SQLAlchemy – 在分组依据之前排序

在本文中，我们将了解如何在 SQLAlchemy 中针对Python中的 PostgreSQL 数据库使用 groupby函数之前执行 orderby函数。

在 PostgreSQL 中，Group by 是使用名为 groupby() 的函数执行的，而 order by 操作是使用 orderby() 执行的。

Usage: func.sum(). func.group_by(), func.sum(), func.order_by()

为演示创建表

从 SQLAlchemy 包中导入必要的函数。使用如下所示的 create_engine()函数建立与 PostgreSQL 数据库的连接，并创建一个名为 books 的表，其中包含 book_id 和 book_price 列。如图所示，使用 insert() 和 values()函数将记录插入表中。

Python3

# import necessary packages
import sqlalchemy
from sqlalchemy import create_engine, MetaData,
Table, Column, Numeric, Integer, VARCHAR
from sqlalchemy.engine import result
 
# establish connections
engine = create_engine(
    "database+dialect://username:password@localhost:port/databasename")
 
# initialize the Metadata Object
meta = MetaData(bind=engine)
MetaData.reflect(meta)
 
# create a table schema
books = Table(
    'books', meta,
    Column('book_id', Integer, primary_key=True),
    Column('book_price', Numeric),
    Column('genre', VARCHAR),
    Column('book_name', VARCHAR)
)
 
meta.create_all(engine)
 
# insert records into the table
statement1 = books.insert().values(book_id=1, book_price=12.2,
                                   genre='fiction',
                                   book_name='Old age')
statement2 = books.insert().values(book_id=2, book_price=13.2,
                                   genre='non-fiction',
                                   book_name='Saturn rings')
statement3 = books.insert().values(book_id=3, book_price=121.6,
                                   genre='fiction',
                                   book_name='Supernova')
statement4 = books.insert().values(book_id=4, book_price=100,
                                   genre='non-fiction',
                                   book_name='History of the world')
statement5 = books.insert().values(book_id=5, book_price=1112.2,
                                   genre='fiction',
                                   book_name='Sun city')
 
# execute the insert records statement
engine.execute(statement1)
engine.execute(statement2)
engine.execute(statement3)
engine.execute(statement4)
engine.execute(statement5)

Python3

# Get the `books` table from the Metadata object
BOOKS = meta.tables['books']
 
# SQLAlchemy Query to ORDER BY and GROUP BY
query = sqlalchemy.select([
    BOOKS.c.genre, sqlalchemy.func.sum(BOOKS.c.book_price)
]).order_by(BOOKS.c.genre).group_by(BOOKS.c.genre)
 
# Fetch all the records
result = engine.execute(query).fetchall()
 
# View the records
for record in result:
    print("\n", record)

输出：

样品表

在 SQLAlchemy 中实现 sum 和 order by

在 groupby函数之前编写 orderby函数与传统 SQL 查询的过程略有不同，如下所示

sqlalchemy.select([

Tablename.c.column_name,

sqlalchemy.func.sum(Tablename.c.column_name)

]).order_by(Tablename.c.column_name).group_by(Tablename.c.column_name)

编程需要懂一点英语

从连接到数据库时初始化的元数据对象获取书籍表。将 SQL 查询传递给 execute()函数并使用 fetchall()函数获取所有结果。使用 for 循环遍历结果。下面代码中显示的 SQLAlchemy 查询按类型对书籍进行分组，然后根据类型按字母顺序对书籍进行排序，并返回每种类型的销售额总和。

Python3

# Get the `books` table from the Metadata object
BOOKS = meta.tables['books']
 
# SQLAlchemy Query to ORDER BY and GROUP BY
query = sqlalchemy.select([
    BOOKS.c.genre, sqlalchemy.func.sum(BOOKS.c.book_price)
]).order_by(BOOKS.c.genre).group_by(BOOKS.c.genre)
 
# Fetch all the records
result = engine.execute(query).fetchall()
 
# View the records
for record in result:
    print("\n", record)

输出：

查询结果分组前的orderby