peewee下載 - peewee原始碼下載

peewee

Python

3.17.8

下載

尿尿

Peewee 是一個簡單且小型的 ORM。它的概念很少（但富有表現力），因此易於學習且直觀易用。

一個小型的、富有表現力的 ORM
python 2.7+ 和 3.4+
支援sqlite、mysql、mariadb、postgresql
大量的擴展

剛接觸小便？這些可能會有所幫助：

快速入門
推特應用程式範例
交互使用 peewee
模型和領域
查詢
關係和連接

範例

定義模型類似 Django 或 SQLAlchemy：

 from peewee import *
import datetime


db = SqliteDatabase ( 'my_database.db' )

class BaseModel ( Model ):
    class Meta :
        database = db

class User ( BaseModel ):
    username = CharField ( unique = True )

class Tweet ( BaseModel ):
    user = ForeignKeyField ( User , backref = 'tweets' )
    message = TextField ()
    created_date = DateTimeField ( default = datetime . datetime . now )
    is_published = BooleanField ( default = True )

連接資料庫並建立表格：

 db . connect ()
db . create_tables ([ User , Tweet ])

建立幾行：

 charlie = User . create ( username = 'charlie' )
huey = User ( username = 'huey' )
huey . save ()

# No need to set `is_published` or `created_date` since they
# will just use the default values we specified.
Tweet . create ( user = charlie , message = 'My first tweet' )

查詢具有表達性和可組合性：

 # A simple query selecting a user.
User . get ( User . username == 'charlie' )

# Get tweets created by one of several users.
usernames = [ 'charlie' , 'huey' , 'mickey' ]
users = User . select (). where ( User . username . in_ ( usernames ))
tweets = Tweet . select (). where ( Tweet . user . in_ ( users ))

# We could accomplish the same using a JOIN:
tweets = ( Tweet
          . select ()
          . join ( User )
          . where ( User . username . in_ ( usernames )))

# How many tweets were published today?
tweets_today = ( Tweet
                . select ()
                . where (
                    ( Tweet . created_date >= datetime . date . today ()) &
                    ( Tweet . is_published == True ))
                . count ())

# Paginate the user table and show me page 3 (users 41-60).
User . select (). order_by ( User . username ). paginate ( 3 , 20 )

# Order users by the number of tweets they've created:
tweet_ct = fn . Count ( Tweet . id )
users = ( User
         . select ( User , tweet_ct . alias ( 'ct' ))
         . join ( Tweet , JOIN . LEFT_OUTER )
         . group_by ( User )
         . order_by ( tweet_ct . desc ()))

# Do an atomic update (for illustrative purposes only, imagine a simple
# table for tracking a "count" associated with each URL). We don't want to
# naively get the save in two separate steps since this is prone to race
# conditions.
Counter . update ( count = Counter . count + 1 ). where ( Counter . url == request . url )