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 :term:`released` 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.Connection` object provides a :meth:`~.Connection.begin` method which returns a :class:`.Transaction` object. This object is usually used within a try/except clause so that it is guaranteed to invoke :meth:`.Transaction.rollback` or :meth:`.Transaction.commit`:
connection = engine.connect() 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
The above block can be created more succinctly using context managers, either given an :class:`.Engine`:
# runs a transaction with engine.begin() as connection: r1 = connection.execute(table1.select()) connection.execute(table1.insert(), col1=7, col2='this is some data')
with connection.begin() as trans: r1 = connection.execute(table1.select()) connection.execute(table1.insert(), col1=7, col2='this is some data')
Nesting of Transaction Blocks
The :class:`.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 :class:`.Connection`, but only the outermost :class:`.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`:
result = engine.execute("select username from users") for row in result: print "username:", row['username']
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:
from sqlalchemy import MetaData, Table, Column, Integer meta = MetaData() users_table = Table('users', meta, Column('id', Integer, primary_key=True), Column('name', String(50)) )
engine = create_engine('sqlite:///file.db') connection = engine.connect() result = connection.execute(users_table.select()) for row in result: # .... connection.close()
engine = create_engine('sqlite:///file.db') result = engine.execute(users_table.select()) for row in result: # .... result.close()
Implicit execution is also connectionless, and makes usage of the :meth:`~.Executable.execute` method on the expression itself. This method is provided as part of the :class:`.Executable` class, which refers to a SQL statement that is sufficient for being invoked against the database. The method makes usage of the assumption that either an :class:`~sqlalchemy.engine.Engine` or :class:`~sqlalchemy.engine.Connection` has been bound to the expression object. By "bound" we mean that the special attribute :attr:`.MetaData.bind` has been used to associate a series of :class:`.Table` objects and all SQL constructs derived from them with a specific engine:
engine = create_engine('sqlite:///file.db') meta.bind = engine result = users_table.select().execute() for row in result: # .... result.close()
Above, we associate an :class:`.Engine` with a :class:`.MetaData` object using the special attribute :attr:`.MetaData.bind`. The :func:`.select` construct produced from the :class:`.Table` object has a method :meth:`~.Executable.execute`, which will search for an :class:`.Engine` that's "bound" to the :class:`.Table`.
Overall, the usage of "bound metadata" has three general effects:
- SQL statement objects gain an :meth:`.Executable.execute` method which automatically locates a "bind" with which to execute themselves.
- The ORM :class:`.Session` object supports using "bound metadata" in order to establish which :class:`.Engine` should be used to invoke SQL statements on behalf of a particular mapped class, though the :class:`.Session` also features its own explicit system of establishing complex :class:`.Engine`/ mapped class configurations.
- The :meth:`.MetaData.create_all`, :meth:`.Metadata.drop_all`, :meth:`.Table.create`, :meth:`.Table.drop`, and "autoload" features all make usage of the bound :class:`.Engine` automatically without the need to pass it explicitly.
The concepts of "bound metadata" and "implicit execution" are not emphasized in modern SQLAlchemy. While they offer some convenience, they are no longer required by any API and are never necessary.
In applications where multiple :class:`.Engine` objects are present, each one logically associated with a certain set of tables (i.e. vertical sharding), the "bound metadata" technique can be used so that individual :class:`.Table` can refer to the appropriate :class:`.Engine` automatically; in particular this is supported within the ORM via the :class:`.Session` object as a means to associate :class:`.Table` objects with an appropriate :class:`.Engine`, as an alternative to using the bind arguments accepted directly by the :class:`.Session`.
However, the "implicit execution" technique is not at all appropriate for use with the ORM, as it bypasses the transactional context maintained by the :class:`.Session`.
Overall, in the vast majority of cases, "bound metadata" and "implicit execution" are not useful. While "bound metadata" has a marginal level of usefulness with regards to ORM configuration, "implicit execution" is a very old usage pattern that in most cases is more confusing than it is helpful, and its usage is discouraged. Both patterns seem to encourage the overuse of expedient "short cuts" in application design which lead to problems later on.
Modern SQLAlchemy usage, especially the ORM, places a heavy stress on working within the context of a transaction at all times; the "implicit execution" concept makes the job of associating statement execution with a particular transaction much more difficult. The :meth:`.Executable.execute` method on a particular SQL statement usually implies that the execution is not part of any particular transaction, which is usually not the desired effect.
In both "connectionless" examples, the :class:`~sqlalchemy.engine.Connection` is created behind the scenes; the :class:`~sqlalchemy.engine.ResultProxy` returned by the execute() call references the :class:`~sqlalchemy.engine.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`.
The "threadlocal" feature is generally discouraged. It's designed for a particular pattern of usage which is generally considered as a legacy pattern. 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 :term:`release` its resources until all other usages of that resource are closed as well, including that any ongoing transactions are rolled back or committed.
Registering New Dialects
The :func:`.create_engine` function call locates the given dialect using setuptools entrypoints. These entry points can be established for third party dialects within the setup.py script. For example, to create a new dialect "foodialect://", the steps are as follows:
Create a package called foodialect.
The package should have a module containing the dialect class, which is typically a subclass of :class:`sqlalchemy.engine.default.DefaultDialect`. In this example let's say it's called FooDialect and its module is accessed via foodialect.dialect.
The entry point can be established in setup.py as follows:
entry_points=""" [sqlalchemy.dialects] foodialect = foodialect.dialect:FooDialect """
If the dialect is providing support for a particular DBAPI on top of an existing SQLAlchemy-supported database, the name can be given including a database-qualification. For example, if FooDialect were in fact a MySQL dialect, the entry point could be established like this:
entry_points=""" [sqlalchemy.dialects] mysql.foodialect = foodialect.dialect:FooDialect """
The above entrypoint would then be accessed as create_engine("mysql+foodialect://").
Registering Dialects In-Process
SQLAlchemy also allows a dialect to be registered within the current process, bypassing the need for separate installation. Use the register() function as follows:
from sqlalchemy.dialects import register registry.register("mysql.foodialect", "myapp.dialect", "MyMySQLDialect")
The above will respond to create_engine("mysql+foodialect://") and load the MyMySQLDialect class from the myapp.dialect module.