SQLAlchemy based RDB support for Grok.
Project description
megrok.rdb
Introduction
The megrok.rdb package adds powerful relational database support to Grok, based on the powerful SQLAlchemy library. It makes available a new megrok.rdb.Model and megrok.rdb.Container which behave much like ones in core Grok, but are instead backed by a relational database.
In this document we will show you how to use megrok.rdb.
Declarative models
megrok.rdb uses SQLAlchemy’s ORM system, in particular its declarative extension, almost directly. megrok.rdb just supplies a few special base classes and directives to make things easier, and a few other conveniences that help with integration with Grok.
We first import the SQLAlchemy bits we’ll need later:
>>> from sqlalchemy import Column, ForeignKey >>> from sqlalchemy.types import Integer, String >>> from sqlalchemy.orm import relation
SQLAlchemy groups database schema information into a unit called MetaData. The schema can be reflected from the database schema, or can be created from a schema defined in Python. With megrok.rdb we typically do the latter, from within the content classes that they are mapped to using the ORM. We need to have some metadata to associate our content classes with.
Let’s set up the metadata object:
>>> from megrok import rdb >>> metadata = rdb.MetaData()
Now we’ll set up a few content classes. We’ll have a very simple structure where a (university) department has zero or more courses associated with it. First we’ll define a container that can contain courses:
>>> class Courses(rdb.Container): ... pass
That’s all. If the rdb.key directive is not used the key in the container will be defined as the (possibly automatically assigned) primary key in the database.
FIXME a hack to make things work in doctests. In some particular setup this hack wasn’t needed anymore, but I am unable at this time to reestablish this combination of packages:
>>> __file__ = 'foo'
Now we can set up the Department class. This has the courses relation that links to its courses:
>>> class Department(rdb.Model): ... rdb.metadata(metadata) ... ... id = Column('id', Integer, primary_key=True) ... name = Column('name', String(50)) ... ... courses = relation('Course', ... backref='department', ... collection_class=Courses)
This is very similar to the way you’d use sqlalchemy.ext.declarative, but there are a few differences:
* we inherit from ``rdb.Model`` to make this behave like a Grok model.
We don’t need to use __tablename__ to set up the table name. By default the table name will be the class name, lowercased, but you can override this by using the rdb.tablename directive.
we need to make explicit the metadata object that is used. We do this in the tests, though in Grok applications it’s enough to use the rdb.metadata directive on a module-level to have all rdb classes automatically associated with that metadata object.
we mark that the courses relation uses the Courses container class we have defined before. This is a normal SQLAlchemy feature, it’s just we have to use it if we want to use Grok-style containers.
We finish up our database definition by defining the Course class:
>>> class Course(rdb.Model): ... rdb.metadata(metadata) ... ... id = Column('id', Integer, primary_key=True) ... department_id = Column('department_id', Integer, ... ForeignKey('department.id')) ... name = Column('name', String(50))
We see here that Course links back to the department it is in, using a foreign key.
Configuration
We need to actually grok these objects to have them fully set up. Normally grok takes care of this automatically, but in this case we’ll need to do it manually.
First we grok this package’s grokkers:
>>> import grokcore.component.testing >>> grokcore.component.testing.grok('megrok.rdb.meta')
Now we can grok the components:
>>> from grokcore.component.testing import grok_component >>> grok_component('Courses', Courses) True >>> grok_component('Department', Department) True >>> grok_component('Course', Course) True
Once we have our metadata and object relational map defined, we need to have a database to actually put these in. While it is possible to set up a different database per Grok application, here we will use a single global database:
>>> TEST_DSN = 'sqlite:///:memory:' >>> from z3c.saconfig import EngineFactory >>> from z3c.saconfig.interfaces import IEngineFactory >>> engine_factory = EngineFactory(TEST_DSN)
We need to supply the engine factory as a utility. Grok can do this automatically for you using the module-level grok.global_utility directive, like this:
grok.global_utility(engine_factory, provides=IEngineFactory, direct=True)
In the tests we’ll use the component architecture directly:
>>> from zope import component >>> component.provideUtility(engine_factory, provides=IEngineFactory)
Now that we’ve set up an engine, we can set up the SQLAlchemy session utility:
>>> from z3c.saconfig import GloballyScopedSession >>> from z3c.saconfig.interfaces import IScopedSession >>> scoped_session = GloballyScopedSession()
With Grok, we’d register it like this:
grok.global_utility(scoped_session, provides=IScopedSession, direct=True)
But again we’ll just register it directly for the tests:
>>> component.provideUtility(scoped_session, provides=IScopedSession)
We now need to create the tables we defined in our database. We can do this only when the engine is first created, so we set up a handler for it:
>>> from z3c.saconfig.interfaces import IEngineCreatedEvent >>> @component.adapter(IEngineCreatedEvent) ... def engine_created(event): ... rdb.setupDatabase(metadata) >>> component.provideHandler(engine_created)
Using the database
Now all that is out the way, we can use the rdb.Session object to make a connection to the database.
>>> session = rdb.Session()
Let’s now create a database structure. We have a department of philosophy:
>>> philosophy = Department(name="Philosophy")
We need to manually add it to the database, as we haven’t defined a particular departments container in our database:
>>> session.add(philosophy)
The philosophy department has a number of courses:
>>> logic = Course(name="Logic") >>> ethics = Course(name="Ethics") >>> metaphysics = Course(name="Metaphysics") >>> session.add_all([logic, ethics, metaphysics])
We’ll add them to the philosophy department’s courses container. Since we want to leave it up to the database what the key will be, we will use the special set method that rdb.Container objects have to add the objects:
>>> philosophy.courses.set(logic) >>> philosophy.courses.set(ethics) >>> philosophy.courses.set(metaphysics)
We can now verify that the courses are there:
>>> for key, value in sorted(philosophy.courses.items()): ... print key, value.name, value.department.name 1 Logic Philosophy 2 Ethics Philosophy 3 Metaphysics Philosophy
As you can see, the automatically generated primary key is also used as the container key now.
The keys to the container are always integer, even if we’re dealing with a primary key:
>>> philosophy.courses['1'].name 'Logic' >>> philosophy.courses.get('1').name 'Logic'
Custom key with rdb.key
Let’s now set up a different attribute to use as the container key. We will use the name attribute of the course.
We’ll set up the data model again, this time with a rdb.key on the Courses class:
>>> metadata = rdb.MetaData() >>> class Courses(rdb.Container): ... rdb.key('name') >>> class Department(rdb.Model): ... rdb.metadata(metadata) ... ... id = Column('id', Integer, primary_key=True) ... name = Column('name', String(50)) ... ... courses = relation('Course', ... backref='department', ... collection_class=Courses) >>> class Course(rdb.Model): ... rdb.metadata(metadata) ... ... id = Column('id', Integer, primary_key=True) ... department_id = Column('department_id', Integer, ... ForeignKey('department.id')) ... name = Column('name', String(50))
We grok these new classes:
>>> grok_component('Courses', Courses) True >>> grok_component('Department', Department) True >>> grok_component('Course', Course) True
We don’t need to change the engine, as the underlying relational database has remained the same. Let’s set up another faculty with some departments:
>>> physics = Department(name="Physics") >>> session.add(physics) >>> quantum = Course(name="Quantum Mechanics") >>> relativity = Course(name="Relativity") >>> high_energy = Course(name="High Energy") >>> session.add_all([quantum, relativity, high_energy])
We’ll now add these departments to the physics faculty:
>>> physics.courses.set(quantum) >>> physics.courses.set(relativity) >>> physics.courses.set(high_energy)
We can now verify that the courses are there, with the names as the keys:
>>> for key, value in sorted(physics.courses.items()): ... print key, value.name, value.department.name High Energy High Energy Physics Quantum Mechanics Quantum Mechanics Physics Relativity Relativity Physics
Custom query container
Sometimes we want to expose objects as a (read-only) container based on a query, not a relation. This is useful when constructing an application and you need a “starting point”, a root object that launches into SQLAlchemy-mapped object that itself is not directly managed by SQLAlchemy.
We can construct such a special container by subclassing from rdb.QueryContainer and implementing the special query method:
>>> class MyQueryContainer(rdb.QueryContainer): ... def query(self): ... return session.query(Department) >>> qc = MyQueryContainer()
Let’s try some common read-only container operations, such as __getitem__:
>>> qc['1'].name u'Philosophy' >>> qc['2'].name 'Physics'
FIXME Why the unicode difference between u’Philosophy’ and ‘Physics’?
__getitem__ with a KeyError:
>>> qc['3'] Traceback (most recent call last): ... KeyError: '3'
get:
>>> qc.get('1').name u'Philosophy' >>> qc.get('3') is None True >>> qc.get('3', 'foo') 'foo'
__contains__:
>>> '1' in qc True >>> '3' in qc False
has_key:
>>> qc.has_key('1') True >>> qc.has_key('3') False
len:
>>> len(qc) 2
values:
>>> sorted([v.name for v in qc.values()]) [u'Philosophy', 'Physics']
The parents of all the values are the query container:
>>> [v.__parent__ is qc for v in qc.values()] [True, True] >>> sorted([v.__name__ for v in qc.values()]) [u'1', u'2']
keys:
>>> sorted([key for key in qc.keys()]) [u'1', u'2']
items:
>>> sorted([(key, value.name) for (key, value) in qc.items()]) [(u'1', u'Philosophy'), (u'2', 'Physics')] >>> [value.__parent__ is qc for (key, value) in qc.items()] [True, True] >>> sorted([value.__name__ for (key, value) in qc.items()]) [u'1', u'2']
__iter__:
>>> result = [] >>> for key in qc: ... result.append(key) >>> sorted(result) [u'1', u'2']
Converting results of QueryContainer
Sometimes it’s useful to convert (or modify) the output of the query to something else before they appear in the container. You can implement the convert method to do so. It takes the individual value resulting from the value and should return the converted value:
>>> class ConvertingQueryContainer(rdb.QueryContainer): ... def query(self): ... return session.query(Department) ... def convert(self, value): ... return SpecialDepartment(value.id) >>> class SpecialDepartment(object): ... def __init__(self, id): ... self.id = id >>> qc = ConvertingQueryContainer()
Let’s now check that all values are SpecialDepartment:
>>> isinstance(qc['1'], SpecialDepartment) True >>> isinstance(qc['2'], SpecialDepartment) True
KeyError still works:
>>> qc['3'] Traceback (most recent call last): ... KeyError: '3'
get:
>>> isinstance(qc.get('1'), SpecialDepartment) True >>> qc.get('3') is None True >>> qc.get('3', 'foo') 'foo'
values:
>>> [isinstance(v, SpecialDepartment) for v in qc.values()] [True, True]
The parents of all the values are the query container:
>>> [v.__parent__ is qc for v in qc.values()] [True, True] >>> sorted([v.__name__ for v in qc.values()]) [u'1', u'2']
items:
>>> sorted([(key, isinstance(value, SpecialDepartment)) for (key, value) in qc.items()]) [(u'1', True), (u'2', True)] >>> [value.__parent__ is qc for (key, value) in qc.items()] [True, True] >>> sorted([value.__name__ for (key, value) in qc.items()]) [u'1', u'2']
Customizing QueryContainer further
Sometimes it’s useful to define a custom keyfunc and custom method to retrieve the key from the database - these usually are implemented together:
>>> class KeyfuncQueryContainer(rdb.QueryContainer): ... def query(self): ... return session.query(Department) ... def keyfunc(self, value): ... return 'd' + unicode(value.id) ... def dbget(self, key): ... if not key.startswith('d'): ... return None ... return self.query().get(key[1:]) >>> qc = KeyfuncQueryContainer() >>> qc.keys() [u'd1', u'd2'] >>> qc[u'd1'].id 1
CHANGES
0.12 (2011-02-02)
Update dependencies and imports to work with Grok 1.2 and 1.3.
0.11 (2010-02-22)
Added a LICENSE.txt file.
Added setupDatabaseSkipCreate. This allows setting up the database without trying to create any tables, just reflection.
0.10 (2009-09-18)
Added to SQLAlchemy to zope.schema adapters so that most of the types in sqlalchemy.types are covered.
Import schema_from_model into megrok.rdb package namespace.
Update buildout to use Grok 1.0b2 versions.
Added a test that demonstrates a common initialization pattern using rdb.setupDatabase` in a IEngineCreatedEvent subscriber.
0.9.1 (2009-08-14)
megrok.rdb 0.9 accidentally had zip_safe set to True, which resulted in a dud release as its ZCML wouldn’t be loaded. Set zip_safe to False.
0.9 (2009-08-14)
Initial public release.
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