本节内容
- 路由系统
- models模型
- admin
- views视图
- template模板
引子
讲django的models之前, 先来想一想, 让你通过django操作数据库,你怎么做? 做苦思冥想,可能会这样写。
import pymysql def index(request): # 创建连接 conn = pymysql.connect(host='127.0.0.1', port=3306, user='root', passwd='alex123', db='luffy_dev') # 创建游标 cursor = conn.cursor() cursor.execute("select username,email,mobile from web_account") data_set = cursor.fetchall() cursor.close() conn.close() return HttpResponse(data_set)
很方便就实现了从数据库里取数据,事实上,很多人确实就是这么做的。但这样做会带来2个问题
- SQL注入危险,因为有的时候你操作数据库的语句不是写死在代码里的,而是通过前端传参数拼接的,这就给黑客有了可趁之机,通过拼接参数实现sql注入。
- 语句跟代码揉在一起了,增加后续维护成本
那怎么办呢?ORM提供了新思路。
什么是ORM呢?
对象关系映射(Object Relational Mapping),它的实质就是将关系数据(库)中的业务数据用对象的形式表示出来,并通过面向对象(Object-Oriented)的方式将这些对象组织起来,实现系统业务逻辑的过程。
在ORM过程中最重要的概念是映射(Mapping),通过这种映射可以使业务对象与数据库分离。从面向对象来说,数据库不应该和业务逻辑绑定到一起,ORM则起到这样的分离作用,使数据库层透明,开发人员真正的面向对象。
上面的解释有点蒙蔽对不?其实你只需要抓住2个关键词, “映射” 和 “对象”,就能知道orm是什么干什么的了。
- 映射(Mapping) —— 把表结构映射成类
- 对象 —— 像操作类对象一样,操作数据库里的数据
映射
看下面的图,就是直观的例子,把右边的表结构映射成了左边的类
Sql语句到对象
ORM可以使你不用再写原生SQL, 而是像操作对象一样就可以实现对表里数据的增删改查
好棒棒,妈妈再也不用逼你写原生sql啦!
但是不要开心太早,ORM确实提高了开发效率,并且降低了数据操作与代码之间的耦合,不过有利就有弊,我们总结一下orm的优缺点。
优点:
- 实现了代码与数据操作的解耦合
- 不需自己写原生sql, 提高开发效率
- 防止SQL注入, 通过对象操作的方式,默认就是防止sql注入的。
缺点:
- 牺牲性能, 对象到原生SQL势必会有转换消耗,对性能有一定的影响
- 复杂语句力不从心, 一些复杂的sql语句,用orm对象操作的方式很难实现,就还得用原生sql
讲Django为什么说ORM? 哈, 好啦,是时候该引出主角啦,因为Django的models基于架构ORM实现的。
Models模型
Django 的models把数据库表结构映射成了一个个的类, 表里的每个字段就是类的属性。我们都知道数据库有很多字段类型,int,float,char等, Django的models类针对不同的字段也设置了不同的类属性。
AutoField #An IntegerField that automatically increments according to available IDs BigAutoField #A 64-bit integer, guaranteed to fit numbers from 1 to 9223372036854775807. BigIntegerField #-9223372036854775808 to 9223372036854775807 BinaryField #A field to store raw binary data. It only supports bytes assignment BooleanField CharField DateField #e.g 2019-04-27 DateTimeField #e.g 2019-04-27 17:53:21 DecimalField DurationField #storing periods of time ,e.g [DD] [HH:[MM:]]ss[.uuuuuu]" EmailField FileField #存储文件 FloatField ImageField #Inherits all attributes and methods from FileField, but also validates that the uploaded object is a valid image. IntegerField GenericIPAddressField #IP地址,支持ipv4 NullBooleanField #Like a BooleanField, but allows NULL as one of the options PositiveIntegerField #Like an IntegerField, but must be either positive or zero (0). Values from 0 to 2147483647 PositiveSmallIntegerField #only allows positive values from 0 to 32767 SlugField # A slug is a short label for something, containing only letters, numbers, underscores or hyphens. SmallIntegerField TextField #A large text field. TimeField #A time, represented in Python by a datetime.time instance. URLField UUIDField #A field for storing universally unique identifiers. Uses Python’s UUID class.
除了普通的表字段,针对外键也有映射
ForeignKey # 外键关联 ManyToManyField #多对多 OneToOneField # 1对1
好啦,接下来就用django的orm来设计一个博客表。
需求
- 每个用户有自己的账户信息
- 用户可以发文章
- 文章可以打多个标签
根据需求,我们设计3张表
注意Article表和Tag表是属于多对多关系,什么是多对多?即一个文章有多个标签,一个标签又可以属于多个文章。
比如上图的Article表中id为3的文章 ,它的标签是4,26, 即投资、大文娱、社交, 你看“投资”这个标签同时还属于文章2。 这就是多对多关系 , 即many to many .
那这种多对多的关系如何在表中存储呢?难道真的像上图中一样,在Article表中加个tags字段,关联Tag表里的多条数据,通过逗号区分?
这倒确实是个解决办法。但是也有问题,一个字段里存多条纪录的id,就没办法做查询优化了。比如不能做索引等。
所以若想实现多对多关系的高效存储+查询优化,可以在Article and Tag表之间再搞出一张表。
这样是不是就实现了多对多关联?
yes, 没错, django也是这么做的, django 有个专门的字段,叫ManyToManyField, 就是用来实现多对多关联的,它会自动生成一个如上图一样的第3张表来存储多对多关系。
正式的表结构
from django.db import models # Create your models here. class Account(models.Model): username = models.CharField(max_length=64,unique=True) email = models.EmailField() password = models.CharField(max_length=128) register_date = models.DateTimeField("注册日期",auto_now_add=True) signature = models.CharField(verbose_name="签名",max_length=128,blank=True,null=True) class Article(models.Model): """文章表""" title = models.CharField(max_length=255,unique=True) content = models.TextField("文章内容") account = models.ForeignKey("Account",verbose_name="作者",on_delete=models.CASCADE) tags = models.ManyToManyField("Tag",blank=True) pub_date = models.DateTimeField() read_count = models.IntegerField(default=0) class Tag(models.Model): """文章标签表""" name = models.CharField(max_length=64,unique=True) date = models.DateTimeField(auto_now_add=True)
我们发现,每个字段其实都是一个独立的对象,一张表其实是很多类的组合。
上面好多字段里还跟了些参数,我们来看以下常用的:
null #If True, Django will store empty values as NULL in the database. Default is False. blank #If True, the field is allowed to be blank. Default is False. db_column #The name of the database column to use for this field. If this isn’t given, Django will use the field’s name. db_index #If True, a database index will be created for this field. default #The default value for the field. This can be a value or a callable object. If callable it will be called every time a new object is created. editable # django admin中用,后面讲 help_text # django admin中用,后面讲 primary_key # If True, this field is the primary key for the model. unique #If True, this field must be unique throughout the table unique_for_date #Set this to the name of a DateField or DateTimeField to require that this field be unique for the value of the date field. For example, if you have a field title that has unique_for_date="pub_date", then Django wouldn’t allow the entry of two records with the same title and pub_date. unique_for_month #Like unique_for_date, but requires the field to be unique with respect to the month. unique_for_year verbose_name #A human-readable name for the field. If the verbose name isn’t given, Django will automatically create it using the field’s attribute name
还有几个特殊的字段属性需要单独介绍下
choices
An iterable (e.g., a list or tuple) consisting itself of iterables of exactly two items (e.g. [(A, B), (A, B) ...]) to use as choices for this field.
The first element in each tuple is the actual value to be set on the model, and the second element is the human-readable name.
class Student(models.Model): YEAR_IN_SCHOOL_CHOICES = ( ('FR', 'Freshman'), ('SO', 'Sophomore'), ('JR', 'Junior'), ('SR', 'Senior'), ) year_in_school = models.CharField( max_length=2, choices=YEAR_IN_SCHOOL_CHOICES, default=FRESHMAN, )
ForeignKey.on_delete
当一条记录关联的外键纪录被删除时,django 也会根据外键关联限制的配置来决定如何处理当前这条纪录。举例,如果你有个可以为null的外键关联,并且你想在本纪录关联的数据被删除时,把当前纪录的关联字段设为null,那就配置如下
user = models.ForeignKey( User, on_delete=models.SET_NULL, blank=True, null=True, )
这个on_delete就是决定在关联对象被删除时,如何处理当前纪录的,常用的参数如下:
- CASCADE——Cascade deletes. Django emulates the behavior of the SQL constraint ON DELETE CASCADE and also deletes the object containing the ForeignKey.
- PROTECT——Prevent deletion of the referenced object by raising ProtectedError, a subclass of django.db.IntegrityError.
- SET_NULL——Set the ForeignKey null; this is only possible if null is True.
- SET_DEFAULT——Set the ForeignKey to its default value; a default for the ForeignKey must be set.
配置Django数据库连接信息
Django支持多种数据库,Sqlite、Mysql、Oracle、PostgreSQL,默认的是小型文件数据库Sqlite
DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': os.path.join(BASE_DIR, 'db.sqlite3'), } }
咱们是干大事的人,怎么也得用个Mysql呀, 改成mysql 也so easy.
DATABASES = { 'default': { 'ENGINE': 'django.db.backends.mysql', 'NAME': 'my_db', 'USER': 'mydatabaseuser', 'PASSWORD': 'mypassword', 'HOST': '127.0.0.1', 'PORT': '3306', } }
不过注意,python3 连接mysql的得使用pymysql,MysqlDB模块300年没更新了,但django默认调用的还是MySQLdb, so pymysql有个功能可以让django以为是用了MySQLdb. 即在项目目录下的__init__.py中加上句代码就好
import pymysql pymysql.install_as_MySQLdb()
不加的话,一会连接数据时会报错噢 。
同步数据库
你在ORM定义的表结构如何同步到真实的数据库里呢? 只需2条命令。但django只能帮你自动创建表,数据库本身还是得你自己来。
create database my_db charset utf8;
好了,可以同步了,说好只需2步。
1. 生成同步文件, django自带一个专门的工具叫migrations, 负责把你的orm表转成实际的表结构,它不旦可以帮自动创建表,对表结构的修改,比如增删改字段、改字段属性等也都能自动同步。只需通过下面神奇的命令。
python manage.py makemigrations
不出意外的话,会显示类似以下信息
$ python manage.py makemigrations Migrations for 'app01': app01/migrations/0001_initial.py - Create model Account - Create model Article - Create model Tag - Add field tags to article
此时你会发现,你的app下的migrations目录里多了一个0001_initial.py的文件 ,这个文件就是因为你这条命令而创建的,migrations工具就会根据这个文件来创建数据库里的表。
2. 同步到数据
$ python manage.py migrate Operations to perform: Apply all migrations: admin, app01, auth, contenttypes, sessions Running migrations: Applying contenttypes.0001_initial... OK Applying auth.0001_initial... OK Applying admin.0001_initial... OK Applying admin.0002_logentry_remove_auto_add... OK Applying app01.0001_initial... OK Applying contenttypes.0002_remove_content_type_name... OK Applying auth.0002_alter_permission_name_max_length... OK Applying auth.0003_alter_user_email_max_length... OK Applying auth.0004_alter_user_username_opts... OK Applying auth.0005_alter_user_last_login_null... OK Applying auth.0006_require_contenttypes_0002... OK Applying auth.0007_alter_validators_add_error_messages... OK Applying auth.0008_alter_user_username_max_length... OK Applying auth.0009_alter_user_last_name_max_length... OK Applying sessions.0001_initial... OK (venv_django2) Alexs-MacBook-Pro:mysite alex$
此时登录你的数据库,会发现创建了好多张表
mysql> show tables; +----------------------------+ | Tables_in_luffy_dev2 | +----------------------------+ | app01_account | #对应Account表 | app01_article | #对应Article表 | app01_article_tags | #自动创建的Article to Tag的多对多关联表 | app01_tag | #对应Tag表 | auth_group | #下面这些,都是django 自带的表,这个是自动用户系统的组 | auth_group_permissions | #自带的组与权限的多对多关联表 | auth_permission | #自带权限表 | auth_user | #用户表 | auth_user_groups | | auth_user_user_permissions | | django_admin_log | #现在你的无法理解 | django_content_type | #现在你的无法理解 | django_migrations | #纪录migartions工具同步纪录的表 | django_session | #现在你的无法理解 +----------------------------+ 14 rows in set (0.00 sec)
好啦,表结构也有了,我们可以往里面插数据啦。
之前说好的是可以不用SQL语句的,一点不骗你。
用orm对表数据进行增删改查
先进入已经连接好数据库的django python环境
(venv_django2) Alexs-MacBook-Pro:mysite alex$ python manage.py shell Python 3.5.2 (v3.5.2:4def2a2901a5, Jun 26 2016, 10:47:25) [GCC 4.2.1 (Apple Inc. build 5666) (dot 3)] on darwin Type "help", "copyright", "credits" or "license" for more information. (InteractiveConsole) >>> >>> from app01 import models
创建
创建数据简单的令人发指
查
filter 支持很多的过滤条件,我们来看下:
contains
包含,相当于sql的like条件
Entry.objects.get(headline__contains='Lennon')
SQL equivalent:
SELECT ... WHERE headline LIKE '%Lennon%';
Note this will match the headline 'Lennon honored today' but not 'lennon honored today'.
icontains 大小写不敏感
in
In a given iterable; often a list, tuple, or queryset.
Entry.objects.filter(id__in=[1, 3, 4])
SQL equivalent:
SELECT ... WHERE id IN (1, 3, 4);
You can also use a queryset to dynamically evaluate the list of values instead of providing a list of literal values:
inner_qs = Blog.objects.filter(name__contains='Cheddar') entries = Entry.objects.filter(blog__in=inner_qs)
This queryset will be evaluated as subselect statement:
SELECT ... WHERE blog.id IN (SELECT id FROM ... WHERE NAME LIKE '%Cheddar%')
gt
Entry.objects.filter(id__gt=4)
SQL equivalent:
SELECT ... WHERE id > 4;
gte
Greater than or equal to.
lt
Less than.
lte
Less than or equal to.
startswith
Case-sensitive starts-with.
Entry.objects.filter(headline__startswith='Lennon')
SQL equivalent:
SELECT ... WHERE headline LIKE 'Lennon%';
SQLite doesn’t support case-sensitive LIKE statements; startswith acts like istartswith for SQLite
istartswith
Case-insensitive starts-with.
endswith
Case-sensitive ends-with.
iendswith
Case-insensitive ends-with
range
区间过渡,可对数字、日期进行过滤
import datetime start_date = datetime.date(2005, 1, 1) end_date = datetime.date(2005, 3, 31) Entry.objects.filter(pub_date__range=(start_date, end_date))
SQL equivalent:
SELECT ... WHERE pub_date BETWEEN '2005-01-01' and '2005-03-31';
Warning!
Filtering a DateTimeField with dates won’t include items on the last day, because the bounds are interpreted as “0am on the given date”. If pub_date was a DateTimeField, the above expression would be turned into this SQL:
SELECT ... WHERE pub_date BETWEEN '2005-01-01 00:00:00' and '2005-03-31 00:00:00';
Generally speaking, you can’t mix dates and datetimes.
date
For datetime fields, casts the value as date. Allows chaining additional field lookups. Takes a date value.
Entry.objects.filter(pub_date__date=datetime.date(2005, 1, 1)) Entry.objects.filter(pub_date__date__gt=datetime.date(2005, 1, 1))
year
For date and datetime fields, an exact year match. Allows chaining additional field lookups. Takes an integer year.
Entry.objects.filter(pub_date__year=2005) Entry.objects.filter(pub_date__year__gte=2005)
SQL equivalent:
SELECT ... WHERE pub_date BETWEEN '2005-01-01' AND '2005-12-31'; SELECT ... WHERE pub_date >= '2005-01-01';
When USE_TZ is True, datetime fields are converted to the current time zone before filtering. 简单解决办法是把USE_TZ=False
month
For date and datetime fields, an exact month match. Allows chaining additional field lookups. Takes an integer 1 (January) through 12 (December).
Entry.objects.filter(pub_date__month=12) Entry.objects.filter(pub_date__month__gte=6)
When USE_TZ
is True
, datetime fields are converted to the current time zone before filtering. This requires time zone definitions in the database.
SQL equivalent:
SELECT ... WHERE EXTRACT('month' FROM pub_date) = '12'; SELECT ... WHERE EXTRACT('month' FROM pub_date) >= '6';
day
For date and datetime fields, an exact day match. Allows chaining additional field lookups. Takes an integer day.
Entry.objects.filter(pub_date__day=3) Entry.objects.filter(pub_date__day__gte=3)
SQL equivalent:
SELECT ... WHERE EXTRACT('day' FROM pub_date) = '3'; SELECT ... WHERE EXTRACT('day' FROM pub_date) >= '3';
week
For date and datetime fields, return the week number (1-52 or 53) according to ISO-8601, i.e., weeks start on a Monday and the first week contains the year’s first Thursday.
Example:
Entry.objects.filter(pub_date__week=52) Entry.objects.filter(pub_date__week__gte=32, pub_date__week__lte=38)
week_day
For date and datetime fields, a ‘day of the week’ match. Allows chaining additional field lookups.
Takes an integer value representing the day of week from 1 (Sunday) to 7 (Saturday).
Example:
Entry.objects.filter(pub_date__week_day=2) Entry.objects.filter(pub_date__week_day__gte=2)
hour
For datetime and time fields, an exact hour match. Allows chaining additional field lookups. Takes an integer between 0 and 23.
Example:
Event.objects.filter(timestamp__hour=23) Event.objects.filter(time__hour=5) Event.objects.filter(timestamp__hour__gte=12)
SQL equivalent:
SELECT ... WHERE EXTRACT('hour' FROM timestamp) = '23'; SELECT ... WHERE EXTRACT('hour' FROM time) = '5'; SELECT ... WHERE EXTRACT('hour' FROM timestamp) >= '12';同
同时,还支持mintue,second
Event.objects.filter(time__minute=46) Event.objects.filter(timestamp__second=31)
isnull
Takes either True
or False
, which correspond to SQL queries of IS NULL
and IS NOT NULL
, respectively.
Example:
Entry.objects.filter(pub_date__isnull=True)
SQL equivalent:
SELECT ... WHERE pub_date IS NULL;
regex
Case-sensitive regular expression match.
Example:
Entry.objects.get(title__regex=r'^(An?|The) +')
SQL equivalents:
SELECT ... WHERE title REGEXP BINARY '^(An?|The) +'; -- MySQL SELECT ... WHERE REGEXP_LIKE(title, '^(An?|The) +', 'c'); -- Oracle SELECT ... WHERE title ~ '^(An?|The) +'; -- PostgreSQL SELECT ... WHERE title REGEXP '^(An?|The) +'; -- SQLite
iregex 大小写不敏感
改删
# 批量修改 models.Account.objects.filter(username='elina').update(password="Luffy#21") # 单条修改 obj = models.Account.objects.get(username='linux') obj.username = 'python' obj.save() # 批量删除 models.User.objects.get(password='oldboy').delete() # 单条删除 obj = models.User.objects.get(id=3) obj.delete()
数据返回后的展示
values()
Returns a QuerySet
that returns dictionaries, rather than model instances, when used as an iterable.
>>> Blog.objects.values() <QuerySet [{'id': 1, 'name': 'Beatles Blog', 'tagline': 'All the latest Beatles news.'}]> >>> Blog.objects.values('id', 'name') <QuerySet [{'id': 1, 'name': 'Beatles Blog'}]>
order_by()
By default, results returned by a QuerySet
are ordered by the ordering tuple given by the ordering
option in the model’s Meta
. You can override this on a per-QuerySet
basis by using the order_by
method.
Entry.objects.filter(pub_date__year=2005).order_by('-pub_date', 'headline')
The result above will be ordered by pub_date
descending, then by headline
ascending. The negative sign in front of "-pub_date"
indicates descending order. Ascending order is implied.
reverse()
Use the reverse()
method to reverse the order in which a queryset’s elements are returned. Calling reverse()
a second time restores the ordering back to the normal direction.
To retrieve the “last” five items in a queryset, you could do this:
my_queryset.reverse()[:5]
ORM对象操作
单表对象操作 o = models.Article.objects.all()[0] o.tilte 外键关联 >>> o.account.username 'jack' >>> o.account.username = rain 外键反向关联操作 >>> a = models.Account.objects.get(username='alex') >>> a.article_set.all() <QuerySet [<Article: 你好,2018>]> >>> a.article_set.select_related() <QuerySet [<Article: 你好,2018>]> 多对多操作 >>> o = models.Article.objects.all()[1] >>> o.tags.all() <QuerySet [<Tag: 投资>, <Tag: 科技>]> 多对多反向操作 >>> t = models.Tag.objects.get(name="投资") >>> t.article_set.all() <QuerySet [<Article: 你好,2018>, <Article: 粉丝超过10万后,我经历了抖音盗号风波>]>
好啦,orm的操作先点到为止,后面学项目时再带你搞复杂的。
练习题
- 基于前面课程设计的表结构,完成以下练习:
- 创建5条account和5条新tag纪录
- 创建5条article信息,关联上面的不同的用户和tag
- 在account表里找到用户名包含al的纪录,然后把密码改掉
- 在article表找到文章内容包含“电影”2个字的,把这些文章加上”大文娱”tag
- 把用户elina发表的文章找出来,并且把作者都改成alex
- 找到用户表里注册日期在2018-04月,并且signature为空的纪录
- 打到文章中标签为“投资”的所有文章
- 找到每个月8号注册的用户
- 找到每年5月发表的文章
- 找到2015-2017年5月发表的文章
- 找到文章作者以’a’或’k’开头的文章