path: root/doc/build/core/connections.rst

.. _connections_toplevel:

====================================
Working with Engines and Connections
====================================

.. module:: sqlalchemy.engine

This section details direct usage of the :class:`_engine.Engine`,
:class:`_engine.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.Engine` and
:class:`_engine.Connection` are king (and queen?) - read on.

Basic Usage
===========

Recall from :doc:`/core/engines` that an :class:`_engine.Engine` is created via
the :func:`.create_engine` call::

    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.Engine` manages many individual :term:`DBAPI` connections on behalf of
the process and is intended to be called upon in a concurrent fashion. The
:class:`_engine.Engine` is **not** synonymous to the DBAPI ``connect`` function, which
represents just one connection resource - the :class:`_engine.Engine` is most
efficient when created just once at the module level of an application, not
per-object or per-function call.

.. sidebar:: tip

    When using an :class:`_engine.Engine` with multiple Python processes, such as when
    using ``os.fork`` or Python ``multiprocessing``, it's important that the
    engine is initialized per process.  See :ref:`pooling_multiprocessing` for
    details.

The most basic function of the :class:`_engine.Engine` is to provide access to a
:class:`_engine.Connection`, which can then invoke SQL statements.   To emit
a textual statement to the database looks like::

    from sqlalchemy import text

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

Above, the :meth:`_engine.Engine.connect` method returns a :class:`_engine.Connection`
object, and by using it in a Python context manager (e.g. the ``with:``
statement) the :meth:`_engine.Connection.close` method is automatically invoked at the
end of the block.  The :class:`_engine.Connection`, is a **proxy** object for an
actual DBAPI connection. The DBAPI connection is retrieved from the connection
pool at the point at which :class:`_engine.Connection` is created.

The object returned is known as :class:`.ResultProxy`, which
references a DBAPI cursor and provides methods for fetching rows
similar to 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 :class:`_engine.Connection` is closed at the end of the ``with:`` block, the
referenced DBAPI connection is :term:`released` to the connection pool.   From
the perspective of the database itself, the connection pool will not actually
"close" the connection assuming the pool has room to store this connection  for
the next use.  When the connection is returned to the pool for re-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 use.

.. deprecated:: 2.0 The :class:`.ResultProxy` object is replaced in SQLAlchemy
   2.0 with a newly refined object known as :class:`.future.Result`.

Our example above illustrated the execution of a textual SQL string, which
should be invoked by using the :func:`_expression.text` construct to indicate that
we'd like to use textual SQL.  The :meth:`_engine.Connection.execute` method can of
course accommodate more than that, including the variety of SQL expression
constructs described in :ref:`sqlexpression_toplevel`.


Using Transactions
==================

.. note::

  This section describes how to use transactions when working directly
  with :class:`_engine.Engine` and :class:`_engine.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:`_engine.Connection.begin`
method which returns a :class:`.Transaction` object.  Like the :class:`_engine.Connection`
itself, this object is usually used within a Python ``with:`` block so
that its scope is managed::

    with engine.connect() as connection:
        with connection.begin():
            r1 = connection.execute(table1.select())
            connection.execute(table1.insert(), {"col1": 7, "col2": "this is some data"})

The above block can be stated more simply by using the :meth:`_engine.Engine.begin`
method of :class:`_engine.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"})

The block managed by each ``.begin()`` method has the behavior such that
the transaction is committed when the block completes.   If an exception is
raised, the transaction is instead rolled back, and the exception propagated
outwards.

The underlying object used to represent the transaction is the
:class:`.Transaction` object.  This object is returned by the
:meth:`_engine.Connection.begin` method and includes the methods
:meth:`.Transaction.commit` and :meth:`.Transaction.rollback`.   The context
manager calling form, which invokes these methods automatically, is recommended
as a best practice.

.. _connections_nested_transactions:

Nesting of Transaction Blocks
-----------------------------

.. note:: The "transaction nesting" feature of SQLAlchemy is a legacy feature
   that will be deprecated in an upcoming release.  New usage paradigms will
   eliminate the need for it to be present.

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:`_engine.Connection`, but only the outermost
:class:`.Transaction` object actually takes effect when it is committed.

.. sourcecode:: python+sql

    # method_a starts a transaction and calls method_b
    def method_a(connection):
        with connection.begin():  # open a transaction
            method_b(connection)

    # method_b also starts a transaction
    def method_b(connection):
        with connection.begin(): # open a transaction - this runs in the
                                 # context of method_a's transaction
            connection.execute(text("insert into mytable values ('bat', 'lala')"))
            connection.execute(mytable.insert(), {"col1": "bat", "col2": "lala"})

    # open a Connection and call method_a
    with engine.connect() as conn:
        method_a(conn)

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.

.. index::
   single: thread safety; transactions

.. _autocommit:

Understanding Autocommit
========================

.. deprecated:: 2.0  The "autocommit" feature of SQLAlchemy Core is deprecated
   and will not be present in version 2.0 of SQLAlchemy.
   See :ref:`migration_20_autocommit` for background.

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(text("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:`_engine.Connection.execution_options` method provided on :class:`_engine.Connection`
and :class:`_engine.Engine`, using the "autocommit" flag which will
turn on or off the autocommit for the selected scope. For example, a
:func:`_expression.text` construct representing a stored procedure that commits might use
it so that a SELECT statement will issue a COMMIT::

    with engine.connect().execution_options(autocommit=True) as conn:
        conn.execute(text("SELECT my_mutating_procedure()"))

.. _dbengine_implicit:


Connectionless Execution, Implicit Execution
============================================

.. deprecated:: 2.0 The features of "connectionless" and "implicit" execution
   in SQLAlchemy are deprecated and will be removed in version 2.0.  See
   :ref:`migration_20_implicit_execution` for background.

Recall from the first section we mentioned executing with and without explicit
usage of :class:`_engine.Connection`. "Connectionless" execution
refers to the usage of the ``execute()`` method on an object
which is not a :class:`_engine.Connection`.  This was illustrated using the
:meth:`_engine.Engine.execute` method of :class:`_engine.Engine`::

    result = engine.execute(text("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.Engine` or :class:`_engine.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
:meth:`_engine.Connection.execute` method of :class:`~sqlalchemy.engine.Connection`:

.. sourcecode:: python+sql

    engine = create_engine('sqlite:///file.db')
    with engine.connect() as connection:
        result = connection.execute(users_table.select())
        for row in result:
            # ....

Explicit, connectionless execution delivers the expression to the
:meth:`_engine.Engine.execute` method of :class:`~sqlalchemy.engine.Engine`:

.. sourcecode:: python+sql

    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:`_schema.MetaData.bind`
has been used to associate a series of
:class:`_schema.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.Engine` with a :class:`_schema.MetaData` object using
the special attribute :attr:`_schema.MetaData.bind`.  The :func:`_expression.select` construct produced
from the :class:`_schema.Table` object has a method :meth:`~.Executable.execute`, which will
search for an :class:`_engine.Engine` that's "bound" to the :class:`_schema.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.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.Engine`/
  mapped class configurations.
* The :meth:`_schema.MetaData.create_all`, :meth:`_schema.MetaData.drop_all`, :meth:`_schema.Table.create`,
  :meth:`_schema.Table.drop`, and "autoload" features all make usage of the bound
  :class:`_engine.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 :class:`_engine.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:`_schema.Table` can refer to the appropriate :class:`_engine.Engine` automatically;
    in particular this is supported within the ORM via the :class:`.Session` object
    as a means to associate :class:`_schema.Table` objects with an appropriate :class:`_engine.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:`_engine.Connection` is closed for us, resulting in the
DBAPI connection being returned to the pool with transactional resources removed.

.. _schema_translating:

Translation of Schema Names
===========================

To support multi-tenancy applications that distribute common sets of tables
into multiple schemas, the
:paramref:`.Connection.execution_options.schema_translate_map`
execution option may be used to repurpose a set of :class:`_schema.Table` objects
to render under different schema names without any changes.

Given a table::

    user_table = Table(
        'user', metadata,
        Column('id', Integer, primary_key=True),
        Column('name', String(50))
    )

The "schema" of this :class:`_schema.Table` as defined by the
:paramref:`_schema.Table.schema` attribute is ``None``.  The
:paramref:`.Connection.execution_options.schema_translate_map` can specify
that all :class:`_schema.Table` objects with a schema of ``None`` would instead
render the schema as ``user_schema_one``::

    connection = engine.connect().execution_options(
        schema_translate_map={None: "user_schema_one"})

    result = connection.execute(user_table.select())

The above code will invoke SQL on the database of the form::

    SELECT user_schema_one.user.id, user_schema_one.user.name FROM
    user_schema_one.user

That is, the schema name is substituted with our translated name.  The
map can specify any number of target->destination schemas::

    connection = engine.connect().execution_options(
        schema_translate_map={
            None: "user_schema_one",     # no schema name -> "user_schema_one"
            "special": "special_schema", # schema="special" becomes "special_schema"
            "public": None               # Table objects with schema="public" will render with no schema
        })

The :paramref:`.Connection.execution_options.schema_translate_map` parameter
affects all DDL and SQL constructs generated from the SQL expression language,
as derived from the :class:`_schema.Table` or :class:`.Sequence` objects.
It does **not** impact literal string SQL used via the :func:`_expression.text`
construct nor via plain strings passed to :meth:`_engine.Connection.execute`.

The feature takes effect **only** in those cases where the name of the
schema is derived directly from that of a :class:`_schema.Table` or :class:`.Sequence`;
it does not impact methods where a string schema name is passed directly.
By this pattern, it takes effect within the "can create" / "can drop" checks
performed by methods such as :meth:`_schema.MetaData.create_all` or
:meth:`_schema.MetaData.drop_all` are called, and it takes effect when
using table reflection given a :class:`_schema.Table` object.  However it does
**not** affect the operations present on the :class:`_reflection.Inspector` object,
as the schema name is passed to these methods explicitly.

.. versionadded:: 1.1

.. _engine_disposal:

Engine Disposal
===============

The :class:`_engine.Engine` refers to a connection pool, which means under normal
circumstances, there are open database connections present while the
:class:`_engine.Engine` object is still resident in memory.   When an :class:`_engine.Engine`
is garbage collected, its connection pool is no longer referred to by
that :class:`_engine.Engine`, and assuming none of its connections are still checked
out, the pool and its connections will also be garbage collected, which has the
effect of closing out the actual database connections as well.   But otherwise,
the :class:`_engine.Engine` will hold onto open database connections assuming
it uses the normally default pool implementation of :class:`.QueuePool`.

The :class:`_engine.Engine` is intended to normally be a permanent
fixture established up-front and maintained throughout the lifespan of an
application.  It is **not** intended to be created and disposed on a
per-connection basis; it is instead a registry that maintains both a pool
of connections as well as configurational information about the database
and DBAPI in use, as well as some degree of internal caching of per-database
resources.

However, there are many cases where it is desirable that all connection resources
referred to by the :class:`_engine.Engine` be completely closed out.  It's
generally not a good idea to rely on Python garbage collection for this
to occur for these cases; instead, the :class:`_engine.Engine` can be explicitly disposed using
the :meth:`_engine.Engine.dispose` method.   This disposes of the engine's
underlying connection pool and replaces it with a new one that's empty.
Provided that the :class:`_engine.Engine`
is discarded at this point and no longer used, all **checked-in** connections
which it refers to will also be fully closed.

Valid use cases for calling :meth:`_engine.Engine.dispose` include:

* When a program wants to release any remaining checked-in connections
  held by the connection pool and expects to no longer be connected
  to that database at all for any future operations.

* When a program uses multiprocessing or ``fork()``, and an
  :class:`_engine.Engine` object is copied to the child process,
  :meth:`_engine.Engine.dispose` should be called so that the engine creates
  brand new database connections local to that fork.   Database connections
  generally do **not** travel across process boundaries.

* Within test suites or multitenancy scenarios where many
  ad-hoc, short-lived :class:`_engine.Engine` objects may be created and disposed.


Connections that are **checked out** are **not** discarded when the
engine is disposed or garbage collected, as these connections are still
strongly referenced elsewhere by the application.
However, after :meth:`_engine.Engine.dispose` is called, those
connections are no longer associated with that :class:`_engine.Engine`; when they
are closed, they will be returned to their now-orphaned connection pool
which will ultimately be garbage collected, once all connections which refer
to it are also no longer referenced anywhere.
Since this process is not easy to control, it is strongly recommended that
:meth:`_engine.Engine.dispose` is called only after all checked out connections
are checked in or otherwise de-associated from their pool.

An alternative for applications that are negatively impacted by the
:class:`_engine.Engine` object's use of connection pooling is to disable pooling
entirely.  This typically incurs only a modest performance impact upon the
use of new connections, and means that when a connection is checked in,
it is entirely closed out and is not held in memory.  See :ref:`pool_switching`
for guidelines on how to disable pooling.

.. _dbapi_connections:

Working with Driver SQL and Raw DBAPI Connections
=================================================

The introduction on using :meth:`_engine.Connection.execute` made use of the
:func:`_expression.text` construct in order to illustrate how textual SQL statements
may be invoked.  When working with SQLAlchemy, textual SQL is actually more
of the exception rather than the norm, as the Core expression language
and the ORM both abstract away the textual representation of SQL.  Hpwever, the
:func:`_expression.text` construct itself also provides some abstraction of textual
SQL in that it normalizes how bound parameters are passed, as well as that
it supports datatyping behavior for parameters and result set rows.

Invoking SQL strings directly to the driver
--------------------------------------------

For the use case where one wants to invoke textual SQL directly passed to the
underlying driver (known as the :term:`DBAPI`) without any intervention
from the :func:`_expression.text` construct, the :meth:`_engine.Connection.exec_driver_sql`
method may be used::

    with engine.connect() as conn:
        conn.exec_driver_sql("SET param='bar'")


.. versionadded:: 1.4  Added the :meth:`_engine.Connection.exec_driver_sql` method.

Working with the DBAPI cursor directly
--------------------------------------

There are some cases where SQLAlchemy does not provide a genericized way
at accessing some :term:`DBAPI` functions, such as calling stored procedures as well
as dealing with multiple result sets.  In these cases, it's just as expedient
to deal with the raw DBAPI connection directly.

The most common way to access the raw DBAPI connection is to get it
from an already present :class:`_engine.Connection` object directly.  It is
present using the :attr:`_engine.Connection.connection` attribute::

    connection = engine.connect()
    dbapi_conn = connection.connection

The DBAPI connection here is actually a "proxied" in terms of the
originating connection pool, however this is an implementation detail
that in most cases can be ignored.    As this DBAPI connection is still
contained within the scope of an owning :class:`_engine.Connection` object, it is
best to make use of the :class:`_engine.Connection` object for most features such
as transaction control as well as calling the :meth:`_engine.Connection.close`
method; if these operations are performed on the DBAPI connection directly,
the owning :class:`_engine.Connection` will not be aware of these changes in state.

To overcome the limitations imposed by the DBAPI connection that is
maintained by an owning :class:`_engine.Connection`, a DBAPI connection is also
available without the need to procure a
:class:`_engine.Connection` first, using the :meth:`_engine.Engine.raw_connection` method
of :class:`_engine.Engine`::

    dbapi_conn = engine.raw_connection()

This DBAPI connection is again a "proxied" form as was the case before.
The purpose of this proxying is now apparent, as when we call the ``.close()``
method of this connection, the DBAPI connection is typically not actually
closed, but instead :term:`released` back to the
engine's connection pool::

    dbapi_conn.close()

While SQLAlchemy may in the future add built-in patterns for more DBAPI
use cases, there are diminishing returns as these cases tend to be rarely
needed and they also vary highly dependent on the type of DBAPI in use,
so in any case the direct DBAPI calling pattern is always there for those
cases where it is needed.

Some recipes for DBAPI connection use follow.

.. _stored_procedures:

Calling Stored Procedures
-------------------------

For stored procedures with special syntactical or parameter concerns,
DBAPI-level `callproc <http://legacy.python.org/dev/peps/pep-0249/#callproc>`_
may be used::

    connection = engine.raw_connection()
    try:
        cursor = connection.cursor()
        cursor.callproc("my_procedure", ['x', 'y', 'z'])
        results = list(cursor.fetchall())
        cursor.close()
        connection.commit()
    finally:
        connection.close()

Multiple Result Sets
--------------------

Multiple result set support is available from a raw DBAPI cursor using the
`nextset <http://legacy.python.org/dev/peps/pep-0249/#nextset>`_ method::

    connection = engine.raw_connection()
    try:
        cursor = connection.cursor()
        cursor.execute("select * from table1; select * from table2")
        results_one = cursor.fetchall()
        cursor.nextset()
        results_two = cursor.fetchall()
        cursor.close()
    finally:
        connection.close()



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:

1. Create a package called ``foodialect``.
2. 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``.
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.


Connection / Engine API
=======================

.. autoclass:: BaseResult
    :members:

.. autoclass:: Connection
   :members:

.. autoclass:: Connectable
   :members:

.. autoclass:: CreateEnginePlugin
   :members:

.. autoclass:: Engine
   :members:

.. autoclass:: ExceptionContext
   :members:

.. autoclass:: LegacyRow
    :members:

.. autoclass:: NestedTransaction
    :members:

.. autoclass:: ResultProxy
    :members:
    :inherited-members:

.. autoclass:: Row
    :members:
    :private-members: _fields, _mapping

.. autoclass:: RowMapping
    :members:

.. autoclass:: Transaction
    :members:

.. autoclass:: TwoPhaseTransaction
    :members: