.. _glossary:

========
Glossary
========

.. note::

	The Glossary is a brand new addition to the documentation.  While
	sparse at the moment we hope to fill it up with plenty of new
	terms soon!

.. glossary::
    :sorted:

    annotations
        Annotations are a concept used internally by SQLAlchemy in order to store
        additional information along with :class:`.ClauseElement` objects.  A Python
        dictionary is associated with a copy of the object, which contains key/value
        pairs significant to various internal systems, mostly within the ORM::

            some_column = Column('some_column', Integer)
            some_column_annotated = some_column._annotate({"entity": User})

        The annotation system differs from the public dictionary :attr:`.Column.info`
        in that the above annotation operation creates a *copy* of the new :class:`.Column`,
        rather than considering all annotation values to be part of a single
        unit.  The ORM creates copies of expression objects in order to
        apply annotations that are specific to their context, such as to differentiate
        columns that should render themselves as relative to a joined-inheritance
        entity versus those which should render relative to their immediate parent
        table alone, as well as to differentiate columns within the "join condition"
        of a relationship where the column in some cases needs to be expressed
        in terms of one particular table alias or another, based on its position
        within the join expression.

    descriptor
    descriptors
        In Python, a descriptor is an object attribute with “binding behavior”, one whose attribute access has been overridden by methods in the `descriptor protocol <http://docs.python.org/howto/descriptor.html>`_.
        Those methods are __get__(), __set__(), and __delete__(). If any of those methods are defined
        for an object, it is said to be a descriptor.

        In SQLAlchemy, descriptors are used heavily in order to provide attribute behavior
        on mapped classes.   When a class is mapped as such::

            class MyClass(Base):
                __tablename__ = 'foo'

                id = Column(Integer, primary_key=True)
                data = Column(String)

        The ``MyClass`` class will be :term:`mapped` when its definition
        is complete, at which point the ``id`` and ``data`` attributes,
        starting out as :class:`.Column` objects, will be replaced
        by the :term:`instrumentation` system with instances
        of :class:`.InstrumentedAttribute`, which are descriptors that
        provide the above mentioned ``__get__()``, ``__set__()`` and
        ``__delete__()`` methods.   The :class:`.InstrumentedAttribute`
        will generate a SQL expression when used at the class level::

            >>> print MyClass.data == 5
            data = :data_1

        and at the instance level, keeps track of changes to values,
        and also :term:`lazy loads` unloaded attributes
        from the database::

            >>> m1 = MyClass()
            >>> m1.id = 5
            >>> m1.data = "some data"

            >>> from sqlalchemy import inspect
            >>> inspect(m1).attrs.data.history.added
            "some data"

    discriminator
        A result-set column which is used during :term:`polymorphic` loading
        to determine what kind of mapped class should be applied to a particular
        incoming result row.   In SQLAlchemy, the classes are always part
        of a hierarchy mapping using inheritance mapping.

        .. seealso::

            :ref:`inheritance_toplevel`

    instrumentation
    instrumented
        Instrumentation refers to the process of augmenting the functionality
        and attribute set of a particular class.   Ideally, the
        behavior of the class should remain close to a regular
        class, except that additional behviors and features are
        made available.  The SQLAlchemy :term:`mapping` process,
        among other things, adds database-enabled :term:`descriptors`
        to a mapped
        class which each represent a particular database column
        or relationship to a related class.

    lazy load
    lazy loads
        In object relational mapping, a "lazy load" refers to an
        attribute that does not contain its database-side value
        for some period of time, typically when the object is
        first loaded.  Instead, the attribute receives a
        *memoization* that causes it to go out to the database
        and load its data when it's first used.   Using this pattern,
        the complexity and time spent within object fetches can
        sometimes be reduced, in that
        attributes for related tables don't need to be addressed
        immediately.

        .. seealso::

            `Lazy Load (on Martin Fowler) <http://martinfowler.com/eaaCatalog/lazyLoad.html>`_

            :term:`N plus one problem`

            :doc:`orm/loading`

    mapping
    mapped
        We say a class is "mapped" when it has been passed through the
        :func:`.orm.mapper` function.   This process associates the
        class with a database table or other :term:`selectable`
        construct, so that instances of it can be persisted
        using a :class:`.Session` as well as loaded using a
        :class:`.Query`.

    N plus one problem
        The N plus one problem is a common side effect of the
        :term:`lazy load` pattern, whereby an application wishes
        to iterate through a related attribute or collection on
        each member of a result set of objects, where that
        attribute or collection is set to be loaded via the lazy
        load pattern.   The net result is that a SELECT statement
        is emitted to load the initial result set of parent objects;
        then, as the application iterates through each member,
        an additional SELECT statement is emitted for each member
        in order to load the related attribute or collection for
        that member.  The end result is that for a result set of
        N parent objects, there will be N + 1 SELECT statements emitted.

        The N plus one problem is alleviated using :term:`eager loading`.

        .. seealso::

            :doc:`orm/loading`

    polymorphic
    polymorphically
        Refers to a function that handles several types at once.  In SQLAlchemy,
        the term is usually applied to the concept of an ORM mapped class
        whereby a query operation will return different subclasses
        based on information in the result set, typically by checking the
        value of a particular column in the result known as the :term:`discriminator`.

        Polymorphic loading in SQLAlchemy implies that a one or a
        combination of three different schemes are used to map a hierarchy
        of classes; "joined", "single", and "concrete".   The section
        :ref:`inheritance_toplevel` describes inheritance mapping fully.

    generative
        A term that SQLAlchemy uses to refer what's normally known
        as :term:`method chaining`; see that term for details.

    method chaining
        An object-oriented technique whereby the state of an object
        is constructed by calling methods on the object.   The
        object features any number of methods, each of which return
        a new object (or in some cases the same object) with
        additional state added to the object.

        The two SQLAlchemy objects that make the most use of
        method chaining are the :class:`~.expression.Select`
        object and the :class:`~.orm.query.Query` object.
        For example, a :class:`~.expression.Select` object can
        be assigned two expressions to its WHERE clause as well
        as an ORDER BY clause by calling upon the :meth:`~.Select.where`
        and :meth:`~.Select.order_by` methods::

            stmt = select([user.c.name]).\
                        where(user.c.id > 5).\
                        where(user.c.name.like('e%').\
                        order_by(user.c.name)

        Each method call above returns a copy of the original
        :class:`~.expression.Select` object with additional qualifiers
        added.

        .. seealso::

            :term:`generative`

    release
    releases
    released
        In the context of SQLAlchemy, the term "released"
        refers to the process of ending the usage of a particular
        database connection.    SQLAlchemy features the usage
        of connection pools, which allows configurability as to
        the lifespan of database connections.   When using a pooled
        connection, the process of "closing" it, i.e. invoking
        a statement like ``connection.close()``, may have the effect
        of the connection being returned to an existing pool,
        or it may have the effect of actually shutting down the
        underlying TCP/IP connection referred to by that connection -
        which one takes place depends on configuration as well
        as the current state of the pool.  So we used the term
        *released* instead, to mean "do whatever it is you do
        with connections when we're done using them".

        The term will sometimes be used in the phrase, "release
        transactional resources", to indicate more explicitly that
        what we are actually "releasing" is any transactional
        state which as accumulated upon the connection.  In most
        situations, the proces of selecting from tables, emitting
        updates, etc. acquires :term:`isolated` state upon
        that connection as well as potential row or table locks.
        This state is all local to a particular transaction
        on the connection, and is released when we emit a rollback.
        An important feature of the connection pool is that when
        we return a connection to the pool, the ``connection.rollback()``
        method of the DBAPI is called as well, so that as the
        connection is set up to be used again, it's in a "clean"
        state with no references held to the previous series
        of operations.

        .. seealso::

        	:ref:`pooling_toplevel`

    DBAPI
        DBAPI is shorthand for the phrase "Python Database API
        Specification".  This is a widely used specification
        within Python to define common usage patterns for all
        database connection packages.   The DBAPI is a "low level"
        API which is typically the lowest level system used
        in a Python application to talk to a database.  SQLAlchemy's
        :term:`dialect` system is constructed around the
        operation of the DBAPI, providing individual dialect
        classes which service a specific DBAPI on top of a
        specific database engine; for example, the :func:`.create_engine`
        URL ``postgresql+psycopg2://@localhost/test``
        refers to the :mod:`psycopg2 <.postgresql.psycopg2>`
        DBAPI/dialect combination, whereas the URL ``mysql+mysqldb://@localhost/test``
        refers to the :mod:`MySQL for Python <.mysql.mysqldb>`
        DBAPI DBAPI/dialect combination.

        .. seealso::

            `PEP 249 - Python Database API Specification v2.0 <http://www.python.org/dev/peps/pep-0249/>`_


    unit of work
        This pattern is where the system transparently keeps
        track of changes to objects and periodically flushes all those
        pending changes out to the database. SQLAlchemy's Session
        implements this pattern fully in a manner similar to that of
        Hibernate.

        .. seealso::

            `Unit of Work by Martin Fowler <http://martinfowler.com/eaaCatalog/unitOfWork.html>`_

            :doc:`orm/session`

    correlates
    correlated subquery
    correlated subqueries
        A :term:`subquery` is correlated if it depends on data in the
        enclosing ``SELECT``.

        Below, a subquery selects the aggregate value ``MIN(a.id)``
        from the ``email_address`` table, such that
        it will be invoked for each value of ``user_account.id``, correlating
        the value of this column against the ``email_address.user_account_id``
        column:

        .. sourcecode:: sql

            SELECT user_account.name, email_address.email
             FROM user_account
             JOIN email_address ON user_account.id=email_address.user_account_id
             WHERE email_address.id = (
                SELECT MIN(a.id) FROM email_address AS a
                WHERE a.user_account_id=user_account.id
             )

        The above subquery refers to the ``user_account`` table, which is not itself
        in the ``FROM`` clause of this nested query.   Instead, the ``user_account``
        table is recieved from the enclosing query, where each row selected from
        ``user_account`` results in a distinct execution of the subquery.

        A correlated subquery is nearly always present in the :term:`WHERE clause`
        or :term:`columns clause` of the enclosing ``SELECT`` statement, and never
        in the :term:`FROM clause`; this is because
        the correlation can only proceed once the original source rows from the enclosing
        statement's FROM clause are available.
