前面豆子已經陸陸續續地學習了在Django中如何操做數據庫 html
單表的基本操做 http://beanxyz.blog.51cto.com/5570417/1945887 python
常見字段的使用 http://beanxyz.blog.51cto.com/5570417/1945909 數據庫
最基本的查詢方式 http://beanxyz.blog.51cto.com/5570417/1950806 django
一對多的基本操做和實例 http://beanxyz.blog.51cto.com/5570417/1946602 編程
多對多的基本操做和實例 http://beanxyz.blog.51cto.com/5570417/1952243 app
下面補充一些高級操做。
ide
條件的過濾 函數
下面是常見的條件設置,除了能夠基本的filter以外,咱們還有大量的條件語句可使用。 性能
查詢數據庫獲取的QuerySet類型,對於這個類型咱們相似Jquery同樣使用鏈式編程,能夠無限制的經過.來添加新的條件來過濾,能夠看見大部分條件都是經過雙下劃線__來實現的 學習
# 獲取個數 # models.Tb1.objects.filter(name='seven').count() # 大於,小於 # models.Tb1.objects.filter(id__gt=1) # 獲取id大於1的值 # models.Tb1.objects.filter(id__gte=1) # 獲取id大於等於1的值 # models.Tb1.objects.filter(id__lt=10) # 獲取id小於10的值 # models.Tb1.objects.filter(id__lte=10) # 獲取id小於10的值 # models.Tb1.objects.filter(id__lt=10, id__gt=1) # 獲取id大於1 且 小於10的值 # in # models.Tb1.objects.filter(id__in=[11, 22, 33]) # 獲取id等於十一、2二、33的數據 # models.Tb1.objects.exclude(id__in=[11, 22, 33]) # not in # isnull # Entry.objects.filter(pub_date__isnull=True) # contains # models.Tb1.objects.filter(name__contains="ven") # models.Tb1.objects.filter(name__icontains="ven") # icontains大小寫不敏感 # models.Tb1.objects.exclude(name__icontains="ven") # range # models.Tb1.objects.filter(id__range=[1, 2]) # 範圍bettwen and # 其餘相似 # startswith,istartswith, endswith, iendswith, # order by # models.Tb1.objects.filter(name='seven').order_by('id') # asc # models.Tb1.objects.filter(name='seven').order_by('-id') # desc # group by # from django.db.models import Count, Min, Max, Sum # models.Tb1.objects.filter(c1=1).values('id').annotate(c=Count('num')) # SELECT "app01_tb1"."id", COUNT("app01_tb1"."num") AS "c" FROM "app01_tb1" WHERE "app01_tb1"."c1" = 1 GROUP BY "app01_tb1"."id" # limit 、offset # models.Tb1.objects.all()[10:20] # regex正則匹配,iregex 不區分大小寫 # Entry.objects.get(title__regex=r'^(An?|The) +') # Entry.objects.get(title__iregex=r'^(an?|the) +') # date # Entry.objects.filter(pub_date__date=datetime.date(2005, 1, 1)) # Entry.objects.filter(pub_date__date__gt=datetime.date(2005, 1, 1)) # year # Entry.objects.filter(pub_date__year=2005) # Entry.objects.filter(pub_date__year__gte=2005) # month # Entry.objects.filter(pub_date__month=12) # Entry.objects.filter(pub_date__month__gte=6) # day # Entry.objects.filter(pub_date__day=3) # Entry.objects.filter(pub_date__day__gte=3) # week_day # Entry.objects.filter(pub_date__week_day=2) # Entry.objects.filter(pub_date__week_day__gte=2) # hour # Event.objects.filter(timestamp__hour=23) # Event.objects.filter(time__hour=5) # Event.objects.filter(timestamp__hour__gte=12) # minute # Event.objects.filter(timestamp__minute=29) # Event.objects.filter(time__minute=46) # Event.objects.filter(timestamp__minute__gte=29) # second # Event.objects.filter(timestamp__second=31) # Event.objects.filter(time__second=2) # Event.objects.filter(timestamp__second__gte=31)
上面這些方法能夠實現大部分常見的簡單查詢過濾。有的時候,咱們須要實現一些更復雜的查詢語句,上面的語句就不夠用了,這個時候能夠經過extra來擴展。例如,主要看看select和where的自定義
# extra # extra(self, select=None, where=None, params=None, tables=None, order_by=None, select_params=None) # Entry.objects.extra(select={'new_id': "select col from sometable where othercol > %s"}, select_params=(1,)) # Entry.objects.extra(where=['headline=%s'], params=['Lennon']) # Entry.objects.extra(where=["foo='a' OR bar = 'a'", "baz = 'a'"]) # Entry.objects.extra(select={'new_id': "select id from tb where id > %s"}, select_params=(1,), order_by=['-nid'])
反向查詢
以前的博文裏面,咱們都是經過正向查找外鍵或者中間表來獲取另一個表的信息;若是但願倒過來,也是經過雙下劃線,好比 表名__字段 這種形式來實現
實例:
3張表,分別是單表,1對多和多對多的關係
#業務線 class Business(models.Model): # id caption = models.CharField(max_length=32) #主機 class Host(models.Model): nid = models.AutoField(primary_key=True) hostname = models.CharField(max_length=32,db_index=True) ip = models.GenericIPAddressField(protocol="ipv4",db_index=True) port = models.IntegerField() b = models.ForeignKey(to="Business", to_field='id') #程序 class Application(models.Model): name = models.CharField(max_length=32,unique=True) r = models.ManyToManyField("Host")
視圖函數
def tt(request): #1對多正向查找 print('1對多正向查找'.center(40, '-')) obj=models.Host.objects.filter(nid__gt=1) print(obj[0].nid,obj[0].hostname,obj[0].b.caption) #一些過濾條件 print('過濾條件'.center(40,'-')) obj=models.Business.objects.filter(caption__contains='SALE').first() print(obj.id,obj.caption) obj=models.Business.objects.all().values('id','caption') print(obj, obj.order_by('id').reverse()) obj=models.Application.objects.filter(name__exact='SQL Server').values('name','r__hostname','r__nid') print(obj) #1對多反向查找 print('1對多反向查找'.center(40,'-')) obj=models.Business.objects.all().values('id','caption','host__ip','host__hostname') print(obj[0]) #多對多正向查找 print('多對多正向查找'.center(40, '-')) obj=models.Application.objects.all().first() print(obj.name, obj.r.all()[0].hostname) #多對多反向查詢 print('多對多反向查找'.center(40, '-')) obj=models.Host.objects.all().filter(nid__gt=1).values('nid','application__name').first() print(obj) return HttpResponse('ok')
執行結果
----------------1對多正向查找----------------- 183 SYDMGM01 SALE ------------------過濾條件------------------ 5 SALE <QuerySet [{'id': 5, 'caption': 'SALE'}, {'id': 19, 'caption': 'IT'}, {'id': 20, 'caption': 'HR'}]> <QuerySet [{'id': 20, 'caption': 'HR'}, {'id': 19, 'caption': 'IT'}, {'id': 5, 'caption': 'SALE'}]> <QuerySet [{'name': 'SQL Server', 'r__hostname': 'SYDMGM01', 'r__nid': 183}, {'name': 'SQL Server', 'r__hostname': 'SYDAV01', 'r__nid': 190}, {'name': 'SQL Server', 'r__hostname': 'SYDMGM02', 'r__nid': 191}]> ----------------1對多反向查找----------------- {'id': 5, 'caption': 'SALE', 'host__ip': '10.2.1.1', 'host__hostname': 'SYDMGM01'} ----------------多對多正向查找----------------- AA SYDMGM01 ----------------多對多反向查找----------------- {'nid': 183, 'application__name': 'AA'}
性能
假設咱們有一個Use表經過外鍵ut綁定了一個UserType表
默認狀況下,若是咱們直接使用下面代碼,若是uses獲取了10行數據,那麼數據庫實際上查詢11次,對user查詢一次,而後在for循環裏面對usertype查詢10次;這樣效率很低
users = models.User.objects.all() for row in users: print(row.user,row.pwd,row.ut_id) print(row.ut.name)
咱們能夠經過select_related進行優化,這樣第一次查詢的時候就進行一個跨表查詢,獲取指定外鍵的全部數據
users = models.User.objects.all().select_related('ut') for row in users: print(row.user,row.pwd,row.ut_id) print(row.ut.name)
若是數據比較多,外鍵也多,那麼速度可能還會比較慢,比較跨表查詢的效率比較低,那麼進一步的咱們能夠經過prefetch_related優化。他的基本原理是進行屢次單表查詢;好比第一次查詢User表,而後第二次查詢外鍵關聯的表,而後把全部數據都放在內存裏面,這樣訪問的速度就會快不少了。
users = models.User.objects.filter(id__gt=30).prefetch_related('ut','tu') # select * from users where id > 30 # 獲取上一步驟中全部的ut_id=[1,2] # select * from user_type where id in [1,2] # select * from user_type where id in [1,2] for row in users: print(row.user,row.pwd,row.ut_id) print(row.ut.name)