Pony是Python的一种ORM,它允许使用生成器表达式来构造查询,通过将生成器表达式的抽象语法树解析成SQL语句。它也有在线ER图编辑器可以帮助你创建Model。
示例分析
Pony语句:
select(p for p in Person if p.age > 20)
翻译成sql语句就是:
SELECT p.id, p.name, p.age, p.classtype, p.mentor, p.gpa, p.degree FROM person p WHERE p.classtype IN ('Student', 'Professor', 'Person') AND p.age > 20
Pony语句:
select(c for c in Customer if sum(c.orders.price) > 1000)
翻译成sql语句就是:
SELECT "c"."id" FROM "Customer" "c" LEFT JOIN "Order" "order-1" ON "c"."id" = "order-1"."customer" GROUP BY "c"."id" HAVING coalesce(SUM("order-1"."total_price"), 0) > 1000
安装Pony
pip install pony
使用Pony
#!/usr/bin/env python #-*- coding:utf-8 -*- import datetime import pony.orm as pny import sqlite3 # conn = sqlite3.connect('D:\日常python学习PY2\Pony学习\music.sqlite') # print conn # database = pny.Database() # database.bind("sqlite","music.sqlite",create_db=True) # 路径建议写绝对路径。我这边开始写相对路径报错 unable to open database file database = pny.Database("sqlite","D:\日常python学习PY2\Pony学习\music.sqlite",create_db=True) ######################################################################## class Artist(database.Entity): """ Pony ORM model of the Artist table """ name = pny.Required(unicode) #被外键关联 albums = pny.Set("Album") ######################################################################## class Album(database.Entity): """ Pony ORM model of album table """ #外键字段artlist,外键关联表Artist,Artist表必须写Set表示被外键关联 #这个外键字段默认就是index=True,除非自己指定index=False才不会创建索引,索引名默认为[idx_表名__字段](artist) artist = pny.Required(Artist) title = pny.Required(unicode) release_date = pny.Required(datetime.date) publisher = pny.Required(unicode) media_type = pny.Required(unicode) # turn on debug mode pny.sql_debug(True) # 显示debug信息(sql语句) # map the models to the database # and create the tables, if they don't exist database.generate_mapping(create_tables=True) # 如果数据库表没有创建表
运行之后生成sqlite如下:
上述代码对应的sqlite语句是:
GET CONNECTION FROM THE LOCAL POOL PRAGMA foreign_keys = false BEGIN IMMEDIATE TRANSACTION CREATE TABLE "Artist" ( "id" INTEGER PRIMARY KEY AUTOINCREMENT, "name" TEXT NOT NULL ) CREATE TABLE "Album" ( "id" INTEGER PRIMARY KEY AUTOINCREMENT, "artist" INTEGER NOT NULL REFERENCES "Artist" ("id"), "title" TEXT NOT NULL, "release_date" DATE NOT NULL, "publisher" TEXT NOT NULL, "media_type" TEXT NOT NULL ) CREATE INDEX "idx_album__artist" ON "Album" ("artist") SELECT "Album"."id", "Album"."artist", "Album"."title", "Album"."release_date", "Album"."publisher", "Album"."media_type" FROM "Album" "Album" WHERE 0 = 1 SELECT "Artist"."id", "Artist"."name" FROM "Artist" "Artist" WHERE 0 = 1 COMMIT PRAGMA foreign_keys = true CLOSE CONNECTION
插入/增加数据
源码地址:https://github.com/flowpig/daily_demos
#!/usr/bin/env python #-*- coding:utf-8 -*- import datetime import pony.orm as pny from models import Album, Artist from database import PonyDatabase # ---------------------------------------------------------------------- @pny.db_session def add_data(): """""" new_artist = Artist(name=u"Newsboys") bands = [u"MXPX", u"Kutless", u"Thousand Foot Krutch"] for band in bands: artist = Artist(name=band) album = Album(artist=new_artist, title=u"Read All About It", release_date=datetime.date(1988, 12, 01), publisher=u"Refuge", media_type=u"CD") albums = [{"artist": new_artist, "title": "Hell is for Wimps", "release_date": datetime.date(1990, 07, 31), "publisher": "Sparrow", "media_type": "CD" }, {"artist": new_artist, "title": "Love Liberty Disco", "release_date": datetime.date(1999, 11, 16), "publisher": "Sparrow", "media_type": "CD" }, {"artist": new_artist, "title": "Thrive", "release_date": datetime.date(2002, 03, 26), "publisher": "Sparrow", "media_type": "CD"} ] for album in albums: a = Album(**album) if __name__ == "__main__": db = PonyDatabase() db.bind("sqlite", "D:\日常python学习PY2\Pony学习\music.sqlite", create_db=True) db.generate_mapping(create_tables=True) add_data() # use db_session as a context manager with pny.db_session: a = Artist(name="Skillet") ''' 您会注意到我们需要使用一个装饰器db_session来处理数据库。 它负责打开连接,提交数据并关闭连接。 你也可以把它作为一个上 下文管理器,with pny.db_session '''
更新数据
#!/usr/bin/env python #-*- coding:utf-8 -*- import pony.orm as pny from models import Artist, Album from database import PonyDatabase db = PonyDatabase() db.bind("sqlite", "D:\日常python学习PY2\Pony学习\music.sqlite", create_db=True) db.generate_mapping(create_tables=True) with pny.db_session: band = Artist.get(name="Newsboys") print band.name for record in band.albums: print record.title # update a record band_name = Artist.get(name="Kutless") band_name.name = "Beach Boys" #使用生成器形式查询 ''' result = pny.select(i.name for i in Artist) result.show() 结果: i.name -------------------- Newsboys MXPX Beach Boys Thousand Foot Krutch Skillet '''
删除记录
import pony.orm as pny from models import Artist with pny.db_session: band = Artist.get(name="MXPX") band.delete()
Pony补充
可以连接的数据库:
##postgres db.bind('postgres', user='', password='', host='', database='') ##sqlite create_db:如果数据库不存在创建数据库文件 db.bind('sqlite', 'filename', create_db=True) ##mysql db.bind('mysql', host='', user='', passwd='', db='') ##Oracle db.bind('oracle', 'user/password@dsn')
Entity(实体)类似mvc里面的model
在创建实体实例之前,需要将实体映射到数据库表,生成映射后,可以通过实体查询数据库并创建新的实例。db.Entity自己定义新的实体必须从db.Entity继承
属性
class Customer(db.Entity): name = Required(str) picture = Optional(buffer) sql_debug(True) # 显示debug信息(sql语句) db.generate_mapping(create_tables=True) # 如果数据库表没有创建表
属性类型
Required and Optional
通常实体属性分为Required(必选)和Optional(可选)
PrimaryKey(主键)
默认每个实体都有一个主键,默认添加了id=PrimaryKey(int,auto=True)属性
class Product(db.Entity): name = Required(str, unique=True) price = Required(Decimal) description = Optional(str) #等价于下面 class Product(db.Entity): id = PrimaryKey(int, auto=True) name = Required(str, unique=True) price = Required(Decimal) description = Optional(str)
Set
定义了一对一,一对多,多对多等数据结构
# 一对一 class User(db.Entity): name = Required(str) cart = Optional("Cart") #必须Optional-Required or Optional-Optional class Cart(db.Entity): user = Required("User") # 多对多 class Student(db.Entity): name = pny.Required(str) courses = pny.Set("Course") class Course(db.Entity): name = pny.Required(str) semester = pny.Required(int) students = pny.Set(Student) pny.PrimaryKey(name, semester) #联合主键 pny.sql_debug(True) # 显示debug信息(sql语句) db.generate_mapping(create_tables=True) # 如果数据库表没有创建表 #------------------------------------------------------- #一对多 class Artist(database.Entity): """ Pony ORM model of the Artist table """ name = pny.Required(unicode) #被外键关联 albums = pny.Set("Album") class Album(database.Entity): """ Pony ORM model of album table """ #外键字段artlist,外键关联表Artist,Artist表必须写Set表示被外键关联 #这个外键字段默认就是index=True,除非自己指定index=False才不会创建索引,索引名默认为[idx_表名__字段](artist) artist = pny.Required(Artist) #外键字段(数据库显示artist) title = pny.Required(unicode) release_date = pny.Required(datetime.date) publisher = pny.Required(unicode) media_type = pny.Required(unicode) # Compositeindexes(复合索引) class Example1(db.Entity): a = Required(str) b = Optional(int) composite_index(a, b) #也可以使用字符串composite_index(a, 'b')
属性数据类型
格式为 :
属性名 = 属性类型(数据类型)
attr1 = Required(str) # 等价 attr2 = Required(unicode) attr3 = Required(LongStr) # 等价 attr4 = Required(LongUnicode) attr1 = Required(buffer) # Python 2 and 3 attr2 = Required(bytes) # Python 3 only #字符串长度,不写默认为255 name = Required(str,40) #VARCHAR(40) #整数的大小,默认2bit attr1 = Required(int, size=8) # 8 bit - TINYINT in MySQL attr2 = Required(int, size=16) # 16 bit - SMALLINT in MySQL attr3 = Required(int, size=24) # 24 bit - MEDIUMINT in MySQL attr4 = Required(int, size=32) # 32 bit - INTEGER in MySQL attr5 = Required(int, size=64) # 64 bit - BIGINT in MySQL #无符号整型 attr1 = Required(int, size=8, unsigned=True) # TINYINT UNSIGNED in MySQL # 小数和精度 price = Required(Decimal, 10, 2) #DECIMAL(10,2) # 时间 dt = Required(datetime,6) # 其它参数 unique 是否唯一 auto 是否自增 default 默认值 sql_default created_at = Required(datetime, sql_default='CURRENT_TIMESTAMP') index 创建索引 index='index_name' 指定索引名称 lazy 延迟加载的属性加载对象 cascade_delete 关联删除对象 column 映射到数据库的列名 columns Set(多对多列名) table 多对多中间表的表名字 nullable 允许该列为空 py_check 可以指定一个函数,检查数据是否合法和修改数据 class Student(db.Entity): name = Required(str) gpa = Required(float, py_check=lambda val: val >= 0 and val <= 5)
实例操作
# 获取实例 p = Person.get(name="Person") #返回单个实例,如同 Django ORM的get #------------------------------ # 查询 persons = Person.select() ''' select并没有连接数据库查询,只是返回一个Query object,调用persons[:]返回所有Person实例 ''' # limit persons [1:5] # show persons.show() # 生成器表达式查询,然后解析AST树的方式构造SQL语句 select(p for p in Person) #和Person.select()一样返回Query object select((p.id, p.name) for p in Person)[:] # 带where条件查询 select((p.id, p.name) for p in Person if p.age ==20)[:] # 分组聚合查询 select((max(p.age)) for p in Person)[:] #[25] max(p.age for p in Person) #25 select(p.age for p in Person).max() #25 #----------------------------- # 修改实例 @db_session def update_persons(): p = Person.get(id=2) p.page = 1000 commit() # 删除 @db_session def delete_persons(): p = Person.get(id=2) p.delete() commit()
pony使用还可以使用游标操作(这样就可以写原生sql语句了)
result = db.execute('''select name from Artist''') print result.fetchall()
类似Django ORM的save函数
before_insert() Is called only for newly created objects before it is inserted into the database. before_update() Is called for entity instances before updating the instance in the database. before_delete() Is called before deletion the entity instance in the database. after_insert() Is called after the row is inserted into the database. after_update() Is called after the instance updated in the database. after_delete() Is called after the entity instance is deleted in the database.
例如:
class Message(db.Entity): title = Required(str) content = Required(str) def before_insert(self): print("Before insert! title=%s" % self.title)
Pony ORM 非常有趣. Pony 可以将 Python Generators 翻译成 SQL. 它拥有可视编辑器和模型等其他特性. Free for Non-commercial use with paid commercial licenses. 语法: select(c for c in Customer if sum(c.orders.price) > 1000)
Pony ORM 实现了一个很有趣的功能:使用类似 Python 生成器的语法来创建数据库查询语句。 比如这样的代码: select( p for p in Person if p.name.startswith('Paul') ).order_by(Person.name)[:2] 会生成下面的 SQL 语句: SELECT "p"."id", "p"."name", "p"."age
Pony 是一个很有意思的 ORM, 它的特别之处在于可以使用 Python 生成器的语法来创建数据库请求, 我们可以用这样的语句来查询数据库: select(p for p in Product if p.name.startswith('A') and p.cost <= 1000) Pony 还提供了一个在线的数据库结构编辑器:Pony Editor 演示示例:University 注意:P
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