:orphan:

.. _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.

    identity map
        A mapping between Python objects and their database identities.
        The identity map is a collection that's associated with an
        ORM :term:`session` object, and maintains a single instance
        of every database object keyed to its identity.   The advantage
        to this pattern is that all operations which occur for a particular
        database identity are transparently coordinated onto a single
        object instance.  When using an identity map in conjunction with
        an :term:`isolated` transaction, having a reference
        to an object that's known to have a particular primary key can
        be considered from a practical standpoint to be a
        proxy to the actual database row.

        .. seealso::

            Martin Fowler - Identity Map - http://martinfowler.com/eaaCatalog/identityMap.html

    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`

    Session
        The container or scope for ORM database operations. Sessions
        load instances from the database, track changes to mapped
        instances and persist changes in a single unit of work when
        flushed.

        .. seealso::

            :doc:`orm/session`

    columns clause
        The portion of the ``SELECT`` statement which enumerates the
        SQL expressions to be returned in the result set.  The expressions
        follow the ``SELECT`` keyword directly and are a comma-separated
        list of individual expressions.

        E.g.:

        .. sourcecode:: sql

            SELECT user_account.name, user_account.email
            FROM user_account WHERE user_account.name = 'fred'

        Above, the list of columns ``user_acount.name``,
        ``user_account.email`` is the columns clause of the ``SELECT``.

    WHERE clause
        The portion of the ``SELECT`` statement which indicates criteria
        by which rows should be filtered.   It is a single SQL expression
        which follows the keyword ``WHERE``.

        .. sourcecode:: sql

            SELECT user_account.name, user_account.email
            FROM user_account
            WHERE user_account.name = 'fred' AND user_account.status = 'E'

        Above, the phrase ``WHERE user_account.name = 'fred' AND user_account.status = 'E'``
        comprises the WHERE clause of the ``SELECT``.

    FROM clause
        The portion of the ``SELECT`` statement which incicates the initial
        source of rows.

        A simple ``SELECT`` will feature one or more table names in its
        FROM clause.  Multiple sources are separated by a comma:

        .. sourcecode:: sql

            SELECT user.name, address.email_address
            FROM user, address
            WHERE user.id=address.user_id

        The FROM clause is also where explicit joins are specified.  We can
        rewrite the above ``SELECT`` using a single ``FROM`` element which consists
        of a ``JOIN`` of the two tables:

        .. sourcecode:: sql

            SELECT user.name, address.email_address
            FROM user JOIN address ON user.id=address.user_id


    subquery
        Refers to a ``SELECT`` statement that is embedded within an enclosing
        ``SELECT``.

        A subquery comes in two general flavors, one known as a "scalar select"
        which specifically must return exactly one row and one column, and the
        other form which acts as a "derived table" and serves as a source of
        rows for the FROM clause of another select.  A scalar select is eligble
        to be placed in the :term:`WHERE clause`, :term:`columns clause`,
        ORDER BY clause or HAVING clause of the enclosing select, whereas the
        derived table form is eligible to be placed in the FROM clause of the
        enclosing ``SELECT``.

        Examples:

        1. a scalar subquery placed in the :term:`columns clause` of an enclosing
           ``SELECT``.  The subquery in this example is a :term:`correlated subquery` because part
           of the rows which it selects from are given via the enclosing statement.

           .. sourcecode:: sql

            SELECT id, (SELECT name FROM address WHERE address.user_id=user.id)
            FROM user

        2. a scalar subquery placed in the :term:`WHERE clause` of an enclosing
           ``SELECT``.  This subquery in this example is not correlated as it selects a fixed result.

           .. sourcecode:: sql

            SELECT id, name FROM user
            WHERE status=(SELECT status_id FROM status_code WHERE code='C')

        3. a derived table subquery placed in the :term:`FROM clause` of an enclosing
           ``SELECT``.   Such a subquery is almost always given an alias name.

           .. sourcecode:: sql

            SELECT user.id, user.name, ad_subq.email_address
            FROM
                user JOIN
                (select user_id, email_address FROM address WHERE address_type='Q') AS ad_subq
                ON user.id = ad_subq.user_id

    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 in most cases present in the :term:`WHERE clause`
        or :term:`columns clause` of the immediately enclosing ``SELECT``
        statement, as well as in the ORDER BY or HAVING clause.

        In less common cases, a correlated subquery may be present in the
        :term:`FROM clause` of an enclosing ``SELECT``; in these cases the
        correlation is typically due to the enclosing ``SELECT`` itself being
        enclosed in the WHERE,
        ORDER BY, columns or HAVING clause of another ``SELECT``, such as:

        .. sourcecode:: sql

            SELECT parent.id FROM parent
            WHERE EXISTS (
                SELECT * FROM (
                    SELECT child.id AS id, child.parent_id AS parent_id, child.pos AS pos
                    FROM child
                    WHERE child.parent_id = parent.id ORDER BY child.pos
                LIMIT 3)
            WHERE id = 7)

        Correlation from one ``SELECT`` directly to one which encloses the correlated
        query via its ``FROM``
        clause is not possible, because the correlation can only proceed once the
        original source rows from the enclosing statement's FROM clause are available.

    ACID
    ACID model
        An acronym for "Atomicity, Consistency, Isolation,
        Durability"; a set of properties that guarantee that
        database transactions are processed reliably.
        (via Wikipedia)

        .. seealso::

            :term:`atomicity`

            :term:`consistency`

            :term:`isolation`

            :term:`durability`

            http://en.wikipedia.org/wiki/ACID_Model

    atomicity
        Atomicity is one of the components of the :term:`ACID` model,
        and requires that each transaction is "all or nothing":
        if one part of the transaction fails, the entire transaction
        fails, and the database state is left unchanged. An atomic
        system must guarantee atomicity in each and every situation,
        including power failures, errors, and crashes.
        (via Wikipedia)

        .. seealso::

            :term:`ACID`

            http://en.wikipedia.org/wiki/Atomicity_(database_systems)

    consistency
        Consistency is one of the compoments of the :term:`ACID` model,
        and ensures that any transaction will
        bring the database from one valid state to another. Any data
        written to the database must be valid according to all defined
        rules, including but not limited to :term:`constraints`, cascades,
        triggers, and any combination thereof.
        (via Wikipedia)

        .. seealso::

            :term:`ACID`

            http://en.wikipedia.org/wiki/Consistency_(database_systems)

    isolation
    isolated
        The isolation property of the :term:`ACID` model
        ensures that the concurrent execution
        of transactions results in a system state that would be
        obtained if transactions were executed serially, i.e. one
        after the other. Each transaction must execute in total
        isolation i.e. if T1 and T2 execute concurrently then each
        should remain independent of the other.
        (via Wikipedia)

        .. seealso::

            :term:`ACID`

            http://en.wikipedia.org/wiki/Isolation_(database_systems)

    durability
        Durability is a property of the :term:`ACID` model
        which means that once a transaction has been committed,
        it will remain so, even in the event of power loss, crashes,
        or errors. In a relational database, for instance, once a
        group of SQL statements execute, the results need to be stored
        permanently (even if the database crashes immediately
        thereafter).
        (via Wikipedia)

        .. seealso::

            :term:`ACID`

            http://en.wikipedia.org/wiki/Durability_(database_systems)

    RETURNING
        This is a non-SQL standard clause provided in various forms by
        certain backends, which provides the service of returning a result
        set upon execution of an INSERT, UPDATE or DELETE statement.  Any set
        of columns from the matched rows can be returned, as though they were
        produced from a SELECT statement.

        The RETURNING clause provides both a dramatic performance boost to
        common update/select scenarios, including retrieval of inline- or
        default- generated primary key values and defaults at the moment they
        were created, as well as a way to get at server-generated
        default values in an atomic way.

        An example of RETURNING, idiomatic to Postgresql, looks like::

            INSERT INTO user_account (name) VALUES ('new name') RETURNING id, timestamp

        Above, the INSERT statement will provide upon execution a result set
        which includes the values of the columns ``user_account.id`` and
        ``user_account.timestamp``, which above should have been generated as default
        values as they are not included otherwise (but note any series of columns
        or SQL expressions can be placed into RETURNING, not just default-value columns).

        The backends that currently support
        RETURNING or a similar construct are Postgresql, SQL Server, Oracle,
        and Firebird.    The Postgresql and Firebird implementations are generally
        full featured, whereas the implementations of SQL Server and Oracle
        have caveats. On SQL Server, the clause is known as "OUTPUT INSERTED"
        for INSERT and UPDATE statements and "OUTPUT DELETED" for DELETE statements;
        the key caveat is that triggers are not supported in conjunction with this
        keyword.  On Oracle, it is known as "RETURNING...INTO", and requires that the
        value be placed into an OUT paramter, meaning not only is the syntax awkward,
        but it can also only be used for one row at a time.

        SQLAlchemy's :meth:`.UpdateBase.returning` system provides a layer of abstraction
        on top of the RETURNING systems of these backends to provide a consistent
        interface for returning columns.  The ORM also includes many optimizations
        that make use of RETURNING when available.

