models.Book.objects.all().exclude(id__gt=2)

• order_by(*field)：對查詢結果排序

    # 用於排序
    models.Book.objects.all().order_by('-id')

• ordered()：如果queryset是有序的就返回True

  # 確認queryset是否已經排好序
   order =  models.Book.objects.all().ordered()

• reverse()：對查詢結果反向排序

 # 用於排序后倒序
    models.Book.objects.all().order_by('id').reverse()

• distinct()：從返回結果中剔除重復紀錄

    # 用於distinct去重
    models.Book.objects.values('title').distinct()
    # select distinct title from app01_book

• values_list(*field)：它與values()非常相似，它返回的是一個元組序列，values返回的是一個字典序列

def values_list(self, *fields, **kwargs):
    # 獲取每行數據為元祖

• count()：返回數據庫中匹配查詢(QuerySet)的對象數量。

def count(self):
   # 獲取queryset中對象個數

• first()：返回第一條記錄

def first(self):
   # 獲取第一個對象

• last()：返回最后一條記錄

def last(self):
   # 獲取最后一個對象

• exists()：如果QuerySet包含數據，就返回True，否則返回False

def exists(self):
   # 判斷queryset是否有數據

• only(self, *fields)：僅取某個表中的數據

 models.Book.objects.only('title','publish')
 #或
 models.Book.objects.filter(id__gt = 4).only('title','publish')

• defer()：映射中排除某列

 models.Book.objects.defer('title','publish')
 #或
 models.Book.objects.filter(id__gt = 4).defer('title','publish')

• raw()：執行原生sql

def raw(self, raw_query, params=None, translations=None, using=None):
    # 執行原生SQL
    models.Book.objects.raw('select * from app01_book')

• none()：空queryset對象

def none(self):
    # 空QuerySet對象

• dates()：根據時間對某一部分進行去重查找，並截取指定內容

def dates(self, field_name, kind, order='ASC'):
    # 根據時間對某一部分進行去重查找並截取指定內容
    # kind只能是："year"（年）, "month"（年-月）, "day"（年-月-日）
    # order只能是："ASC"  "DESC"
    # 並獲取轉換后的時間
        - year : 年-01-01
        - month: 年-月-01
        - day  : 年-月-日

models.Publish.objects.dates('ctime','day','DESC')

• datetimes()：根據時間對某一部分進行去重查找並截取指定內容，將時間轉換為指定時區時間

def datetimes(self, field_name, kind, order='ASC', tzinfo=None):
    # 根據時間對某一部分進行去重查找並截取指定內容，將時間轉換為指定時區時間
    # kind只能是 "year", "month", "day", "hour", "minute", "second"
    # order只能是："ASC"  "DESC"
    # tzinfo時區對象
    models.Publish.objects.datetimes('ctime','hour',tzinfo=pytz.UTC)
    models.Publish.objects.datetimes('ctime','hour',tzinfo=pytz.timezone('Asia/Shanghai'))

2、高級用法

• F查詢

 當字段和字段進行比較時用F查詢

from django.db.models import F
from django.db.models.functions import Concat
from django.db.models import Value

#兩個字段作比較，收藏數大於給贊數Goods.objects.filter(collection_num__gt=F('star_num'))

#F() 對象和常數之間的加減乘除和取模的操作，將價格都加10元
Book.objects.all().update(price=F('price')+10)

#字符串拼接
Book.objects.update(title=Concat(F("title"), Value("第一版")))

• Q查詢

當查詢條件是”或“ 的時候 用Q查詢，而默認的filter參數都是”且“的關系

 Book.objects.all().filter(Q(name='python')|Q(price=24)

上面使用Q查詢用的是字段名，如果是字符串（“title”，"price"）應該怎么處理呢？

q = Q()                                # 實例化一個Q對象
q.connector = "or"                     # 默認是且的關系，這里是或的關系
q.children.append("title", "python")    
q.children.append("price", 24)
Book.objects.filter(q)  

這和字段名的效果是一樣的，只不過這里使用的是字符串。

• 子查詢  extra(self, select=None, where=None, params=None, tables=None, order_by=None, select_params=None)

在執行原生sql語句中有時會有較為復雜的子查詢：

    """
        select 
            id,
            title,
            (select count(1) from app01_publish) as n
        from app01_book
    """

而在ORM操作中，這種子查詢可以使用extra方法，在QuerySet的基礎上繼續執行子語句：

 book_obj=models.Book.objects.all().extra(select={
        'n':"select count(1) from app01_publish WHERE id=%s or id=%s",
    },
    select_params=[1,2])

#可以取出id,title,n(子查詢的結果)的值

當然，extra中還有其它其它參數，可以進行where子語句等：

models.Book.objects.extra(where=[‘id in (1,3) OR title like "py%" ‘,‘id>2‘],order_by='-id')

注意：參數中select和select_params是一組，where和params是一組，tables用來設置from哪個表

• 執行原生SQL

from django.db import connection

cursor = connection.cursor()  # cursor = connections['default'].cursor()

cursor.execute("""SELECT * from app01_book where id = %s""", [1])

row = cursor.fetchone()

print(row)

• 聚合查詢  aggregate(*args, **kwargs)

　　aggregate()是QuerySet 的一個終止子句，它返回一個包含一些鍵值對的字典。鍵的名稱是聚合值的標識符，值是計算出來的聚合值。鍵的名稱是按照字段和聚合函數的名稱自動生成出來的。

from django.db.models import Avg
def test(request):
    averge_price = models.Book.objects.all().aggregate(Avg("price"))
    print(averge_price) #{'price__avg': 27.0}

當然，也可以將其重新命名：

    averge_price = models.Book.objects.all().aggregate(avg_price=Avg("price"))
    print(averge_price) #{'avg_price': 27.0}

另外，aggregate還可以生成多個聚合，只需要向其傳遞另外的參數：

#書籍的平均價格、最大價格、最小價格、價格的總和
from django.db.models import Avg,Max,Min,Sum
def test(request):
    averge_price = models.Book.objects.all().aggregate(Avg("price"),Max("price"),Min("price"),Sum("price"))
    print(averge_price) #{'price__avg': 27.0, 'price__max': 56, 'price__min': 12, 'price__sum': 135}

注意：聚合函數中的字段是可以使用‘__’跨表，查詢其它表中的內容

• 分組查詢 annotate(*args, **kwargs)

用於實現聚合group by查詢，為調用的QuerySet中每一個對象都生成一個獨立的統計值 ，例如要檢索每本書有多少個作者：

from django.db.models import Avg,Max,Min,Sum,Count
def test(request):
    #分組查詢
    book_list = models.Book.objects.all().annotate(authors_num = Count('authors'))
    print(book_list[0].authors_num) #取出第一本書的作者數量

#或者循環取出每一本的作者數量
    for book in book_list:
        print(book.authors_num)

其sql語句類似：

 SELECT id,title COUNT(authors) AS `authors_num` FROM app01_book GROUP BY authors

與aggregate()返回的字典不同，annotate()的返回值是一個QuerySet。

3、字段參數查找

字段查找是指定SQL WHERE子句的內容的方式。它們被指定為QuerySet方法的關鍵字參數，如filter()， exclude()以及get()等。

• exact

#精確匹配
models.Book.objects.get(id__exact=4)

#SQL等價於：
SELECT ... WHERE id = 4;

• iexact

#不區分大小寫的完全匹配。
models.Book.objects.get(title__iexact='python')

#SQL等價於：
SELECT ... WHERE name ILIKE 'python';

• contains

#大小寫敏感的匹配查詢，帶有%為模糊查詢
models.Book.objects.get(title__contains='python')

#SQL等價於：
SELECT ... WHERE title LIKE '%python%';

• icontains

#大小寫不敏感的匹配查詢
models.Book.objects.get(title__icontains='python')

#SQL等價於：
SELECT ... WHERE title LIKE '%python%';

• in

#在給定的可迭代中; 通常是列表，元組或查詢集
models.Book.objects.get(id__in=[1,2])
models.Book.objects.get(id__title='abc')

#SQL等價於：
SELECT ... WHERE id IN (1, 2);
SELECT ... WHERE title IN ('a', 'b', 'c');

• gt

#大小
models.Book.objects.get(id__gt=2)

#SQL等價於：
SELECT ... WHERE id > 2;

• gte

#大小等於
models.Book.objects.get(id__gte=2)

#SQL等價於：
SELECT ... WHERE id >= 2;

• lt

#小於
models.Book.objects.get(id__lt=2)

#SQL等價於：
SELECT ... WHERE id < 2;

• lte

#小於等於
models.Book.objects.get(id__lte=2)

#SQL等價於：
SELECT ... WHERE id <= 2; 

• startswith

#區分大小寫的開頭，以..為開頭
models.Book.objects.get(title__startswith='py')

#SQL等價於：
SELECT ... WHERE titleLIKE 'py%';

注意：istartswith是不區分大小寫開頭

• endswith

#區分大小寫的結尾，以..為結尾
models.Book.objects.get(title__endswith='thon')

#SQL等價於：
SELECT ... WHERE titleLIKE '%thon';

注意：iendswith是不區分大小寫開頭

• range

#在某一個范圍內，包括兩端
import datetime
start_date = datetime.date(2015, 3, 1)
end_date = datetime.date(2015, 3, 23)
models.Publish.objects.filter(pub_date__range=(start_date, end_date))

#SQL等價於：
SELECT ... WHERE pub_date BETWEEN '2015-03-01' and '2015-03-23';

• isnull

#根據某一個字段的值是否為空進行過濾
models.Book.objects.get(title__isnull=True)

#SQL等價於：
SELECT ... WHERE title IS NULL;

• regex

#區分大小寫的正則表達式匹配，正則表達式語法是Python re模塊的語法
models.Book.objects.get(title__regex=r'^(An?|The) +')

#SQL等價於：
SELECT ... WHERE title REGEXP BINARY '^(An?|The) +'; 

注意：iregex不區分大小寫的正則表達式匹配。並且建議使用原始字符串（例如，r'foo'而不是'foo'）來傳遞正則表達式語法。

• date

#對於datetime字段，將值轉換為日期。允許鏈接其他字段查找。采用日期值。
models.Publish.objects.filter(pub_date__date=datetime.date(2005, 1, 1))
models.Publish.objects.filter(pub_date__date__gt=datetime.date(2005, 1, 1))

• time

#對於datetime字段，將值轉換為時間。允許鏈接其他字段查找。取一個datetime.time值
models.Publish.objects.filter(pub_date__time=datetime.time(14, 30))
models.Publish.objects.filter(pub_date__time__range=(datetime.time(8), datetime.time(17)))

詳情查看：https://docs.djangoproject.com/en/2.2/ref/models/querysets/#date

（二）其它API

 1、數據庫添加、更新操作

• 批量插入

def bulk_create(self, objs, batch_size=None):
    # 批量插入
    # batch_size表示一次插入的個數
    objs = [
        models.Book(title='aaa'),
        models.Book(title='bbb')
    ]
    models.Book.objects.bulk_create(objs, 10)

• 獲取或者創建

def get_or_create(self, defaults=None, **kwargs):
    # 如果存在，則獲取，否則，創建
    # defaults 指定創建時，其他字段的值
    obj, created = models.Book.objects.get_or_create(title='aaa', defaults={'publish_id': 2,})

• 更新或者創建

def update_or_create(self, defaults=None, **kwargs):
    # 如果存在，則更新，否則，創建
    # defaults 指定創建時或更新時的其他字段
    obj, created = models.Book.objects.update_or_create(title='aaa', defaults={'publish_id': 2,})

• 根據主鍵id進行查找

def in_bulk(self, id_list=None):
   # 根據主鍵ID進行查找
   id_list = [1,2,3]
   models.Book.objects.in_bulk(id_list)

 2、數據庫性能相關

• select_related

　　對於一對一字段（OneToOneField）和多對一字段，可以使用select_related 來對QuerySet進行優化，在對QuerySet使用select_related()函數后，Django會獲取相應外鍵對應的對象，從而在之后需要的時候不必再查詢數據庫了。實際上就是表之間進行join連表操作，一次性獲取關聯的數據。

def select_related(self, *fields)
    #表之間進行join連表操作，一次性獲取關聯的數據。
    #沒有指定的字段不會緩存，如果要訪問的話Django會再次進行SQL查詢。
    #使用雙下划線“__”連接字段名來實現指定的遞歸查詢。


models.Book.objects.select_related('publish').all()    

• prefetch_related

　　對於多對多字段（ManyToManyField）和一對多字段，可以使用prefetch_related()來進行優化。prefetch_related()利用的是分別查詢每個表，然后用Python處理他們之間的關系。

def prefetch_related(self, *lookups)
    #性能相關：多表連表操作時速度會慢，使用其執行多次SQL查詢在Python代碼中實現連表操作。 

models.Book.objects.prefetch_related('authors').all() #authors是多對多字段

（三）QuerySet的特點

 1、queryset是惰性的

Django的queryset對應於數據庫的若干記錄（row），通過可選的查詢來過濾。例如，下面的代碼會得到數據庫中書名稱為‘Python’的所有書籍：

book_set = models.Book.objects.filter(title="Python").all()

但是 上面的代碼並沒有運行任何的數據庫查詢。要真正從數據庫獲得數據，需要遍歷queryset或者說當用到數據時就會執行sql，去數據庫中查詢：

book_set = models.Book.objects.filter(title="Python").all()

for book in book_set:
    print(book.title)

2、queryset是具有cache的

　　當遍歷queryset時，所有匹配的記錄會從數據庫獲取，然后轉換成Django的model。這些model會保存在queryset內置的cache中，這樣如果再次遍歷這個queryset， 不需要重復運行通用的查詢。

3、queryset的iterator

　　一次性向內存讀入大量的數據，會造成內存的浪費，並且很可能會造成程序的崩潰。要避免在遍歷數據的同時產生queryset cache，可以使用iterator()方法 來獲取數據，處理完數據就將其丟棄。

        book_set= Book.objects.all().iterator()
        # iterator()可以一次只從數據庫獲取少量數據，這樣可以節省內存
        for obj in book_set:
            print(obj.name)

    def iterator(self, chunk_size=2000):
        """
        An iterator over the results from applying this QuerySet to the
        database.
        """
        if chunk_size <= 0:
            raise ValueError('Chunk size must be strictly positive.')
        use_chunked_fetch = not connections[self.db].settings_dict.get('DISABLE_SERVER_SIDE_CURSORS')
        return self._iterator(use_chunked_fetch, chunk_size)

iterator中有默認參數 chunk_size=2000，表示在數據庫驅動程序級別緩存的結果數。

 4、QuerySet源碼

以上的API都是基於django.db.models.query.QuerySet中的API所得，詳情參考：

class QuerySet:
    """Represent a lazy database lookup for a set of objects."""

    def __init__(self, model=None, query=None, using=None, hints=None):
        self.model = model
        self._db = using
        self._hints = hints or {}
        self.query = query or sql.Query(self.model)
        self._result_cache = None
        self._sticky_filter = False
        self._for_write = False
        self._prefetch_related_lookups = ()
        self._prefetch_done = False
        self._known_related_objects = {}  # {rel_field: {pk: rel_obj}}
        self._iterable_class = ModelIterable
        self._fields = None

    def as_manager(cls):
        # Address the circular dependency between `Queryset` and `Manager`.
        from django.db.models.manager import Manager
        manager = Manager.from_queryset(cls)()
        manager._built_with_as_manager = True
        return manager
    as_manager.queryset_only = True
    as_manager = classmethod(as_manager)

    ########################
    # PYTHON MAGIC METHODS #
    ########################

    def __deepcopy__(self, memo):
        """Don't populate the QuerySet's cache."""
        obj = self.__class__()
        for k, v in self.__dict__.items():
            if k == '_result_cache':
                obj.__dict__[k] = None
            else:
                obj.__dict__[k] = copy.deepcopy(v, memo)
        return obj

    def __getstate__(self):
        # Force the cache to be fully populated.
        self._fetch_all()
        obj_dict = self.__dict__.copy()
        obj_dict[DJANGO_VERSION_PICKLE_KEY] = get_version()
        return obj_dict

    def __setstate__(self, state):
        msg = None
        pickled_version = state.get(DJANGO_VERSION_PICKLE_KEY)
        if pickled_version:
            current_version = get_version()
            if current_version != pickled_version:
                msg = (
                    "Pickled queryset instance's Django version %s does not "
                    "match the current version %s." % (pickled_version, current_version)
                )
        else:
            msg = "Pickled queryset instance's Django version is not specified."

        if msg:
            warnings.warn(msg, RuntimeWarning, stacklevel=2)

        self.__dict__.update(state)

    def __repr__(self):
        data = list(self[:REPR_OUTPUT_SIZE + 1])
        if len(data) > REPR_OUTPUT_SIZE:
            data[-1] = "...(remaining elements truncated)..."
        return '<%s %r>' % (self.__class__.__name__, data)

    def __len__(self):
        self._fetch_all()
        return len(self._result_cache)

    def __iter__(self):
        """
        The queryset iterator protocol uses three nested iterators in the
        default case:
            1. sql.compiler:execute_sql()
               - Returns 100 rows at time (constants.GET_ITERATOR_CHUNK_SIZE)
                 using cursor.fetchmany(). This part is responsible for
                 doing some column masking, and returning the rows in chunks.
            2. sql.compiler.results_iter()
               - Returns one row at time. At this point the rows are still just
                 tuples. In some cases the return values are converted to
                 Python values at this location.
            3. self.iterator()
               - Responsible for turning the rows into model objects.
        """
        self._fetch_all()
        return iter(self._result_cache)

    def __bool__(self):
        self._fetch_all()
        return bool(self._result_cache)

    def __getitem__(self, k):
        """Retrieve an item or slice from the set of results."""
        if not isinstance(k, (int, slice)):
            raise TypeError
        assert ((not isinstance(k, slice) and (k >= 0)) or
                (isinstance(k, slice) and (k.start is None or k.start >= 0) and
                 (k.stop is None or k.stop >= 0))), \
            "Negative indexing is not supported."

        if self._result_cache is not None:
            return self._result_cache[k]

        if isinstance(k, slice):
            qs = self._chain()
            if k.start is not None:
                start = int(k.start)
            else:
                start = None
            if k.stop is not None:
                stop = int(k.stop)
            else:
                stop = None
            qs.query.set_limits(start, stop)
            return list(qs)[::k.step] if k.step else qs

        qs = self._chain()
        qs.query.set_limits(k, k + 1)
        qs._fetch_all()
        return qs._result_cache[0]

    def __and__(self, other):
        self._merge_sanity_check(other)
        if isinstance(other, EmptyQuerySet):
            return other
        if isinstance(self, EmptyQuerySet):
            return self
        combined = self._chain()
        combined._merge_known_related_objects(other)
        combined.query.combine(other.query, sql.AND)
        return combined

    def __or__(self, other):
        self._merge_sanity_check(other)
        if isinstance(self, EmptyQuerySet):
            return other
        if isinstance(other, EmptyQuerySet):
            return self
        combined = self._chain()
        combined._merge_known_related_objects(other)
        combined.query.combine(other.query, sql.OR)
        return combined

    ####################################
    # METHODS THAT DO DATABASE QUERIES #
    ####################################

    def _iterator(self, use_chunked_fetch, chunk_size):
        yield from self._iterable_class(self, chunked_fetch=use_chunked_fetch, chunk_size=chunk_size)

    def iterator(self, chunk_size=2000):
        """
        An iterator over the results from applying this QuerySet to the
        database.
        """
        if chunk_size <= 0:
            raise ValueError('Chunk size must be strictly positive.')
        use_chunked_fetch = not connections[self.db].settings_dict.get('DISABLE_SERVER_SIDE_CURSORS')
        return self._iterator(use_chunked_fetch, chunk_size)

    def aggregate(self, *args, **kwargs):
        """
        Return a dictionary containing the calculations (aggregation)
        over the current queryset.

        If args is present the expression is passed as a kwarg using
        the Aggregate object's default alias.
        """
        if self.query.distinct_fields:
            raise NotImplementedError("aggregate() + distinct(fields) not implemented.")
        self._validate_values_are_expressions(args + tuple(kwargs.values()), method_name='aggregate')
        for arg in args:
            # The default_alias property raises TypeError if default_alias
            # can't be set automatically or AttributeError if it isn't an
            # attribute.
            try:
                arg.default_alias
            except (AttributeError, TypeError):
                raise TypeError("Complex aggregates require an alias")
            kwargs[arg.default_alias] = arg

        query = self.query.chain()
        for (alias, aggregate_expr) in kwargs.items():
            query.add_annotation(aggregate_expr, alias, is_summary=True)
            if not query.annotations[alias].contains_aggregate:
                raise TypeError("%s is not an aggregate expression" % alias)
        return query.get_aggregation(self.db, kwargs)

    def count(self):
        """
        Perform a SELECT COUNT() and return the number of records as an
        integer.

        If the QuerySet is already fully cached, return the length of the
        cached results set to avoid multiple SELECT COUNT(*) calls.
        """
        if self._result_cache is not None:
            return len(self._result_cache)

        return self.query.get_count(using=self.db)

    def get(self, *args, **kwargs):
        """
        Perform the query and return a single object matching the given
        keyword arguments.
        """
        clone = self.filter(*args, **kwargs)
        if self.query.can_filter() and not self.query.distinct_fields:
            clone = clone.order_by()
        num = len(clone)
        if num == 1:
            return clone._result_cache[0]
        if not num:
            raise self.model.DoesNotExist(
                "%s matching query does not exist." %
                self.model._meta.object_name
            )
        raise self.model.MultipleObjectsReturned(
            "get() returned more than one %s -- it returned %s!" %
            (self.model._meta.object_name, num)
        )

    def create(self, **kwargs):
        """
        Create a new object with the given kwargs, saving it to the database
        and returning the created object.
        """
        obj = self.model(**kwargs)
        self._for_write = True
        obj.save(force_insert=True, using=self.db)
        return obj

    def _populate_pk_values(self, objs):
        for obj in objs:
            if obj.pk is None:
                obj.pk = obj._meta.pk.get_pk_value_on_save(obj)

    def bulk_create(self, objs, batch_size=None):
        """
        Insert each of the instances into the database. Do *not* call
        save() on each of the instances, do not send any pre/post_save
        signals, and do not set the primary key attribute if it is an
        autoincrement field (except if features.can_return_ids_from_bulk_insert=True).
        Multi-table models are not supported.
        """
        # When you bulk insert you don't get the primary keys back (if it's an
        # autoincrement, except if can_return_ids_from_bulk_insert=True), so
        # you can't insert into the child tables which references this. There
        # are two workarounds:
        # 1) This could be implemented if you didn't have an autoincrement pk
        # 2) You could do it by doing O(n) normal inserts into the parent
        #    tables to get the primary keys back and then doing a single bulk
        #    insert into the childmost table.
        # We currently set the primary keys on the objects when using
        # PostgreSQL via the RETURNING ID clause. It should be possible for
        # Oracle as well, but the semantics for  extracting the primary keys is
        # trickier so it's not done yet.
        assert batch_size is None or batch_size > 0
        # Check that the parents share the same concrete model with the our
        # model to detect the inheritance pattern ConcreteGrandParent ->
        # MultiTableParent -> ProxyChild. Simply checking self.model._meta.proxy
        # would not identify that case as involving multiple tables.
        for parent in self.model._meta.get_parent_list():
            if parent._meta.concrete_model is not self.model._meta.concrete_model:
                raise ValueError("Can't bulk create a multi-table inherited model")
        if not objs:
            return objs
        self._for_write = True
        connection = connections[self.db]
        fields = self.model._meta.concrete_fields
        objs = list(objs)
        self._populate_pk_values(objs)
        with transaction.atomic(using=self.db, savepoint=False):
            objs_with_pk, objs_without_pk = partition(lambda o: o.pk is None, objs)
            if objs_with_pk:
                self._batched_insert(objs_with_pk, fields, batch_size)
            if objs_without_pk:
                fields = [f for f in fields if not isinstance(f, AutoField)]
                ids = self._batched_insert(objs_without_pk, fields, batch_size)
                if connection.features.can_return_ids_from_bulk_insert:
                    assert len(ids) == len(objs_without_pk)
                for obj_without_pk, pk in zip(objs_without_pk, ids):
                    obj_without_pk.pk = pk
                    obj_without_pk._state.adding = False
                    obj_without_pk._state.db = self.db

        return objs

    def get_or_create(self, defaults=None, **kwargs):
        """
        Look up an object with the given kwargs, creating one if necessary.
        Return a tuple of (object, created), where created is a boolean
        specifying whether an object was created.
        """
        lookup, params = self._extract_model_params(defaults, **kwargs)
        # The get() needs to be targeted at the write database in order
        # to avoid potential transaction consistency problems.
        self._for_write = True
        try:
            return self.get(**lookup), False
        except self.model.DoesNotExist:
            return self._create_object_from_params(lookup, params)

    def update_or_create(self, defaults=None, **kwargs):
        """
        Look up an object with the given kwargs, updating one with defaults
        if it exists, otherwise create a new one.
        Return a tuple (object, created), where created is a boolean
        specifying whether an object was created.
        """
        defaults = defaults or {}
        lookup, params = self._extract_model_params(defaults, **kwargs)
        self._for_write = True
        with transaction.atomic(using=self.db):
            try:
                obj = self.select_for_update().get(**lookup)
            except self.model.DoesNotExist:
                obj, created = self._create_object_from_params(lookup, params)
                if created:
                    return obj, created
            for k, v in defaults.items():
                setattr(obj, k, v() if callable(v) else v)
            obj.save(using=self.db)
        return obj, False

    def _create_object_from_params(self, lookup, params):
        """
        Try to create an object using passed params. Used by get_or_create()
        and update_or_create().
        """
        try:
            with transaction.atomic(using=self.db):
                params = {k: v() if callable(v) else v for k, v in params.items()}
                obj = self.create(**params)
            return obj, True
        except IntegrityError as e:
            try:
                return self.get(**lookup), False
            except self.model.DoesNotExist:
                pass
            raise e

    def _extract_model_params(self, defaults, **kwargs):
        """
        Prepare `lookup` (kwargs that are valid model attributes), `params`
        (for creating a model instance) based on given kwargs; for use by
        get_or_create() and update_or_create().
        """
        defaults = defaults or {}
        lookup = kwargs.copy()
        for f in self.model._meta.fields:
            if f.attname in lookup:
                lookup[f.name] = lookup.pop(f.attname)
        params = {k: v for k, v in kwargs.items() if LOOKUP_SEP not in k}
        params.update(defaults)
        property_names = self.model._meta._property_names
        invalid_params = []
        for param in params:
            try:
                self.model._meta.get_field(param)
            except exceptions.FieldDoesNotExist:
                # It's okay to use a model's property if it has a setter.
                if not (param in property_names and getattr(self.model, param).fset):
                    invalid_params.append(param)
        if invalid_params:
            raise exceptions.FieldError(
                "Invalid field name(s) for model %s: '%s'." % (
                    self.model._meta.object_name,
                    "', '".join(sorted(invalid_params)),
                ))
        return lookup, params

    def _earliest_or_latest(self, *fields, field_name=None):
        """
        Return the latest object, according to the model's
        'get_latest_by' option or optional given field_name.
        """
        if fields and field_name is not None:
            raise ValueError('Cannot use both positional arguments and the field_name keyword argument.')

        order_by = None
        if field_name is not None:
            warnings.warn(
                'The field_name keyword argument to earliest() and latest() '
                'is deprecated in favor of passing positional arguments.',
                RemovedInDjango30Warning,
            )
            order_by = (field_name,)
        elif fields:
            order_by = fields
        else:
            order_by = getattr(self.model._meta, 'get_latest_by')
            if order_by and not isinstance(order_by, (tuple, list)):
                order_by = (order_by,)
        if order_by is None:
            raise ValueError(
                "earliest() and latest() require either fields as positional "
                "arguments or 'get_latest_by' in the model's Meta."
            )

        assert self.query.can_filter(), \
            "Cannot change a query once a slice has been taken."
        obj = self._chain()
        obj.query.set_limits(high=1)
        obj.query.clear_ordering(force_empty=True)
        obj.query.add_ordering(*order_by)
        return obj.get()

    def earliest(self, *fields, field_name=None):
        return self._earliest_or_latest(*fields, field_name=field_name)

    def latest(self, *fields, field_name=None):
        return self.reverse()._earliest_or_latest(*fields, field_name=field_name)

    def first(self):
        """Return the first object of a query or None if no match is found."""
        for obj in (self if self.ordered else self.order_by('pk'))[:1]:
            return obj

    def last(self):
        """Return the last object of a query or None if no match is found."""
        for obj in (self.reverse() if self.ordered else self.order_by('-pk'))[:1]:
            return obj

    def in_bulk(self, id_list=None, *, field_name='pk'):
        """
        Return a dictionary mapping each of the given IDs to the object with
        that ID. If `id_list` isn't provided, evaluate the entire QuerySet.
        """
        assert self.query.can_filter(), \
            "Cannot use 'limit' or 'offset' with in_bulk"
        if field_name != 'pk' and not self.model._meta.get_field(field_name).unique:
            raise ValueError("in_bulk()'s field_name must be a unique field but %r isn't." % field_name)
        if id_list is not None:
            if not id_list:
                return {}
            filter_key = '{}__in'.format(field_name)
            batch_size = connections[self.db].features.max_query_params
            id_list = tuple(id_list)
            # If the database has a limit on the number of query parameters
            # (e.g. SQLite), retrieve objects in batches if necessary.
            if batch_size and batch_size < len(id_list):
                qs = ()
                for offset in range(0, len(id_list), batch_size):
                    batch = id_list[offset:offset + batch_size]
                    qs += tuple(self.filter(**{filter_key: batch}).order_by())
            else:
                qs = self.filter(**{filter_key: id_list}).order_by()
        else:
            qs = self._chain()
        return {getattr(obj, field_name): obj for obj in qs}

    def delete(self):
        """Delete the records in the current QuerySet."""
        assert self.query.can_filter(), \
            "Cannot use 'limit' or 'offset' with delete."

        if self._fields is not None:
            raise TypeError("Cannot call delete() after .values() or .values_list()")

        del_query = self._chain()

        # The delete is actually 2 queries - one to find related objects,
        # and one to delete. Make sure that the discovery of related
        # objects is performed on the same database as the deletion.
        del_query._for_write = True

        # Disable non-supported fields.
        del_query.query.select_for_update = False
        del_query.query.select_related = False
        del_query.query.clear_ordering(force_empty=True)

        collector = Collector(using=del_query.db)
        collector.collect(del_query)
        deleted, _rows_count = collector.delete()

        # Clear the result cache, in case this QuerySet gets reused.
        self._result_cache = None
        return deleted, _rows_count

    delete.alters_data = True
    delete.queryset_only = True

    def _raw_delete(self, using):
        """
        Delete objects found from the given queryset in single direct SQL
        query. No signals are sent and there is no protection for cascades.
        """
        return sql.DeleteQuery(self.model).delete_qs(self, using)
    _raw_delete.alters_data = True

    def update(self, **kwargs):
        """
        Update all elements in the current QuerySet, setting all the given
        fields to the appropriate values.
        """
        assert self.query.can_filter(), \
            "Cannot update a query once a slice has been taken."
        self._for_write = True
        query = self.query.chain(sql.UpdateQuery)
        query.add_update_values(kwargs)
        # Clear any annotations so that they won't be present in subqueries.
        query._annotations = None
        with transaction.atomic(using=self.db, savepoint=False):
            rows = query.get_compiler(self.db).execute_sql(CURSOR)
        self._result_cache = None
        return rows
    update.alters_data = True

    def _update(self, values):
        """
        A version of update() that accepts field objects instead of field names.
        Used primarily for model saving and not intended for use by general
        code (it requires too much poking around at model internals to be
        useful at that level).
        """
        assert self.query.can_filter(), \
            "Cannot update a query once a slice has been taken."
        query = self.query.chain(sql.UpdateQuery)
        query.add_update_fields(values)
        self._result_cache = None
        return query.get_compiler(self.db).execute_sql(CURSOR)
    _update.alters_data = True
    _update.queryset_only = False

    def exists(self):
        if self._result_cache is None:
            return self.query.has_results(using=self.db)
        return bool(self._result_cache)

    def _prefetch_related_objects(self):
        # This method can only be called once the result cache has been filled.
        prefetch_related_objects(self._result_cache, *self._prefetch_related_lookups)
        self._prefetch_done = True

    ##################################################
    # PUBLIC METHODS THAT RETURN A QUERYSET SUBCLASS #
    ##################################################

    def raw(self, raw_query, params=None, translations=None, using=None):
        if using is None:
            using = self.db
        return RawQuerySet(raw_query, model=self.model, params=params, translations=translations, using=using)

    def _values(self, *fields, **expressions):
        clone = self._chain()
        if expressions:
            clone = clone.annotate(**expressions)
        clone._fields = fields
        clone.query.set_values(fields)
        return clone

    def values(self, *fields, **expressions):
        fields += tuple(expressions)
        clone = self._values(*fields, **expressions)
        clone._iterable_class = ValuesIterable
        return clone

    def values_list(self, *fields, flat=False, named=False):
        if flat and named:
            raise TypeError("'flat' and 'named' can't be used together.")
        if flat and len(fields) > 1:
            raise TypeError("'flat' is not valid when values_list is called with more than one field.")

        field_names = {f for f in fields if not hasattr(f, 'resolve_expression')}
        _fields = []
        expressions = {}
        counter = 1
        for field in fields:
            if hasattr(field, 'resolve_expression'):
                field_id_prefix = getattr(field, 'default_alias', field.__class__.__name__.lower())
                while True:
                    field_id = field_id_prefix + str(counter)
                    counter += 1
                    if field_id not in field_names:
                        break
                expressions[field_id] = field
                _fields.append(field_id)
            else:
                _fields.append(field)

        clone = self._values(*_fields, **expressions)
        clone._iterable_class = (
            NamedValuesListIterable if named
            else FlatValuesListIterable if flat
            else ValuesListIterable
        )
        return clone

    def dates(self, field_name, kind, order='ASC'):
        """
        Return a list of date objects representing all available dates for
        the given field_name, scoped to 'kind'.
        """
        assert kind in ("year", "month", "day"), \
            "'kind' must be one of 'year', 'month' or 'day'."
        assert order in ('ASC', 'DESC'), \
            "'order' must be either 'ASC' or 'DESC'."
        return self.annotate(
            datefield=Trunc(field_name, kind, output_field=DateField()),
            plain_field=F(field_name)
        ).values_list(
            'datefield', flat=True
        ).distinct().filter(plain_field__isnull=False).order_by(('-' if order == 'DESC' else '') + 'datefield')

    def datetimes(self, field_name, kind, order='ASC', tzinfo=None):
        """
        Return a list of datetime objects representing all available
        datetimes for the given field_name, scoped to 'kind'.
        """
        assert kind in ("year", "month", "day", "hour", "minute", "second"), \
            "'kind' must be one of 'year', 'month', 'day', 'hour', 'minute' or 'second'."
        assert order in ('ASC', 'DESC'), \
            "'order' must be either 'ASC' or 'DESC'."
        if settings.USE_TZ:
            if tzinfo is None:
                tzinfo = timezone.get_current_timezone()
        else:
            tzinfo = None
        return self.annotate(
            datetimefield=Trunc(field_name, kind, output_field=DateTimeField(), tzinfo=tzinfo),
            plain_field=F(field_name)
        ).values_list(
            'datetimefield', flat=True
        ).distinct().filter(plain_field__isnull=False).order_by(('-' if order == 'DESC' else '') + 'datetimefield')

    def none(self):
        """Return an empty QuerySet."""
        clone = self._chain()
        clone.query.set_empty()
        return clone

    ##################################################################
    # PUBLIC METHODS THAT ALTER ATTRIBUTES AND RETURN A NEW QUERYSET #
    ##################################################################

    def all(self):
        """
        Return a new QuerySet that is a copy of the current one. This allows a
        QuerySet to proxy for a model manager in some cases.
        """
        return self._chain()

    def filter(self, *args, **kwargs):
        """
        Return a new QuerySet instance with the args ANDed to the existing
        set.
        """
        return self._filter_or_exclude(False, *args, **kwargs)

    def exclude(self, *args, **kwargs):
        """
        Return a new QuerySet instance with NOT (args) ANDed to the existing
        set.
        """
        return self._filter_or_exclude(True, *args, **kwargs)

    def _filter_or_exclude(self, negate, *args, **kwargs):
        if args or kwargs:
            assert self.query.can_filter(), \
                "Cannot filter a query once a slice has been taken."

        clone = self._chain()
        if negate:
            clone.query.add_q(~Q(*args, **kwargs))
        else:
            clone.query.add_q(Q(*args, **kwargs))
        return clone

    def complex_filter(self, filter_obj):
        """
        Return a new QuerySet instance with filter_obj added to the filters.

        filter_obj can be a Q object or a dictionary of keyword lookup
        arguments.

        This exists to support framework features such as 'limit_choices_to',
        and usually it will be more natural to use other methods.
        """
        if isinstance(filter_obj, Q):
            clone = self._chain()
            clone.query.add_q(filter_obj)
            return clone
        else:
            return self._filter_or_exclude(None, **filter_obj)

    def _combinator_query(self, combinator, *other_qs, all=False):
        # Clone the query to inherit the select list and everything
        clone = self._chain()
        # Clear limits and ordering so they can be reapplied
        clone.query.clear_ordering(True)
        clone.query.clear_limits()
        clone.query.combined_queries = (self.query,) + tuple(qs.query for qs in other_qs)
        clone.query.combinator = combinator
        clone.query.combinator_all = all
        return clone

    def union(self, *other_qs, all=False):
        # If the query is an EmptyQuerySet, combine all nonempty querysets.
        if isinstance(self, EmptyQuerySet):
            qs = [q for q in other_qs if not isinstance(q, EmptyQuerySet)]
            return qs[0]._combinator_query('union', *qs[1:], all=all) if qs else self
        return self._combinator_query('union', *other_qs, all=all)

    def intersection(self, *other_qs):
        # If any query is an EmptyQuerySet, return it.
        if isinstance(self, EmptyQuerySet):
            return self
        for other in other_qs:
            if isinstance(other, EmptyQuerySet):
                return other
        return self._combinator_query('intersection', *other_qs)

    def difference(self, *other_qs):
        # If the query is an EmptyQuerySet, return it.
        if isinstance(self, EmptyQuerySet):
            return self
        return self._combinator_query('difference', *other_qs)

    def select_for_update(self, nowait=False, skip_locked=False, of=()):
        """
        Return a new QuerySet instance that will select objects with a
        FOR UPDATE lock.
        """
        if nowait and skip_locked:
            raise ValueError('The nowait option cannot be used with skip_locked.')
        obj = self._chain()
        obj._for_write = True
        obj.query.select_for_update = True
        obj.query.select_for_update_nowait = nowait
        obj.query.select_for_update_skip_locked = skip_locked
        obj.query.select_for_update_of = of
        return obj

    def select_related(self, *fields):
        """
        Return a new QuerySet instance that will select related objects.

        If fields are specified, they must be ForeignKey fields and only those
        related objects are included in the selection.

        If select_related(None) is called, clear the list.
        """

        if self._fields is not None:
            raise TypeError("Cannot call select_related() after .values() or .values_list()")

        obj = self._chain()
        if fields == (None,):
            obj.query.select_related = False
        elif fields:
            obj.query.add_select_related(fields)
        else:
            obj.query.select_related = True
        return obj

    def prefetch_related(self, *lookups):
        """
        Return a new QuerySet instance that will prefetch the specified
        Many-To-One and Many-To-Many related objects when the QuerySet is
        evaluated.

        When prefetch_related() is called more than once, append to the list of
        prefetch lookups. If prefetch_related(None) is called, clear the list.
        """
        clone = self._chain()
        if lookups == (None,):
            clone._prefetch_related_lookups = ()
        else:
            for lookup in lookups:
                if isinstance(lookup, Prefetch):
                    lookup = lookup.prefetch_to
                lookup = lookup.split(LOOKUP_SEP, 1)[0]
                if lookup in self.query._filtered_relations:
                    raise ValueError('prefetch_related() is not supported with FilteredRelation.')
            clone._prefetch_related_lookups = clone._prefetch_related_lookups + lookups
        return clone

    def annotate(self, *args, **kwargs):
        """
        Return a query set in which the returned objects have been annotated
        with extra data or aggregations.
        """
        self._validate_values_are_expressions(args + tuple(kwargs.values()), method_name='annotate')
        annotations = OrderedDict()  # To preserve ordering of args
        for arg in args:
            # The default_alias property may raise a TypeError.
            try:
                if arg.default_alias in kwargs:
                    raise ValueError("The named annotation '%s' conflicts with the "
                                     "default name for another annotation."
                                     % arg.default_alias)
            except TypeError:
                raise TypeError("Complex annotations require an alias")
            annotations[arg.default_alias] = arg
        annotations.update(kwargs)

        clone = self._chain()
        names = self._fields
        if names is None:
            names = {f.name for f in self.model._meta.get_fields()}

        for alias, annotation in annotations.items():
            if alias in names:
                raise ValueError("The annotation '%s' conflicts with a field on "
                                 "the model." % alias)
            if isinstance(annotation, FilteredRelation):
                clone.query.add_filtered_relation(annotation, alias)
            else:
                clone.query.add_annotation(annotation, alias, is_summary=False)

        for alias, annotation in clone.query.annotations.items():
            if alias in annotations and annotation.contains_aggregate:
                if clone._fields is None:
                    clone.query.group_by = True
                else:
                    clone.query.set_group_by()
                break

        return clone

    def order_by(self, *field_names):
        """Return a new QuerySet instance with the ordering changed."""
        assert self.query.can_filter(), \
            "Cannot reorder a query once a slice has been taken."
        obj = self._chain()
        obj.query.clear_ordering(force_empty=False)
        obj.query.add_ordering(*field_names)
        return obj

    def distinct(self, *field_names):
        """
        Return a new QuerySet instance that will select only distinct results.
        """
        assert self.query.can_filter(), \
            "Cannot create distinct fields once a slice has been taken."
        obj = self._chain()
        obj.query.add_distinct_fields(*field_names)
        return obj

    def extra(self, select=None, where=None, params=None, tables=None,
              order_by=None, select_params=None):
        """Add extra SQL fragments to the query."""
        assert self.query.can_filter(), \
            "Cannot change a query once a slice has been taken"
        clone = self._chain()
        clone.query.add_extra(select, select_params, where, params, tables, order_by)
        return clone

    def reverse(self):
        """Reverse the ordering of the QuerySet."""
        if not self.query.can_filter():
            raise TypeError('Cannot reverse a query once a slice has been taken.')
        clone = self._chain()
        clone.query.standard_ordering = not clone.query.standard_ordering
        return clone

    def defer(self, *fields):
        """
        Defer the loading of data for certain fields until they are accessed.
        Add the set of deferred fields to any existing set of deferred fields.
        The only exception to this is if None is passed in as the only
        parameter, in which case removal all deferrals.
        """
        if self._fields is not None:
            raise TypeError("Cannot call defer() after .values() or .values_list()")
        clone = self._chain()
        if fields == (None,):
            clone.query.clear_deferred_loading()
        else:
            clone.query.add_deferred_loading(fields)
        return clone

    def only(self, *fields):
        """
        Essentially, the opposite of defer(). Only the fields passed into this
        method and that are not already specified as deferred are loaded
        immediately when the queryset is evaluated.
        """
        if self._fields is not None:
            raise TypeError("Cannot call only() after .values() or .values_list()")
        if fields == (None,):
            # Can only pass None to defer(), not only(), as the rest option.
            # That won't stop people trying to do this, so let's be explicit.
            raise TypeError("Cannot pass None as an argument to only().")
        for field in fields:
            field = field.split(LOOKUP_SEP, 1)[0]
            if field in self.query._filtered_relations:
                raise ValueError('only() is not supported with FilteredRelation.')
        clone = self._chain()
        clone.query.add_immediate_loading(fields)
        return clone

    def using(self, alias):
        """Select which database this QuerySet should execute against."""
        clone = self._chain()
        clone._db = alias
        return clone

    ###################################
    # PUBLIC INTROSPECTION ATTRIBUTES #
    ###################################

    @property
    def ordered(self):
        """
        Return True if the QuerySet is ordered -- i.e. has an order_by()
        clause or a default ordering on the model.
        """
        if self.query.extra_order_by or self.query.order_by:
            return True
        elif self.query.default_ordering and self.query.get_meta().ordering:
            return True
        else:
            return False

    @property
    def db(self):
        """Return the database used if this query is executed now."""
        if self._for_write:
            return self._db or router.db_for_write(self.model, **self._hints)
        return self._db or router.db_for_read(self.model, **self._hints)

    ###################
    # PRIVATE METHODS #
    ###################

    def _insert(self, objs, fields, return_id=False, raw=False, using=None):
        """
        Insert a new record for the given model. This provides an interface to
        the InsertQuery class and is how Model.save() is implemented.
        """
        self._for_write = True
        if using is None:
            using = self.db
        query = sql.InsertQuery(self.model)
        query.insert_values(fields, objs, raw=raw)
        return query.get_compiler(using=using).execute_sql(return_id)
    _insert.alters_data = True
    _insert.queryset_only = False

    def _batched_insert(self, objs, fields, batch_size):
        """
        A helper method for bulk_create() to insert the bulk one batch at a
        time. Insert recursively a batch from the front of the bulk and then
        _batched_insert() the remaining objects again.
        """
        if not objs:
            return
        ops = connections[self.db].ops
        batch_size = (batch_size or max(ops.bulk_batch_size(fields, objs), 1))
        inserted_ids = []
        for item in [objs[i:i + batch_size] for i in range(0, len(objs), batch_size)]:
            if connections[self.db].features.can_return_ids_from_bulk_insert:
                inserted_id = self._insert(item, fields=fields, using=self.db, return_id=True)
                if isinstance(inserted_id, list):
                    inserted_ids.extend(inserted_id)
                else:
                    inserted_ids.append(inserted_id)
            else:
                self._insert(item, fields=fields, using=self.db)
        return inserted_ids

    def _chain(self, **kwargs):
        """
        Return a copy of the current QuerySet that's ready for another
        operation.
        """
        obj = self._clone()
        if obj._sticky_filter:
            obj.query.filter_is_sticky = True
            obj._sticky_filter = False
        obj.__dict__.update(kwargs)
        return obj

    def _clone(self):
        """
        Return a copy of the current QuerySet. A lightweight alternative
        to deepcopy().
        """
        c = self.__class__(model=self.model, query=self.query.chain(), using=self._db, hints=self._hints)
        c._sticky_filter = self._sticky_filter
        c._for_write = self._for_write
        c._prefetch_related_lookups = self._prefetch_related_lookups[:]
        c._known_related_objects = self._known_related_objects
        c._iterable_class = self._iterable_class
        c._fields = self._fields
        return c

    def _fetch_all(self):
        if self._result_cache is None:
            self._result_cache = list(self._iterable_class(self))
        if self._prefetch_related_lookups and not self._prefetch_done:
            self._prefetch_related_objects()

    def _next_is_sticky(self):
        """
        Indicate that the next filter call and the one following that should
        be treated as a single filter. This is only important when it comes to
        determining when to reuse tables for many-to-many filters. Required so
        that we can filter naturally on the results of related managers.

        This doesn't return a clone of the current QuerySet (it returns
        "self"). The method is only used internally and should be immediately
        followed by a filter() that does create a clone.
        """
        self._sticky_filter = True
        return self

    def _merge_sanity_check(self, other):
        """Check that two QuerySet classes may be merged."""
        if self._fields is not None and (
                set(self.query.values_select) != set(other.query.values_select) or
                set(self.query.extra_select) != set(other.query.extra_select) or
                set(self.query.annotation_select) != set(other.query.annotation_select)):
            raise TypeError(
                "Merging '%s' classes must involve the same values in each case."
                % self.__class__.__name__
            )

    def _merge_known_related_objects(self, other):
        """
        Keep track of all known related objects from either QuerySet instance.
        """
        for field, objects in other._known_related_objects.items():
            self._known_related_objects.setdefault(field, {}).update(objects)

    def resolve_expression(self, *args, **kwargs):
        if self._fields and len(self._fields) > 1:
            # values() queryset can only be used as nested queries
            # if they are set up to select only a single field.
            raise TypeError('Cannot use multi-field values as a filter value.')
        query = self.query.resolve_expression(*args, **kwargs)
        query._db = self._db
        return query
    resolve_expression.queryset_only = True

    def _add_hints(self, **hints):
        """
        Update hinting information for use by routers. Add new key/values or
        overwrite existing key/values.
        """
        self._hints.update(hints)

    def _has_filters(self):
        """
        Check if this QuerySet has any filtering going on. This isn't
        equivalent with checking if all objects are present in results, for
        example, qs[1:]._has_filters() -> False.
        """
        return self.query.has_filters()

    @staticmethod
    def _validate_values_are_expressions(values, method_name):
        invalid_args = sorted(str(arg) for arg in values if not hasattr(arg, 'resolve_expression'))
        if invalid_args:
            raise TypeError(
                'QuerySet.%s() received non-expression(s): %s.' % (
                    method_name,
                    ', '.join(invalid_args),
                )
            )

參考文章：https://docs.djangoproject.com/en/2.2/ref/models/querysets/

               https://www.cnblogs.com/yuanchenqi/articles/7570003.html