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Django 发布时间：2022-04-10 发布网站：大佬教程 code.js-code.com

大佬教程收集整理的这篇文章主要介绍了Django-model进阶(中介模型，查询优化，extra,整体插入)，大佬教程大佬觉得挺不错的，现在分享给大家，也给大家做个参考。

QuerySet

可切片

E internal">记录的数目。和子句。

</td>
<td class="code">
<div class="container">
<div class="line number1 index0 alt2"><code class="sql plain">>>> Entry.objects.<code class="sql color1">all<code class="sql plain">()[:5] # (LIMIT5)

</td>

</tr>

</table>

>>> Entry.objects.all()[5:10]    # (OFFSET5LIMIT5)

不支持负的索引（例如）。通常，的切片返回一个新的—— 它不会执行查询。

可迭代

articleListmodels.Article.objects.<span style="color: #0000ff;">for article <span style="color: #808080;">in<span style="color: #000000;"> articleList:
<span style="color: #0000ff;">print(article.title)

惰性查询

是惰性执行的 —— 创建不会带来任何数据库的访问。需要求值时，Django 才会真正运行这个查询。

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number1 index0 alt2">s.Article.objects.

 
number2 index1 alt1">
number3 index2 alt2">

number4 index3 alt1">
number5 index4 alt2">  

number6 index5 alt1">titlE) # hits 






E internal">的结果时才会到数据库中去获取它们。E internal">通过访问数据库来求值。何时计算查询集。
缓存机制
E internal">都包含一个缓存来最小化对数据库的访问。
E internal">中，缓存为空。E internal">进行求值 —— 同时发生数据库查询 ——Django 将保存查询的结果到E internal">的缓存中并返回明确请求的结果（例如，如果正在迭代E internal">，则返回下一个结果）。197" class="yiyi-st">接下来对该E internal">的求值将重用缓存的结果。
E internal">使用不当的话，它会坑你的。E internal">，对它们求值，然后扔掉它们：



  

  






Article并重新使用它：

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number1 index0 alt2">s.Article.objects.
number2 index1 alt1">title   

number3 index2 alt2">create_time   






@H_673_140@




>> queryset  

>>  

>>  






然而，如果已经对全部查询集求值过，则将检查缓存：

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number1 index0 alt2">1
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number4 index3 alt1">4
number1 index0 alt2">>> queryset  .objects.
number2 index1 alt1">>> [entry   

number3 index2 alt2">>>  

number4 index3 alt1">>>  






下面是一些其它例子，它们会使得全部的查询集被求值并填充到缓存中：





>> [entry   

>> 

>> entry  

>>












exists()与iterator()方法
exists：
简单的使用if语句进行判断也会完全执行整个queryset并且把数据放入cache，虽然你并不需要这些 数据！为了避免这个，可以用exists()方法来检查是否有数据：
 
        ()

iterator:
当queryset非常巨大时，cache会成为问题。
处理成千上万的记录时，将它们一次装入内存是很浪费的。更糟糕的是，巨大的queryset可能会锁住系统 进程，让你的程序濒临崩溃。要避免在遍历数据的同时产生queryset cache，可以使用iterator()方法 来获取数据，处理完数据就将其丢弃。

objs =.objects.all().iterator()

 obj titlE)

 obj (obj.titlE)


当然，使用iterator()方法来防止生成cache，意味着遍历同一个queryset时会重复执行查询。所以使 #用iterator()的时候要当心，确保你的代码在操作一个大的queryset时没有重复执行查询。
总结:
queryset的cache是用于减少程序对数据库的查询，在通常的使用下会保证只有在需要的时候才会查询数据库。 使用exists()和iterator()方法可以优化程序对内存的使用。不过，由于它们并不会生成queryset cache，可能 会造成额外的数据库查询。　

中介模型
 就可以了。可能需要关联数据到两个模型之间的关系上。
表示小组和成员之间的多对多关系。
字段将使用参数指向中介模型。





















  


 

 


 

 


 

 

 


 

 


 

 

 

 

 






来使用中介模型（在这个例子中就是），接下来你要开始创建多对多关系。

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number1 index0 alt2">>> ringo  .objects.create(nameString">"Ringo Starr"
number2 index1 alt1">>> paul  .objects.create(nameString">"Paul McCartney"

number3 index2 alt2">>> beatles  .objects.create(nameString">"The Beatles"

number4 index3 alt1">>> m1  

number5 index4 alt2">

number6 index5 alt1">String">"Needed a new drummer."

number7 index6 alt2">>> m1.save()
number8 index7 alt1">>> beatles.members.

number9 index8 alt2">]
number10 index9 alt1">>> ringo.group_set.

number11 index10 alt2">]
number12 index11 alt1">>> m2  .objects.create(person

number13 index12 alt2">

number14 index13 alt1">String">"Wanted to form a band."

number15 index14 alt2">>> beatles.members.

number16 index15 alt1">,]





与普通的多对多字段不同，你不能使用、和赋值语句（比如，s.members）来创建关系：








>> beatles.members.add(john)

>> beatles.members.create(name


>> beatles.members  






和之间的关联关系，你还要指定模型中所需要的所有信息；、和赋值语句是做不到这一点的。
方法被禁用也是出于同样的原因。方法却是可用的。它可以清空某个实例所有的多对多关系：

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number1 index0 alt2">>> 
number2 index1 alt1">>> beatles.members.clear()
number3 index2 alt2">>> deletes thE intermediate model instances
number4 index3 alt1">>> Membership.objects.

number5 index4 alt2">







查询优化
表数据

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number1 index0 alt2">
number2 index1 alt1">String">""String">"

number3 index2 alt2">String">用户信息

number4 index3 alt1">String">"String">""

number5 index4 alt2">.bigAutoField(priMary_key=

number6 index5 alt1">s.CharField(verbose_name=String">'昵称'

number7 index6 alt2">s.CharField(max_length=11,blank=String">'手机号码'

number8 index7 alt1">s.FileField(verbose_name=String">'头像'String">'avatar/'String">"/avatar/default.png"

number9 index8 alt2">create_time = models.datetiR_30_11845@eField(verbose_name=String">'创建时间'

number10 index9 alt1">
number11 index10 alt2">s.ManyToManyField(verbose_name=String">'粉丝们'

number12 index11 alt1">String">'UserInfo'

number13 index12 alt2">String">'UserFans'

number14 index13 alt1">String">'f'

number15 index14 alt2">String">'user'String">'follower'

number16 index15 alt1">
number17 index16 alt2">

number18 index17 alt1"> 

number19 index18 alt2">
number20 index19 alt1">s.Model):
number21 index20 alt2">String">""String">"

number22 index21 alt1">String">互粉关系表

number23 index22 alt2">String">"String">""

number24 index23 alt1">s.AutoField(priMary_key=

number25 index24 alt2"> s.ForeignKey(verbose_name=String">'博主'String">'UserInfo'String">'nid'String">'users'

number26 index25 alt1">s.ForeignKey(verbose_name=String">'粉丝'String">'followers'

number27 index26 alt2">
number28 index27 alt1">s.Model):
number29 index28 alt2">
number30 index29 alt1">String">""String">"

number31 index30 alt2">String">博客信息

number32 index31 alt1">String">"String">""

number33 index32 alt2">.bigAutoField(priMary_key=

number34 index33 alt1">title = models.CharField(verbose_name=String">'个人博客标题'

number35 index34 alt2">s.CharField(verbose_name=String">'个人博客后缀'

number36 index35 alt1">s.CharField(verbose_name=String">'博客主题'

number37 index36 alt2"> s.OneToOneField(String">'UserInfo'String">'nid'

number38 index37 alt1">

number39 index38 alt2"> title

number40 index39 alt1">
number41 index40 alt2">s.Model):
number42 index41 alt1">String">""String">"

number43 index42 alt2">String">博主个人文章分类表

number44 index43 alt1">String">"String">""

number45 index44 alt2">s.AutoField(priMary_key=

number46 index45 alt1">title = models.CharField(verbose_name=String">'分类标题'

number47 index46 alt2">
number48 index47 alt1">s.ForeignKey(verbose_name=String">'所属博客'String">'Blog'String">'nid'

number49 index48 alt2">
number50 index49 alt1">s.Model):
number51 index50 alt2">
number52 index51 alt1">.bigAutoField(priMary_key=

number53 index52 alt2">title = models.CharField(max_length=50,verbose_name=String">'文章标题'

number54 index53 alt1"> s.CharField(max_length=255,verbose_name=String">'文章描述'

number55 index54 alt2">s.IntegerField(=0)

number56 index55 alt1">s.IntegerField(=0)

number57 index56 alt2">s.IntegerField(=0)

number58 index57 alt1">s.IntegerField(=0)

number59 index58 alt2">s.ForeignKey(verbose_name=String">'文章类型'String">'Category'

number60 index59 alt1">create_time = models.DateField(verbose_name=String">'创建时间'

number61 index60 alt2">s.ForeignKey(verbose_name=String">'所属博客'String">'nid'

number62 index61 alt1">s.ManyToManyField(

number63 index62 alt2">String">"Tag"

number64 index63 alt1">String">'Article2Tag'

number65 index64 alt2">String">'article'String">'tag'

number66 index65 alt1">

number67 index66 alt2">
number68 index67 alt1">
number69 index68 alt2">s.Model):
number70 index69 alt1">String">""String">"

number71 index70 alt2">String">文章详细表

number72 index71 alt1">String">"String">""

number73 index72 alt2">s.AutoField(priMary_key=

number74 index73 alt1">s.TextField(verbose_name=String">'文章内容'

number75 index74 alt2">
number76 index75 alt1">s.OneToOneField(verbose_name=String">'所属文章'String">'Article'String">'nid'

number77 index76 alt2">
number78 index77 alt1">
number79 index78 alt2">s.Model):
number80 index79 alt1">String">""String">"

number81 index80 alt2">String">评论表

number82 index81 alt1">String">"String">""

number83 index82 alt2">.bigAutoField(priMary_key=

number84 index83 alt1">s.ForeignKey(verbose_name=String">'评论文章'String">'nid'

number85 index84 alt2">s.CharField(verbose_name=String">'评论内容'

number86 index85 alt1">create_time = models.datetiR_30_11845@eField(verbose_name=String">'创建时间'

number87 index86 alt2">
number88 index87 alt1">s.ForeignKey(String">'self'String">'父级评论'

number89 index88 alt2"> s.ForeignKey(verbose_name=String">'评论者'String">'nid'

number90 index89 alt1">
number91 index90 alt2">s.IntegerField(=0)

number92 index91 alt1">
number93 index92 alt2">

number94 index93 alt1"> 

number95 index94 alt2">
number96 index95 alt1">s.Model):
number97 index96 alt2">String">""String">"

number98 index97 alt1">String">点赞表

number99 index98 alt2">String">"String">""

number100 index99 alt1">s.AutoField(priMary_key=

number101 index100 alt2"> s.ForeignKey(String">'UserInfo'

number102 index101 alt1">s.ForeignKey(String">"Article"

number103 index102 alt2">s.BooleanField(verbose_name=String">'是否赞'

number104 index103 alt1">
number105 index104 alt2">s.Model):
number106 index105 alt1">String">""String">"

number107 index106 alt2">String">点赞表

number108 index107 alt1">String">"String">""

number109 index108 alt2">s.AutoField(priMary_key=

number110 index109 alt1"> s.ForeignKey(String">'UserInfo'

number111 index110 alt2">s.ForeignKey(String">"Comment"

number112 index111 alt1">
number113 index112 alt2">
number114 index113 alt1">s.Model):
number115 index114 alt2">s.AutoField(priMary_key=

number116 index115 alt1">title = models.CharField(verbose_name=String">'标签名称'

number117 index116 alt2">s.ForeignKey(verbose_name=String">'所属博客'String">'nid'

number118 index117 alt1">
number119 index118 alt2">
number120 index119 alt1">
number121 index120 alt2">s.Model):
number122 index121 alt1">s.AutoField(priMary_key=

number123 index122 alt2">s.ForeignKey(verbose_name=String">'文章'String">"Article"String">'nid'

number124 index123 alt1">s.ForeignKey(verbose_name=String">'标签'String">"Tag"String">'nid'






SELEct_related

ForeignKey），可以使用SELEct_related 来对QuerySet进行优化。
SELEct_related 返回一个，当执行它的查询时它沿着外键关系查询关联的对象的数据。
简单说，在对QuerySet使用SELEct_related()函数后，Django会获取相应外键对应的对象，从而在之后需要的时候不必再查询数据库了。
SELEct_related()查询的区别。


Help Help" href="#">?

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number1 index0 alt2">
number2 index1 alt1">s.Article.objects.get(nid

number3 index2 alt2">
number4 index3 alt1">ject.
number5 index4 alt2">titlE)

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number1 index0 alt2">String">''String">'
number2 index1 alt1">
number3 index2 alt2">String">SELECT 
number4 index3 alt1">String">"blog_article"."nid",

number5 index4 alt2">String">"blog_article"."title",

number6 index5 alt1">String">"blog_article"."desc",

number7 index6 alt2">String">"blog_article"."read_count",

number8 index7 alt1">String">"blog_article"."comment_count",

number9 index8 alt2">String">"blog_article"."up_count",

number10 index9 alt1">String">"blog_article"."down_count",

number11 index10 alt2">String">"blog_article"."category_id",

number12 index11 alt1">String">"blog_article"."create_time",

number13 index12 alt2">String">"blog_article"."blog_id",

number14 index13 alt1">String">"blog_article"."article_type_id" 

number15 index14 alt2">String">FROM "blog_article" 

number16 index15 alt1">String">WHERE "blog_article"."nid" = 2; args=(2,)

number17 index16 alt2">
number18 index17 alt1">String">SELECT
number19 index18 alt2">String">"blog_category"."nid",

number20 index19 alt1">String">"blog_category"."title",

number21 index20 alt2">String">"blog_category"."blog_id"

number22 index21 alt1">String">FROM "blog_category" 

number23 index22 alt2">String">WHERE "blog_category"."nid" = 4; args=(4,)

number24 index23 alt1">
number25 index24 alt2">
number26 index25 alt1">String">'String">''





如果我们使用SELEct_related()函数：

Help Help" href="#">?

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number1 index0 alt2">s.Article.objects.SELEct_related(String">"category"
number2 index1 alt1">
number3 index2 alt2">
number4 index3 alt1">  

number5 index4 alt2">

number6 index5 alt1"> 

number7 index6 alt2">titlE)

LPADding="0">

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number19 index18 alt2">19
number1 index0 alt2">SELECT
number2 index1 alt1">String">"blog_article"String">"nid"

number3 index2 alt2">String">"blog_article"String">"title"

number4 index3 alt1">String">"blog_article"String">"desc"

number5 index4 alt2">String">"blog_article"String">"read_count"

number6 index5 alt1">String">"blog_article"String">"comment_count"

number7 index6 alt2">String">"blog_article"String">"up_count"

number8 index7 alt1">String">"blog_article"String">"down_count"

number9 index8 alt2">String">"blog_article"String">"category_id"

number10 index9 alt1">String">"blog_article"String">"create_time"

number11 index10 alt2">String">"blog_article"String">"blog_id"

number12 index11 alt1">String">"blog_article"String">"article_type_id"

number13 index12 alt2">
number14 index13 alt1">String">"blog_category"String">"nid"

number15 index14 alt2">String">"blog_category"String">"title"

number16 index15 alt1">String">"blog_category"String">"blog_id"

number17 index16 alt2">
number18 index17 alt1"> String">"blog_article"

number19 index18 alt2">   String">"blog_category"  String">"blog_article"String">"category_id" String">"blog_category"String">"nid"); 






多外键查询
这是针对category的外键查询，如果是另外一个外键呢？让我们一起看下：










观察logging结果，发现依然需要查询两次，所以需要改为：

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number1 index0 alt2">1
number2 index1 alt1">2
number1 index0 alt2">s.Article.objects.SELEct_related(String">"category"String">"articledetail"
number2 index1 alt1">






或者：
article@models.Article.objects
　　　　　　　　　　　　　.SELEct_related("category")
　　　　　　　　　　　　　.SELEct_related("articledetail")
　　　　　　　　　　　　　.get(nid)  # django (article.articledetail)

<div class="cnblogs_Highlighter sh-gutter">

80148" class="syntaxhighlighter   sql">

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number1 index0 alt2">SELECT
number2 index1 alt1">
number3 index2 alt2">String">"blog_article"String">"nid"

number4 index3 alt1">String">"blog_article"String">"title"

number5 index4 alt2">

number6 index5 alt1">
number7 index6 alt2">String">"blog_category"String">"nid"

number8 index7 alt1">String">"blog_category"String">"title"

number9 index8 alt2">String">"blog_category"String">"blog_id"

number10 index9 alt1">
number11 index10 alt2">String">"blog_articledetail"String">"nid"

number12 index11 alt1">String">"blog_articledetail"String">"content"

number13 index12 alt2">String">"blog_articledetail"String">"article_id"

number14 index13 alt1">
number15 index14 alt2"> String">"blog_article"

number16 index15 alt1">   String">"blog_category"  String">"blog_article"String">"category_id" String">"blog_category"String">"nid"

number17 index16 alt2">   String">"blog_articledetail"  String">"blog_article"String">"nid" String">"blog_articledetail"String">"article_id"

number18 index17 alt1"> String">"blog_article"String">"nid" 






深层查询

Help Help" href="#">?

LPADding="0">

number1 index0 alt2">1
number2 index1 alt1">2
number3 index2 alt2">3
number4 index3 alt1">4
number1 index0 alt2">
number2 index1 alt1">
number3 index2 alt2">s.Article.objects.SELEct_related(String">"blog"

number4 index3 alt1">.blog.Name)






依然需要查询两次：

LPADding="0">

number1 index0 alt2">1
number2 index1 alt1">2
number3 index2 alt2">3
number4 index3 alt1">4
number5 index4 alt2">5
number6 index5 alt1">6
number7 index6 alt2">7
number8 index7 alt1">8
number9 index8 alt2">9
number10 index9 alt1">10
number11 index10 alt2">11
number12 index11 alt1">12
number13 index12 alt2">13
number14 index13 alt1">14
number15 index14 alt2">15
number16 index15 alt1">16
number17 index16 alt2">17
number18 index17 alt1">18
number19 index18 alt2">19
number20 index19 alt1">20
number21 index20 alt2">21
number1 index0 alt2">SELECT
number2 index1 alt1">String">"blog_article"String">"nid"

number4 index3 alt1">

number5 index4 alt2">
number6 index5 alt1">String">"blog_blog"String">"nid"

number7 index6 alt2">String">"blog_blog"String">"title"

number8 index7 alt1">
number9 index8 alt2"> String">"blog_article"   String">"blog_blog"  String">"blog_article"String">"blog_id" String">"blog_blog"String">"nid"

number10 index9 alt1"> String">"blog_article"String">"nid" 

number11 index10 alt2">
number12 index11 alt1">
number13 index12 alt2">
number14 index13 alt1">
number15 index14 alt2">SELECT
number16 index15 alt1">String">"blog_userinfo"String">"password"

number17 index16 alt2">String">"blog_userinfo"String">"last_login"

number18 index17 alt1">

number19 index18 alt2">
number20 index19 alt1"> String">"blog_userinfo"

number21 index20 alt2"> String">"blog_userinfo"String">"nid" 






这是因为第一次查询没有query到userInfo表，所以，修改如下：

Help Help" href="#">?

LPADding="0">

number1 index0 alt2">1
number2 index1 alt1">2
number1 index0 alt2">s.Article.objects.SELEct_related(String">"blog__user"
number2 index1 alt1">.blog.Name)

LPADding="0">

number1 index0 alt2">1
number2 index1 alt1">2
number3 index2 alt2">3
number4 index3 alt1">4
number5 index4 alt2">5
number6 index5 alt1">6
number7 index6 alt2">7
number8 index7 alt1">8
number9 index8 alt2">9
number10 index9 alt1">10
number11 index10 alt2">11
number12 index11 alt1">12
number13 index12 alt2">13
number14 index13 alt1">14
number15 index14 alt2">15
number16 index15 alt1">16
number17 index16 alt2">17
number1 index0 alt2">SELECT
number2 index1 alt1">
number3 index2 alt2">String">"blog_article"String">"nid"String">"blog_article"String">"title"

number4 index3 alt1">

number5 index4 alt2">
number6 index5 alt1">String">"blog_blog"String">"nid"String">"blog_blog"String">"title"

number7 index6 alt2">

number8 index7 alt1">
number9 index8 alt2">String">"blog_userinfo"String">"password"String">"blog_userinfo"String">"last_login"

number10 index9 alt1">

number11 index10 alt2">
number12 index11 alt1"> String">"blog_article"

number13 index12 alt2">
number14 index13 alt1">  String">"blog_blog"  String">"blog_article"String">"blog_id" String">"blog_blog"String">"nid"

number15 index14 alt2">
number16 index15 alt1">  String">"blog_userinfo"  String">"blog_blog"String">"user_id" String">"blog_userinfo"String">"nid"

number17 index16 alt2"> String">"blog_article"String">"nid" 






总结

SELEct_related主要针一对一和多对一关系进行优化。
SELEct_related使用sqL的JOIN语句进行优化，通过减少SQL查询的次数来进行优化、提高性能。
可以通过可变长参数指定需要SELEct_related的字段名。也可以通过使用双下划线“__”连接字段名来实现指定的递归查询。
没有指定的字段不会缓存，没有指定的深度不会缓存，如果要访问的话Django会再次进行SQL查询。
也可以通过depth参数指定递归的深度，Django会自动缓存指定深度内所有的字段。如果要访问指定深度外的字段，Django会再次进行SQL查询。
也接受无参数的调用，Django会尽可能深的递归查询所有的字段。但注意有Django递归的限制和性能的浪费。
Django >= 1.7，链式调用的SELEct_related相当于使用可变长参数。Django < 1.7，链式调用会导致前边的SELEct_related失效，只保留最后一个。

prefetch_related()
对于多对多字段（ManyToManyField）和一对多字段，可以使用prefetch_related()来进行优化。
prefetch_related()和SELEct_related()的设计目的很相似，都是为了减少SQL查询的数量，但是实现的方式不一样。后者是通过JOIN语句，在SQL查询内解决问题。但是对于多对多关系，使用sql语句解决就显得有些不太明智，因为JOIN得到的表将会很长，会导致sql语句运行时间的增加和内存占用的增加。若有n个对象，每个对象的多对多字段对应Mi条，就会生成Σ(n)Mi 行的结果表。
prefetch_related()的解决方法是，分别查询每个表，然后用Python处理他们之间的关系。








  


 






改为prefetch_related：

LPADding="0">

number1 index0 alt2">1
number2 index1 alt1">2
number3 index2 alt2">3
number4 index3 alt1">4
number5 index4 alt2">5
number1 index0 alt2">
number2 index1 alt1">s.Article.objects.prefetch_related(String">"tags"

number3 index2 alt2">  

number4 index3 alt1">
number5 index4 alt2">s.

LPADding="0">

number1 index0 alt2">1
number2 index1 alt1">2
number3 index2 alt2">3
number4 index3 alt1">4
number5 index4 alt2">5
number6 index5 alt1">6
number7 index6 alt2">7
number8 index7 alt1">8
number9 index8 alt2">9
number10 index9 alt1">10
number11 index10 alt2">11
number12 index11 alt1">12
number13 index12 alt2">13
number14 index13 alt1">14
number15 index14 alt2">15
number16 index15 alt1">16
number1 index0 alt2">SELECT String">"blog_article"String">"nid"
number2 index1 alt1">String">"blog_article"String">"title"

number3 index2 alt2">

number4 index3 alt1">
number5 index4 alt2"> String">"blog_article"

number6 index5 alt1">
number7 index6 alt2">
number8 index7 alt1">
number9 index8 alt2">SELECT
number10 index9 alt1">String">"blog_article2tag"String">"article_id" String">"_prefetch_related_val_article_id"

number11 index10 alt2">String">"blog_tag"String">"nid"

number12 index11 alt1">String">"blog_tag"String">"title"

number13 index12 alt2">String">"blog_tag"String">"blog_id"

number14 index13 alt1"> String">"blog_tag"

number15 index14 alt2">  String">"blog_article2tag"  String">"blog_tag"String">"nid" String">"blog_article2tag"String">"tag_id"

number16 index15 alt1"> String">"blog_article2tag"String">"article_id"  ); 








extra(SELEctNone,None,paramsNone,
      tablesNone,order_byNone,SELEct_paramsNonE)

有些情况下，Django的查询语法难以简单的表达复杂的子句，修改机制 — 它能在生成的SQL从句中注入新子句
,例如SELEct,or.但是你至少要使用一个!要注意这些额外的方式对不同的数据库引擎可能存在移植性问题.(因为你在显式的书写SQL语句),除非万不得已,尽量避免这样做
SELEct
SELEct参数可以让你在SELECT从句中添加其他字段信息，
queryResult@models.Article
　　　　　　　　　　　.objects.extra(SELEct{: "create_time  "})

结果集中每个 Entry 对象都有一个额外的属性is_recent,它是一个布尔值，表示 Article对象的create_time 是否晚于2017-09-05.
练习：

# sqlite:
    article_obj@models.Article.objects
　　　　　　　　　　　　　　.filter(nid)
　　　　　　　　　　　　　　.extra(SELEct{"standard_time":"strftime(,create_timE)"})
　　　　　　　　　　　　　　.title")
    QuerySet {'title': 'MongoDb 入门教程','standard_time': '2017-09-03','nid': 1}


参数之where/tables
定义显式SQL子句 - 也许执行非显式连接。手动将表添加到SQL子句。
和都接受字符串列表。参数均为“与”任何其他搜索条件。

queryResult@models.Article
　　　　　　　　　　　.objects.extra(2')



创建对象时，尽可能使用bulk_create()来减少SQL查询的数量。例如：
Entry.objects.bulk_create([
    Entry(headline="Python 3.0 Released"),Entry(headline="Python 3.1 PlAnned")
])

...更优于：
Entry.objects.create(headline="Python 3.0 Released")
Entry.objects.create(headline="Python 3.1 PlAnned")

注意该方法有很多注意事项，所以确保它适用于你的情况。
这也可以用在ManyToManyFields中，所以：
@H_839_2223@my_band.members.add(me,my_friend)

...更优于：
@H_839_2223@my_band.members.add(mE)
my_band.members.add(my_friend)

...其中Bands和Artists具有多对多关联。





       

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