A connection pool is a standard technique used to maintain long running connections in memory for efficient re-use, as well as to provide management for the total number of connections an application might use simultaneously.
Particularly for server-side web applications, a connection pool is the standard way to maintain a "pool" of active database connections in memory which are reused across requests.
SQLAlchemy includes several connection pool implementations which integrate with the :class:`.Engine`. They can also be used directly for applications that want to add pooling to an otherwise plain DBAPI approach.
Connection Pool Configuration
The :class:`~.engine.Engine` returned by the :func:`~sqlalchemy.create_engine` function in most cases has a :class:`.QueuePool` integrated, pre-configured with reasonable pooling defaults. If you're reading this section only to learn how to enable pooling - congratulations! You're already done.
The most common :class:`.QueuePool` tuning parameters can be passed directly to :func:`~sqlalchemy.create_engine` as keyword arguments: pool_size, max_overflow, pool_recycle and pool_timeout. For example:
engine = create_engine('postgresql://me@localhost/mydb', pool_size=20, max_overflow=0)
In the case of SQLite, the :class:`.SingletonThreadPool` or :class:`.NullPool` are selected by the dialect to provide greater compatibility with SQLite's threading and locking model, as well as to provide a reasonable default behavior to SQLite "memory" databases, which maintain their entire dataset within the scope of a single connection.
All SQLAlchemy pool implementations have in common that none of them "pre create" connections - all implementations wait until first use before creating a connection. At that point, if no additional concurrent checkout requests for more connections are made, no additional connections are created. This is why it's perfectly fine for :func:`.create_engine` to default to using a :class:`.QueuePool` of size five without regard to whether or not the application really needs five connections queued up - the pool would only grow to that size if the application actually used five connections concurrently, in which case the usage of a small pool is an entirely appropriate default behavior.
Switching Pool Implementations
The usual way to use a different kind of pool with :func:`.create_engine` is to use the poolclass argument. This argument accepts a class imported from the sqlalchemy.pool module, and handles the details of building the pool for you. Common options include specifying :class:`.QueuePool` with SQLite:
from sqlalchemy.pool import QueuePool engine = create_engine('sqlite:///file.db', poolclass=QueuePool)
Disabling pooling using :class:`.NullPool`:
from sqlalchemy.pool import NullPool engine = create_engine( 'postgresql+psycopg2://scott:tiger@localhost/test', poolclass=NullPool)
Using a Custom Connection Function
All :class:`.Pool` classes accept an argument creator which is a callable that creates a new connection. :func:`.create_engine` accepts this function to pass onto the pool via an argument of the same name:
import sqlalchemy.pool as pool import psycopg2 def getconn(): c = psycopg2.connect(username='ed', host='127.0.0.1', dbname='test') # do things with 'c' to set up return c engine = create_engine('postgresql+psycopg2://', creator=getconn)
For most "initialize on connection" routines, it's more convenient to use the :class:`.PoolEvents` event hooks, so that the usual URL argument to :func:`.create_engine` is still usable. creator is there as a last resort for when a DBAPI has some form of connect that is not at all supported by SQLAlchemy.
Constructing a Pool
To use a :class:`.Pool` by itself, the creator function is the only argument that's required and is passed first, followed by any additional options:
import sqlalchemy.pool as pool import psycopg2 def getconn(): c = psycopg2.connect(username='ed', host='127.0.0.1', dbname='test') return c mypool = pool.QueuePool(getconn, max_overflow=10, pool_size=5)
DBAPI connections can then be procured from the pool using the :meth:`.Pool.connect` function. The return value of this method is a DBAPI connection that's contained within a transparent proxy:
# get a connection conn = mypool.connect() # use it cursor = conn.cursor() cursor.execute("select foo")
The purpose of the transparent proxy is to intercept the close() call, such that instead of the DBAPI connection being closed, its returned to the pool:
# "close" the connection. Returns # it to the pool. conn.close()
The proxy also returns its contained DBAPI connection to the pool when it is garbage collected, though it's not deterministic in Python that this occurs immediately (though it is typical with cPython).
e = create_engine('postgresql://', pool=mypool)
Connection pools support an event interface that allows hooks to execute upon first connect, upon each new connection, and upon checkout and checkin of connections. See :class:`.PoolEvents` for details.
Dealing with Disconnects
The connection pool has the ability to refresh individual connections as well as its entire set of connections, setting the previously pooled connections as "invalid". A common use case is allow the connection pool to gracefully recover when the database server has been restarted, and all previously established connections are no longer functional. There are two approaches to this.
Disconnect Handling - Optimistic
The most common approach is to let SQLAlchemy handle disconnects as they occur, at which point the pool is refreshed. This assumes the :class:`.Pool` is used in conjunction with a :class:`.Engine`. The :class:`.Engine` has logic which can detect disconnection events and refresh the pool automatically.
When the :class:`.Connection` attempts to use a DBAPI connection, and an exception is raised that corresponds to a "disconnect" event, the connection is invalidated. The :class:`.Connection` then calls the :meth:`.Pool.recreate` method, effectively invalidating all connections not currently checked out so that they are replaced with new ones upon next checkout:
from sqlalchemy import create_engine, exc e = create_engine(...) c = e.connect() try: # suppose the database has been restarted. c.execute("SELECT * FROM table") c.close() except exc.DBAPIError, e: # an exception is raised, Connection is invalidated. if e.connection_invalidated: print "Connection was invalidated!" # after the invalidate event, a new connection # starts with a new Pool c = e.connect() c.execute("SELECT * FROM table")
The above example illustrates that no special intervention is needed, the pool continues normally after a disconnection event is detected. However, an exception is raised. In a typical web application using an ORM Session, the above condition would correspond to a single request failing with a 500 error, then the web application continuing normally beyond that. Hence the approach is "optimistic" in that frequent database restarts are not anticipated.
Setting Pool Recycle
An additional setting that can augment the "optimistic" approach is to set the pool recycle parameter. This parameter prevents the pool from using a particular connection that has passed a certain age, and is appropriate for database backends such as MySQL that automatically close connections that have been stale after a particular period of time:
from sqlalchemy import create_engine e = create_engine("mysql://scott:tiger@localhost/test", pool_recycle=3600)
Above, any DBAPI connection that has been open for more than one hour will be invalidated and replaced, upon next checkout. Note that the invalidation only occurs during checkout - not on any connections that are held in a checked out state. pool_recycle is a function of the :class:`.Pool` itself, independent of whether or not an :class:`.Engine` is in use.
Disconnect Handling - Pessimistic
At the expense of some extra SQL emitted for each connection checked out from the pool, a "ping" operation established by a checkout event handler can detect an invalid connection before it's used:
from sqlalchemy import exc from sqlalchemy import event from sqlalchemy.pool import Pool @event.listens_for(Pool, "checkout") def ping_connection(dbapi_connection, connection_record, connection_proxy): cursor = dbapi_connection.cursor() try: cursor.execute("SELECT 1") except: # optional - dispose the whole pool # instead of invalidating one at a time # connection_proxy._pool.dispose() # raise DisconnectionError - pool will try # connecting again up to three times before raising. raise exc.DisconnectionError() cursor.close()
Above, the :class:`.Pool` object specifically catches :class:`~sqlalchemy.exc.DisconnectionError` and attempts to create a new DBAPI connection, up to three times, before giving up and then raising :class:`~sqlalchemy.exc.InvalidRequestError`, failing the connection. This recipe will ensure that a new :class:`.Connection` will succeed even if connections in the pool have gone stale, provided that the database server is actually running. The expense is that of an additional execution performed per checkout. When using the ORM :class:`.Session`, there is one connection checkout per transaction, so the expense is fairly low. The ping approach above also works with straight connection pool usage, that is, even if no :class:`.Engine` were involved.
The event handler can be tested using a script like the following, restarting the database server at the point at which the script pauses for input:
from sqlalchemy import create_engine e = create_engine("mysql://scott:tiger@localhost/test", echo_pool=True) c1 = e.connect() c2 = e.connect() c3 = e.connect() c1.close() c2.close() c3.close() # pool size is now three. print "Restart the server" raw_input() for i in xrange(10): c = e.connect() print c.execute("select 1").fetchall() c.close()
API Documentation - Available Pool Implementations
Pooling Plain DB-API Connections
Any PEP 249 DB-API module can be "proxied" through the connection pool transparently. Usage of the DB-API is exactly as before, except the connect() method will consult the pool. Below we illustrate this with psycopg2:
import sqlalchemy.pool as pool import psycopg2 as psycopg psycopg = pool.manage(psycopg) # then connect normally connection = psycopg.connect(database='test', username='scott', password='tiger')
This produces a :class:`_DBProxy` object which supports the same connect() function as the original DB-API module. Upon connection, a connection proxy object is returned, which delegates its calls to a real DB-API connection object. This connection object is stored persistently within a connection pool (an instance of :class:`.Pool`) that corresponds to the exact connection arguments sent to the connect() function.
The connection proxy supports all of the methods on the original connection object, most of which are proxied via __getattr__(). The close() method will return the connection to the pool, and the cursor() method will return a proxied cursor object. Both the connection proxy and the cursor proxy will also return the underlying connection to the pool after they have both been garbage collected, which is detected via weakref callbacks (__del__ is not used).
Additionally, when connections are returned to the pool, a rollback() is issued on the connection unconditionally. This is to release any locks still held by the connection that may have resulted from normal activity.
By default, the connect() method will return the same connection that is already checked out in the current thread. This allows a particular connection to be used in a given thread without needing to pass it around between functions. To disable this behavior, specify use_threadlocal=False to the manage() function.