How do I configure logging?¶

See Configuring Logging.

How do I pool database connections? Are my connections pooled?¶

SQLAlchemy performs application-level connection pooling automatically in most cases. With the exception of SQLite, a Engine object refers to a QueuePool as a source of connectivity.

For more detail, see Engine Configuration and Connection Pooling.

How do I pass custom connect arguments to my database API?¶

The create_engine() call accepts additional arguments either directly via the connect_args keyword argument:

e = create_engine("mysql://scott:tiger@localhost/test",
                    connect_args={"encoding": "utf8"})

Or for basic string and integer arguments, they can usually be specified in the query string of the URL:

e = create_engine("mysql://scott:tiger@localhost/test?encoding=utf8")

“MySQL Server has gone away”¶

There are two major causes for this error:

1. The MySQL client closes connections which have been idle for a set period of time, defaulting to eight hours. This can be avoided by using the pool_recycle setting with create_engine(), described at Connection Timeouts.

2. Usage of the MySQLdb DBAPI, or a similar DBAPI, in a non-threadsafe manner, or in an otherwise inappropriate way. The MySQLdb connection object is not threadsafe - this expands out to any SQLAlchemy system that links to a single connection, which includes the ORM Session. For background on how Session should be used in a multithreaded environment, see Is the session thread-safe?.

Why does SQLAlchemy issue so many ROLLBACKs?¶

SQLAlchemy currently assumes DBAPI connections are in “non-autocommit” mode - this is the default behavior of the Python database API, meaning it must be assumed that a transaction is always in progress. The connection pool issues connection.rollback() when a connection is returned. This is so that any transactional resources remaining on the connection are released. On a database like Postgresql or MSSQL where table resources are aggressively locked, this is critical so that rows and tables don’t remain locked within connections that are no longer in use. An application can otherwise hang. It’s not just for locks, however, and is equally critical on any database that has any kind of transaction isolation, including MySQL with InnoDB. Any connection that is still inside an old transaction will return stale data, if that data was already queried on that connection within isolation. For background on why you might see stale data even on MySQL, see http://dev.mysql.com/doc/refman/5.1/en/innodb-transaction-model.html

from sqlalchemy import create_engine
from sqlalchemy.pool import QueuePool

engine = create_engine('mysql://scott:tiger@localhost/myisam_database', pool=QueuePool(reset_on_return=False))

engine = create_engine('mssql://scott:tiger@mydsn', pool=QueuePool(reset_on_return='commit'))

I am using multiple connections with a SQLite database (typically to test transaction operation), and my test program is not working!¶

If using a SQLite :memory: database, or a version of SQLAlchemy prior to version 0.7, the default connection pool is the SingletonThreadPool, which maintains exactly one SQLite connection per thread. So two connections in use in the same thread will actually be the same SQLite connection. Make sure you’re not using a :memory: database and use NullPool, which is the default for non-memory databases in current SQLAlchemy versions.

How do I get at the raw DBAPI connection when using an Engine?¶

With a regular SA engine-level Connection, you can get at a pool-proxied version of the DBAPI connection via the Connection.connection attribute on Connection, and for the really-real DBAPI connection you can call the ConnectionFairy.connection attribute on that - but there should never be any need to access the non-pool-proxied DBAPI connection, as all methods are proxied through:

engine = create_engine(...)
conn = engine.connect()
conn.connection.<do DBAPI things>
cursor = conn.connection.cursor(<DBAPI specific arguments..>)

You must ensure that you revert any isolation level settings or other operation-specific settings on the connection back to normal before returning it to the pool.

As an alternative to reverting settings, you can call the Connection.detach() method on either Connection or the proxied connection, which will de-associate the connection from the pool such that it will be closed and discarded when Connection.close() is called:

conn = engine.connect()
conn.detach()  # detaches the DBAPI connection from the connection pool
conn.connection.<go nuts>
conn.close()  # connection is closed for real, the pool replaces it with a new connection

How do I use engines / connections / sessions with Python multiprocessing, or os.fork()?¶

The key goal with multiple python processes is to prevent any database connections from being shared across processes. Depending on specifics of the driver and OS, the issues that arise here range from non-working connections to socket connections that are used by multiple processes concurrently, leading to broken messaging (the latter case is typically the most common).

The SQLAlchemy Engine object refers to a connection pool of existing database connections. So when this object is replicated to a child process, the goal is to ensure that no database connections are carried over. There are three general approaches to this:

1. Disable pooling using NullPool. This is the most simplistic, one shot system that prevents the Engine from using any connection more than once.

2. Call Engine.dispose() on any given Engine as soon one is within the new process. In Python multiprocessing, constructs such as multiprocessing.Pool include “initializer” hooks which are a place that this can be performed; otherwise at the top of where os.fork() or where the Process object begins the child fork, a single call to Engine.dispose() will ensure any remaining connections are flushed.

3. An event handler can be applied to the connection pool that tests for connections being shared across process boundaries, and invalidates them. This looks like the following:

   import os
   import warnings
   
   from sqlalchemy import event
   from sqlalchemy import exc
   
   def add_engine_pidguard(engine):
       """Add multiprocessing guards.
   
       Forces a connection to be reconnected if it is detected
       as having been shared to a sub-process.
   
       """
   
       @event.listens_for(engine, "connect")
       def connect(dbapi_connection, connection_record):
           connection_record.info['pid'] = os.getpid()
   
       @event.listens_for(engine, "checkout")
       def checkout(dbapi_connection, connection_record, connection_proxy):
           pid = os.getpid()
           if connection_record.info['pid'] != pid:
               # substitute log.debug() or similar here as desired
               warnings.warn(
                   "Parent process %(orig)s forked (%(newproc)s) with an open "
                   "database connection, "
                   "which is being discarded and recreated." %
                   {"newproc": pid, "orig": connection_record.info['pid']})
               connection_record.connection = connection_proxy.connection = None
               raise exc.DisconnectionError(
                   "Connection record belongs to pid %s, "
                   "attempting to check out in pid %s" %
                   (connection_record.info['pid'], pid)
               )

   These events are applied to an Engine as soon as its created:

   engine = create_engine("...")
   
   add_engine_pidguard(engine)

The above strategies will accommodate the case of an Engine being shared among processes. However, for the case of a transaction-active Session or Connection being shared, there’s no automatic fix for this; an application needs to ensure a new child process only initiate new Connection objects and transactions, as well as ORM Session objects. For a Session object, technically this is only needed if the session is currently transaction-bound, however the scope of a single Session is in any case intended to be kept within a single call stack in any case (e.g. not a global object, not shared between processes or threads).