企业🤖AI Agent构建引擎,智能编排和调试,一键部署,支持私有化部署方案 广告
# Day 4 - 编写Model 有了ORM,我们就可以把Web App需要的3个表用`Model`表示出来: ``` import time, uuid from transwarp.db import next_id from transwarp.orm import Model, StringField, BooleanField, FloatField, TextField class User(Model): __table__ = 'users' id = StringField(primary_key=True, default=next_id, ddl='varchar(50)') email = StringField(updatable=False, ddl='varchar(50)') password = StringField(ddl='varchar(50)') admin = BooleanField() name = StringField(ddl='varchar(50)') image = StringField(ddl='varchar(500)') created_at = FloatField(updatable=False, default=time.time) class Blog(Model): __table__ = 'blogs' id = StringField(primary_key=True, default=next_id, ddl='varchar(50)') user_id = StringField(updatable=False, ddl='varchar(50)') user_name = StringField(ddl='varchar(50)') user_image = StringField(ddl='varchar(500)') name = StringField(ddl='varchar(50)') summary = StringField(ddl='varchar(200)') content = TextField() created_at = FloatField(updatable=False, default=time.time) class Comment(Model): __table__ = 'comments' id = StringField(primary_key=True, default=next_id, ddl='varchar(50)') blog_id = StringField(updatable=False, ddl='varchar(50)') user_id = StringField(updatable=False, ddl='varchar(50)') user_name = StringField(ddl='varchar(50)') user_image = StringField(ddl='varchar(500)') content = TextField() created_at = FloatField(updatable=False, default=time.time) ``` 在编写ORM时,给一个Field增加一个`default`参数可以让ORM自己填入缺省值,非常方便。并且,缺省值可以作为函数对象传入,在调用`insert()`时自动计算。 例如,主键`id`的缺省值是函数`next_id`,创建时间`created_at`的缺省值是函数`time.time`,可以自动设置当前日期和时间。 日期和时间用`float`类型存储在数据库中,而不是`datetime`类型,这么做的好处是不必关心数据库的时区以及时区转换问题,排序非常简单,显示的时候,只需要做一个`float`到`str`的转换,也非常容易。 ### 初始化数据库表 如果表的数量很少,可以手写创建表的SQL脚本: ``` -- schema.sql drop database if exists awesome; create database awesome; use awesome; grant select, insert, update, delete on awesome.* to 'www-data'@'localhost' identified by 'www-data'; create table users ( `id` varchar(50) not null, `email` varchar(50) not null, `password` varchar(50) not null, `admin` bool not null, `name` varchar(50) not null, `image` varchar(500) not null, `created_at` real not null, unique key `idx_email` (`email`), key `idx_created_at` (`created_at`), primary key (`id`) ) engine=innodb default charset=utf8; create table blogs ( `id` varchar(50) not null, `user_id` varchar(50) not null, `user_name` varchar(50) not null, `user_image` varchar(500) not null, `name` varchar(50) not null, `summary` varchar(200) not null, `content` mediumtext not null, `created_at` real not null, key `idx_created_at` (`created_at`), primary key (`id`) ) engine=innodb default charset=utf8; create table comments ( `id` varchar(50) not null, `blog_id` varchar(50) not null, `user_id` varchar(50) not null, `user_name` varchar(50) not null, `user_image` varchar(500) not null, `content` mediumtext not null, `created_at` real not null, key `idx_created_at` (`created_at`), primary key (`id`) ) engine=innodb default charset=utf8; ``` 如果表的数量很多,可以从`Model`对象直接通过脚本自动生成SQL脚本,使用更简单。 把SQL脚本放到MySQL命令行里执行: ``` $ mysql -u root -p < schema.sql ``` 我们就完成了数据库表的初始化。 ### 编写数据访问代码 接下来,就可以真正开始编写代码操作对象了。比如,对于`User`对象,我们就可以做如下操作: ``` # test_db.py from models import User, Blog, Comment from transwarp import db db.create_engine(user='www-data', password='www-data', database='awesome') u = User(name='Test', email='test@example.com', password='1234567890', image='about:blank') u.insert() print 'new user id:', u.id u1 = User.find_first('where email=?', 'test@example.com') print 'find user\'s name:', u1.name u1.delete() u2 = User.find_first('where email=?', 'test@example.com') print 'find user:', u2 ``` 可以在MySQL客户端命令行查询,看看数据是不是正常存储到MySQL里面了。