Peewee is a simple and small ORM. It has few (but expressive) concepts, making it easy to learn and intuitive to use.
- A small, expressive ORM
- Written in python with support for versions 2.6+ and 3.2+.
- built-in support for sqlite, mysql and postgresql
- tons of extensions available in the playhouse
New to peewee? Here is a list of documents you might find most helpful when getting started:
- Quickstart guide -- this guide covers all the essentials. It will take you between 5 and 10 minutes to go through it.
- Guide to the various query operators describes how to construct queries and combine expressions.
- Field types table lists the various field types peewee supports and the parameters they accept.
Defining models is similar to Django or SQLAlchemy:
from peewee import * import datetime db = SqliteDatabase('my_database.db', threadlocals=True) class BaseModel(Model): class Meta: database = db class User(BaseModel): username = CharField(unique=True) class Tweet(BaseModel): user = ForeignKeyField(User, related_name='tweets') message = TextField() created_date = DateTimeField(default=datetime.datetime.now) is_published = BooleanField(default=True)
Connect to the database and create tables:
db.connect() db.create_tables([User, Tweet])
Create a few rows:
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')
Queries are expressive and composable:
# A simple query selecting a user. User.get(User.username == 'charles') # Get tweets created by one of several users. The "<<" operator # corresponds to the SQL "IN" operator. usernames = ['charlie', 'huey', 'mickey'] users = User.select().where(User.username << usernames) tweets = Tweet.select().where(Tweet.user << users) # We could accomplish the same using a JOIN: tweets = (Tweet .select() .join(User) .where(User.username << 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 Counter.update(count=Counter.count + 1).where( Counter.url == request.url)
Check out the example app for a working Twitter-clone website written with Flask.
Check the documentation for more examples.
Specific question? Come hang out in the #peewee channel on freenode.irc.net, or post to the mailing list, http://groups.google.com/group/peewee-orm . If you would like to report a bug, create a new issue on GitHub.
Still want more info?
I've written a number of blog posts about building applications and web-services with peewee (and usually Flask). If you'd like to see some real-life applications that use peewee, the following resources may be useful:
- Building a note-taking app with Flask and Peewee as well as Part 2 and Part 3.
- Analytics web service built with Flask and Peewee.
- Personalized news digest (with a boolean query parser!).
- Using peewee to explore CSV files.
- Structuring Flask apps with Peewee.
- Creating a lastpass clone with Flask and Peewee.
- Building a web-based encrypted file manager with Flask, peewee and S3.
- Creating a bookmarking web-service that takes screenshots of your bookmarks.
- Building a pastebin, wiki and a bookmarking service using Flask and Peewee.
- Encrypted databases with Python and SQLCipher.
- Dear Diary: An Encrypted, Command-Line Diary with Peewee.
- Query Tree Structures in SQLite using Peewee and the Transitive Closure Extension.