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``````````
SQLBuilder
``````````
.. contents::
A number of variables from SQLBuilder are included with ``from
sqlobject import *`` -- see the `relevant SQLObject documentation`_
for more. Its functionality is also available through the special
``q`` attribute of `SQLObject` classes.
.. _`relevant SQLObject documentation`: SQLObject.html#exported-symbols
SQLExpression
=============
SQLExpression uses clever overriding of operators to make Python
expressions build SQL expressions -- so long as you start with a Magic
Object that knows how to fake it.
With SQLObject, you get a Magic Object by accessing the ``q`` attribute
of a table class -- this gives you an object that represents the
field. All of this is probably easier to grasp in an example::
>>> from sqlobject.sqlbuilder import *
>>> person = table.person
# person is now equivalent to the Person.q object from the SQLObject
# documentation
>>> person
person
>>> person.first_name
person.first_name
>>> person.first_name == 'John'
person.first_name = 'John'
>>> name = 'John'
>>> person.first_name != name
person.first_name != 'John'
>>> AND(person.first_name == 'John', person.last_name == 'Doe')
(person.first_name = 'John' AND person.last_name = 'Doe')
Most of the operators work properly: <, >, <=, >=, !=, ==, +, -, /,
\*, \*\*, %. However, ``and``, ``or``, and ``not`` **do not work**.
You can use &, \|, and ~ instead -- but be aware that these have
the same precedence as multiplication. So::
# This isn't what you want:
>> person.first_name == 'John' & person.last_name == 'Doe'
(person.first_name = ('John' AND person.last_name)) = 'Doe')
# This is:
>> (person.first_name == 'John') & (person.last_name == 'Doe')
((person.first_name = 'John') AND (person.last_name == 'Doe'))
SQLBuilder also contains the functions ``AND``, ``OR``, and ``NOT`` which
also work -- I find these easier to work with. ``AND`` and ``OR`` can
take any number of arguments.
You can also use ``.startswith()`` and ``.endswith()`` on an SQL
expression -- these will translate to appropriate ``LIKE`` statements
and all ``%`` quoting is handled for you, so you can ignore that
implementation detail. There is also a ``LIKE`` function, where you
can pass your string, with ``%`` for the wildcard, as usual.
If you want to access an SQL function, use the ``func`` variable,
like::
>> person.created < func.NOW()
To pass a constant, use the ``const`` variable which is actually an
alias for func.
SQL statements
==============
SQLBuilder implements objects that execute SQL statements. SQLObject
uses them internally in its `higher-level API`_, but users can use this
mid-level API to execute SQL queries that are not supported by the
high-level API. To use these objects first construct an instance of a
statement object, then ask the connection to convert the instance to an
SQL query and finally ask the connection to execute the query and return
the results. For example, for ``Select`` class::
>>> from sqlobject.sqlbuilder import *
>> select = Select(['name', 'AVG(salary)'], staticTables=['employees'],
>> groupBy='name') # create an instance
>> query = connection.sqlrepr(select) # Convert to SQL string:
>> # SELECT name, AVG(salary) FROM employees GROUP BY name
>> rows = connection.queryAll(query) # Execute the query
>> # and get back the results as a list of rows
>> # where every row is a sequence of length 2 (name and average salary)
.. _`higher-level API`: SQLObject.html
Select
~~~~~~
A class to build ``SELECT`` queries. Accepts a number of parameters, all
parameters except `items` are optional. Use ``connection.queryAll(query)``
to execute the query and get back the results as a list of rows.
`items`:
A string, an SQLExpression or a sequence of strings or
SQLExpression's, represents the list of columns. If there are
q-values SQLExpression's ``Select`` derives a list of tables for
SELECT query.
`where`:
A string or an SQLExpression, represents the ``WHERE`` clause.
`groupBy`:
A string or an SQLExpression, represents the ``GROUP BY`` clause.
`having`:
A string or an SQLExpression, represents the ``HAVING`` part of the
``GROUP BY`` clause.
`orderBy`:
A string or an SQLExpression, represents the ``ORDER BY`` clause.
`join`:
A (list of) JOINs (``LEFT JOIN``, etc.)
`distinct`:
A bool flag to turn on ``DISTINCT`` query.
`start`, `end`:
Integers. The way to calculate ``OFFSET`` and ``LIMIT``.
`limit`:
An integer. `limit`, if passed, overrides `end`.
`reversed`:
A bool flag to do ``ORDER BY`` in the reverse direction.
`forUpdate`:
A bool flag to turn on ``SELECT FOR UPDATE`` query.
`staticTables`:
A sequence of strings or SQLExpression's that name tables for
``FROM``. This parameter must be used if `items` is a list of strings
from which Select cannot derive the list of tables.
Insert
~~~~~~
A class to build ``INSERT`` queries. Accepts a number of parameters.
Use ``connection.query(query)`` to execute the query.
`table`:
A string that names the table to ``INSERT`` into. Required.
`valueList`:
A list of (key, value) sequences or {key: value} dictionaries; keys
are column names. Either `valueList` or `values` must be passed, but
not both. Example::
>> insert = Insert('person', valueList=[('name', 'Test'), ('age', 42)])
# or
>> insert = Insert('person', valueList=[{'name': 'Test'}, {'age': 42}])
>> query = connection.sqlrepr(insert)
# Both generate the same query:
# INSERT INTO person (name, age) VALUES ('Test', 42)
>> connection.query(query)
`values`:
A dictionary {key: value}; keys are column names. Either `valueList`
or `values` must be passed, but not both. Example::
>> insert = Insert('person', values={'name': 'Test', 'age': 42})
>> query = connection.sqlrepr(insert)
# The query is the same
# INSERT INTO person (name, age) VALUES ('Test', 42)
>> connection.query(query)
Instances of the class work fast and thus are suitable for
mass-insertion. If one needs to populate a database with SQLObject
running a lot of ``INSERT`` queries this class is the way to go.
Update
~~~~~~
A class to build ``UPDATE`` queries. Accepts a number of parameters.
Use ``connection.query(query)`` to execute the query.
`table`:
A string that names the table to ``UPDATE``. Required.
`values`:
A dictionary {key: value}; keys are column names. Required.
`where`:
An optional string or SQLExpression, represents the ``WHERE`` clause.
Example::
>> update = Update('person',
>> values={'name': 'Test', 'age': 42}, where='id=1')
>> query = connection.sqlrepr(update)
# UPDATE person SET name='Test', age=42 WHERE id=1
>> connection.query(query)
Delete
~~~~~~
A class to build ``DELETE FROM`` queries. Accepts a number of parameters.
Use ``connection.query(query)`` to execute the query.
`table`:
A string that names the table to ``UPDATE``. Required.
`where`:
An optional string or an SQLExpression, represents the ``WHERE``
clause. Required. If you need to delete all rows pass ``where=None``;
this is a safety measure.
Example::
>> update = Delete('person', where='id=1')
>> query = connection.sqlrepr(update)
# DELETE FROM person WHERE id=1
>> connection.query(query)
Union
~~~~~
A class to build ``UNION`` queries. Accepts a number of parameters -
``Select`` queries. Use ``connection.queryAll(query)`` to execute the
query and get back the results.
Example::
>> select1 = Select(['min', func.MIN(const.salary)], staticTables=['employees'])
>> select2 = Select(['max', func.MAX(const.salary)], staticTables=['employees'])
>> union = Union(select1, select2)
>> query = connection.sqlrepr(union)
# SELECT 'min', MIN(salary) FROM employees
# UNION
# SELECT 'max', MAX(salary) FROM employees
>> rows = connection.queryAll(query)
Nested SQL statements (subqueries)
==================================
There are a few special operators that receive as parameter SQL
statements. These are ``IN``, ``NOTIN``, ``EXISTS``, ``NOTEXISTS``,
``SOME``, ``ANY`` and ``ALL``. Consider the following example: You are
interested in removing records from a table using deleteMany. However,
the criterion for doing so depends on another table.
You would expect the following to work::
>> PersonWorkplace.deleteMany(where=
((PersonWorkplace.q.WorkplaceID==Workplace.q.id) &
(Workplace.q.id==SOME_ID)))
But this doesn't work! However, you can't do a join in a deleteMany
call. To work around this issue, use ``IN``::
>> PersonWorkplace.deleteMany(where=
IN(PersonWorkplace.q.WorkplaceID,
Select(Workplace.q.id, Workplace.q.id==SOME_ID)))
.. footer:: Get SQLObject at Sourceforge.net_. Fast, secure and Free Open Source software downloads
.. _Sourceforge.net: http://sourceforge.net/projects/sqlobject
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