练了一天,基本的东东应该有感觉了。

#coding=utf-8

from datetime import datetime
from sqlalchemy import (MetaData, Table, Column, Integer, Numeric, String, Boolean,
                        DateTime, ForeignKey, ForeignKey, create_engine)
from sqlalchemy import (insert, select, update, delete, text, desc, cast, and_, or_, not_)
from sqlalchemy.sql import func

metadata = MetaData()

cookies = Table('cookies', metadata,
                Column('cookie_id', Integer(), primary_key=True),
                Column('cookie_name', String(50), index=True),
                Column('cookie_recipe_url', String(255)),
                Column('cookie_sku', String(55)),
                Column('quantity', Integer()),
                Column('unit_cost', Numeric(12, 2))
                )

users = Table('users', metadata,
              Column('user_id', Integer(), primary_key=True),
              Column('username', String(15), nullable=False, unique=True),
              Column('email_address', String(255), nullable=False),
              Column('phone', String(20), nullable=False),
              Column('password' ,String(25), nullable=False),
              Column('created_on', DateTime(), default=datetime.now),
              Column('updated_on', DateTime(), default=datetime.now, onupdate=datetime.now)
              )

orders = Table('orders', metadata,
               Column('order_id', Integer(), primary_key=True),
               Column('user_id', ForeignKey('users.user_id')),
               Column('shipped', Boolean(), default=False)
               )

line_items = Table('line_items', metadata,
                   Column('line_items_id', Integer(), primary_key=True),
                   Column('order_id', ForeignKey('orders.order_id')),
                   Column('cookie_id', ForeignKey('cookies.cookie_id')),
                   Column('quantity', Integer()),
                   Column('extended_cost', Numeric(12, 2))
                   )

engine = create_engine('mysql+pymysql://user:password@1.2.3.4:3306/cookies')
metadata.create_all(engine)
connection = engine.connect()
'''
s = select([cookies])
rp = connection.execute(s)
results = rp.fetchall()
print results

s = cookies.select()
rp = connection.execute(s)
# print rp.first()
for record in rp:
    print(record.cookie_name)

results = rp.fetchall()
first_row = results[0]
print first_row[1], first_row.cookie_name, first_row[cookies.c.cookie_name]

s = select([cookies.c.cookie_name, cookies.c.quantity])
s = s.order_by(desc(cookies.c.quantity))
s = s.limit(4)
rp = connection.execute(s)
print(rp.keys())
for cookie in rp:
    print('{} - {}'.format(cookie.quantity, cookie.cookie_name))

s = select([func.sum(cookies.c.quantity)])
rp = connection.execute(s)
print(rp.scalar())

# s = select([func.count(cookies.c.cookie_name)])
s = select([func.count(cookies.c.cookie_name).label('inventory_count')])
rp = connection.execute(s)
record = rp.first()
print(record.keys())
print(record.inventory_count

# s = select([cookies]).where(cookies.c.cookie_name == 'chocolate chip')
s = select([cookies]).where(cookies.c.cookie_name.like('%chocolate%'))
rp = connection.execute(s)
for record in rp.fetchall():
    print(record.cookie_name)

s = select([cookies.c.cookie_name, 'SKU-' + cookies.c.cookie_sku])
for row in connection.execute(s):
    print(row)

s = select([cookies.c.cookie_name,
            cast((cookies.c.quantity * cookies.c.unit_cost),
                 Numeric(12, 2)).label('inv_cost')])

for row in connection.execute(s):
    print('{} - {}'.format(row.cookie_name, row.inv_cost))

s = select([cookies]).where(
    and_(cookies.c.quantity.between(10, 50),
         cookies.c.cookie_name.contains('chip')
         )
    )
for row in connection.execute(s):
    print(row.cookie_name)

u = update(cookies).where(cookies.c.cookie_name == "chocolate chip")
u = u.values(quantity=(cookies.c.quantity + 120))
result = connection.execute(u)
print(result.rowcount)
s = select([cookies]).where(cookies.c.cookie_name == "chocolate chip")
result = connection.execute(s).first()
for key in result.keys():
    print('{:>20}: {}'.format(key, result[key]))

u = delete(cookies).where(cookies.c.cookie_name == "dark chocolate chip")
result = connection.execute(u)
print(result.rowcount)

s = select([cookies]).where(cookies.c.cookie_name == "dark chocolate chip")
result = connection.execute(s).fetchall()
print(len(result))

customer_list = [
    {
        'username': 'cookiemon',
        'email_address': 'mon@cookie.com',
        'phone': '111-111-1111',
        'password': 'password'
        },
    {
        'username': 'cakeeater',
        'email_address': 'cakeeater@cake.com',
        'phone': '222-222-2222',
        'password': 'password'
        },
    {
        'username': 'pieguy',
        'email_address': 'guy@pie.com',
        'phone': '333-333-3333',
        'password': 'password'
        }
    ]
ins = users.insert()
result = connection.execute(ins, customer_list)

ins = insert(orders).values(user_id=1, order_id=1)
result = connection.execute(ins)
ins = insert(line_items)

order_items = [
    {
        'order_id': 1,
        'cookie_id': 1,
        'quantity': 2,
        'extended_cost': 1.00
        },
    {
        'order_id': 1,
        'cookie_id': 3,
        'quantity': 12,
        'extended_cost': 3.00
        }
    ]

result = connection.execute(ins, order_items)
ins = insert(orders).values(user_id=2, order_id=2)
result = connection.execute(ins)
ins = insert(line_items)
order_items = [
    {
        'order_id': 2,
        'cookie_id': 1,
        'quantity': 24,
        'extended_cost': 12.00
        },
    {
        'order_id': 2,
        'cookie_id': 4,
        'quantity': 6,
        'extended_cost': 6.00
        }
    ]
result = connection.execute(ins, order_items)

columns = [orders.c.order_id, users.c.username, users.c.phone,
           cookies.c.cookie_name, line_items.c.quantity,
           line_items.c.extended_cost]
cookiemon_orders = select(columns)
cookiemon_orders = cookiemon_orders.select_from(orders.join(users).join(
    line_items).join(cookies)).where(users.c.username == 'cookiemon')
result = connection.execute(cookiemon_orders).fetchall()
for row in result:
    print(row)

columns = [users.c.username, func.count(orders.c.order_id)]
all_orders = select(columns)
all_orders = all_orders.select_from(users.outerjoin(orders))
all_orders = all_orders.group_by(users.c.username)
result = connection.execute(all_orders).fetchall()
for row in result:
    print(row)

def get_orders_by_customer(cust_name, shipped=None, details=False):
    columns = [orders.c.order_id, users.c.username, users.c.phone]
    joins = users.join(orders)
    if details:
        columns.extend([cookies.c.cookie_name,
               line_items.c.quantity,line_items.c.extended_cost])
        joins = joins.join(line_items).join(cookies)
    cust_orders = select(columns)
    cust_orders = cust_orders.select_from(joins)
    cust_orders = cust_orders.where(users.c.username == cust_name)
    if shipped is not None:
        cust_orders = cust_orders.where(orders.c.shipped == shipped)
    result = connection.execute(cust_orders).fetchall()
    for row in result:
        print(row)
    return result

get_orders_by_customer('cakeeater')
get_orders_by_customer('cakeeater', details=True)
get_orders_by_customer('cakeeater', shipped=True)
get_orders_by_customer('cakeeater', shipped=False)
get_orders_by_customer('cakeeater', shipped=False, details=True)

result = connection.execute("select * from orders").fetchall()
print(result)
'''
stmt = select([users]).where(text("username='cookiemon'"))
print(connection.execute(stmt).fetchall())

SQLAlchemy增删改查基本操作,及SQL基本技能样码(join,group)的更多相关文章

  1. SQLAlchemy 增删改查 一对多 多对多

    1.创建数据表 # ORM中的数据表是什么呢? # Object Relation Mapping # Object - Table 通过 Object 去操纵数据表 # 从而引出了我们的第一步创建数 ...

  2. SQLAlchemyの增删改查

    用a*my写原味sql from sqlalchemy.ext.declarative import declarative_base from sqlalchemy import Column, I ...

  3. 13,SQLAlchemy 增删改查 一对多 多对多

    今天来聊一聊 Python 的 ORM 框架 SQLAlchemy Models 是配置和使用比较简单,因为他是Django自带的ORM框架,也正是因为是Django原生的,所以兼容性远远不如SQLA ...

  4. SQLAlchemy 增删改查 一对一 多对多

    首先要导入SQLAIchemy模块 from sqlalchemy.ect.declaative import declarative_base 创建orm基类 Base = declarative_ ...

  5. MySQL数据库学习笔记(九)----JDBC的ResultSet接口(查询操作)、PreparedStatement接口重构增删改查(含SQL注入的解释)

    [声明] 欢迎转载,但请保留文章原始出处→_→ 生命壹号:http://www.cnblogs.com/smyhvae/ 文章来源:http://www.cnblogs.com/smyhvae/p/4 ...

  6. (2)MySQL的增删改查基本操作

    数据库增删改查的基本操作(数据文件在data目录下) 数据库的专业术语 1.文件夹:数据库 2.文件:数据表 指令的注意事项 1.用use的时候指令结尾不需要跟一个分号 ‘:’ 2.如果用show或其 ...

  7. 利用Java针对MySql封装的jdbc框架类 JdbcUtils 完整实现(包含增删改查、JavaBean反射原理,附源码)

    最近看老罗的视频,跟着完成了利用Java操作MySql数据库的一个框架类JdbcUtils.java,完成对数据库的增删改查.其中查询这块,包括普通的查询和利用反射完成的查询,主要包括以下几个函数接口 ...

  8. 偏于SQL语句的 sqlAlchemy 增删改查操作

    ORM 江湖 曾几何时,程序员因为惧怕SQL而在开发的时候小心翼翼的写着sql,心中总是少不了恐慌,万一不小心sql语句出错,搞坏了数据库怎么办?又或者为了获取一些数据,什么内外左右连接,函数存储过程 ...

  9. SQLAlchemy增删改查

    sqlalchemy中让MySQL支持中文字符 engine = create_engine("mysql+pymysql://root:mysql8@localhost/mysqltest ...

随机推荐

  1. Hibernate中的GetCurrentSession()方法

    从3.0.1版本开 始,Hibernate增加了SessionFactory.getCurrentSession()方法. 采用getCurrentSession()创建的session在commit ...

  2. centos 谷歌浏览器安装

    首先,这个是坑 http://www.tecmint.com/install-google-chrome-on-redhat-centos-fedora-linux/ 安装会报错,按照错误找到以下资源 ...

  3. 转:TopN推荐系统——推荐的实现与推荐效果的评价指标

    转自:用户推荐系统_python 代码-豆瓣书籍:项亮的<推荐系统实践> import random import math class UserBasedCF: def __init__ ...

  4. 不知道数据库中表的列类型的前提下,使用JDBC正确的取出数据

    概要: 使用jdbc 如果在不知道表结构的情况下,如何读出表信息? 使用ResultSetMetaData; 然后使用getColumnType 获取column 类型 使用getColumnName ...

  5. glib-2.49.4-msys-x86-staticLib.7z

    glib-2.49.4 MSYS 静态库 编译 export LIBFFI_CFLAGS=" -I/usr/local/lib/libffi-3.2.1/include " \ e ...

  6. Java for LeetCode 236 Lowest Common Ancestor of a Binary Tree

    解题思路一: DFS到每个节点的路径,根据路径算出LCA: public class Solution { public TreeNode lowestCommonAncestor(TreeNode ...

  7. ubuntu下安装mysql

    现在的软件越来越好安装,尤其是在ubuntu下安装软件,更是没有技巧,只需要在联网的情况下使用apt-get inatll 即可.在决定安装mysql之前,要先确定系统是否已经安装mysql.如下图: ...

  8. 【leetcode】Remove Element (easy)

    Given an array and a value, remove all instances of that value in place and return the new length. T ...

  9. 【hadoop2.6.0】通过代码运行程序流程

    之前跑了一下hadoop里面自带的例子,现在顺一下如何通过源代码来运行程序. 我懒得装eclipse,就全部用命令行了. 整体参考官网上的:http://hadoop.apache.org/docs/ ...

  10. HDU 5901 Count primes (1e11内的素数个数) -2016 ICPC沈阳赛区网络赛

    题目链接 题意:求[1,n]有多少个素数,1<=n<=10^11.时限为6000ms. 官方题解:一个模板题, 具体方法参考wiki或者Four Divisors. 题解:给出两种代码. ...