Sqlalchemy 简明教程

SQLAlchemy Core - Using Multiple Tables

RDBMS 的重要特性之一是在表之间建立关系。SQL 运算(例如 SELECT、UPDATE 和 DELETE)可以在相关表上执行。本节使用 SQLAlchemy 描述了这些运算。

为此,在我们的 SQLite 数据库 (college.db) 中创建两个表。学生表具有与前一节中给出的相同的结构;而地址表具有使用外键约束映射到 id column in students tablest_id 列。

以下代码将在 college.db 中创建两个表:

from sqlalchemy import create_engine, MetaData, Table, Column, Integer, String, ForeignKey
engine = create_engine('sqlite:///college.db', echo=True)
meta = MetaData()

students = Table(
   'students', meta,
   Column('id', Integer, primary_key = True),
   Column('name', String),
   Column('lastname', String),
)

addresses = Table(
   'addresses', meta,
   Column('id', Integer, primary_key = True),
   Column('st_id', Integer, ForeignKey('students.id')),
   Column('postal_add', String),
   Column('email_add', String))

meta.create_all(engine)

上面的代码将转换为下面显示的学生和地址表的 CREATE TABLE 查询:

CREATE TABLE students (
   id INTEGER NOT NULL,
   name VARCHAR,
   lastname VARCHAR,
   PRIMARY KEY (id)
)

CREATE TABLE addresses (
   id INTEGER NOT NULL,
   st_id INTEGER,
   postal_add VARCHAR,
   email_add VARCHAR,
   PRIMARY KEY (id),
   FOREIGN KEY(st_id) REFERENCES students (id)
)

以下屏幕截图清晰地展示了上述代码:

create table queries
addresses table queries

通过执行表对象 insert() method 填充表中的数据。要在学生表中插入 5 行,可以使用下面给出的代码:

from sqlalchemy import create_engine, MetaData, Table, Column, Integer, String
engine = create_engine('sqlite:///college.db', echo = True)
meta = MetaData()

conn = engine.connect()
students = Table(
   'students', meta,
   Column('id', Integer, primary_key = True),
   Column('name', String),
   Column('lastname', String),
)

conn.execute(students.insert(), [
   {'name':'Ravi', 'lastname':'Kapoor'},
   {'name':'Rajiv', 'lastname' : 'Khanna'},
   {'name':'Komal','lastname' : 'Bhandari'},
   {'name':'Abdul','lastname' : 'Sattar'},
   {'name':'Priya','lastname' : 'Rajhans'},
])

Rows 在地址表中使用以下代码添加:

from sqlalchemy import create_engine, MetaData, Table, Column, Integer, String
engine = create_engine('sqlite:///college.db', echo = True)
meta = MetaData()
conn = engine.connect()

addresses = Table(
   'addresses', meta,
   Column('id', Integer, primary_key = True),
   Column('st_id', Integer),
   Column('postal_add', String),
   Column('email_add', String)
)

conn.execute(addresses.insert(), [
   {'st_id':1, 'postal_add':'Shivajinagar Pune', 'email_add':'ravi@gmail.com'},
   {'st_id':1, 'postal_add':'ChurchGate Mumbai', 'email_add':'kapoor@gmail.com'},
   {'st_id':3, 'postal_add':'Jubilee Hills Hyderabad', 'email_add':'komal@gmail.com'},
   {'st_id':5, 'postal_add':'MG Road Bangaluru', 'email_add':'as@yahoo.com'},
   {'st_id':2, 'postal_add':'Cannought Place new Delhi', 'email_add':'admin@khanna.com'},
])

请注意,地址表中的 st_id 列引用学生表中的 id 列。我们现在可以使用此关系从这两个表中提取数据。我们希望从与地址表中 st_id 相对应的学生表中提取 namelastname

from sqlalchemy.sql import select
s = select([students, addresses]).where(students.c.id == addresses.c.st_id)
result = conn.execute(s)

for row in result:
   print (row)

选择对象将有效地转换成以下 SQL 表达式,该表达式在公共关系上联接两个表:

SELECT students.id,
   students.name,
   students.lastname,
   addresses.id,
   addresses.st_id,
   addresses.postal_add,
   addresses.email_add
FROM students, addresses
WHERE students.id = addresses.st_id

这将产生从两个表中提取相应数据的输出,如下所示:

(1, 'Ravi', 'Kapoor', 1, 1, 'Shivajinagar Pune', 'ravi@gmail.com')
(1, 'Ravi', 'Kapoor', 2, 1, 'ChurchGate Mumbai', 'kapoor@gmail.com')
(3, 'Komal', 'Bhandari', 3, 3, 'Jubilee Hills Hyderabad', 'komal@gmail.com')
(5, 'Priya', 'Rajhans', 4, 5, 'MG Road Bangaluru', 'as@yahoo.com')
(2, 'Rajiv', 'Khanna', 5, 2, 'Cannought Place new Delhi', 'admin@khanna.com')