Introduction to SQLAlchemy relational operations under Python (with code)

This article brings you an introduction to SQLAlchemy relational operations under Python (with code). It has certain reference value. Friends in need can refer to it. I hope it will be helpful to you.

Relational database is a database based on the relational model, so the relationship between tables is particularly important in database programming. This section focuses on how to define relationships in SQLAlchemy and how to use relationships to perform queries, so that readers can quickly master the relationship operations of SQLAlchemy.

1. Case

Design 3 entity tables: class table, student table, teacher table, and 1 relational table: class_teacher. There is a one-to-many relationship between classes and students, and a many-to-many relationship between classes and teachers.

from sqlalchemy import Table,Column,Integer,ForeignKey,String
from sqlalchemy.orm import relationship,backref
from sqlalchemy.ext.declarative import declarative_base

Base=declarative_base()

class Class(Base):
    __tablename__='class'
    class_id=Column(Integer,primary_key=True)
    name=Column(String(50))
    level=Column(Integer)
    address=Column(String(50))

    class_teachers=relationship("ClassTeacher",backref="class")
    students=relationship("Student",backref="class")

class Student(Base):
    __tablename__='student'
    student_id=Column(Integer,primary_key=True)
    name=Column(String(50))
    age=Column(Integer)
    gender=Column(String(10))
    address=Column(String(50))
    class_id=Column(Integer,ForeignKey('class.id'))

class Teacher(Base):
    __tablename__='teacher'
    teacher_id=Column(Integer,primary_key=True)
    name=Column(String(50))
    gender=Column(String(10))
    telephone=Column(String(50))
    address=Column(String(50))
    class_teachers=relationship("ClassTeacher",backref="teacher")

class ClassTeacher(Base):
    __tablename__='class_teacher'
    teacher_id=Column(Integer,ForeignKey('teacher.teacher_id'),primary_key=True)
    class_id=Column(Integer,ForeignKey("class.id"),primary_key=True)

The code uses 4 SQLAlchemy models to define 4 tables. The parts related to the relationship definition are as follows:

• Foreign key settings: in the column In the definition, pass in the ForeignKey for Column to set the foreign key.

class_id=Column(Integer,ForeignKey('class.id'))

• Relationship settings: Establish a reference to the word table in the parent model through the relationship keyword. For example, the relationship settings in the Class model are as follows:

students=relationship("Student",backref="calss")

The backref parameter is an optional parameter. If backref is set, this statement also sets a reference to the child table from the parent table.

• Use of one-to-many relationship: In the future, you can directly obtain the information of all students in the relevant class through the students attribute. The following code can print all the student information of the class [Class 3, Class 2].

class=session.query(Class).filter(Clss.name=="三年二班").first()

for student in class_.students:
    print(student)

• The use of many-to-many relationships: implemented through the associated model ClassTeacher, where the foreign keys of the model Class and Teacher are set respectively, and set in the parent model The corresponding relationship is implemented. The many-to-many relationship can also be imagined as an association table, which implements a many-to-one relationship between two parent tables. There is a many-to-many relationship between classes and teachers. The following code can print the information of all teachers in the class [Class 2, Grade 3]

class=session.query(Class).filter(Class.name=="三年二班").first()
for class_teacher in class_.class_teachers:
    teacher=class_teacher.teacher
    print(teacher)

In the above code, class_teacher.teacher is targeted in the model teacher Backreference defined by ClassTeacher.

2. Connection query

In actual development, when there is a relationship, there is an indispensable need for multi-table connection query. The following is a practical example to demonstrate how to perform multi-table join queries.

You can use the join keyword in the query statement to perform a connection query and print out the names of all third-year students:

students=session.query(Student).join(Class).filter(Class.level==3).all()
for student in students:
    print(student.namr)

The above query function will automatically use the foreign key relationship as a connection condition. This query It is automatically translated into the following SQL statement by SQLAlchemy and executed:

SELECT student.student_id AS student_student_id,
    student.name AS student.name,
    student.age AS student.age,
    student.gender AS student.gender,
    student.address AS student.address,
    student.class_id AS student_class_id
FROM student JOIN class ON student.class_id=class.class_id
WHERE class.leve=?
(3,)

If you need to print out the inner part of the connected table, you can specify multiple table objects in the query.

The following statement prints out the names of all third-grade students as well as the names of their classes.

for student,class_ in session.query(Student,Class).join(Class).filter(Class.level==3).all():
    print(student.name,class_.name)

The above query function will automatically use the foreign key relationship as a connection condition. The query will be automatically translated by SQLAlchemy into the following SQL statement and executed:

SELECT student.student_id AS student_student_id,
    student.name AS student.name,
    student.age AS student.age,
    student.gender AS student.gender,
    student.address AS student.address,
    student.class_id AS student_class_id,
    class.class_id AS class_class_id,
    class.name AS class_name,
    class.level AS class_level,
    class.address AS class_location
FROM student JOIN class ON student.class_id=class.class_id
WHERE class.leve=?
(3,)

If you need to use other fields other than foreign keys as The connection conditions need to be set by the developer in join. The following prints out the names of students whose class address is the same as the student's address:

for student_name, in session.query(Student.name).join(Class,Class.address==Student.address).filter(Class.level==3).all():
    print(student_name)

The above query function is based on the statement specified by the developer as the connection condition, and because the field to be queried is directly specified, it is reduced The queried fields in actual SQL improve performance. The query is automatically translated by SQLAlchemy into the following SQL statement for execution:

SELECT student.name AS student_name, FROM student JOIN class ON student.address=class.address

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