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00001 """

SqlSoup provides a convenient way to access database tables without having
to declare table or mapper classes ahead of time.

Suppose we have a database with users, books, and loans tables
(corresponding to the PyWebOff dataset, if you're curious).
For testing purposes, we'll create this db as follows:

    >>> from sqlalchemy import create_engine
    >>> e = create_engine('sqlite:///:memory:')
    >>> for sql in _testsql: e.execute(sql) #doctest: +ELLIPSIS

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 metadata:

    >>> db = SqlSoup(BoundMetaData(e))

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.select()
    >>> users.sort()
    >>> users
    [MappedUsers(name='Joe Student',email='student@example.edu',password='student',classname=None,admin=0), MappedUsers(name='Bhargan Basepair',email='basepair@example.edu',password='basepair',classname=None,admin=1)]

Of course, letting the database do the sort is better (".c" is short for ".columns"):

    >>> db.users.select(order_by=[db.users.c.name])
    [MappedUsers(name='Bhargan Basepair',email='basepair@example.edu',password='basepair',classname=None,admin=1), MappedUsers(name='Joe Student',email='student@example.edu',password='student',classname=None,admin=0)]

Field access is intuitive:

    >>> users[0].email

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.c.name=='Bhargan Basepair', db.users.c.email=='student@example.edu')
    >>> db.users.select(where, order_by=[desc(db.users.c.name)])
    [MappedUsers(name='Joe Student',email='student@example.edu',password='student',classname=None,admin=0), MappedUsers(name='Bhargan Basepair',email='basepair@example.edu',password='basepair',classname=None,admin=1)]

You can also use the select...by methods if you're querying on a single column.
This allows using keyword arguments as column names:

    >>> db.users.selectone_by(name='Bhargan Basepair')
    MappedUsers(name='Bhargan Basepair',email='basepair@example.edu',password='basepair',classname=None,admin=1)

Select variants

All the SqlAlchemy Query select variants are available.
Here's a quick summary of these methods:

- get(PK): load a single object identified by its primary key (either a scalar, or a tuple)
- select(Clause, \*\*kwargs): perform a select restricted by the Clause argument; returns a list of objects.  The most common clause argument takes the form "db.tablename.c.columname == value."  The most common optional argument is order_by.
- select_by(\*\*params): select methods ending with _by allow using bare column names.  (columname=value)  This feels more natural to most Python programmers; the downside is you can't specify order_by or other select options.
- selectfirst, selectfirst_by: returns only the first object found; equivalent to select(...)[0] or select_by(...)[0], except None is returned if no rows are selected.
- selectone, selectone_by: like selectfirst or selectfirst_by, but raises if less or more than one object is selected.
- count, count_by: returns an integer count of the rows selected.

See the SqlAlchemy documentation for details:

- http://www.sqlalchemy.org/docs/datamapping.myt#datamapping_query for general info and examples,
- http://www.sqlalchemy.org/docs/sqlconstruction.myt for details on constructing WHERE clauses.

Modifying objects

Modifying objects is intuitive:

    >>> user = _
    >>> user.email = 'basepair+nospam@example.edu'
    >>> db.flush()

(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 flush.)

To finish covering the basics, let's insert a new loan, then delete it:

    >>> book_id = db.books.selectfirst(db.books.c.title=='Regional Variation in Moss').id
    >>> db.loans.insert(book_id=book_id, user_name=user.name)
    MappedLoans(book_id=2,user_name='Bhargan Basepair',loan_date=None)
    >>> db.flush()

    >>> loan = db.loans.selectone_by(book_id=2, user_name='Bhargan Basepair')
    >>> db.delete(loan)
    >>> db.flush()

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='Bhargan Basepair',loan_date=None)
    >>> db.flush()
    >>> db.loans.delete(db.loans.c.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.c.book_id==2, book_id=1)
    >>> db.loans.select_by(db.loans.c.book_id==1)
    [MappedLoans(book_id=1,user_name='Joe Student',loan_date=datetime.datetime(2006, 7, 12, 0, 0))]


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.select_by(name='Joe Student')
    [MappedJoin(name='Joe Student',email='student@example.edu',password='student',classname=None,admin=0,book_id=1,user_name='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.c.name==db.loans.c.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.select()
    [MappedJoin(name='Joe Student',email='student@example.edu',password='student',classname=None,admin=0,book_id=1,user_name='Joe Student',loan_date=datetime.datetime(2006, 7, 12, 0, 0),id=1,title='Mustards I Have Known',published_year='1989',authors='Jones')]

If you join tables that have an identical column name, wrap your join with "with_labels",
to disambiguate columns with their table name:

    >>> db.with_labels(join1).c.keys()
    ['users_name', 'users_email', 'users_password', 'users_classname', 'users_admin', 'loans_book_id', 'loans_user_name', 'loans_loan_date']

Advanced Use

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.select_by(published_year='1989')
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.)


You can access the SqlSoup's ``engine`` attribute to compose SQL directly.
The engine's ``execute`` method corresponds
to the one of a DBAPI cursor, and returns a ``ResultProxy`` that has ``fetch`` methods
you would also see on a cursor.

    >>> rp = db.engine.execute('select name, email from users order by name')
    >>> for name, email in rp.fetchall(): print name, email
    Bhargan Basepair basepair+nospam@example.edu
    Joe Student student@example.edu

You can also pass this engine object to other SQLAlchemy constructs.

Extra tests

Boring tests here.  Nothing of real expository value.

    >>> db.users.select(db.users.c.classname==None, order_by=[db.users.c.name])
    [MappedUsers(name='Bhargan Basepair',email='basepair+nospam@example.edu',password='basepair',classname=None,admin=1), MappedUsers(name='Joe Student',email='student@example.edu',password='student',classname=None,admin=0)]
    >>> db.nopk
    Traceback (most recent call last):
    PKNotFoundError: table 'nopk' does not have a primary key defined
    >>> db.nosuchtable
    Traceback (most recent call last):
    NoSuchTableError: nosuchtable

    >>> years_with_count.insert(published_year='2007', n=1)
    Traceback (most recent call last):
    InvalidRequestError: SQLSoup can only modify mapped Tables (found: Alias)

from sqlalchemy import *
from sqlalchemy.ext.sessioncontext import SessionContext
from sqlalchemy.ext.assignmapper import assign_mapper
from sqlalchemy.exceptions import *

_testsql = """
    id                   integer PRIMARY KEY, -- auto-SERIAL in sqlite
    title                text NOT NULL,
    published_year       char(4) NOT NULL,
    authors              text NOT NULL

    name                 varchar(32) PRIMARY KEY,
    email                varchar(128) NOT NULL,
    password             varchar(128) NOT NULL,
    classname            text,
    admin                int NOT NULL -- 0 = false

    book_id              int PRIMARY KEY REFERENCES books(id),
    user_name            varchar(32) references users(name) 
    loan_date            datetime DEFAULT current_timestamp

insert into users(name, email, password, admin)
values('Bhargan Basepair', 'basepair@example.edu', 'basepair', 1);
insert into users(name, email, password, admin)
values('Joe Student', 'student@example.edu', 'student', 0);

insert into books(title, published_year, authors)
values('Mustards I Have Known', '1989', 'Jones');
insert into books(title, published_year, authors)
values('Regional Variation in Moss', '1971', 'Flim and Flam');

insert into loans(book_id, user_name, loan_date)
values (
    (select min(id) from books), 
    (select name from users where name like 'Joe%'),
    '2006-07-12 0:0:0')

    i                    int

__all__ = ['PKNotFoundError', 'SqlSoup']

# thread local SessionContext
class Objectstore(SessionContext):
    def __getattr__(self, key):
        return getattr(self.current, key)
    def get_session(self):
        return self.current

objectstore = Objectstore(create_session)

class PKNotFoundError(SQLAlchemyError): pass

# metaclass is necessary to expose class methods with getattr, e.g.
# we want to pass db.users.select through to users._mapper.select
def _ddl_check(cls):
    if not isinstance(cls._table, Table):
        msg = 'SQLSoup can only modify mapped Tables (found: %s)' \
              % cls._table.__class__.__name__
        raise InvalidRequestError(msg)
class TableClassType(type):
    def insert(cls, **kwargs):
        o = cls()
        return o
    def delete(cls, *args, **kwargs):
        cls._table.delete(*args, **kwargs).execute()
    def update(cls, whereclause=None, values=None, **kwargs):
        cls._table.update(whereclause, values).execute(**kwargs)
    def _selectable(cls):
        return cls._table
    def __getattr__(cls, attr):
        if attr == '_query':
            # called during mapper init
            raise AttributeError()
        return getattr(cls._query, attr)

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.selectable)
    elif isinstance(selectable, sql.Select):
        # sometimes a Select has itself in _froms
        nonrecursive_froms = [s for s in selectable._froms if s is not selectable]
        return ''.join([_selectable_name(s) for s in nonrecursive_froms])
    elif isinstance(selectable, schema.Table):
        return selectable.name.capitalize()
        x = selectable.__class__.__name__
        if x[0] == '_':
            x = x[1:]
        return x

def class_for_table(selectable, **mapper_kwargs):
    if not hasattr(selectable, '_selectable') \
    or selectable._selectable() != selectable:
        raise 'class_for_table requires a selectable as its argument'
    mapname = 'Mapped' + _selectable_name(selectable)
    klass = TableClassType(mapname, (object,), {})
    def __cmp__(self, o):
        L = self.__class__.c.keys()
        t1 = [getattr(self, k) for k in L]
            t2 = [getattr(o, k) for k in L]
        except AttributeError:
            raise TypeError('unable to compare with %s' % o.__class__)
        return cmp(t1, t2)
    def __repr__(self):
        import locale
        encoding = locale.getdefaultlocale()[1]
        L = []
        for k in self.__class__.c.keys():
            value = getattr(self, k, '')
            if isinstance(value, unicode):
                value = value.encode(encoding)
            L.append("%s=%r" % (k, value))
        return '%s(%s)' % (self.__class__.__name__, ','.join(L))
    for m in ['__cmp__', '__repr__']:
        setattr(klass, m, eval(m))
    klass._table = selectable
    klass._mapper = mapper(klass,
    klass._query = Query(klass._mapper)
    return klass

class SqlSoup:
    def __init__(self, *args, **kwargs):
        args may either be an SQLEngine or a set of arguments suitable
        for passing to create_engine
        # meh, sometimes having method overloading instead of kwargs would be easier
        if isinstance(args[0], MetaData):
            args = list(args)
            metadata = args.pop(0)
            if args or kwargs:
                raise ArgumentError('Extra arguments not allowed when metadata is given')
            metadata = BoundMetaData(*args, **kwargs)
        self._metadata = metadata
        self._cache = {}
        self.schema = None
    def engine(self):
        return self._metadata._engine
    engine = property(engine)
    def delete(self, *args, **kwargs):
        objectstore.delete(*args, **kwargs)
    def flush(self):
    def rollback(self):
    def map(self, selectable, **kwargs):
            t = self._cache[selectable]
        except KeyError:
            t = class_for_table(selectable, **kwargs)
            self._cache[selectable] = t
        return t
    def with_labels(self, item):
        # TODO give meaningful aliases
        return self.map(item._selectable().select(use_labels=True).alias('foo'))
    def join(self, *args, **kwargs):
        j = join(*args, **kwargs)
        return self.map(j)
    def __getattr__(self, attr):
            t = self._cache[attr]
        except KeyError:
            table = Table(attr, self._metadata, autoload=True, schema=self.schema)
            if not table.primary_key.columns:
                raise PKNotFoundError('table %r does not have a primary key defined' % attr)
            if table.columns:
                t = class_for_table(table)
                t = None
            self._cache[attr] = t
        return t

if __name__ == '__main__':
    import doctest

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