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、删、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、删除操作
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()方法擷取的内容更新的是所有的，效率較低，并且隻能擷取一個對象，而filter()擷取的是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()#對于某一個字段去重
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，是以以它們為例進行增、删、改、查操作：
#方式一： 直接給外鍵的資料庫字段指派
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) - 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() - 雙下劃線方式
#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() #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') - 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表内容',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')#用于反向跨表 - 雙下劃線
#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，是以Book和Author表會生成第三張表，在第三張表中儲存了這兩張表的關系，是以以這兩張表為執行個體進行增、删、改、查操作：
#建構第三張表中的關系
#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)#等同于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]) #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) # 等同于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) 删除操作可以使用clear方法，删除操作也就是j将第三張表中的關系清除掉：
book1.authors.clear() #将與book1對象相關的關系在第三張表所有清空 book1 = Book.objects.get(id=2)
author = Author.objects.filter(id__gt=2)[0]
book1.authors.clear() #clear先将第三張表清空
book1.authors.add(author) #這裡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，不存在就設定，如果不符合條件的删除，重建立立。第三張表id從最後一個開始往上加 4、查找操作
#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) #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。并且可以以清單的形式添加多個
remove() #删除，實際上就是移除掉與指定對象在第三張表中的關系
clear() #也可用于删除，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清單 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比對的對象
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)
# 擷取所有的資料對象 - get(*args,**kwargs)：傳回與所給篩選條件相比對的對象，傳回結果有且隻有一個，如果符合篩選條件的對象超過一個或者沒有都會抛出錯誤。
def get(self, *args, **kwargs):
#傳回一個比對的對象 - values(*field)：傳回一個ValueQuerySet——一個特殊的QuerySet，運作後得到的并不是一系列 model的執行個體化對象，而是一個可疊代的字典序列。
def values(self, *fields):
# 擷取每行資料為字典格式 - exclude(*args,**kwargs)： 它包含了與所給篩選條件不比對的對象。
def exclude(self, *args, **kwargs)
# 條件查詢
# 條件可以是：參數，字典，Q
# 用于取反
models.Book.objects.all().exclude(id__gt=2) - order_by(*field)：對查詢結果排序
# 用于排序
models.Book.objects.all().order_by('-id') - ordered()：如果queryset是有序的就傳回True
# 确認queryset是否已經排好序
order = models.Book.objects.all().ordered() - reverse()：對查詢結果反向排序
# 用于排序後倒序
models.Book.objects.all().order_by('id').reverse() - distinct()：從傳回結果中剔除重複紀錄
# 用于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，它傳回的是一個元組序列，values傳回的是一個字典序列
def values_list(self, *fields, **kwargs):
# 擷取每行資料為元祖 - count()：傳回資料庫中比對查詢(QuerySet)的對象數量。
def count(self):
# 擷取queryset中對象個數 - first()：傳回第一條記錄
def first(self):
# 擷取第一個對象 - last()：傳回最後一條記錄
def last(self):
# 擷取最後一個對象 - exists()：如果QuerySet包含資料，就傳回True，否則傳回False
def exists(self):
# 判斷queryset是否有資料 - only(self, *fields)：僅取某個表中的資料
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，并截取指定内容
def dates(self, field_name, kind, order='ASC'):
# 根據時間對某一部分進行去重查找并截取指定内容
# kind隻能是："year"（年）, "month"（年-月）, "day"（年-月-日）
# order隻能是："ASC" "DESC"
# 并擷取轉換後的時間
- 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并截取指定内容，将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并截取指定内容，将時間轉換為指定時區時間
# kind隻能是 "year", "month", "day", "hour", "minute", "second"
# order隻能是："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、進階用法
- 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，收藏數大于給贊數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，将價格都加10元
Book.objects.all().update(price=F('price')+10)
#字元串拼接
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，而預設的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，如果是字元串（“title”，"price"）應該怎麼處理呢？
q = Q() # 執行個體化一個Q對象
q.connector = "or" # 預設是且的關系，這裡是或的關系
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，隻不過這裡使用的是字元串。
- 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複雜的子查詢：
"""
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用來設定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，它傳回一個包含一些鍵值對的字典。鍵的名稱是聚合值的辨別符，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，也可以将其重新命名：
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，隻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，查詢其它表中的内容
- 分組查詢 annotate(*args, **kwargs)
用于實作聚合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()傳回的字典不同，annotate()的傳回值是一個QuerySet。
3、字段參數查找
字段查找是指定SQL
WHERE
子句的内容的方式。它們被指定為
QuerySet
方法的關鍵字參數，如
filter()
，
exclude()以及
get()等
。
- exact
#精确比對
models.Book.objects.get(id__exact=4)
#SQL等價于：
SELECT ... WHERE id = 4; - iexact
#不區分大小寫的完全比對。
models.Book.objects.get(title__iexact='python')
#SQL等價于：
SELECT ... WHERE name ILIKE 'python'; - contains
#大小寫敏感的比對查詢，帶有%為模糊查詢
models.Book.objects.get(title__contains='python')
#SQL等價于：
SELECT ... WHERE title LIKE '%python%'; - icontains
#大小寫不敏感的比對查詢
models.Book.objects.get(title__icontains='python')
#SQL等價于：
SELECT ... WHERE title LIKE '%python%'; - in
#在給定的可疊代中; 通常是清單，元組或查詢集
models.Book.objects.get(id__in=[1,2])
models.Book.objects.get(id__title='abc')
#SQL等價于：
SELECT ... WHERE id IN (1, 2);
SELECT ... WHERE title IN ('a', 'b', 'c'); - gt
#大小
models.Book.objects.get(id__gt=2)
#SQL等價于：
SELECT ... WHERE id > 2; - gte
#大小等于
models.Book.objects.get(id__gte=2)
#SQL等價于：
SELECT ... WHERE id >= 2; - lt
#小于
models.Book.objects.get(id__lt=2)
#SQL等價于：
SELECT ... WHERE id < 2; - lte
#小于等于
models.Book.objects.get(id__lte=2)
#SQL等價于：
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等價于：
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等價于：
SELECT ... WHERE titleLIKE '%thon'; 注意：iendswith是不區分大小寫開頭
- range
#在某一個範圍内，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等價于：
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等價于：
SELECT ... WHERE title IS NULL; - regex
#區分大小寫的正規表達式比對，正規表達式文法是Python re子產品的文法
models.Book.objects.get(title__regex=r'^(An?|The) +')
#SQL等價于：
SELECT ... WHERE title REGEXP BINARY '^(An?|The) +'; 注意：iregex不區分大小寫的正規表達式比對。并且建議使用原始字元串（例如，
r'foo'
而不是
'foo'
）來傳遞正規表達式文法。
- date
#對于datetime字段，将值轉換為日期。允許連結其他字段查找。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
#對于datetime字段，将值轉換為時間。允許連結其他字段查找。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))) 詳情檢視：https://docs.djangoproject.com/en/2.2/ref/models/querysets/#date
（二）其它API
1、資料庫添加、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) - 擷取或者建立
def get_or_create(self, defaults=None, **kwargs):
# 如果存在，則擷取，否則，建立
# defaults 指定建立時，其他字段的值
obj, created = models.Book.objects.get_or_create(title='aaa', defaults={'publish_id': 2,}) - 更新或者建立
def update_or_create(self, defaults=None, **kwargs):
# 如果存在，則更新，否則，建立
# defaults 指定建立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、資料庫性能相關
- select_related
對于一對一字段（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()函數後，Django會擷取相應外鍵對應的對象，進而在之後需要的時候不必再查詢資料庫了。實際上就是表之間進行join連表操作，一次性擷取關聯的資料。
def select_related(self, *fields)
#表之間進行join連表操作，一次性擷取關聯的資料。
#沒有指定的字段不會緩存，如果要通路的話Django會再次進行SQL查詢。
#使用雙下劃線“__”連接配接字段名來實作指定的遞歸查詢。
models.Book.objects.select_related('publish').all() - prefetch_related
對于多對多字段（ManyToManyField）和一對多字段，可以使用prefetch_related()來進行優化。prefetch_related()利用的是分别查詢每個表，然後用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代碼中實作連表操作。
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對應于資料庫的若幹記錄（row），通過可選的查詢來過濾。例如，下面的代碼會得到資料庫中書名稱為‘Python’的所有書籍：
book_set = models.Book.objects.filter(title="Python").all() 但是 上面的代碼并沒有運作任何的資料庫查詢。要真正從資料庫獲得資料，需要周遊queryset或者說當用到資料時就會執行sql，去資料庫中查詢：
book_set = models.Book.objects.filter(title="Python").all()
for book in book_set:
print(book.title) 2、queryset是具有cache的
當周遊queryset時，所有比對的記錄會從資料庫擷取，然後轉換成Django的model。這些model會儲存在queryset内置的cache中，這樣如果再次周遊這個queryset， 不需要重複運作通用的查詢。
3、queryset的iterator
一次性向記憶體讀入大量的資料，會造成記憶體的浪費，并且很可能會造成程式的崩潰。要避免在周遊資料的同時産生queryset cache，可以使用iterator()方法 來擷取資料，處理完資料就将其丢棄。
book_set= Book.objects.all().iterator()
# iterator()可以一次隻從資料庫擷取少量資料，這樣可以節省記憶體
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
iterator中有預設參數 chunk_size=2000，表示在資料庫驅動程式級别緩存的結果數。
4、QuerySet源碼
以上的API都是基于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),
)
) QuerySet
參考文章：https://docs.djangoproject.com/en/2.2/ref/models/querysets/
https://www.cnblogs.com/yuanchenqi/articles/7570003.html
作者：iveBoy
出處：http://www.cnblogs.com/shenjianping/
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