# SQLAlchemy 0.8 Documentation

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Release: 0.8.2 | Release Date: July 3, 2013

# Working with Engines and Connections

This section details direct usage of the `Engine`, `Connection`, and related objects. Its important to note that when using the SQLAlchemy ORM, these objects are not generally accessed; instead, the `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 `Engine` and `Connection` are king (and queen?) - read on.

## Basic Usage

Recall from Engine Configuration that an `Engine` is created via the `create_engine()` call:

    engine = create_engine('mysql://scott:tiger@localhost/test')

The typical usage of `create_engine()` is once per particular database URL, held globally for the lifetime of a single application process. A single `Engine` manages many individual DBAPI connections on behalf of the process and is intended to be called upon in a concurrent fashion. The `Engine` is not synonymous to the DBAPI `connect` function, which represents just one connection resource - the `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 `Engine` be used for each child process. This is because the `Engine` maintains a reference to a connection pool that ultimately references DBAPI connections - these tend to not be portable across process boundaries. An `Engine` that is configured not to use pooling (which is achieved via the usage of `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 `Engine.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 `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 `Connection` is created.

The returned result is an instance of `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 `ResultProxy` when all of its result rows (if any) are exhausted. A `ResultProxy` that returns no rows, such as that of an UPDATE statement (without any returned rows), releases cursor resources immediately upon construction.

When the `close()` method is called, the referenced DBAPI connection is 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.

The above procedure can be performed in a shorthand way by using the `execute()` method of `Engine` itself:

    result = engine.execute("select username from users")
    for row in result:
        print "username:", row['username']

Where above, the `execute()` method acquires a new `Connection` on its own, executes the statement with that object, and returns the `ResultProxy`. In this case, the `ResultProxy` contains a special flag known as `close_with_result`, which indicates that when its underlying DBAPI cursor is closed, the `Connection` object itself is also closed, which again returns the DBAPI connection to the connection pool, releasing transactional resources.

If the `ResultProxy` potentially has rows remaining, it can be instructed to close out its resources explicitly:

    result.close()

If the `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 `execute()` method can of course accommodate more than that, including the variety of SQL expression constructs described in SQL Expression Language Tutorial.

## Using Transactions

Note

This section describes how to use transactions when working directly with `Engine` and `Connection` objects. When using the SQLAlchemy ORM, the public API for transaction control is via the `Session` object, which makes usage of the `Transaction` object internally. See Managing Transactions for further information.

The `Connection` object provides a `begin()` method which returns a `Transaction` object. This object is usually used within a try/except clause so that it is guaranteed to invoke `Transaction.rollback()` or `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 `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')

Or from the `Connection`, in which case the `Transaction` object is available as well:

    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 `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.

## Understanding Autocommit

The previous transaction example illustrates how to use `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 `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 `Transaction` has otherwise been declared. This means the feature is not generally used with the ORM, as the `Session` object by default always maintains an ongoing `Transaction`.

Full control of the “autocommit” behavior is available using the generative `Connection.execution_options()` method provided on `Connection`, `Engine`, `Executable`, using the “autocommit” flag which will turn on or off the autocommit for the selected scope. For example, a `text()` construct representing a stored procedure that commits might use it so that a SELECT statement will issue a COMMIT:

    engine.execute(text("SELECT my_mutating_procedure()").execution_options(autocommit=True))

## Connectionless Execution, Implicit Execution

Recall from the first section we mentioned executing with and without explicit usage of `Connection`. “Connectionless” execution refers to the usage of the `execute()` method on an object which is not a `Connection`. This was illustrated using the `execute()` method of `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 `execute()` method of any `Executable` construct, which is a marker for SQL expression objects that support execution. The SQL expression object itself references an `Engine` or `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))
    )

Explicit execution delivers the SQL text or constructed SQL expression to the `execute()` method of `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 `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 makes usage of the `execute()` method on the expression itself. This method is provided as part of the `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 `Engine` or `Connection` has been bound to the expression object. By “bound” we mean that the special attribute `MetaData.bind` has been used to associate a series of `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 `Engine` with a `MetaData` object using the special attribute `MetaData.bind`. The `select()` construct produced from the `Table` object has a method `execute()`, which will search for an `Engine` that’s “bound” to the `Table`.

Overall, the usage of “bound metadata” has three general effects:

- SQL statement objects gain an `Executable.execute()` method which automatically locates a “bind” with which to execute themselves.
- The ORM `Session` object supports using “bound metadata” in order to establish which `Engine` should be used to invoke SQL statements on behalf of a particular mapped class, though the `Session` also features its own explicit system of establishing complex `Engine`/ mapped class configurations.
- The `MetaData.create_all()`, `MetaData.drop_all()`, `Table.create()`, `Table.drop()`, and “autoload” features all make usage of the bound `Engine` automatically without the need to pass it explicitly.

Note

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 `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 `Table` can refer to the appropriate `Engine` automatically; in particular this is supported within the ORM via the `Session` object as a means to associate `Table` objects with an appropriate `Engine`, as an alternative to using the bind arguments accepted directly by the `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 `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 `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 `Connection` is created behind the scenes; the `ResultProxy` returned by the `execute()` call references the `Connection` used to issue the SQL statement. When the `ResultProxy` is closed, the underlying `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 `Connection`.

Note

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 `Session` object, as the `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 `Engine` will now acquire a `Connection` using connection resources derived from a thread-local variable whenever `Engine.execute()` or `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()

Explicit execution can be mixed with connectionless execution by using the `Engine.connect()` method to acquire a `Connection` that is not part of the threadlocal scope:

    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()

To access the `Connection` that is bound to the threadlocal scope, call `Engine.contextual_connect()`:

    conn = db.contextual_connect()
    call_operation3(conn)
    conn.close()

Calling `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.

## Registering New Dialects

The `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:

1. Create a package called `foodialect`.

2. The package should have a module containing the dialect class, which is typically a subclass of `sqlalchemy.engine.default.DefaultDialect`. In this example let’s say it’s called `FooDialect` and its module is accessed via `foodialect.dialect`.

3. 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 registry
    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.

New in version 0.8.

## Connection / Engine API

class `sqlalchemy.engine.``Connection`(engine, connection=None, close_with_result=False, _branch=False, _execution_options=None, _dispatch=None, _has_events=False)

  Bases: `sqlalchemy.engine.interfaces.Connectable`

  Provides high-level functionality for a wrapped DB-API connection.

  Provides execution support for string-based SQL statements as well as `ClauseElement`, `Compiled` and `DefaultGenerator` objects. Provides a `begin()` method to return `Transaction` objects.

  The Connection object is not thread-safe. While a Connection can be shared among threads using properly synchronized access, it is still possible that the underlying DBAPI connection may not support shared access between threads. Check the DBAPI documentation for details.

  The Connection object represents a single dbapi connection checked out from the connection pool. In this state, the connection pool has no affect upon the connection, including its expiration or timeout state. For the connection pool to properly manage connections, connections should be returned to the connection pool (i.e. `connection.close()`) whenever the connection is not in use.

  `__init__`(engine, connection=None, close_with_result=False, _branch=False, _execution_options=None, _dispatch=None, _has_events=False)

    Construct a new Connection.

    The constructor here is not public and is only called only by an `Engine`. See `Engine.connect()` and `Engine.contextual_connect()` methods.

  `begin`()

    Begin a transaction and return a transaction handle.

    The returned object is an instance of `Transaction`. This object represents the “scope” of the transaction, which completes when either the `Transaction.rollback()` or `Transaction.commit()` method is called.

    Nested calls to `begin()` on the same `Connection` will return new `Transaction` objects that represent an emulated transaction within the scope of the enclosing transaction, that is:

        trans = conn.begin()   # outermost transaction
        trans2 = conn.begin()  # "nested"
        trans2.commit()        # does nothing
        trans.commit()         # actually commits

    Calls to `Transaction.commit()` only have an effect when invoked via the outermost `Transaction` object, though the `Transaction.rollback()` method of any of the `Transaction` objects will roll back the transaction.

    See also:

    `Connection.begin_nested()` - use a SAVEPOINT

    `Connection.begin_twophase()` - use a two phase /XID transaction

    `Engine.begin()` - context manager available from `Engine`.

  `begin_nested`()

    Begin a nested transaction and return a transaction handle.

    The returned object is an instance of `NestedTransaction`.

    Nested transactions require SAVEPOINT support in the underlying database. Any transaction in the hierarchy may `commit` and `rollback`, however the outermost transaction still controls the overall `commit` or `rollback` of the transaction of a whole.

    See also `Connection.begin()`, `Connection.begin_twophase()`.

  `begin_twophase`(xid=None)

    Begin a two-phase or XA transaction and return a transaction handle.

    The returned object is an instance of `TwoPhaseTransaction`, which in addition to the methods provided by `Transaction`, also provides a `prepare()` method.

    Parameters: | xid – the two phase transaction id. If not supplied, a random id will be generated.

    See also `Connection.begin()`, `Connection.begin_twophase()`.

  `close`()

    Close this `Connection`.

    This results in a release of the underlying database resources, that is, the DBAPI connection referenced internally. The DBAPI connection is typically restored back to the connection-holding `Pool` referenced by the `Engine` that produced this `Connection`. Any transactional state present on the DBAPI connection is also unconditionally released via the DBAPI connection’s `rollback()` method, regardless of any `Transaction` object that may be outstanding with regards to this `Connection`.

    After `close()` is called, the `Connection` is permanently in a closed state, and will allow no further operations.

  `closed`

    Return True if this connection is closed.

  `connect`()

    Returns a branched version of this `Connection`.

    The `Connection.close()` method on the returned `Connection` can be called and this `Connection` will remain open.

    This method provides usage symmetry with `Engine.connect()`, including for usage with context managers.

  `connection`

    The underlying DB-API connection managed by this Connection.

  `contextual_connect`(**kwargs)

    Returns a branched version of this `Connection`.

    The `Connection.close()` method on the returned `Connection` can be called and this `Connection` will remain open.

    This method provides usage symmetry with `Engine.contextual_connect()`, including for usage with context managers.

  `detach`()

    Detach the underlying DB-API connection from its connection pool.

    This Connection instance will remain usable. When closed, the DB-API connection will be literally closed and not returned to its pool. The pool will typically lazily create a new connection to replace the detached connection.

    This method can be used to insulate the rest of an application from a modified state on a connection (such as a transaction isolation level or similar). Also see `PoolListener` for a mechanism to modify connection state when connections leave and return to their connection pool.

  `execute`(object, *multiparams, **params)

    Executes the a SQL statement construct and returns a `ResultProxy`.

    Parameters:

    - object –

      The statement to be executed. May be one of:

      - a plain string
      - any `ClauseElement` construct that is also a subclass of `Executable`, such as a `select()` construct
      - a `FunctionElement`, such as that generated by `func`, will be automatically wrapped in a SELECT statement, which is then executed.
      - a `DDLElement` object
      - a `DefaultGenerator` object
      - a `Compiled` object
    - *multiparams/**params –

      represent bound parameter values to be used in the execution. Typically, the format is either a collection of one or more dictionaries passed to *multiparams:

          conn.execute(
              table.insert(),
              {"id":1, "value":"v1"},
              {"id":2, "value":"v2"}
          )

      ...or individual key/values interpreted by **params:

          conn.execute(
              table.insert(), id=1, value="v1"
          )

      In the case that a plain SQL string is passed, and the underlying DBAPI accepts positional bind parameters, a collection of tuples or individual values in *multiparams may be passed:

          conn.execute(
              "INSERT INTO table (id, value) VALUES (?, ?)",
              (1, "v1"), (2, "v2")
          )

          conn.execute(
              "INSERT INTO table (id, value) VALUES (?, ?)",
              1, "v1"
          )

      Note above, the usage of a question mark ”?” or other symbol is contingent upon the “paramstyle” accepted by the DBAPI in use, which may be any of “qmark”, “named”, “pyformat”, “format”, “numeric”. See pep-249 for details on paramstyle.

      To execute a textual SQL statement which uses bound parameters in a DBAPI-agnostic way, use the `text()` construct.

  `execution_options`(**opt)

    Set non-SQL options for the connection which take effect during execution.

    The method returns a copy of this `Connection` which references the same underlying DBAPI connection, but also defines the given execution options which will take effect for a call to `execute()`. As the new `Connection` references the same underlying resource, it’s usually a good idea to ensure that the copies would be discarded immediately, which is implicit if used as in:

        result = connection.execution_options(stream_results=True).\
                            execute(stmt)

    Note that any key/value can be passed to `Connection.execution_options()`, and it will be stored in the `_execution_options` dictionary of the `Connection`. It is suitable for usage by end-user schemes to communicate with event listeners, for example.

    The keywords that are currently recognized by SQLAlchemy itself include all those listed under `Executable.execution_options()`, as well as others that are specific to `Connection`.

    Parameters:

    - autocommit – Available on: Connection, statement. When True, a COMMIT will be invoked after execution when executed in ‘autocommit’ mode, i.e. when an explicit transaction is not begun on the connection. Note that DBAPI connections by default are always in a transaction - SQLAlchemy uses rules applied to different kinds of statements to determine if COMMIT will be invoked in order to provide its “autocommit” feature. Typically, all INSERT/UPDATE/DELETE statements as well as CREATE/DROP statements have autocommit behavior enabled; SELECT constructs do not. Use this option when invoking a SELECT or other specific SQL construct where COMMIT is desired (typically when calling stored procedures and such), and an explicit transaction is not in progress.
    - compiled_cache –

      Available on: Connection. A dictionary where `Compiled` objects will be cached when the `Connection` compiles a clause expression into a `Compiled` object. It is the user’s responsibility to manage the size of this dictionary, which will have keys corresponding to the dialect, clause element, the column names within the VALUES or SET clause of an INSERT or UPDATE, as well as the “batch” mode for an INSERT or UPDATE statement. The format of this dictionary is not guaranteed to stay the same in future releases.

      Note that the ORM makes use of its own “compiled” caches for some operations, including flush operations. The caching used by the ORM internally supersedes a cache dictionary specified here.

    - isolation_level –

      Available on: Connection. Set the transaction isolation level for the lifespan of this connection. Valid values include those string values accepted by the `isolation_level` parameter passed to `create_engine()`, and are database specific, including those for SQLite, PostgreSQL - see those dialect’s documentation for further info.

      Note that this option necessarily affects the underlying DBAPI connection for the lifespan of the originating `Connection`, and is not per-execution. This setting is not removed until the underlying DBAPI connection is returned to the connection pool, i.e. the `Connection.close()` method is called.

    - no_parameters –

      When `True`, if the final parameter list or dictionary is totally empty, will invoke the statement on the cursor as `cursor.execute(statement)`, not passing the parameter collection at all. Some DBAPIs such as psycopg2 and mysql-python consider percent signs as significant only when parameters are present; this option allows code to generate SQL containing percent signs (and possibly other characters) that is neutral regarding whether it’s executed by the DBAPI or piped into a script that’s later invoked by command line tools.

      New in version 0.7.6.

    - stream_results – Available on: Connection, statement. Indicate to the dialect that results should be “streamed” and not pre-buffered, if possible. This is a limitation of many DBAPIs. The flag is currently understood only by the psycopg2 dialect.

  `in_transaction`()

    Return True if a transaction is in progress.

  `info`

    Info dictionary associated with the underlying DBAPI connection referred to by this `Connection`, allowing user-defined data to be associated with the connection.

    The data here will follow along with the DBAPI connection including after it is returned to the connection pool and used again in subsequent instances of `Connection`.

  `invalidate`(exception=None)

    Invalidate the underlying DBAPI connection associated with this Connection.

    The underlying DB-API connection is literally closed (if possible), and is discarded. Its source connection pool will typically lazily create a new connection to replace it.

    Upon the next usage, this Connection will attempt to reconnect to the pool with a new connection.

    Transactions in progress remain in an “opened” state (even though the actual transaction is gone); these must be explicitly rolled back before a reconnect on this Connection can proceed. This is to prevent applications from accidentally continuing their transactional operations in a non-transactional state.

  `invalidated`

    Return True if this connection was invalidated.

  `run_callable`(callable_, *args, **kwargs)

    Given a callable object or function, execute it, passing a `Connection` as the first argument.

    The given *args and **kwargs are passed subsequent to the `Connection` argument.

    This function, along with `Engine.run_callable()`, allows a function to be run with a `Connection` or `Engine` object without the need to know which one is being dealt with.

  `scalar`(object, *multiparams, **params)

    Executes and returns the first column of the first row.

    The underlying result/cursor is closed after execution.

  `transaction`(callable_, *args, **kwargs)

    Execute the given function within a transaction boundary.

    The function is passed this `Connection` as the first argument, followed by the given *args and **kwargs, e.g.:

        def do_something(conn, x, y):
            conn.execute("some statement", {'x':x, 'y':y})

        conn.transaction(do_something, 5, 10)

    The operations inside the function are all invoked within the context of a single `Transaction`. Upon success, the transaction is committed. If an exception is raised, the transaction is rolled back before propagating the exception.

    Note

    The `transaction()` method is superseded by the usage of the Python `with:` statement, which can be used with `Connection.begin()`:

        with conn.begin():
            conn.execute("some statement", {'x':5, 'y':10})

    As well as with `Engine.begin()`:

        with engine.begin() as conn:
            conn.execute("some statement", {'x':5, 'y':10})

    See also:

    > `Engine.begin()` - engine-level transactional context

    > `Engine.transaction()` - engine-level version of `Connection.transaction()`

class `sqlalchemy.engine.``Connectable`

  Bases: `object`

  Interface for an object which supports execution of SQL constructs.

  The two implementations of `Connectable` are `Connection` and `Engine`.

  Connectable must also implement the ‘dialect’ member which references a `Dialect` instance.

  `connect`(**kwargs)

    Return a `Connection` object.

    Depending on context, this may be `self` if this object is already an instance of `Connection`, or a newly procured `Connection` if this object is an instance of `Engine`.

  `contextual_connect`()

    Return a `Connection` object which may be part of an ongoing context.

    Depending on context, this may be `self` if this object is already an instance of `Connection`, or a newly procured `Connection` if this object is an instance of `Engine`.

  `create`(entity, **kwargs)

    Emit CREATE statements for the given schema entity.

    Deprecated since version 0.7: Use the create() method on the given schema object directly, i.e. `Table.create()`, `Index.create()`, `MetaData.create_all()`

  `drop`(entity, **kwargs)

    Emit DROP statements for the given schema entity.

    Deprecated since version 0.7: Use the drop() method on the given schema object directly, i.e. `Table.drop()`, `Index.drop()`, `MetaData.drop_all()`

  `execute`(object, *multiparams, **params)

    Executes the given construct and returns a `ResultProxy`.

  `scalar`(object, *multiparams, **params)

    Executes and returns the first column of the first row.

    The underlying cursor is closed after execution.

class `sqlalchemy.engine.``Engine`(pool, dialect, url, logging_name=None, echo=None, proxy=None, execution_options=None)

  Bases: `sqlalchemy.engine.interfaces.Connectable`, `sqlalchemy.log.Identified`

  Connects a `Pool` and `Dialect` together to provide a source of database connectivity and behavior.

  An `Engine` object is instantiated publicly using the `create_engine()` function.

  See also:

  Engine Configuration

  Working with Engines and Connections

  `begin`(close_with_result=False)

    Return a context manager delivering a `Connection` with a `Transaction` established.

    E.g.:

        with engine.begin() as conn:
            conn.execute("insert into table (x, y, z) values (1, 2, 3)")
            conn.execute("my_special_procedure(5)")

    Upon successful operation, the `Transaction` is committed. If an error is raised, the `Transaction` is rolled back.

    The `close_with_result` flag is normally `False`, and indicates that the `Connection` will be closed when the operation is complete. When set to `True`, it indicates the `Connection` is in “single use” mode, where the `ResultProxy` returned by the first call to `Connection.execute()` will close the `Connection` when that `ResultProxy` has exhausted all result rows.

    New in version 0.7.6.

    See also:

    `Engine.connect()` - procure a `Connection` from an `Engine`.

    `Connection.begin()` - start a `Transaction` for a particular `Connection`.

  `connect`(**kwargs)

    Return a new `Connection` object.

    The `Connection` object is a facade that uses a DBAPI connection internally in order to communicate with the database. This connection is procured from the connection-holding `Pool` referenced by this `Engine`. When the `close()` method of the `Connection` object is called, the underlying DBAPI connection is then returned to the connection pool, where it may be used again in a subsequent call to `connect()`.

  `contextual_connect`(close_with_result=False, **kwargs)

    Return a `Connection` object which may be part of some ongoing context.

    By default, this method does the same thing as `Engine.connect()`. Subclasses of `Engine` may override this method to provide contextual behavior.

    Parameters: | close_with_result – When True, the first `ResultProxy` created by the `Connection` will call the `Connection.close()` method of that connection as soon as any pending result rows are exhausted. This is used to supply the “connectionless execution” behavior provided by the `Engine.execute()` method.

  `dispose`()

    Dispose of the connection pool used by this `Engine`.

    A new connection pool is created immediately after the old one has been disposed. This new pool, like all SQLAlchemy connection pools, does not make any actual connections to the database until one is first requested.

    This method has two general use cases:

    > - When a dropped connection is detected, it is assumed that all connections held by the pool are potentially dropped, and the entire pool is replaced.
    > - An application may want to use `dispose()` within a test suite that is creating multiple engines.

    It is critical to note that `dispose()` does not guarantee that the application will release all open database connections - only those connections that are checked into the pool are closed. Connections which remain checked out or have been detached from the engine are not affected.

  `driver`

    Driver name of the `Dialect` in use by this `Engine`.

  `execute`(statement, *multiparams, **params)

    Executes the given construct and returns a `ResultProxy`.

    The arguments are the same as those used by `Connection.execute()`.

    Here, a `Connection` is acquired using the `contextual_connect()` method, and the statement executed with that connection. The returned `ResultProxy` is flagged such that when the `ResultProxy` is exhausted and its underlying cursor is closed, the `Connection` created here will also be closed, which allows its associated DBAPI connection resource to be returned to the connection pool.

  `execution_options`(**opt)

    Return a new `Engine` that will provide `Connection` objects with the given execution options.

    The returned `Engine` remains related to the original `Engine` in that it shares the same connection pool and other state:

    - The `Pool` used by the new `Engine` is the same instance. The `Engine.dispose()` method will replace the connection pool instance for the parent engine as well as this one.
    - Event listeners are “cascaded” - meaning, the new `Engine` inherits the events of the parent, and new events can be associated with the new `Engine` individually.
    - The logging configuration and logging_name is copied from the parent `Engine`.

    The intent of the `Engine.execution_options()` method is to implement “sharding” schemes where multiple `Engine` objects refer to the same connection pool, but are differentiated by options that would be consumed by a custom event:

        primary_engine = create_engine("mysql://")
        shard1 = primary_engine.execution_options(shard_id="shard1")
        shard2 = primary_engine.execution_options(shard_id="shard2")

    Above, the `shard1` engine serves as a factory for `Connection` objects that will contain the execution option `shard_id=shard1`, and `shard2` will produce `Connection` objects that contain the execution option `shard_id=shard2`.

    An event handler can consume the above execution option to perform a schema switch or other operation, given a connection. Below we emit a MySQL `use` statement to switch databases, at the same time keeping track of which database we’ve established using the `Connection.info` dictionary, which gives us a persistent storage space that follows the DBAPI connection:

        from sqlalchemy import event
        from sqlalchemy.engine import Engine

        shards = {"default": "base", shard_1: "db1", "shard_2": "db2"}

        @event.listens_for(Engine, "before_cursor_execute")
        def _switch_shard(conn, cursor, stmt, params, context, executemany):
            shard_id = conn._execution_options.get('shard_id', "default")
            current_shard = conn.info.get("current_shard", None)

            if current_shard != shard_id:
                cursor.execute("use %s" % shards[shard_id])
                conn.info["current_shard"] = shard_id

    New in version 0.8.

    See also

    `Connection.execution_options()` - update execution options on a `Connection` object.

    `Engine.update_execution_options()` - update the execution options for a given `Engine` in place.

  `name`

    String name of the `Dialect` in use by this `Engine`.

  `raw_connection`()

    Return a “raw” DBAPI connection from the connection pool.

    The returned object is a proxied version of the DBAPI connection object used by the underlying driver in use. The object will have all the same behavior as the real DBAPI connection, except that its `close()` method will result in the connection being returned to the pool, rather than being closed for real.

    This method provides direct DBAPI connection access for special situations. In most situations, the `Connection` object should be used, which is procured using the `Engine.connect()` method.

  `run_callable`(callable_, *args, **kwargs)

    Given a callable object or function, execute it, passing a `Connection` as the first argument.

    The given *args and **kwargs are passed subsequent to the `Connection` argument.

    This function, along with `Connection.run_callable()`, allows a function to be run with a `Connection` or `Engine` object without the need to know which one is being dealt with.

  `table_names`(schema=None, connection=None)

    Return a list of all table names available in the database.

    Parameters:

    - schema – Optional, retrieve names from a non-default schema.
    - connection – Optional, use a specified connection. Default is the `contextual_connect` for this `Engine`.

  `transaction`(callable_, *args, **kwargs)

    Execute the given function within a transaction boundary.

    The function is passed a `Connection` newly procured from `Engine.contextual_connect()` as the first argument, followed by the given *args and **kwargs.

    e.g.:

        def do_something(conn, x, y):
            conn.execute("some statement", {'x':x, 'y':y})

        engine.transaction(do_something, 5, 10)

    The operations inside the function are all invoked within the context of a single `Transaction`. Upon success, the transaction is committed. If an exception is raised, the transaction is rolled back before propagating the exception.

    Note

    The `transaction()` method is superseded by the usage of the Python `with:` statement, which can be used with `Engine.begin()`:

        with engine.begin() as conn:
            conn.execute("some statement", {'x':5, 'y':10})

    See also:

    > `Engine.begin()` - engine-level transactional context

    > `Connection.transaction()` - connection-level version of `Engine.transaction()`

  `update_execution_options`(**opt)

    Update the default execution_options dictionary of this `Engine`.

    The given keys/values in **opt are added to the default execution options that will be used for all connections. The initial contents of this dictionary can be sent via the `execution_options` parameter to `create_engine()`.

    See also

    `Connection.execution_options()`

    `Engine.execution_options()`

class `sqlalchemy.engine.``NestedTransaction`(connection, parent)

  Bases: `sqlalchemy.engine.base.Transaction`

  Represent a ‘nested’, or SAVEPOINT transaction.

  A new `NestedTransaction` object may be procured using the `Connection.begin_nested()` method.

  The interface is the same as that of `Transaction`.

class `sqlalchemy.engine.``ResultProxy`(context)

  Wraps a DB-API cursor object to provide easier access to row columns.

  Individual columns may be accessed by their integer position, case-insensitive column name, or by `schema.Column` object. e.g.:

      row = fetchone()

      col1 = row[0]    # access via integer position

      col2 = row['col2']   # access via name

      col3 = row[mytable.c.mycol] # access via Column object.

  `ResultProxy` also handles post-processing of result column data using `TypeEngine` objects, which are referenced from the originating SQL statement that produced this result set.

  `close`(_autoclose_connection=True)

    Close this ResultProxy.

    Closes the underlying DBAPI cursor corresponding to the execution.

    Note that any data cached within this ResultProxy is still available. For some types of results, this may include buffered rows.

    If this ResultProxy was generated from an implicit execution, the underlying Connection will also be closed (returns the underlying DBAPI connection to the connection pool.)

    This method is called automatically when:

    - all result rows are exhausted using the fetchXXX() methods.
    - cursor.description is None.
  `fetchall`()

    Fetch all rows, just like DB-API `cursor.fetchall()`.

  `fetchmany`(size=None)

    Fetch many rows, just like DB-API `cursor.fetchmany(size=cursor.arraysize)`.

    If rows are present, the cursor remains open after this is called. Else the cursor is automatically closed and an empty list is returned.

  `fetchone`()

    Fetch one row, just like DB-API `cursor.fetchone()`.

    If a row is present, the cursor remains open after this is called. Else the cursor is automatically closed and None is returned.

  `first`()

    Fetch the first row and then close the result set unconditionally.

    Returns None if no row is present.

  `inserted_primary_key`

    Return the primary key for the row just inserted.

    The return value is a list of scalar values corresponding to the list of primary key columns in the target table.

    This only applies to single row `insert()` constructs which did not explicitly specify `Insert.returning()`.

    Note that primary key columns which specify a server_default clause, or otherwise do not qualify as “autoincrement” columns (see the notes at `Column`), and were generated using the database-side default, will appear in this list as `None` unless the backend supports “returning” and the insert statement executed with the “implicit returning” enabled.

    Raises `InvalidRequestError` if the executed statement is not a compiled expression construct or is not an insert() construct.

  `is_insert`

    True if this `ResultProxy` is the result of a executing an expression language compiled `expression.insert()` construct.

    When True, this implies that the `inserted_primary_key` attribute is accessible, assuming the statement did not include a user defined “returning” construct.

  `keys`()

    Return the current set of string keys for rows.

  `last_inserted_params`()

    Return the collection of inserted parameters from this execution.

    Raises `InvalidRequestError` if the executed statement is not a compiled expression construct or is not an insert() construct.

  `last_updated_params`()

    Return the collection of updated parameters from this execution.

    Raises `InvalidRequestError` if the executed statement is not a compiled expression construct or is not an update() construct.

  `lastrow_has_defaults`()

    Return `lastrow_has_defaults()` from the underlying `ExecutionContext`.

    See `ExecutionContext` for details.

  `lastrowid`

    return the ‘lastrowid’ accessor on the DBAPI cursor.

    This is a DBAPI specific method and is only functional for those backends which support it, for statements where it is appropriate. It’s behavior is not consistent across backends.

    Usage of this method is normally unnecessary when using insert() expression constructs; the `inserted_primary_key` attribute provides a tuple of primary key values for a newly inserted row, regardless of database backend.

  `postfetch_cols`()

    Return `postfetch_cols()` from the underlying `ExecutionContext`.

    See `ExecutionContext` for details.

    Raises `InvalidRequestError` if the executed statement is not a compiled expression construct or is not an insert() or update() construct.

  `prefetch_cols`()

    Return `prefetch_cols()` from the underlying `ExecutionContext`.

    See `ExecutionContext` for details.

    Raises `InvalidRequestError` if the executed statement is not a compiled expression construct or is not an insert() or update() construct.

  `returns_rows`

    True if this `ResultProxy` returns rows.

    I.e. if it is legal to call the methods `fetchone()`, `fetchmany()` `fetchall()`.

  `rowcount`

    Return the ‘rowcount’ for this result.

    The ‘rowcount’ reports the number of rows matched by the WHERE criterion of an UPDATE or DELETE statement.

    Note

    Notes regarding `ResultProxy.rowcount`:

    - This attribute returns the number of rows matched, which is not necessarily the same as the number of rows that were actually modified - an UPDATE statement, for example, may have no net change on a given row if the SET values given are the same as those present in the row already. Such a row would be matched but not modified. On backends that feature both styles, such as MySQL, rowcount is configured by default to return the match count in all cases.
    - `ResultProxy.rowcount` is only useful in conjunction with an UPDATE or DELETE statement. Contrary to what the Python DBAPI says, it does not return the number of rows available from the results of a SELECT statement as DBAPIs cannot support this functionality when rows are unbuffered.
    - `ResultProxy.rowcount` may not be fully implemented by all dialects. In particular, most DBAPIs do not support an aggregate rowcount result from an executemany call. The `ResultProxy.supports_sane_rowcount()` and `ResultProxy.supports_sane_multi_rowcount()` methods will report from the dialect if each usage is known to be supported.
    - Statements that use RETURNING may not return a correct rowcount.
  `scalar`()

    Fetch the first column of the first row, and close the result set.

    Returns None if no row is present.

  `supports_sane_multi_rowcount`()

    Return `supports_sane_multi_rowcount` from the dialect.

    See `ResultProxy.rowcount` for background.

  `supports_sane_rowcount`()

    Return `supports_sane_rowcount` from the dialect.

    See `ResultProxy.rowcount` for background.

class `sqlalchemy.engine.``RowProxy`(parent, row, processors, keymap)

  Proxy values from a single cursor row.

  Mostly follows “ordered dictionary” behavior, mapping result values to the string-based column name, the integer position of the result in the row, as well as Column instances which can be mapped to the original Columns that produced this result set (for results that correspond to constructed SQL expressions).

  `has_key`(key)

    Return True if this RowProxy contains the given key.

  `items`()

    Return a list of tuples, each tuple containing a key/value pair.

  `keys`()

    Return the list of keys as strings represented by this RowProxy.

class `sqlalchemy.engine.``Transaction`(connection, parent)

  Bases: `object`

  Represent a database transaction in progress.

  The `Transaction` object is procured by calling the `begin()` method of `Connection`:

      from sqlalchemy import create_engine
      engine = create_engine("postgresql://scott:tiger@localhost/test")
      connection = engine.connect()
      trans = connection.begin()
      connection.execute("insert into x (a, b) values (1, 2)")
      trans.commit()

  The object provides `rollback()` and `commit()` methods in order to control transaction boundaries. It also implements a context manager interface so that the Python `with` statement can be used with the `Connection.begin()` method:

      with connection.begin():
          connection.execute("insert into x (a, b) values (1, 2)")

  The Transaction object is not threadsafe.

  See also: `Connection.begin()`, `Connection.begin_twophase()`, `Connection.begin_nested()`.

  `close`()

    Close this `Transaction`.

    If this transaction is the base transaction in a begin/commit nesting, the transaction will rollback(). Otherwise, the method returns.

    This is used to cancel a Transaction without affecting the scope of an enclosing transaction.

  `commit`()

    Commit this `Transaction`.

  `rollback`()

    Roll back this `Transaction`.

class `sqlalchemy.engine.``TwoPhaseTransaction`(connection, xid)

  Bases: `sqlalchemy.engine.base.Transaction`

  Represent a two-phase transaction.

  A new `TwoPhaseTransaction` object may be procured using the `Connection.begin_twophase()` method.

  The interface is the same as that of `Transaction` with the addition of the `prepare()` method.

  `prepare`()

    Prepare this `TwoPhaseTransaction`.

    After a PREPARE, the transaction can be committed.