>>> conn = engine.connect()
>>> conn #doctest: +ELLIPSIS
- <sqlalchemy.engine.Connection object at 0x...>
+ <sqlalchemy.engine.base.Connection object at 0x...>
-The :class:`~sqlalchemy.engine.Connection` object represents an actively
+The :class:`~sqlalchemy.engine.base.Connection` object represents an actively
checked out DBAPI connection resource. Lets feed it our
:class:`~sqlalchemy.sql.expression.Insert` object and see what happens:
So the INSERT statement was now issued to the database. Although we got
positional "qmark" bind parameters instead of "named" bind parameters in the
output. How come ? Because when executed, the
-:class:`~sqlalchemy.engine.Connection` used the SQLite **dialect** to
+:class:`~sqlalchemy.engine.base.Connection` used the SQLite **dialect** to
help generate the statement; when we use the ``str()`` function, the statement
isn't aware of this dialect, and falls back onto a default which uses named
parameters. We can view this manually as follows:
'INSERT INTO users (name, fullname) VALUES (?, ?)'
What about the ``result`` variable we got when we called ``execute()`` ? As
-the SQLAlchemy :class:`~sqlalchemy.engine.Connection` object references a
+the SQLAlchemy :class:`~sqlalchemy.engine.base.Connection` object references a
DBAPI connection, the result, known as a
-:class:`~sqlalchemy.engine.ResultProxy` object, is analogous to the DBAPI
+:class:`~sqlalchemy.engine.result.ResultProxy` object, is analogous to the DBAPI
cursor object. In the case of an INSERT, we can get important information from
it, such as the primary key values which were generated from our statement:
various behaviors of expression language constructs. In the usual case, an
:class:`~sqlalchemy.sql.expression.Insert` statement is usually compiled
against the parameters sent to the ``execute()`` method on
-:class:`~sqlalchemy.engine.Connection`, so that there's no need to use
+:class:`~sqlalchemy.engine.base.Connection`, so that there's no need to use
the ``values`` keyword with :class:`~sqlalchemy.sql.expression.Insert`. Lets
create a generic :class:`~sqlalchemy.sql.expression.Insert` statement again
and use it in the "normal" way:
{opensql}INSERT INTO users (id, name, fullname) VALUES (?, ?, ?)
(2, 'wendy', 'Wendy Williams')
COMMIT
- {stop}<sqlalchemy.engine.ResultProxy object at 0x...>
+ {stop}<sqlalchemy.engine.result.ResultProxy object at 0x...>
Above, because we specified all three columns in the the ``execute()`` method,
-the compiled :class:`~sqlalchemy.sql.expression.Insert` included all three
-columns. The :class:`~sqlalchemy.sql.expression.Insert` statement is compiled
+the compiled :class:`~.expression.Insert` included all three
+columns. The :class:`~.expression.Insert` statement is compiled
at execution time based on the parameters we specified; if we specified fewer
-parameters, the :class:`~sqlalchemy.sql.expression.Insert` would have fewer
+parameters, the :class:`~.expression.Insert` would have fewer
entries in its VALUES clause.
To issue many inserts using DBAPI's ``executemany()`` method, we can send in a
{opensql}INSERT INTO addresses (user_id, email_address) VALUES (?, ?)
((1, 'jack@yahoo.com'), (1, 'jack@msn.com'), (2, 'www@www.org'), (2, 'wendy@aol.com'))
COMMIT
- {stop}<sqlalchemy.engine.ResultProxy object at 0x...>
+ {stop}<sqlalchemy.engine.result.ResultProxy object at 0x...>
Above, we again relied upon SQLite's automatic generation of primary key
identifiers for each ``addresses`` row.
within the COLUMNS clause of the select, and then executing. SQLAlchemy
expanded the ``users`` table into the set of each of its columns, and also
generated a FROM clause for us. The result returned is again a
-:class:`~sqlalchemy.engine.ResultProxy` object, which acts much like a
+:class:`~sqlalchemy.engine.result.ResultProxy` object, which acts much like a
DBAPI cursor, including methods such as
-:func:`~sqlalchemy.engine.ResultProxy.fetchone` and
-:func:`~sqlalchemy.engine.ResultProxy.fetchall`. The easiest way to get
+:func:`~sqlalchemy.engine.result.ResultProxy.fetchone` and
+:func:`~sqlalchemy.engine.result.ResultProxy.fetchall`. The easiest way to get
rows from it is to just iterate:
.. sourcecode:: pycon+sql
... print row
(1, u'jack', u'Jack Jones')
(2, u'wendy', u'Wendy Williams')
- (3, u'fred', u'Fred Flintstone')
- (4, u'mary', u'Mary Contrary')
Above, we see that printing each row produces a simple tuple-like result. We
have more options at accessing the data in each row. One very common way is
()
{stop}name: jack ; fullname: Jack Jones
name: wendy ; fullname: Wendy Williams
- name: fred ; fullname: Fred Flintstone
- name: mary ; fullname: Mary Contrary
Result sets which have pending rows remaining should be explicitly closed
before discarding. While the cursor and connection resources referenced by the
-:class:`~sqlalchemy.engine.ResultProxy` will be respectively closed and
+:class:`~sqlalchemy.engine.result.ResultProxy` will be respectively closed and
returned to the connection pool when the object is garbage collected, it's
better to make it explicit as some database APIs are very picky about such
things:
... print row
(u'jack', u'Jack Jones')
(u'wendy', u'Wendy Williams')
- (u'fred', u'Fred Flintstone')
- (u'mary', u'Mary Contrary')
Lets observe something interesting about the FROM clause. Whereas the
generated statement contains two distinct sections, a "SELECT columns" part
(2, u'wendy', u'Wendy Williams', 2, 1, u'jack@msn.com')
(2, u'wendy', u'Wendy Williams', 3, 2, u'www@www.org')
(2, u'wendy', u'Wendy Williams', 4, 2, u'wendy@aol.com')
- (3, u'fred', u'Fred Flintstone', 1, 1, u'jack@yahoo.com')
- (3, u'fred', u'Fred Flintstone', 2, 1, u'jack@msn.com')
- (3, u'fred', u'Fred Flintstone', 3, 2, u'www@www.org')
- (3, u'fred', u'Fred Flintstone', 4, 2, u'wendy@aol.com')
- (4, u'mary', u'Mary Contrary', 1, 1, u'jack@yahoo.com')
- (4, u'mary', u'Mary Contrary', 2, 1, u'jack@msn.com')
- (4, u'mary', u'Mary Contrary', 3, 2, u'www@www.org')
- (4, u'mary', u'Mary Contrary', 4, 2, u'wendy@aol.com')
It placed **both** tables into the FROM clause. But also, it made a real mess.
Those who are familiar with SQL joins know that this is a **Cartesian
product**; each row from the ``users`` table is produced against each row from
the ``addresses`` table. So to put some sanity into this statement, we need a
-WHERE clause. Which brings us to the second argument of :func:`.select`:
+WHERE clause. We do that using :meth:`.Select.where`:
.. sourcecode:: pycon+sql
- >>> s = select([users, addresses], users.c.id==addresses.c.user_id)
+ >>> s = select([users, addresses]).where(users.c.id == addresses.c.user_id)
{sql}>>> for row in conn.execute(s):
... print row # doctest: +NORMALIZE_WHITESPACE
- SELECT users.id, users.name, users.fullname, addresses.id, addresses.user_id, addresses.email_address
+ SELECT users.id, users.name, users.fullname, addresses.id,
+ addresses.user_id, addresses.email_address
FROM users, addresses
WHERE users.id = addresses.user_id
()
``addresses`` rows made sense. But let's look at that expression? It's using
just a Python equality operator between two different
:class:`~sqlalchemy.schema.Column` objects. It should be clear that something
-is up. Saying ``1==1`` produces ``True``, and ``1==2`` produces ``False``, not
+is up. Saying ``1 == 1`` produces ``True``, and ``1 == 2`` produces ``False``, not
a WHERE clause. So lets see exactly what that expression is doing:
.. sourcecode:: pycon+sql
- >>> users.c.id==addresses.c.user_id #doctest: +ELLIPSIS
+ >>> users.c.id == addresses.c.user_id #doctest: +ELLIPSIS
<sqlalchemy.sql.expression.BinaryExpression object at 0x...>
Wow, surprise ! This is neither a ``True`` nor a ``False``. Well what is it ?
.. sourcecode:: pycon+sql
- >>> str(users.c.id==addresses.c.user_id)
+ >>> str(users.c.id == addresses.c.user_id)
'users.id = addresses.user_id'
As you can see, the ``==`` operator is producing an object that is very much
-like the :class:`~sqlalchemy.sql.expression.Insert` and :func:`.select`
+like the :class:`~.expression.Insert` and :func:`.select`
objects we've made so far, thanks to Python's ``__eq__()`` builtin; you call
``str()`` on it and it produces SQL. By now, one can see that everything we
are working with is ultimately the same type of object. SQLAlchemy terms the
-base class of all of these expressions as ``sqlalchemy.sql.ClauseElement``.
+base class of all of these expressions as :class:`~.expression.ColumnElement`.
Operators
==========
.. sourcecode:: pycon+sql
- >>> print users.c.id==addresses.c.user_id
+ >>> print users.c.id == addresses.c.user_id
users.id = addresses.user_id
If we use a literal value (a literal meaning, not a SQLAlchemy clause object),
.. sourcecode:: pycon+sql
- >>> print users.c.id==7
+ >>> print users.c.id == 7
users.id = :id_1
-The ``7`` literal is embedded in
-:class:`~sqlalchemy.sql.expression.ClauseElement`; we can use the same trick
+The ``7`` literal is embedded the resulting
+:class:`~.expression.ColumnElement`; we can use the same trick
we did with the :class:`~sqlalchemy.sql.expression.Insert` object to see it:
.. sourcecode:: pycon+sql
- >>> (users.c.id==7).compile().params
+ >>> (users.c.id == 7).compile().params
{u'id_1': 7}
Most Python operators, as it turns out, produce a SQL expression here, like
>>> print users.c.id + addresses.c.id
users.id + addresses.id
-Interestingly, the type of the :class:`~sqlalchemy.schema.Column` is important
-! If we use ``+`` with two string based columns (recall we put types like
+Interestingly, the type of the :class:`~sqlalchemy.schema.Column` is important!
+If we use ``+`` with two string based columns (recall we put types like
:class:`~sqlalchemy.types.Integer` and :class:`~sqlalchemy.types.String` on
our :class:`~sqlalchemy.schema.Column` objects at the beginning), we get
something different:
.. sourcecode:: pycon+sql
- >>> print (users.c.name + users.c.fullname).compile(bind=create_engine('mysql://'))
+ >>> print (users.c.name + users.c.fullname).\
+ ... compile(bind=create_engine('mysql://'))
concat(users.name, users.fullname)
The above illustrates the SQL that's generated for an
We'd like to show off some of our operators inside of :func:`.select`
constructs. But we need to lump them together a little more, so let's first
introduce some conjunctions. Conjunctions are those little words like AND and
-OR that put things together. We'll also hit upon NOT. AND, OR and NOT can work
+OR that put things together. We'll also hit upon NOT. :func:`.and_`, :func:`.or_`,
+and :func:`.not_` can work
from the corresponding functions SQLAlchemy provides (notice we also throw in
-a LIKE):
+a :meth:`~.ColumnOperators.like`):
.. sourcecode:: pycon+sql
>>> from sqlalchemy.sql import and_, or_, not_
- >>> print and_(users.c.name.like('j%'), users.c.id==addresses.c.user_id, #doctest: +NORMALIZE_WHITESPACE
- ... or_(addresses.c.email_address=='wendy@aol.com', addresses.c.email_address=='jack@yahoo.com'),
- ... not_(users.c.id>5))
+ >>> print and_(
+ ... users.c.name.like('j%'),
+ ... users.c.id == addresses.c.user_id, #doctest: +NORMALIZE_WHITESPACE
+ ... or_(
+ ... addresses.c.email_address == 'wendy@aol.com',
+ ... addresses.c.email_address == 'jack@yahoo.com'
+ ... ),
+ ... not_(users.c.id > 5)
+ ... )
users.name LIKE :name_1 AND users.id = addresses.user_id AND
- (addresses.email_address = :email_address_1 OR addresses.email_address = :email_address_2)
+ (addresses.email_address = :email_address_1
+ OR addresses.email_address = :email_address_2)
AND users.id <= :id_1
And you can also use the re-jiggered bitwise AND, OR and NOT operators,
.. sourcecode:: pycon+sql
- >>> print users.c.name.like('j%') & (users.c.id==addresses.c.user_id) & \
- ... ((addresses.c.email_address=='wendy@aol.com') | (addresses.c.email_address=='jack@yahoo.com')) \
+ >>> print users.c.name.like('j%') & (users.c.id == addresses.c.user_id) & \
+ ... (
+ ... (addresses.c.email_address == 'wendy@aol.com') | \
+ ... (addresses.c.email_address == 'jack@yahoo.com')
+ ... ) \
... & ~(users.c.id>5) # doctest: +NORMALIZE_WHITESPACE
users.name LIKE :name_1 AND users.id = addresses.user_id AND
- (addresses.email_address = :email_address_1 OR addresses.email_address = :email_address_2)
+ (addresses.email_address = :email_address_1
+ OR addresses.email_address = :email_address_2)
AND users.id <= :id_1
So with all of this vocabulary, let's select all users who have an email
address at AOL or MSN, whose name starts with a letter between "m" and "z",
and we'll also generate a column containing their full name combined with
their email address. We will add two new constructs to this statement,
-``between()`` and ``label()``. ``between()`` produces a BETWEEN clause, and
-``label()`` is used in a column expression to produce labels using the ``AS``
+:meth:`~.ColumnOperators.between` and :meth:`~.ColumnElement.label`.
+:meth:`~.ColumnOperators.between` produces a BETWEEN clause, and
+:meth:`~.ColumnElement.label` is used in a column expression to produce labels using the ``AS``
keyword; it's recommended when selecting from expressions that otherwise would
not have a name:
.. sourcecode:: pycon+sql
- >>> s = select([(users.c.fullname + ", " + addresses.c.email_address).label('title')],
- ... and_(
- ... users.c.id==addresses.c.user_id,
- ... users.c.name.between('m', 'z'),
- ... or_(
- ... addresses.c.email_address.like('%@aol.com'),
- ... addresses.c.email_address.like('%@msn.com')
+ >>> s = select([(users.c.fullname +
+ ... ", " + addresses.c.email_address).
+ ... label('title')]).\
+ ... where(
+ ... and_(
+ ... users.c.id == addresses.c.user_id,
+ ... users.c.name.between('m', 'z'),
+ ... or_(
+ ... addresses.c.email_address.like('%@aol.com'),
+ ... addresses.c.email_address.like('%@msn.com')
+ ... )
... )
... )
- ... )
>>> print conn.execute(s).fetchall() #doctest: +NORMALIZE_WHITESPACE
SELECT users.fullname || ? || addresses.email_address AS title
FROM users, addresses
clause, the where clause, and also some other elements which we haven't
covered yet, which include ORDER BY, GROUP BY, and HAVING.
+A shortcut to using :func:`.and_` is to chain together multiple
+:meth:`~.Select.where` clauses. The above can also be written as:
+
+.. sourcecode:: pycon+sql
+
+ >>> s = select([(users.c.fullname +
+ ... ", " + addresses.c.email_address).
+ ... label('title')]).\
+ ... where(users.c.id == addresses.c.user_id).\
+ ... where(users.c.name.between('m', 'z')).\
+ ... where(
+ ... or_(
+ ... addresses.c.email_address.like('%@aol.com'),
+ ... addresses.c.email_address.like('%@msn.com')
+ ... )
+ ... )
+ >>> print conn.execute(s).fetchall() #doctest: +NORMALIZE_WHITESPACE
+ SELECT users.fullname || ? || addresses.email_address AS title
+ FROM users, addresses
+ WHERE users.id = addresses.user_id AND users.name BETWEEN ? AND ? AND
+ (addresses.email_address LIKE ? OR addresses.email_address LIKE ?)
+ (', ', 'm', 'z', '%@aol.com', '%@msn.com')
+ [(u'Wendy Williams, wendy@aol.com',)]
+
+The way that we can build up a :func:`.select` construct through successive
+method calls is called :term:`method chaining`.
+
.. _sqlexpression_text:
Using Text
Our last example really became a handful to type. Going from what one
understands to be a textual SQL expression into a Python construct which
groups components together in a programmatic style can be hard. That's why
-SQLAlchemy lets you just use strings too. The ``text()`` construct represents
-any textual statement. To use bind parameters with ``text()``, always use the
-named colon format. Such as below, we create a ``text()`` and execute it,
-feeding in the bind parameters to the ``execute()`` method:
+SQLAlchemy lets you just use strings too. The :func:`~.expression.text` construct represents
+any textual statement, in a backend-agnostic way.
+To use bind parameters with :func:`~.expression.text`, always use the
+named colon format. Such as below, we create a :func:`~.expression.text` and execute it,
+feeding in the bind parameters to the :meth:`~.Connection.execute` method:
.. sourcecode:: pycon+sql
>>> from sqlalchemy.sql import text
- >>> s = text("""SELECT users.fullname || ', ' || addresses.email_address AS title
- ... FROM users, addresses
- ... WHERE users.id = addresses.user_id AND users.name BETWEEN :x AND :y AND
- ... (addresses.email_address LIKE :e1 OR addresses.email_address LIKE :e2)
- ... """)
+ >>> s = text(
+ ... "SELECT users.fullname || ', ' || addresses.email_address AS title "
+ ... "FROM users, addresses "
+ ... "WHERE users.id = addresses.user_id "
+ ... "AND users.name BETWEEN :x AND :y "
+ ... "AND (addresses.email_address LIKE :e1 "
+ ... "OR addresses.email_address LIKE :e2)")
{sql}>>> print conn.execute(s, x='m', y='z', e1='%@aol.com', e2='%@msn.com').fetchall() # doctest:+NORMALIZE_WHITESPACE
SELECT users.fullname || ', ' || addresses.email_address AS title
FROM users, addresses
('m', 'z', '%@aol.com', '%@msn.com')
{stop}[(u'Wendy Williams, wendy@aol.com',)]
-To gain a "hybrid" approach, the `select()` construct accepts strings for most
+To gain a "hybrid" approach, the :func:`.select` construct accepts strings for most
of its arguments. Below we combine the usage of strings with our constructed
:func:`.select` object, by using the :func:`.select` object to structure the
statement, and strings to provide all the content within the structure. For
this example, SQLAlchemy is not given any :class:`~sqlalchemy.schema.Column`
or :class:`~sqlalchemy.schema.Table` objects in any of its expressions, so it
-cannot generate a FROM clause. So we also give it the ``from_obj`` keyword
-argument, which is a list of ``ClauseElements`` (or strings) to be placed
-within the FROM clause:
-
-.. sourcecode:: pycon+sql
-
- >>> s = select(["users.fullname || ', ' || addresses.email_address AS title"],
- ... and_(
- ... "users.id = addresses.user_id",
- ... "users.name BETWEEN 'm' AND 'z'",
- ... "(addresses.email_address LIKE :x OR addresses.email_address LIKE :y)"
- ... ),
- ... from_obj=['users', 'addresses']
- ... )
+cannot generate a FROM clause. So we also use the :meth:`~.Select.select_from`
+method, which accepts a :class:`.FromClause` or string expression
+to be placed within the FROM clause:
+
+.. sourcecode:: pycon+sql
+
+ >>> s = select([
+ ... "users.fullname || ', ' || addresses.email_address AS title"
+ ... ]).\
+ ... where(
+ ... and_(
+ ... "users.id = addresses.user_id",
+ ... "users.name BETWEEN 'm' AND 'z'",
+ ... "(addresses.email_address LIKE :x OR addresses.email_address LIKE :y)"
+ ... )
+ ... ).select_from('users, addresses')
{sql}>>> print conn.execute(s, x='%@aol.com', y='%@msn.com').fetchall() #doctest: +NORMALIZE_WHITESPACE
SELECT users.fullname || ', ' || addresses.email_address AS title
FROM users, addresses
- WHERE users.id = addresses.user_id AND users.name BETWEEN 'm' AND 'z' AND (addresses.email_address LIKE ? OR addresses.email_address LIKE ?)
+ WHERE users.id = addresses.user_id AND users.name BETWEEN 'm' AND 'z'
+ AND (addresses.email_address LIKE ? OR addresses.email_address LIKE ?)
('%@aol.com', '%@msn.com')
{stop}[(u'Wendy Williams, wendy@aol.com',)]
datatypes in use; for example, if our bind parameters required UTF-8 encoding
before going in, or conversion from a Python ``datetime`` into a string (as is
required with SQLite), we would have to add extra information to our
-``text()`` construct. Similar issues arise on the result set side, where
+:func:`~.expression.text` construct. Similar issues arise on the result set side, where
SQLAlchemy also performs type-specific data conversion in some cases; still
-more information can be added to ``text()`` to work around this. But what we
+more information can be added to :func:`~.expression.text` to work around this. But what we
really lose from our statement is the ability to manipulate it, transform it,
and analyze it. These features are critical when using the ORM, which makes
heavy usage of relational transformations. To show off what we mean, we'll
>>> a1 = addresses.alias()
>>> a2 = addresses.alias()
- >>> s = select([users], and_(
- ... users.c.id==a1.c.user_id,
- ... users.c.id==a2.c.user_id,
- ... a1.c.email_address=='jack@msn.com',
- ... a2.c.email_address=='jack@yahoo.com'
- ... ))
+ >>> s = select([users]).\
+ ... where(and_(
+ ... users.c.id == a1.c.user_id,
+ ... users.c.id == a2.c.user_id,
+ ... a1.c.email_address == 'jack@msn.com',
+ ... a2.c.email_address == 'jack@yahoo.com'
+ ... ))
{sql}>>> print conn.execute(s).fetchall() # doctest: +NORMALIZE_WHITESPACE
SELECT users.id, users.name, users.fullname
FROM users, addresses AS addresses_1, addresses AS addresses_2
- WHERE users.id = addresses_1.user_id AND users.id = addresses_2.user_id AND addresses_1.email_address = ? AND addresses_2.email_address = ?
+ WHERE users.id = addresses_1.user_id
+ AND users.id = addresses_2.user_id
+ AND addresses_1.email_address = ?
+ AND addresses_2.email_address = ?
('jack@msn.com', 'jack@yahoo.com')
{stop}[(1, u'jack', u'Jack Jones')]
.. sourcecode:: pycon+sql
>>> a1 = s.correlate(None).alias()
- >>> s = select([users.c.name], users.c.id==a1.c.id)
+ >>> s = select([users.c.name]).where(users.c.id == a1.c.id)
{sql}>>> print conn.execute(s).fetchall() # doctest: +NORMALIZE_WHITESPACE
SELECT users.name
- FROM users, (SELECT users.id AS id, users.name AS name, users.fullname AS fullname
- FROM users, addresses AS addresses_1, addresses AS addresses_2
- WHERE users.id = addresses_1.user_id AND users.id = addresses_2.user_id AND addresses_1.email_address = ? AND addresses_2.email_address = ?) AS anon_1
+ FROM users,
+ (SELECT users.id AS id, users.name AS name, users.fullname AS fullname
+ FROM users, addresses AS addresses_1, addresses AS addresses_2
+ WHERE users.id = addresses_1.user_id AND users.id = addresses_2.user_id
+ AND addresses_1.email_address = ?
+ AND addresses_2.email_address = ?) AS anon_1
WHERE users.id = anon_1.id
('jack@msn.com', 'jack@yahoo.com')
{stop}[(u'jack',)]
cornerstone of the SELECT is the JOIN expression. We've already been doing
joins in our examples, by just placing two tables in either the columns clause
or the where clause of the :func:`.select` construct. But if we want to make a
-real "JOIN" or "OUTERJOIN" construct, we use the ``join()`` and
-``outerjoin()`` methods, most commonly accessed from the left table in the
+real "JOIN" or "OUTERJOIN" construct, we use the :meth:`~.FromClause.join` and
+:meth:`~.FromClause.outerjoin` methods, most commonly accessed from the left table in the
join:
.. sourcecode:: pycon+sql
.. sourcecode:: pycon+sql
- >>> print users.join(addresses, addresses.c.email_address.like(users.c.name + '%'))
- users JOIN addresses ON addresses.email_address LIKE users.name || :name_1
+ >>> print users.join(addresses,
+ ... addresses.c.email_address.like(users.c.name + '%')
+ ... )
+ users JOIN addresses ON addresses.email_address LIKE (users.name || :name_1)
When we create a :func:`.select` construct, SQLAlchemy looks around at the
tables we've mentioned and then places them in the FROM clause of the
statement. When we use JOINs however, we know what FROM clause we want, so
-here we make usage of the ``from_obj`` keyword argument:
+here we make use of the :meth:`~.Select.select_from` method:
.. sourcecode:: pycon+sql
- >>> s = select([users.c.fullname], from_obj=[
- ... users.join(addresses, addresses.c.email_address.like(users.c.name + '%'))
- ... ])
+ >>> s = select([users.c.fullname]).select_from(
+ ... users.join(addresses,
+ ... addresses.c.email_address.like(users.c.name + '%'))
+ ... )
{sql}>>> print conn.execute(s).fetchall() # doctest: +NORMALIZE_WHITESPACE
SELECT users.fullname
- FROM users JOIN addresses ON addresses.email_address LIKE users.name || ?
+ FROM users JOIN addresses ON addresses.email_address LIKE (users.name || ?)
('%',)
{stop}[(u'Jack Jones',), (u'Jack Jones',), (u'Wendy Williams',)]
-The ``outerjoin()`` function just creates ``LEFT OUTER JOIN`` constructs. It's
-used just like ``join()``:
+The :meth:`~.FromClause.outerjoin` method creates ``LEFT OUTER JOIN`` constructs,
+and is used in the same way as :meth:`~.FromClause.join`:
.. sourcecode:: pycon+sql
- >>> s = select([users.c.fullname], from_obj=[users.outerjoin(addresses)])
+ >>> s = select([users.c.fullname]).select_from(users.outerjoin(addresses))
>>> print s # doctest: +NORMALIZE_WHITESPACE
SELECT users.fullname
- FROM users LEFT OUTER JOIN addresses ON users.id = addresses.user_id
+ FROM users
+ LEFT OUTER JOIN addresses ON users.id = addresses.user_id
That's the output ``outerjoin()`` produces, unless, of course, you're stuck in
a gig using Oracle prior to version 9, and you've set up your engine (which
If you don't know what that SQL means, don't worry ! The secret tribe of
Oracle DBAs don't want their black magic being found out ;).
-Intro to Generative Selects
-================================================
-
-We've now gained the ability to construct very sophisticated statements. We
-can use all kinds of operators, table constructs, text, joins, and aliases.
-The point of all of this, as mentioned earlier, is not that it's an "easier"
-or "better" way to write SQL than just writing a SQL statement yourself; the
-point is that it's better for writing *programmatically generated* SQL which
-can be morphed and adapted as needed in automated scenarios.
-
-To support this, the :func:`.select` construct we've been working with
-supports piecemeal construction, in addition to the "all at once" method we've
-been doing. Suppose you're writing a search function, which receives criterion
-and then must construct a select from it. To accomplish this, upon each
-criterion encountered, you apply "generative" criterion to an existing
-:func:`.select` construct with new elements, one at a time. We start with a
-basic :func:`.select` constructed with the shortcut method available on the
-``users`` table:
-
-.. sourcecode:: pycon+sql
-
- >>> query = users.select()
- >>> print query # doctest: +NORMALIZE_WHITESPACE
- SELECT users.id, users.name, users.fullname
- FROM users
-
-We encounter search criterion of "name='jack'". So we apply WHERE criterion
-stating such:
-
-.. sourcecode:: pycon+sql
-
- >>> query = query.where(users.c.name=='jack')
-
-Next, we encounter that they'd like the results in descending order by full
-name. We apply ORDER BY, using an extra modifier ``desc``:
-
-.. sourcecode:: pycon+sql
-
- >>> query = query.order_by(users.c.fullname.desc())
-
-We also come across that they'd like only users who have an address at MSN. A
-quick way to tack this on is by using an EXISTS clause, which we correlate to
-the ``users`` table in the enclosing SELECT:
-
-.. sourcecode:: pycon+sql
-
- >>> from sqlalchemy.sql import exists
- >>> query = query.where(
- ... exists([addresses.c.id],
- ... and_(addresses.c.user_id==users.c.id, addresses.c.email_address.like('%@msn.com'))
- ... ).correlate(users))
-
-And finally, the application also wants to see the listing of email addresses
-at once; so to save queries, we outerjoin the ``addresses`` table (using an
-outer join so that users with no addresses come back as well; since we're
-programmatic, we might not have kept track that we used an EXISTS clause
-against the ``addresses`` table too...). Additionally, since the ``users`` and
-``addresses`` table both have a column named ``id``, let's isolate their names
-from each other in the COLUMNS clause by using labels:
-
-.. sourcecode:: pycon+sql
-
- >>> query = query.column(addresses).select_from(users.outerjoin(addresses)).apply_labels()
-
-Let's bake for .0001 seconds and see what rises:
-
-.. sourcecode:: pycon+sql
-
- >>> conn.execute(query).fetchall() # doctest: +NORMALIZE_WHITESPACE
- {opensql}SELECT users.id AS users_id, users.name AS users_name, users.fullname AS users_fullname, addresses.id AS addresses_id, addresses.user_id AS addresses_user_id, addresses.email_address AS addresses_email_address
- FROM users LEFT OUTER JOIN addresses ON users.id = addresses.user_id
- WHERE users.name = ? AND (EXISTS (SELECT addresses.id
- FROM addresses
- WHERE addresses.user_id = users.id AND addresses.email_address LIKE ?)) ORDER BY users.fullname DESC
- ('jack', '%@msn.com')
- {stop}[(1, u'jack', u'Jack Jones', 1, 1, u'jack@yahoo.com'), (1, u'jack', u'Jack Jones', 2, 1, u'jack@msn.com')]
-
-The generative approach is about starting small, adding one thing at a time,
-to arrive with a full statement.
-
-Transforming a Statement
-------------------------
-
-We've seen how methods like :meth:`.Select.where` and :meth:`.SelectBase.order_by` are
-part of the so-called *Generative* family of methods on the :func:`.select` construct,
-where one :func:`.select` copies itself to return a new one with modifications.
-SQL constructs also support another form of generative behavior which is
-the *transformation*. This is an advanced technique that most core applications
-won't use directly; however, it is a system which the ORM relies on heavily,
-and can be useful for any system that deals with generalized behavior of Core SQL
-constructs.
-
-Using a transformation we can take our ``users``/``addresses`` query and replace
-all occurrences of ``addresses`` with an alias of itself. That is, anywhere
-that ``addresses`` is referred to in the original query, the new query will
-refer to ``addresses_1``, which is selected as ``addresses AS addresses_1``.
-The :meth:`.FromClause.replace_selectable` method can achieve this:
-
-.. sourcecode:: pycon+sql
-
- >>> a1 = addresses.alias()
- >>> query = query.replace_selectable(addresses, a1)
- >>> print query # doctest: +NORMALIZE_WHITESPACE
- {opensql}SELECT users.id AS users_id, users.name AS users_name, users.fullname AS users_fullname, addresses_1.id AS addresses_1_id, addresses_1.user_id AS addresses_1_user_id, addresses_1.email_address AS addresses_1_email_address
- FROM users LEFT OUTER JOIN addresses AS addresses_1 ON users.id = addresses_1.user_id
- WHERE users.name = :name_1 AND (EXISTS (SELECT addresses_1.id
- FROM addresses AS addresses_1
- WHERE addresses_1.user_id = users.id AND addresses_1.email_address LIKE :email_address_1)) ORDER BY users.fullname DESC
-
-For a query such as the above, we can access the columns referred
-to by the ``a1`` alias in a result set using the :class:`.Column` objects
-present directly on ``a1``:
-
-.. sourcecode:: pycon+sql
-
- {sql}>>> for row in conn.execute(query):
- ... print "Name:", row[users.c.name], "; Email Address", row[a1.c.email_address] # doctest: +NORMALIZE_WHITESPACE
- SELECT users.id AS users_id, users.name AS users_name, users.fullname AS users_fullname, addresses_1.id AS addresses_1_id, addresses_1.user_id AS addresses_1_user_id, addresses_1.email_address AS addresses_1_email_address
- FROM users LEFT OUTER JOIN addresses AS addresses_1 ON users.id = addresses_1.user_id
- WHERE users.name = ? AND (EXISTS (SELECT addresses_1.id
- FROM addresses AS addresses_1
- WHERE addresses_1.user_id = users.id AND addresses_1.email_address LIKE ?)) ORDER BY users.fullname DESC
- ('jack', '%@msn.com')
- {stop}Name: jack ; Email Address jack@yahoo.com
- Name: jack ; Email Address jack@msn.com
-
Everything Else
================
.. sourcecode:: pycon+sql
>>> from sqlalchemy.sql import bindparam
- >>> s = users.select(users.c.name==bindparam('username'))
+ >>> s = users.select(users.c.name == bindparam('username'))
{sql}>>> conn.execute(s, username='wendy').fetchall() # doctest: +NORMALIZE_WHITESPACE
SELECT users.id, users.name, users.fullname
FROM users
{sql}>>> conn.execute(s, username='wendy').fetchall() # doctest: +NORMALIZE_WHITESPACE
SELECT users.id, users.name, users.fullname
FROM users
- WHERE users.name LIKE ? || '%'
+ WHERE users.name LIKE (? || '%')
('wendy',)
{stop}[(2, u'wendy', u'Wendy Williams')]
.. sourcecode:: pycon+sql
- >>> s = select([users, addresses],
- ... users.c.name.like(bindparam('name', type_=String) + text("'%'")) |
- ... addresses.c.email_address.like(bindparam('name', type_=String) + text("'@%'")),
- ... from_obj=[users.outerjoin(addresses)])
+ >>> s = select([users, addresses]).\
+ ... where(
+ ... or_(
+ ... users.c.name.like(
+ ... bindparam('name', type_=String) + text("'%'")),
+ ... addresses.c.email_address.like(
+ ... bindparam('name', type_=String) + text("'@%'"))
+ ... )
+ ... ).\
+ ... select_from(users.outerjoin(addresses)).\
+ ... order_by(addresses.c.id)
{sql}>>> conn.execute(s, name='jack').fetchall() # doctest: +NORMALIZE_WHITESPACE
- SELECT users.id, users.name, users.fullname, addresses.id, addresses.user_id, addresses.email_address
+ SELECT users.id, users.name, users.fullname, addresses.id,
+ addresses.user_id, addresses.email_address
FROM users LEFT OUTER JOIN addresses ON users.id = addresses.user_id
- WHERE users.name LIKE ? || '%' OR addresses.email_address LIKE ? || '@%'
+ WHERE users.name LIKE (? || '%') OR addresses.email_address LIKE (? || '@%')
+ ORDER BY addresses.id
('jack', 'jack')
{stop}[(1, u'jack', u'Jack Jones', 1, 1, u'jack@yahoo.com'), (1, u'jack', u'Jack Jones', 2, 1, u'jack@msn.com')]
>>> from sqlalchemy.sql import union
>>> u = union(
- ... addresses.select(addresses.c.email_address=='foo@bar.com'),
+ ... addresses.select(addresses.c.email_address == 'foo@bar.com'),
... addresses.select(addresses.c.email_address.like('%@yahoo.com')),
... ).order_by(addresses.c.email_address)
{sql}>>> print conn.execute(select([ # doctest: +NORMALIZE_WHITESPACE
... users.c.name,
- ... select([func.count(addresses.c.id)], users.c.id==addresses.c.user_id).as_scalar()
+ ... select([func.count(addresses.c.id)], users.c.id == addresses.c.user_id).as_scalar()
... ])).fetchall()
SELECT users.name, (SELECT count(addresses.id) AS count_1
FROM addresses
WHERE users.id = addresses.user_id) AS anon_1
FROM users
()
- {stop}[(u'jack', 2), (u'wendy', 2), (u'fred', 0), (u'mary', 0)]
+ {stop}[(u'jack', 2), (u'wendy', 2)]
Alternatively, applying a ``label()`` to a select evaluates it as a scalar as
well:
{sql}>>> print conn.execute(select([ # doctest: +NORMALIZE_WHITESPACE
... users.c.name,
- ... select([func.count(addresses.c.id)], users.c.id==addresses.c.user_id).label('address_count')
+ ... select([func.count(addresses.c.id)], users.c.id == addresses.c.user_id).label('address_count')
... ])).fetchall()
SELECT users.name, (SELECT count(addresses.id) AS count_1
FROM addresses
WHERE users.id = addresses.user_id) AS address_count
FROM users
()
- {stop}[(u'jack', 2), (u'wendy', 2), (u'fred', 0), (u'mary', 0)]
+ {stop}[(u'jack', 2), (u'wendy', 2)]
.. _correlated_subqueries:
of an enclosing query. To disable this, or to specify explicit FROM clauses to
be correlated, use ``correlate()``::
- >>> s = select([users.c.name], users.c.id==select([users.c.id]).correlate(None))
+ >>> s = select([users.c.name], users.c.id == select([users.c.id]).correlate(None))
>>> print s # doctest: +NORMALIZE_WHITESPACE
SELECT users.name
FROM users
FROM users)
>>> s = select([users.c.name, addresses.c.email_address], users.c.id==
- ... select([users.c.id], users.c.id==addresses.c.user_id).correlate(addresses)
+ ... select([users.c.id], users.c.id == addresses.c.user_id).correlate(addresses)
... )
>>> print s # doctest: +NORMALIZE_WHITESPACE
SELECT users.name, addresses.email_address
{sql}>>> print conn.execute(s).fetchall() # doctest: +NORMALIZE_WHITESPACE
SELECT addresses.id, addresses.user_id, addresses.email_address
FROM addresses
- LIMIT 1 OFFSET 1
- ()
+ LIMIT ? OFFSET ?
+ (1, 1)
{stop}[(2, 1, u'jack@msn.com')]
.. _inserts_and_updates:
>>> # change 'jack' to 'ed'
{sql}>>> conn.execute(users.update().
- ... where(users.c.name=='jack').
+ ... where(users.c.name == 'jack').
... values(name='ed')
... ) #doctest: +ELLIPSIS
UPDATE users SET name=? WHERE users.name = ?
('ed', 'jack')
COMMIT
- {stop}<sqlalchemy.engine.ResultProxy object at 0x...>
+ {stop}<sqlalchemy.engine.result.ResultProxy object at 0x...>
>>> # use bind parameters
>>> u = users.update().\
- ... where(users.c.name==bindparam('oldname')).\
+ ... where(users.c.name == bindparam('oldname')).\
... values(name=bindparam('newname'))
{sql}>>> conn.execute(u, oldname='jack', newname='ed') #doctest: +ELLIPSIS
UPDATE users SET name=? WHERE users.name = ?
('ed', 'jack')
COMMIT
- {stop}<sqlalchemy.engine.ResultProxy object at 0x...>
+ {stop}<sqlalchemy.engine.result.ResultProxy object at 0x...>
>>> # with binds, you can also update many rows at once
- {sql}>>> conn.execute(u,
+ {sql}>>> conn.execute(u, [
... {'oldname':'jack', 'newname':'ed'},
... {'oldname':'wendy', 'newname':'mary'},
... {'oldname':'jim', 'newname':'jake'},
- ... ) #doctest: +ELLIPSIS
+ ... ]) #doctest: +ELLIPSIS
UPDATE users SET name=? WHERE users.name = ?
- [('ed', 'jack'), ('mary', 'wendy'), ('jake', 'jim')]
+ (('ed', 'jack'), ('mary', 'wendy'), ('jake', 'jim'))
COMMIT
- {stop}<sqlalchemy.engine.ResultProxy object at 0x...>
+ {stop}<sqlalchemy.engine.result.ResultProxy object at 0x...>
>>> # update a column to an expression.:
{sql}>>> conn.execute(users.update().
UPDATE users SET fullname=(? || users.name)
('Fullname: ',)
COMMIT
- {stop}<sqlalchemy.engine.ResultProxy object at 0x...>
+ {stop}<sqlalchemy.engine.result.ResultProxy object at 0x...>
Correlated Updates
------------------
.. sourcecode:: pycon+sql
- >>> s = select([addresses.c.email_address], addresses.c.user_id==users.c.id).limit(1)
+ >>> s = select([addresses.c.email_address]).\
+ ... where(addresses.c.user_id == users.c.id).\
+ ... limit(1)
{sql}>>> conn.execute(users.update().values(fullname=s)) #doctest: +ELLIPSIS,+NORMALIZE_WHITESPACE
UPDATE users SET fullname=(SELECT addresses.email_address
- FROM addresses
- WHERE addresses.user_id = users.id
- LIMIT 1 OFFSET 0)
- ()
+ FROM addresses
+ WHERE addresses.user_id = users.id
+ LIMIT ? OFFSET ?)
+ (1, 0)
COMMIT
- {stop}<sqlalchemy.engine.ResultProxy object at 0x...>
+ {stop}<sqlalchemy.engine.result.ResultProxy object at 0x...>
Multiple Table Updates
----------------------
stmt = users.update().\
values(name='ed wood').\
- where(users.c.id==addresses.c.id).\
+ where(users.c.id == addresses.c.id).\
where(addresses.c.email_address.startswith('ed%'))
conn.execute(stmt)
users.c.name:'ed wood',
addresses.c.email_address:'ed.wood@foo.com'
}).\
- where(users.c.id==addresses.c.id).\
+ where(users.c.id == addresses.c.id).\
where(addresses.c.email_address.startswith('ed%'))
The tables are referenced explicitly in the SET clause::
DELETE FROM addresses
()
COMMIT
- {stop}<sqlalchemy.engine.ResultProxy object at 0x...>
+ {stop}<sqlalchemy.engine.result.ResultProxy object at 0x...>
{sql}>>> conn.execute(users.delete().where(users.c.name > 'm')) #doctest: +ELLIPSIS
DELETE FROM users WHERE users.name > ?
('m',)
COMMIT
- {stop}<sqlalchemy.engine.ResultProxy object at 0x...>
+ {stop}<sqlalchemy.engine.result.ResultProxy object at 0x...>
Further Reference
==================
projects / thirdparty / sqlalchemy / sqlalchemy.git / commitdiff
