"""
Introduction
============
SqlSoup provides a convenient way to access existing database tables without
having to declare table or mapper classes ahead of time. It is built on top of the SQLAlchemy ORM and provides a super-minimalistic interface to an existing database.
Suppose we have a database with users, books, and loans tables
(corresponding to the PyWebOff dataset, if you're curious).
Creating a SqlSoup gateway is just like creating an SQLAlchemy
engine::
>>> from sqlalchemy.ext.sqlsoup import SqlSoup
>>> db = SqlSoup('sqlite:///:memory:')
or, you can re-use an existing engine::
>>> db = SqlSoup(engine)
You can optionally specify a schema within the database for your
SqlSoup::
>>> db.schema = myschemaname
Loading objects
===============
Loading objects is as easy as this::
>>> users = db.users.all()
>>> users.sort()
>>> users
[MappedUsers(name=u'Joe Student',email=u'student@example.edu',password=u'student',classname=None,admin=0), MappedUsers(name=u'Bhargan Basepair',email=u'basepair@example.edu',password=u'basepair',classname=None,admin=1)]
Of course, letting the database do the sort is better::
>>> db.users.order_by(db.users.name).all()
[MappedUsers(name=u'Bhargan Basepair',email=u'basepair@example.edu',password=u'basepair',classname=None,admin=1), MappedUsers(name=u'Joe Student',email=u'student@example.edu',password=u'student',classname=None,admin=0)]
Field access is intuitive::
>>> users[0].email
u'student@example.edu'
Of course, you don't want to load all users very often. Let's add a
WHERE clause. Let's also switch the order_by to DESC while we're at
it::
>>> from sqlalchemy import or_, and_, desc
>>> where = or_(db.users.name=='Bhargan Basepair', db.users.email=='student@example.edu')
>>> db.users.filter(where).order_by(desc(db.users.name)).all()
[MappedUsers(name=u'Joe Student',email=u'student@example.edu',password=u'student',classname=None,admin=0), MappedUsers(name=u'Bhargan Basepair',email=u'basepair@example.edu',password=u'basepair',classname=None,admin=1)]
You can also use .first() (to retrieve only the first object from a query) or
.one() (like .first when you expect exactly one user -- it will raise an
exception if more were returned)::
>>> db.users.filter(db.users.name=='Bhargan Basepair').one()
MappedUsers(name=u'Bhargan Basepair',email=u'basepair@example.edu',password=u'basepair',classname=None,admin=1)
Since name is the primary key, this is equivalent to
>>> db.users.get('Bhargan Basepair')
MappedUsers(name=u'Bhargan Basepair',email=u'basepair@example.edu',password=u'basepair',classname=None,admin=1)
This is also equivalent to
>>> db.users.filter_by(name='Bhargan Basepair').one()
MappedUsers(name=u'Bhargan Basepair',email=u'basepair@example.edu',password=u'basepair',classname=None,admin=1)
filter_by is like filter, but takes kwargs instead of full clause expressions.
This makes it more concise for simple queries like this, but you can't do
complex queries like the or\_ above or non-equality based comparisons this way.
Full query documentation
------------------------
Get, filter, filter_by, order_by, limit, and the rest of the
query methods are explained in detail in :ref:`ormtutorial_querying`.
Modifying objects
=================
Modifying objects is intuitive::
>>> user = _
>>> user.email = 'basepair+nospam@example.edu'
>>> db.commit()
(SqlSoup leverages the sophisticated SQLAlchemy unit-of-work code, so
multiple updates to a single object will be turned into a single
``UPDATE`` statement when you commit.)
To finish covering the basics, let's insert a new loan, then delete
it::
>>> book_id = db.books.filter_by(title='Regional Variation in Moss').first().id
>>> db.loans.insert(book_id=book_id, user_name=user.name)
MappedLoans(book_id=2,user_name=u'Bhargan Basepair',loan_date=None)
>>> loan = db.loans.filter_by(book_id=2, user_name='Bhargan Basepair').one()
>>> db.delete(loan)
>>> db.commit()
You can also delete rows that have not been loaded as objects. Let's
do our insert/delete cycle once more, this time using the loans
table's delete method. (For SQLAlchemy experts: note that no flush()
call is required since this delete acts at the SQL level, not at the
Mapper level.) The same where-clause construction rules apply here as
to the select methods.
::
>>> db.loans.insert(book_id=book_id, user_name=user.name)
MappedLoans(book_id=2,user_name=u'Bhargan Basepair',loan_date=None)
>>> db.loans.delete(db.loans.book_id==2)
You can similarly update multiple rows at once. This will change the
book_id to 1 in all loans whose book_id is 2::
>>> db.loans.update(db.loans.book_id==2, book_id=1)
>>> db.loans.filter_by(book_id=1).all()
[MappedLoans(book_id=1,user_name=u'Joe Student',loan_date=datetime.datetime(2006, 7, 12, 0, 0))]
Joins
=====
Occasionally, you will want to pull out a lot of data from related
tables all at once. In this situation, it is far more efficient to
have the database perform the necessary join. (Here we do not have *a
lot of data* but hopefully the concept is still clear.) SQLAlchemy is
smart enough to recognize that loans has a foreign key to users, and
uses that as the join condition automatically.
::
>>> join1 = db.join(db.users, db.loans, isouter=True)
>>> join1.filter_by(name='Joe Student').all()
[MappedJoin(name=u'Joe Student',email=u'student@example.edu',password=u'student',classname=None,admin=0,book_id=1,user_name=u'Joe Student',loan_date=datetime.datetime(2006, 7, 12, 0, 0))]
If you're unfortunate enough to be using MySQL with the default MyISAM
storage engine, you'll have to specify the join condition manually,
since MyISAM does not store foreign keys. Here's the same join again,
with the join condition explicitly specified::
>>> db.join(db.users, db.loans, db.users.name==db.loans.user_name, isouter=True)
<class 'sqlalchemy.ext.sqlsoup.MappedJoin'>
You can compose arbitrarily complex joins by combining Join objects
with tables or other joins. Here we combine our first join with the
books table::
>>> join2 = db.join(join1, db.books)
>>> join2.all()
[MappedJoin(name=u'Joe Student',email=u'student@example.edu',password=u'student',classname=None,admin=0,book_id=1,user_name=u'Joe Student',loan_date=datetime.datetime(2006, 7, 12, 0, 0),id=1,title=u'Mustards I Have Known',published_year=u'1989',authors=u'Jones')]
If you join tables that have an identical column name, wrap your join
with `with_labels`, to disambiguate columns with their table name
(.c is short for .columns)::
>>> db.with_labels(join1).c.keys()
[u'users_name', u'users_email', u'users_password', u'users_classname', u'users_admin', u'loans_book_id', u'loans_user_name', u'loans_loan_date']
You can also join directly to a labeled object::
>>> labeled_loans = db.with_labels(db.loans)
>>> db.join(db.users, labeled_loans, isouter=True).c.keys()
[u'name', u'email', u'password', u'classname', u'admin', u'loans_book_id', u'loans_user_name', u'loans_loan_date']
Relationships
=============
You can define relationships on SqlSoup classes:
>>> db.users.relate('loans', db.loans)
These can then be used like a normal SA property:
>>> db.users.get('Joe Student').loans
[MappedLoans(book_id=1,user_name=u'Joe Student',loan_date=datetime.datetime(2006, 7, 12, 0, 0))]
>>> db.users.filter(~db.users.loans.any()).all()
[MappedUsers(name=u'Bhargan Basepair',email='basepair+nospam@example.edu',password=u'basepair',classname=None,admin=1)]
relate can take any options that the relationship function accepts in normal mapper definition:
>>> del db._cache['users']
>>> db.users.relate('loans', db.loans, order_by=db.loans.loan_date, cascade='all, delete-orphan')
Advanced Use
============
Sessions, Transations and Application Integration
-------------------------------------------------
**Note:** please read and understand this section thoroughly before using SqlSoup in any web application.
SqlSoup uses a ScopedSession to provide thread-local sessions. You
can get a reference to the current one like this::
>>> session = db.session
The default session is available at the module level in SQLSoup, via::
>>> from sqlalchemy.ext.sqlsoup import Session
The configuration of this session is ``autoflush=True``, ``autocommit=False``.
This means when you work with the SqlSoup object, you need to call ``db.commit()``
in order to have changes persisted. You may also call ``db.rollback()`` to
roll things back.
Since the SqlSoup object's Session automatically enters into a transaction as soon
as it's used, it is *essential* that you call ``commit()`` or ``rollback()``
on it when the work within a thread completes. This means all the guidelines
for web application integration at :ref:`session_lifespan` must be followed.
The SqlSoup object can have any session or scoped session configured onto it.
This is of key importance when integrating with existing code or frameworks
such as Pylons. If your application already has a ``Session`` configured,
pass it to your SqlSoup object::
>>> from myapplication import Session
>>> db = SqlSoup(session=Session)
If the ``Session`` is configured with ``autocommit=True``, use ``flush()``
instead of ``commit()`` to persist changes - in this case, the ``Session``
closes out its transaction immediately and no external management is needed. ``rollback()`` is also not available. Configuring a new SQLSoup object in "autocommit" mode looks like::
>>> from sqlalchemy.orm import scoped_session, sessionmaker
>>> db = SqlSoup('sqlite://', session=scoped_session(sessionmaker(autoflush=False, expire_on_commit=False, autocommit=True)))
Mapping arbitrary Selectables
-----------------------------
SqlSoup can map any SQLAlchemy ``Selectable`` with the map
method. Let's map a ``Select`` object that uses an aggregate function;
we'll use the SQLAlchemy ``Table`` that SqlSoup introspected as the
basis. (Since we're not mapping to a simple table or join, we need to
tell SQLAlchemy how to find the *primary key* which just needs to be
unique within the select, and not necessarily correspond to a *real*
PK in the database.)
::
>>> from sqlalchemy import select, func
>>> b = db.books._table
>>> s = select([b.c.published_year, func.count('*').label('n')], from_obj=[b], group_by=[b.c.published_year])
>>> s = s.alias('years_with_count')
>>> years_with_count = db.map(s, primary_key=[s.c.published_year])
>>> years_with_count.filter_by(published_year='1989').all()
[MappedBooks(published_year=u'1989',n=1)]
Obviously if we just wanted to get a list of counts associated with
book years once, raw SQL is going to be less work. The advantage of
mapping a Select is reusability, both standalone and in Joins. (And if
you go to full SQLAlchemy, you can perform mappings like this directly
to your object models.)
An easy way to save mapped selectables like this is to just hang them on
your db object::
>>> db.years_with_count = years_with_count
Python is flexible like that!
Raw SQL
-------
SqlSoup works fine with SQLAlchemy's text construct, described in :ref:`sqlexpression_text`.
You can also execute textual SQL directly using the `execute()` method,
which corresponds to the `execute()` method on the underlying `Session`.
Expressions here are expressed like ``text()`` constructs, using named parameters
with colons::
>>> rp = db.execute('select name, email from users where name like :name order by name', name='%Bhargan%')
>>> for name, email in rp.fetchall(): print name, email
Bhargan Basepair basepair+nospam@example.edu
Or you can get at the current transaction's connection using `connection()`. This is the
raw connection object which can accept any sort of SQL expression or raw SQL string passed to the database::
>>> conn = db.connection()
>>> conn.execute("'select name, email from users where name like ? order by name'", '%Bhargan%')
Dynamic table names
-------------------
You can load a table whose name is specified at runtime with the entity() method:
>>> tablename = 'loans'
>>> db.entity(tablename) == db.loans
True
entity() also takes an optional schema argument. If none is specified, the
default schema is used.
"""
from sqlalchemy import Table,MetaData,join
from sqlalchemy import schema,sql
from sqlalchemy.engine.base import Engine
from sqlalchemy.orm import scoped_session,sessionmaker,mapper,\
class_mapper, relationship, session,\
object_session
from sqlalchemy.orm.interfaces import MapperExtension,EXT_CONTINUE
from sqlalchemy.exceptions import SQLAlchemyError,InvalidRequestError,ArgumentError
from sqlalchemy.sql import expression
__all__ = ['PKNotFoundError', 'SqlSoup']
Session = scoped_session(sessionmaker(autoflush=True, autocommit=False))
class AutoAdd(MapperExtension):
def __init__(self, scoped_session):
self.scoped_session = scoped_session
def instrument_class(self, mapper, class_):
class_.__init__ = self._default__init__(mapper)
def _default__init__(ext, mapper):
def __init__(self, **kwargs):
for key, value in kwargs.iteritems():
setattr(self, key, value)
return __init__
def init_instance(self, mapper, class_, oldinit, instance, args, kwargs):
session = self.scoped_session()
session._save_without_cascade(instance)
return EXT_CONTINUE
def init_failed(self, mapper, class_, oldinit, instance, args, kwargs):
sess = object_session(instance)
if sess:
sess.expunge(instance)
return EXT_CONTINUE
class PKNotFoundError(SQLAlchemyError):
pass
def _ddl_error(cls):
msg = 'SQLSoup can only modify mapped Tables (found: %s)' \
% cls._table.__class__.__name__
raise InvalidRequestError(msg)
# metaclass is necessary to expose class methods with getattr, e.g.
# we want to pass db.users.select through to users._mapper.select
class SelectableClassType(type):
def insert(cls, **kwargs):
_ddl_error(cls)
def __clause_element__(cls):
return cls._table
def __getattr__(cls, attr):
if attr == '_query':
# called during mapper init
raise AttributeError()
return getattr(cls._query, attr)
class TableClassType(SelectableClassType):
def insert(cls, **kwargs):
o = cls()
o.__dict__.update(kwargs)
return o
def relate(cls, propname, *args, **kwargs):
class_mapper(cls)._configure_property(propname, relationship(*args, **kwargs))
def _is_outer_join(selectable):
if not isinstance(selectable, sql.Join):
return False
if selectable.isouter:
return True
return _is_outer_join(selectable.left) or _is_outer_join(selectable.right)
def _selectable_name(selectable):
if isinstance(selectable, sql.Alias):
return _selectable_name(selectable.element)
elif isinstance(selectable, sql.Select):
return ''.join(_selectable_name(s) for s in selectable.froms)
elif isinstance(selectable, schema.Table):
return selectable.name.capitalize()
else:
x = selectable.__class__.__name__
if x[0] == '_':
x = x[1:]
return x
def _class_for_table(session, engine, selectable, **mapper_kwargs):
selectable = expression._clause_element_as_expr(selectable)
mapname = 'Mapped' + _selectable_name(selectable)
# Py2K
if isinstance(mapname, unicode):
engine_encoding = engine.dialect.encoding
mapname = mapname.encode(engine_encoding)
# end Py2K
if isinstance(selectable, Table):
klass = TableClassType(mapname, (object,), {})
else:
klass = SelectableClassType(mapname, (object,), {})
def _compare(self, o):
L = list(self.__class__.c.keys())
L.sort()
t1 = [getattr(self, k) for k in L]
try:
t2 = [getattr(o, k) for k in L]
except AttributeError:
raise TypeError('unable to compare with %s' % o.__class__)
return t1, t2
# python2/python3 compatible system of
# __cmp__ - __lt__ + __eq__
def __lt__(self, o):
t1, t2 = _compare(self, o)
return t1 < t2
def __eq__(self, o):
t1, t2 = _compare(self, o)
return t1 == t2
def __repr__(self):
L = ["%s=%r" % (key, getattr(self, key, ''))
for key in self.__class__.c.keys()]
return '%s(%s)' % (self.__class__.__name__, ','.join(L))
for m in ['__eq__', '__repr__', '__lt__']:
setattr(klass, m, eval(m))
klass._table = selectable
klass.c = expression.ColumnCollection()
mappr = mapper(klass,
selectable,
extension=AutoAdd(session),
**mapper_kwargs)
for k in mappr.iterate_properties:
klass.c[k.key] = k.columns[0]
klass._query = session.query_property()
return klass
class SqlSoup(object):
def __init__(self, engine_or_metadata, **kw):
"""Initialize a new ``SqlSoup``.
`args` may either be an ``SQLEngine`` or a set of arguments
suitable for passing to ``create_engine``.
"""
self.session = kw.pop('session', Session)
if isinstance(engine_or_metadata, MetaData):
self._metadata = engine_or_metadata
elif isinstance(engine_or_metadata, (basestring, Engine)):
self._metadata = MetaData(engine_or_metadata)
else:
raise ArgumentError("invalid engine or metadata argument %r" % engine_or_metadata)
self._cache = {}
self.schema = None
@property
def engine(self):
return self._metadata.bind
bind = engine
def delete(self, *args, **kwargs):
self.session.delete(*args, **kwargs)
def execute(self, stmt, **params):
return self.session.execute(sql.text(stmt, bind=self.bind), **params)
@property
def _underlying_session(self):
if isinstance(self.session, session.Session):
return self.session
else:
return self.session()
def connection(self):
return self._underlying_session._connection_for_bind(self.bind)
def flush(self):
self.session.flush()
def rollback(self):
self.session.rollback()
def commit(self):
self.session.commit()
def clear(self):
self.session.expunge_all()
def expunge(self, *args, **kw):
self.session.expunge(*args, **kw)
def expunge_all(self):
self.session.expunge_all()
def map(self, selectable, **kwargs):
try:
t = self._cache[selectable]
except KeyError:
t = _class_for_table(self.session, self.engine, selectable, **kwargs)
self._cache[selectable] = t
return t
def with_labels(self, item):
# TODO give meaningful aliases
return self.map(
expression._clause_element_as_expr(item).
select(use_labels=True).
alias('foo'))
def join(self, *args, **kwargs):
j = join(*args, **kwargs)
return self.map(j)
def entity(self, attr, schema=None):
try:
t = self._cache[attr]
except KeyError, ke:
table = Table(attr, self._metadata, autoload=True, autoload_with=self.bind, schema=schema or self.schema)
if not table.primary_key.columns:
raise PKNotFoundError('table %r does not have a primary key defined [columns: %s]' % (attr, ','.join(table.c.keys())))
if table.columns:
t = _class_for_table(self.session, self.engine, table)
else:
t = None
self._cache[attr] = t
return t
def __getattr__(self, attr):
return self.entity(attr)
def __repr__(self):
return 'SqlSoup(%r)' % self._metadata
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