- Open and close connections.
- Execute queries.
- Manage transactions (and savepoints).
- Introspect tables, columns, indexes, and constraints.
- Model integration
Peewee comes with support for SQLite, MySQL and Postgres. Each database class provides some basic, database-specific configuration options.
from peewee import * # SQLite database using WAL journal mode and 64MB cache. sqlite_db = SqliteDatabase('/path/to/app.db', pragmas=( ('journal_mode', 'wal'), ('cache_size', -1024 * 64))) # Connect to a MySQL database on network. mysql_db = MySQLDatabase('my_app', user='app', password='db_password', host='10.1.0.8', port=3316) # Connect to a Postgres database. pg_db = PostgresqlDatabase('my_app', user='postgres', password='secret', host='10.1.0.9', port=5432)
Peewee provides advanced support for SQLite and Postgres via database-specific extension modules. To use the extended-functionality, import the appropriate database-specific module and use the database class provided:
from playhouse.sqlite_ext import SqliteExtDatabase # Use SQLite (will register a REGEXP function and set busy timeout to 3s). db = SqliteExtDatabase('/path/to/app.db', regexp_function=True, timeout=3, pragmas=(('journal_mode', 'wal'),)) from playhouse.postgres_ext import PostgresqlExtDatabase # Use Postgres (and register hstore extension). db = PostgresqlExtDatabase('my_app', user='postgres', register_hstore=True)
For more information on database extensions, see:
Initializing a Database¶
Database initialization method expects the name of the database
as the first parameter. Subsequent keyword arguments are passed to the
underlying database driver when establishing the connection, allowing you to
pass vendor-specific parameters easily.
For instance, with Postgresql it is common to need to specify the
password when creating your connection. These are not standard
Database parameters, so they will be passed directly back to
psycopg2 when creating connections:
db = PostgresqlDatabase( 'database_name', # Required by Peewee. user='postgres', # Will be passed directly to psycopg2. password='secret', # Ditto. host='db.mysite.com') # Ditto.
As another example, the
pymysql driver accepts a
which is not a standard Peewee
Database parameter. To set this
value, simply pass in
charset alongside your other values:
db = MySQLDatabase('database_name', user='www-data', charset='utf8mb4')
Consult your database driver’s documentation for the available parameters:
psql_db = PostgresqlDatabase('my_database', user='postgres') class BaseModel(Model): """A base model that will use our Postgresql database""" class Meta: database = psql_db class User(BaseModel): username = CharField()
If you would like to use these awesome features, use the
PostgresqlExtDatabase from the
from playhouse.postgres_ext import PostgresqlExtDatabase psql_db = PostgresqlExtDatabase('my_database', user='postgres')
To connect to a SQLite database, we will use
first parameter is the filename containing the database, or the string
:memory: to create an in-memory database. After the database filename, you
can specify arbitrary sqlite3 parameters.
sqlite_db = SqliteDatabase('my_app.db') class BaseModel(Model): """A base model that will use our Sqlite database.""" class Meta: database = sqlite_db class User(BaseModel): username = CharField() # etc, etc
The Playhouse, extensions to Peewee contains a SQLite extension module
which provides many SQLite-specific features such as full-text search, json extension support, and much, much more. If you would like
to use these awesome features, use the
SqliteExtDatabase from the
from playhouse.sqlite_ext import SqliteExtDatabase sqlite_db = SqliteExtDatabase('my_app.db', journal_mode='WAL')
SQLite allows run-time configuration of a number of parameters through
PRAGMA statements (documentation).
These statements are typically run against a new database connection. To run
one or more
PRAGMA statements against new connections, you can specify them
as a list or tuple of 2-tuples containing the pragma name and value:
db = SqliteDatabase('my_app.db', pragmas=( ('journal_mode', 'WAL'), ('cache_size', 10000), ('mmap_size', 1024 * 1024 * 32), ))
# Set cache size to 64MB for current connection. db.pragma('cache_size', -1024 * 64) # Same as above. db.cache_size = -1024 * 64 # Read the value of several pragmas: print('cache_size:', db.cache_size) print('foreign_keys:', db.foreign_keys) print('journal_mode:', db.journal_mode) print('page_size:', db.page_size) # Set foreign_keys pragma on current connection *AND* on all # connections opened subsequently. db.pragma('foreign_keys', 1, permanent=True)
Pragmas set using the
pragma() method, by default,
do not persist after the connection is closed. To configure a pragma to be
run whenever a connection is opened, specify
SQLite can be extended with user-defined Python code. The
SqliteDatabase class supports three types of user-defined
- Functions - which take any number of parameters and return a single value.
- Aggregates - which aggregate parameters from multiple rows and return a single value.
- Collations - which describe how to sort some value.
For even more extension support, see
is in the
Example user-defined function:
db = SqliteDatabase('analytics.db') from urllib.parse import urlparse @db.func('hostname') def hostname(url): if url is not None: return urlparse(url).netloc # Call this function in our code: # The following finds the most common hostnames of referrers by count: query = (PageView .select(fn.hostname(PageView.referrer), fn.COUNT(PageView.id)) .group_by(fn.hostname(PageView.referrer)) .order_by(fn.COUNT(PageView.id).desc()))
Example user-defined aggregate:
from hashlib import md5 @db.aggregate('md5') class MD5Checksum(object): def __init__(self): self.checksum = md5() def step(self, value): self.checksum.update(value.encode('utf-8')) def finalize(self): return self.checksum.hexdigest() # Usage: # The following computes an aggregate MD5 checksum for files broken # up into chunks and stored in the database. query = (FileChunk .select(FileChunk.filename, fn.MD5(FileChunk.data)) .group_by(FileChunk.filename) .order_by(FileChunk.filename, FileChunk.sequence))
@db.collation('ireverse') def collate_reverse(s1, s2): # Case-insensitive reverse. s1, s2 = s1.lower(), s2.lower() return (s1 < s2) - (s1 > s2) # Equivalent to -cmp(s1, s2) # To use this collation to sort books in reverse order... Book.select().order_by(collate_reverse.collation(Book.title)) # Or... Book.select().order_by(Book.title.asc(collation='reverse'))
For more information, see:
Set locking mode for transaction¶
SQLite transactions can be opened in three different modes:
- Deferred (default) - only acquires lock when a read or write is performed. The first read creates a shared lock and the first write creates a reserved lock. Because the acquisition of the lock is deferred until actually needed, it is possible that another thread or process could create a separate transaction and write to the database after the BEGIN on the current thread has executed.
- Immediate - a reserved lock is acquired immediately. In this mode, no other database may write to the database or open an immediate or exclusive transaction. Other processes can continue to read from the database, however.
- Exclusive - opens an exclusive lock which prevents all (except for read uncommitted) connections from accessing the database until the transaction is complete.
Example specifying the locking mode:
db = SqliteDatabase('app.db') with db.atomic('EXCLUSIVE'): do_something() @db.atomic('IMMEDIATE') def some_other_function(): # This function is wrapped in an "IMMEDIATE" transaction. do_something_else()
APSW, an Advanced SQLite Driver¶
Peewee also comes with an alternate SQLite database that uses apsw, an advanced sqlite driver, an advanced Python SQLite driver. More information on APSW can be obtained on the APSW project website. APSW provides special features like:
- Virtual tables, virtual file-systems, Blob I/O, backups and file control.
- Connections can be shared across threads without any additional locking.
- Transactions are managed explicitly by your code.
- Unicode is handled correctly.
- APSW is faster that the standard library sqlite3 module.
- Exposes pretty much the entire SQLite C API to your Python app.
If you would like to use APSW, use the
APSWDatabase from the
from playhouse.apsw_ext import APSWDatabase apsw_db = APSWDatabase('my_app.db')
To connect to a MySQL database, we will use
the database name, you can specify arbitrary connection parameters that will be
passed back to the driver (either MySQLdb or pymysql).
mysql_db = MySQLDatabase('my_database') class BaseModel(Model): """A base model that will use our MySQL database""" class Meta: database = mysql_db class User(BaseModel): username = CharField() # etc, etc
Error 2006: MySQL server has gone away¶
This particular error can occur when MySQL kills an idle database connection. This typically happens with web apps that do not explicitly manage database connections. What happens is your application starts, a connection is opened to handle the first query that executes, and, since that connection is never closed, it remains open, waiting for more queries.
To fix this, make sure you are explicitly connecting to the database when you need to execute queries, and close your connection when you are done. In a web-application, this typically means you will open a connection when a request comes in, and close the connection when you return a response.
See the adding_request_hooks for more information.
Connecting using a Database URL¶
import os from peewee import * from playhouse.db_url import connect # Connect to the database URL defined in the environment, falling # back to a local Sqlite database if no database URL is specified. db = connect(os.environ.get('DATABASE') or 'sqlite:///default.db') class BaseModel(Model): class Meta: database = db
Example database URLs:
- sqlite:///my_database.db will create a
SqliteDatabaseinstance for the file
my_database.dbin the current directory.
- sqlite:///:memory: will create an in-memory
- postgresql://postgres:my_password@localhost:5432/my_database will create a
PostgresqlDatabaseinstance. A username and password are provided, as well as the host and port to connect to.
- mysql://user:passwd@ip:port/my_db will create a
MySQLDatabaseinstance for the local MySQL database my_db.
- More examples in the db_url documentation.
Run-time database configuration¶
Sometimes the database connection settings are not known until run-time, when
these values may be loaded from a configuration file or the environment. In
these cases, you can defer the initialization of the database by specifying
None as the database_name.
database = SqliteDatabase(None) # Un-initialized database. class SomeModel(Model): class Meta: database = database
If you try to connect or issue any queries while your database is uninitialized you will get an exception:
>>> database.connect() Exception: Error, database not properly initialized before opening connection
To initialize your database, call the
init() method with the
database name and any additional keyword arguments:
database_name = raw_input('What is the name of the db? ') database.init(database_name, host='localhost', user='postgres')
For even more control over initializing your database, see the next section, Dynamically defining a database.
Dynamically defining a database¶
For even more control over how your database is defined/initialized, you can
Proxy objects act as a
placeholder, and then at run-time you can swap it out for a different object.
In the example below, we will swap out the database depending on how the app is
database_proxy = Proxy() # Create a proxy for our db. class BaseModel(Model): class Meta: database = database_proxy # Use proxy for our DB. class User(BaseModel): username = CharField() # Based on configuration, use a different database. if app.config['DEBUG']: database = SqliteDatabase('local.db') elif app.config['TESTING']: database = SqliteDatabase(':memory:') else: database = PostgresqlDatabase('mega_production_db') # Configure our proxy to use the db we specified in config. database_proxy.initialize(database)
Only use this method if your actual database driver varies at run-time. For
instance, if your tests and local dev environment run on SQLite, but your
deployed app uses PostgreSQL, you can use the
Proxy to swap out
engines at run-time.
However, if it is only connection values that vary at run-time, such as the
path to the database file, or the database host, you should instead use
Database.init(). See Run-time database configuration for more
To open a connection to a database, use the
>>> db = SqliteDatabase(':memory:') # In-memory SQLite database. >>> db.connect() True
If we try to call
connect() on an already-open database, we get a
>>> db.connect() Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/charles/pypath/peewee.py", line 2390, in connect raise OperationalError('Connection already opened.') peewee.OperationalError: Connection already opened.
To prevent this exception from being raised, we can call
connect() with an
>>> db.close() # Close connection. True >>> db.connect() True >>> db.connect(reuse_if_open=True) False
Note that the call to
False if the database
connection was already open.
To close a connection, use the
>>> db.close() True
close() on an already-closed connection will not result in an
exception, but will return
>>> db.connect() # Open connection. True >>> db.close() # Close connection. True >>> db.close() # Connection already closed, returns False. False
You can test whether the database is closed using the
>>> db.is_closed() True
A note of caution¶
Although it is not necessary to explicitly connect to the database before using
it, managing connections explicitly is considered a best practice. For
example, if the connection fails, the exception will be caught when the
connection is being opened, rather than some arbitrary time later when a query
is executed. Furthermore, if you are using a connection pool, it
is necessary to call
close() to ensure connections are recycled properly.
Peewee keeps track of the connection state using thread-local storage, making
Database object safe to use with multiple threads. Each
thread will have it’s own connection, and conversely, any given thread will
only have a single connection open at a given time.
The database object itself can be used as a context-manager, which opens a connection for the duration of the wrapped block of code. Additionally, a transaction is opened at the start of the wrapped block and committed before the connection is closed (unless an error occurs, in which case the transaction is rolled back).
>>> db.is_closed() True >>> with db: ... print(db.is_closed()) # db is open inside context manager. ... False >>> db.is_closed() # db is closed. True
If you want to manage transactions separately, you can use the
Database.connection_context() context manager.
>>> with db.connection_context(): ... # db connection is open. ... pass ... >>> db.is_closed() # db connection is closed. True
connection_context() method can also be used as a decorator:
@db.connection_context() def prepare_database(): # DB connection will be managed by the decorator, which opens # a connection, calls function, and closes upon returning. db.create_tables(MODELS) # Create schema. load_fixture_data(db)
DB-API Connection Object¶
To obtain a reference to the underlying DB-API 2.0 connection, use the
Database.connection() method. This method will return the
currently-open connection object, if one exists, otherwise it will open a new
>>> db.connection() <sqlite3.Connection object at 0x7f94e9362f10>
- Timeout after which connections will be recycled.
- Upper bound on the number of open connections.
from playhouse.pool import PooledPostgresqlExtDatabase db = PooledPostgresqlExtDatabase( 'my_database', max_connections=8, stale_timeout=300, user='postgres') class BaseModel(Model): class Meta: database = db
The following pooled database classes are available:
For web applications, it is common to open a connection when a request is received, and to close the connection when the response is delivered. In this section I will describe how to add hooks to your web app to ensure the database connection is handled properly.
These steps will ensure that regardless of whether you’re using a simple SQLite database, or a pool of multiple Postgres connections, peewee will handle the connections correctly.
Applications that receive lots of traffic may benefit from using a connection pool to mitigate the cost of setting up and tearing down connections on every request.
Flask and peewee are a great combo and my go-to for projects of any size. Flask provides two hooks which we will use to open and close our db connection. We’ll open the connection when a request is received, then close it when the response is returned.
from flask import Flask from peewee import * database = SqliteDatabase('my_app.db') app = Flask(__name__) # This hook ensures that a connection is opened to handle any queries # generated by the request. @app.before_request def _db_connect(): database.connect() # This hook ensures that the connection is closed when we've finished # processing the request. @app.teardown_request def _db_close(exc): if not database.is_closed(): database.close()
While it’s less common to see peewee used with Django, it is actually very easy to use the two. To manage your peewee database connections with Django, the easiest way in my opinion is to add a middleware to your app. The middleware should be the very first in the list of middlewares, to ensure it runs first when a request is handled, and last when the response is returned.
If you have a django project named my_blog and your peewee database is
defined in the module
my_blog.db, you might add the following middleware
# middleware.py from my_blog.db import database # Import the peewee database instance. class PeeweeConnectionMiddleware(object): def process_request(self, request): database.connect() def process_response(self, request, response): if not database.is_closed(): database.close() return response
To ensure this middleware gets executed, add it to your
# settings.py MIDDLEWARE_CLASSES = ( # Our custom middleware appears first in the list. 'my_blog.middleware.PeeweeConnectionMiddleware', # These are the default Django 1.7 middlewares. Yours may differ, # but the important this is that our Peewee middleware comes first. 'django.middleware.common.CommonMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', ) # ... other Django settings ...
I haven’t used bottle myself, but looking at the documentation I believe the following code should ensure the database connections are properly managed:
# app.py from bottle import hook #, route, etc, etc. from peewee import * db = SqliteDatabase('my-bottle-app.db') @hook('before_request') def _connect_db(): db.connect() @hook('after_request') def _close_db(): if not db.is_closed(): db.close() # Rest of your bottle app goes here.
See the documentation for application processors.
db = SqliteDatabase('my_webpy_app.db') def connection_processor(handler): db.connect() try: return handler() finally: if not db.is_closed(): db.close() app.add_processor(connection_processor)
It looks like Tornado’s
RequestHandler class implements two hooks which can
be used to open and close connections when a request is handled.
from tornado.web import RequestHandler db = SqliteDatabase('my_db.db') class PeeweeRequestHandler(RequestHandler): def prepare(self): db.connect() return super(PeeweeRequestHandler, self).prepare() def on_finish(self): if not db.is_closed(): db.close() return super(PeeweeRequestHandler, self).on_finish()
In your app, instead of extending the default
RequestHandler, now you can
Note that this does not address how to use peewee asynchronously with Tornado or another event loop.
The connection handling code can be placed in a middleware.
def peewee_middleware(request, following): db.connect() try: response = following(request) finally: if not db.is_closed(): db.close() return response app = WSGIApplication(middleware=[ lambda x: peewee_middleware, # ... other middlewares ... ])
Thanks to GitHub user @tuukkamustonen for submitting this code.
The connection handling code can be placed in a middleware component.
import falcon from peewee import * database = SqliteDatabase('my_app.db') class PeeweeConnectionMiddleware(object): def process_request(self, req, resp): database.connect() def process_response(self, req, resp, resource): if not database.is_closed(): database.close() application = falcon.API(middleware=[ PeeweeConnectionMiddleware(), # ... other middlewares ... ])
Set up a Request factory that handles database connection lifetime as follows:
from pyramid.request import Request db = SqliteDatabase('pyramidapp.db') class MyRequest(Request): def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) db.connect() self.add_finished_callback(self.finish) def finish(self, request): if not db.is_closed(): db.close()
In your application main() make sure MyRequest is used as request_factory:
def main(global_settings, **settings): config = Configurator(settings=settings, ...) config.set_request_factory(MyRequest)
def _db_connect(): db.connect() def _db_close(): if not db.is_closed(): db.close() cherrypy.engine.subscribe('before_request', _db_connect) cherrypy.engine.subscribe('after_request', _db_close)
SQL queries will typically be executed by calling
execute() on a query
constructed using the query-builder APIs (or by simply iterating over a query
object in the case of a
Select query). For cases where you wish to
execute SQL directly, you can use the
db = SqliteDatabase('my_app.db') db.connect() # Example of executing a simple query and ignoring the results. db.execute_sql("ATTACH DATABASE ':memory:' AS cache;") # Example of iterating over the results of a query using the cursor. cursor = db.execute_sql('SELECT * FROM users WHERE status = ?', (ACTIVE,)) for row in cursor.fetchall(): # Do something with row, which is a tuple containing column data. pass
Peewee provides several interfaces for working with transactions. The most
general is the
Database.atomic() method, which also supports nested
atomic() blocks will be run in a transaction
or savepoint, depending on the level of nesting.
If an exception occurs in a wrapped block, the current transaction/savepoint will be rolled back. Otherwise the statements will be committed at the end of the wrapped block.
While inside a block wrapped by the
manager, you can explicitly rollback or commit at any point by calling
Transaction.commit(). When you
do this inside a wrapped block of code, a new transaction will be started
with db.atomic() as transaction: # Opens new transaction. try: save_some_objects() except ErrorSavingData: # Because this block of code is wrapped with "atomic", a # new transaction will begin automatically after the call # to rollback(). transaction.rollback() error_saving = True create_report(error_saving=error_saving) # Note: no need to call commit. Since this marks the end of the # wrapped block of code, the `atomic` context manager will # automatically call commit for us.
atomic() can be used as either a context manager or
atomic as context manager:
db = SqliteDatabase(':memory:') with db.atomic() as txn: # This is the outer-most level, so this block corresponds to # a transaction. User.create(username='charlie') with db.atomic() as nested_txn: # This block corresponds to a savepoint. User.create(username='huey') # This will roll back the above create() query. nested_txn.rollback() User.create(username='mickey') # When the block ends, the transaction is committed (assuming no error # occurs). At that point there will be two users, "charlie" and "mickey".
You can use the
atomic method to perform get or create operations as
try: with db.atomic(): user = User.create(username=username) return 'Success' except peewee.IntegrityError: return 'Failure: %s is already in use.' % username
atomic as a decorator:
@db.atomic() def create_user(username): # This statement will run in a transaction. If the caller is already # running in an `atomic` block, then a savepoint will be used instead. return User.create(username=username) create_user('charlie')
with db.atomic() as txn: perform_operation() with db.atomic() as nested_txn: perform_another_operation()
Peewee supports nested transactions through the use of savepoints (for more
If an exception occurs in a wrapped block, the transaction will be rolled back. Otherwise the statements will be committed at the end of the wrapped block.
db = SqliteDatabase(':memory:') with db.transaction() as txn: # Delete the user and their associated tweets. user.delete_instance(recursive=True)
Transactions can be explicitly committed or rolled-back within the wrapped block. When this happens, a new transaction will be started.
with db.transaction() as txn: User.create(username='mickey') txn.commit() # Changes are saved and a new transaction begins. User.create(username='huey') # Roll back. "huey" will not be saved, but since "mickey" was already # committed, that row will remain in the database. txn.rollback() with db.transaction() as txn: User.create(username='whiskers') # Roll back changes, which removes "whiskers". txn.rollback() # Create a new row for "mr. whiskers" which will be implicitly committed # at the end of the `with` block. User.create(username='mr. whiskers')
Just as you can explicitly create transactions, you can also explicitly create
savepoints using the
savepoint() method. Savepoints must
occur within a transaction, but can be nested arbitrarily deep.
with db.transaction() as txn: with db.savepoint() as sp: User.create(username='mickey') with db.savepoint() as sp2: User.create(username='zaizee') sp2.rollback() # "zaizee" will not be saved, but "mickey" will be.
If you manually commit or roll back a savepoint, a new savepoint will
not automatically be created. This differs from the behavior of
transaction, which will automatically open a new transaction
after manual commit/rollback.
By default, Peewee operates in autocommit mode, such that any statements
executed outside of a transaction are run in their own transaction. To group
multiple statements into a transaction, Peewee provides the
atomic() context-manager/decorator. This should cover all
use-cases, but in the unlikely event you want to temporarily disable Peewee’s
transaction management completely, you can use the
Here is how you might emulate the behavior of the
transaction() context manager:
with db.manual_commit(): db.begin() # Have to begin transaction explicitly. try: user.delete_instance(recursive=True) except: db.rollback() # Rollback! An error occurred. raise else: try: db.commit() # Commit changes. except: db.rollback() raise
Again – I don’t anticipate anyone needing this, but it’s here just in case.
The Python DB-API 2.0 spec describes several types of exceptions. Because most database drivers have their own implementations of these exceptions, Peewee simplifies things by providing its own wrappers around any implementation-specific exception classes. That way, you don’t need to worry about importing any special exception classes, you can just use the ones from peewee:
All of these error classes extend
All queries are logged to the peewee namespace using the standard library
logging module. Queries are logged using the DEBUG level. If you’re interested in doing something with the queries, you can simply register a handler.
# Print all queries to stderr. import logging logger = logging.getLogger('peewee') logger.setLevel(logging.DEBUG) logger.addHandler(logging.StreamHandler())
Adding a new Database Driver¶
Peewee comes with built-in support for Postgres, MySQL and SQLite. These databases are very popular and run the gamut from fast, embeddable databases to heavyweight servers suitable for large-scale deployments. That being said, there are a ton of cool databases out there and adding support for your database-of-choice should be really easy, provided the driver supports the DB-API 2.0 spec.
The db-api 2.0 spec should be familiar to you if you’ve used the standard library sqlite3 driver, psycopg2 or the like. Peewee currently relies on a handful of parts:
These methods are generally wrapped up in higher-level abstractions and exposed
Database, so even if your driver doesn’t do these exactly
you can still get a lot of mileage out of peewee. An example is the apsw
sqlite driver in the “playhouse” module.
The first thing is to provide a subclass of
Database that will open
from peewee import Database import foodb # Our fictional DB-API 2.0 driver. class FooDatabase(Database): def _connect(self, database, **kwargs): return foodb.connect(database, **kwargs)
Database provides a higher-level API and is responsible for
executing queries, creating tables and indexes, and introspecting the database
to get lists of tables. The above implementation is the absolute minimum
needed, though some features will not work – for best results you will want to
additionally add a method for extracting a list of tables and indexes for a
table from the database. We’ll pretend that
FooDB is a lot like MySQL and
has special “SHOW” statements:
class FooDatabase(Database): def _connect(self, database, **kwargs): return foodb.connect(database, **kwargs) def get_tables(self): res = self.execute('SHOW TABLES;') return [r for r in res.fetchall()]
Other things the database handles that are not covered here include:
op_overridesfor mapping operations such as “LIKE/ILIKE” to their database equivalent
If your driver conforms to the DB-API 2.0 spec, there shouldn’t be much work needed to get up and running.
Our new database can be used just like any of the other database subclasses:
from peewee import * from foodb_ext import FooDatabase db = FooDatabase('my_database', user='foo', password='secret') class BaseModel(Model): class Meta: database = db class Blog(BaseModel): title = CharField() contents = TextField() pub_date = DateTimeField()