# Connection Pooling

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():
# 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():
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).

A particular pre-created :class:.Pool can be shared with one or more engines by passing it to the pool argument of :func:.create_engine:

e = create_engine('postgresql://', pool=mypool)


## Pool Events

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()


## 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

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.