Working with Engines and Connections
This section details direct usage of the :class:`.Engine`, :class:`.Connection`, and related objects. Its important to note that when using the SQLAlchemy ORM, these objects are not generally accessed; instead, the :class:`.Session` object is used as the interface to the database. However, for applications that are built around direct usage of textual SQL statements and/or SQL expression constructs without involvement by the ORM's higher level management services, the :class:`.Engine` and :class:`.Connection` are king (and queen?) - read on.
engine = create_engine('mysql://scott:tiger@localhost/test')
The typical usage of :func:`.create_engine()` is once per particular database URL, held globally for the lifetime of a single application process. A single :class:`.Engine` manages many individual DBAPI connections on behalf of the process and is intended to be called upon in a concurrent fashion. The :class:`.Engine` is not synonymous to the DBAPI connect function, which represents just one connection resource - the :class:`.Engine` is most efficient when created just once at the module level of an application, not per-object or per-function call.
For a multiple-process application that uses the os.fork system call, or for example the Python multiprocessing module, it's usually required that a separate :class:`.Engine` be used for each child process. This is because the :class:`.Engine` maintains a reference to a connection pool that ultimately references DBAPI connections - these tend to not be portable across process boundaries. An :class:`.Engine` that is configured not to use pooling (which is achieved via the usage of :class:`.NullPool`) does not have this requirement.
The engine can be used directly to issue SQL to the database. The most generic way is first procure a connection resource, which you get via the :class:`connect` method:
connection = engine.connect() result = connection.execute("select username from users") for row in result: print "username:", row['username'] connection.close()
The connection is an instance of :class:`.Connection`, which is a proxy object for an actual DBAPI connection. The DBAPI connection is retrieved from the connection pool at the point at which :class:`.Connection` is created.
The returned result is an instance of :class:`.ResultProxy`, which references a DBAPI cursor and provides a largely compatible interface with that of the DBAPI cursor. The DBAPI cursor will be closed by the :class:`.ResultProxy` when all of its result rows (if any) are exhausted. A :class:`.ResultProxy` that returns no rows, such as that of an UPDATE statement (without any returned rows), releases cursor resources immediately upon construction.
When the :meth:`~.Connection.close` method is called, the referenced DBAPI connection is returned to the connection pool. From the perspective of the database itself, nothing is actually "closed", assuming pooling is in use. The pooling mechanism issues a rollback() call on the DBAPI connection so that any transactional state or locks are removed, and the connection is ready for its next usage.
result = engine.execute("select username from users") for row in result: print "username:", row['username']
Where above, the :meth:`~.Engine.execute` method acquires a new :class:`.Connection` on its own, executes the statement with that object, and returns the :class:`.ResultProxy`. In this case, the :class:`.ResultProxy` contains a special flag known as close_with_result, which indicates that when its underlying DBAPI cursor is closed, the :class:`.Connection` object itself is also closed, which again returns the DBAPI connection to the connection pool, releasing transactional resources.
If the :class:`.ResultProxy` potentially has rows remaining, it can be instructed to close out its resources explicitly:
If the :class:`.ResultProxy` has pending rows remaining and is dereferenced by the application without being closed, Python garbage collection will ultimately close out the cursor as well as trigger a return of the pooled DBAPI connection resource to the pool (SQLAlchemy achieves this by the usage of weakref callbacks - never the __del__ method) - however it's never a good idea to rely upon Python garbage collection to manage resources.
Our example above illustrated the execution of a textual SQL string. The :meth:`~.Connection.execute` method can of course accommodate more than that, including the variety of SQL expression constructs described in :ref:`sqlexpression_toplevel`.
This section describes how to use transactions when working directly with :class:`.Engine` and :class:`.Connection` objects. When using the SQLAlchemy ORM, the public API for transaction control is via the :class:`.Session` object, which makes usage of the :class:`.Transaction` object internally. See :ref:`unitofwork_transaction` for further information.
The :class:`~sqlalchemy.engine.base.Connection` object provides a begin() method which returns a :class:`~sqlalchemy.engine.base.Transaction` object. This object is usually used within a try/except clause so that it is guaranteed to rollback() or commit():
trans = connection.begin() try: r1 = connection.execute(table1.select()) connection.execute(table1.insert(), col1=7, col2='this is some data') trans.commit() except: trans.rollback() raise
Nesting of Transaction Blocks
The :class:`~sqlalchemy.engine.base.Transaction` object also handles "nested" behavior by keeping track of the outermost begin/commit pair. In this example, two functions both issue a transaction on a Connection, but only the outermost Transaction object actually takes effect when it is committed.
# method_a starts a transaction and calls method_b def method_a(connection): trans = connection.begin() # open a transaction try: method_b(connection) trans.commit() # transaction is committed here except: trans.rollback() # this rolls back the transaction unconditionally raise # method_b also starts a transaction def method_b(connection): trans = connection.begin() # open a transaction - this runs in the context of method_a's transaction try: connection.execute("insert into mytable values ('bat', 'lala')") connection.execute(mytable.insert(), col1='bat', col2='lala') trans.commit() # transaction is not committed yet except: trans.rollback() # this rolls back the transaction unconditionally raise # open a Connection and call method_a conn = engine.connect() method_a(conn) conn.close()
Above, method_a is called first, which calls connection.begin(). Then it calls method_b. When method_b calls connection.begin(), it just increments a counter that is decremented when it calls commit(). If either method_a or method_b calls rollback(), the whole transaction is rolled back. The transaction is not committed until method_a calls the commit() method. This "nesting" behavior allows the creation of functions which "guarantee" that a transaction will be used if one was not already available, but will automatically participate in an enclosing transaction if one exists.
The previous transaction example illustrates how to use :class:`.Transaction` so that several executions can take part in the same transaction. What happens when we issue an INSERT, UPDATE or DELETE call without using :class:`.Transaction`? While some DBAPI implementations provide various special "non-transactional" modes, the core behavior of DBAPI per PEP-0249 is that a transaction is always in progress, providing only rollback() and commit() methods but no begin(). SQLAlchemy assumes this is the case for any given DBAPI.
Given this requirement, SQLAlchemy implements its own "autocommit" feature which works completely consistently across all backends. This is achieved by detecting statements which represent data-changing operations, i.e. INSERT, UPDATE, DELETE, as well as data definition language (DDL) statements such as CREATE TABLE, ALTER TABLE, and then issuing a COMMIT automatically if no transaction is in progress. The detection is based on the presence of the autocommit=True execution option on the statement. If the statement is a text-only statement and the flag is not set, a regular expression is used to detect INSERT, UPDATE, DELETE, as well as a variety of other commands for a particular backend:
conn = engine.connect() conn.execute("INSERT INTO users VALUES (1, 'john')") # autocommits
The "autocommit" feature is only in effect when no :class:`.Transaction` has otherwise been declared. This means the feature is not generally used with the ORM, as the :class:`.Session` object by default always maintains an ongoing :class:`.Transaction`.
Full control of the "autocommit" behavior is available using the generative :meth:`.Connection.execution_options` method provided on :class:`.Connection`, :class:`.Engine`, :class:`.Executable`, using the "autocommit" flag which will turn on or off the autocommit for the selected scope. For example, a :func:`.text` construct representing a stored procedure that commits might use it so that a SELECT statement will issue a COMMIT:
Connectionless Execution, Implicit Execution
Recall from the first section we mentioned executing with and without explicit usage of :class:`.Connection`. "Connectionless" execution refers to the usage of the execute() method on an object which is not a :class:`.Connection`. This was illustrated using the :meth:`~.Engine.execute` method of :class:`.Engine`.
In addition to "connectionless" execution, it is also possible to use the :meth:`~.Executable.execute` method of any :class:`.Executable` construct, which is a marker for SQL expression objects that support execution. The SQL expression object itself references an :class:`.Engine` or :class:`.Connection` known as the bind, which it uses in order to provide so-called "implicit" execution services.
Given a table as below:
meta = MetaData() users_table = Table('users', meta, Column('id', Integer, primary_key=True), Column('name', String(50)) )
Explicit execution delivers the SQL text or constructed SQL expression to the execute() method of :class:`~sqlalchemy.engine.base.Connection`:
engine = create_engine('sqlite:///file.db') connection = engine.connect() result = connection.execute(users_table.select()) for row in result: # .... connection.close()
Explicit, connectionless execution delivers the expression to the execute() method of :class:`~sqlalchemy.engine.base.Engine`:
engine = create_engine('sqlite:///file.db') result = engine.execute(users_table.select()) for row in result: # .... result.close()
Implicit execution is also connectionless, and calls the execute() method on the expression itself, utilizing the fact that either an :class:`~sqlalchemy.engine.base.Engine` or :class:`~sqlalchemy.engine.base.Connection` has been bound to the expression object (binding is discussed further in :ref:`metadata_toplevel`):
engine = create_engine('sqlite:///file.db') meta.bind = engine result = users_table.select().execute() for row in result: # .... result.close()
In both "connectionless" examples, the :class:`~sqlalchemy.engine.base.Connection` is created behind the scenes; the :class:`~sqlalchemy.engine.base.ResultProxy` returned by the execute() call references the :class:`~sqlalchemy.engine.base.Connection` used to issue the SQL statement. When the :class:`.ResultProxy` is closed, the underlying :class:`.Connection` is closed for us, resulting in the DBAPI connection being returned to the pool with transactional resources removed.
Using the Threadlocal Execution Strategy
The "threadlocal" engine strategy is an optional feature which can be used by non-ORM applications to associate transactions with the current thread, such that all parts of the application can participate in that transaction implicitly without the need to explicitly reference a :class:`.Connection`. "threadlocal" is designed for a very specific pattern of use, and is not appropriate unless this very specfic pattern, described below, is what's desired. It has no impact on the "thread safety" of SQLAlchemy components or one's application. It also should not be used when using an ORM :class:`~sqlalchemy.orm.session.Session` object, as the :class:`~sqlalchemy.orm.session.Session` itself represents an ongoing transaction and itself handles the job of maintaining connection and transactional resources.
Enabling threadlocal is achieved as follows:
db = create_engine('mysql://localhost/test', strategy='threadlocal')
The above :class:`.Engine` will now acquire a :class:`.Connection` using connection resources derived from a thread-local variable whenever :meth:`.Engine.execute` or :meth:`.Engine.contextual_connect` is called. This connection resource is maintained as long as it is referenced, which allows multiple points of an application to share a transaction while using connectionless execution:
def call_operation1(): engine.execute("insert into users values (?, ?)", 1, "john") def call_operation2(): users.update(users.c.user_id==5).execute(name='ed') db.begin() try: call_operation1() call_operation2() db.commit() except: db.rollback()
db.begin() conn = db.connect() try: conn.execute(log_table.insert(), message="Operation started") call_operation1() call_operation2() db.commit() conn.execute(log_table.insert(), message="Operation succeeded") except: db.rollback() conn.execute(log_table.insert(), message="Operation failed") finally: conn.close()
conn = db.contextual_connect() call_operation3(conn) conn.close()
Calling :meth:`~.Connection.close` on the "contextual" connection does not release its resources until all other usages of that resource are closed as well, including that any ongoing transactions are rolled back or committed.