This is a pre-production deployment of Warehouse, however changes made here WILL affect the production instance of PyPI.
Latest Version Dependencies status unknown Test status unknown Test coverage unknown
Project Description

Data caching components for the SPARC platform.

SQL Cache Area
SQL implementation of ICacheArea, providing a mechanism to store items
implementing either ICachableItem (a single item) or ICachableSource
(many items).

This implementation utilizes SQLAlchemy to provide abstraction from the
specific SQL technology (MySQL, Oracle, SQL Server, etc) to be used. Also,
this is implemented as a ZCA multi-adapter...allowing easy lookup given
an instance of ISqlAlchemySession and ICachedItemMapper.

Although we provide a *very* flexible implementation for caching information,
this flexibility comes at the cost of some added complexities. We use ZCA as a
framework to help us manage the complexity.

Even though, technically, this class can be used outside of ZCA...our examples
will use ZCA because it helps to simplify the explanation.

Cachable Item
Of course, as a first step, we need some information that is to be cached.
We need structured information that our SQL Cache Area object can understand.
We have the ICachableItem interface to help us here. So as a first step,
we'll create an implementation of this interface.

>>> from zope.interface import implements
>>> from sparc.cache import ICachableItem
>>> class myItem(object):
... implements(ICachableItem)
... def __init__(self, attributes = None):
... self.key = 'ENTRY #'
... self.attributes = attributes
... def getId(self):
... return self.attributes[self.key]
... def validate(self):
... if not self.attributes.has_key(self.key):
... raise KeyError("expected item's attributes to have entry for key field: %s", self.key)
... if not self.attributes[self.key]:
... raise ValueError("expected item's key attribute to have a non-empty value")

Notice...we did not need to explicitly add members in the class that represent
individually cachable information (i.e. column definitions). Instead we
have single myItem.attributes which will contain a Dictionary of the
information that is to be cached in key, value pairs.

Also notice...we had to specify the key name of the attribute entry which will
be used to uniquely identify the item within a group of items.

Although the above code shows how to create the implementation, mostly it is
boiler plate so we have a readily available mixin class to help simplify
things for us.

>>> del(myItem)
>>> from sparc.cache.item import cachableItemMixin
>>> class myItem(cachableItemMixin):
... def __init__(self, attributes=None):
... super(myItem, self).__init__('ENTRY #', attributes)

Finally, we create a factory...whose responsibility is simply to generate new
instances of our implementation.

>>> from zope.component.factory import IFactory, Factory
>>> myCachableItemFactory = Factory(myItem, 'myCachableItemFactory')

Cached Item
Information that has been cached may require some subtle translations from the
original information source (ICachableItem). For example, if the cachable
item has a date string then it would be nice to store that information in
the DB as a datetime type...therefore allowing date searches. IF we just
stored the information as a string-type...we couldn't utilze the DB's full
capabilities for type-specific searching.

For this, and other reasons, we need a new data structure (class) that will
represent the information after it has been cached. For this task, we
have the ICachedItem interface. Again, we require an implementation of this
interface to do anything useful.

>>> import sqlalchemy.ext.declarative
>>> class myBaseMixin(object):
... @sqlalchemy.ext.declarative.declared_attr
... def __tablename__(cls):
... return cls.__name__.lower()
... __mapper_args__= {'always_refresh': True}
... def __repr__(self):
... return "<" + self.__class__.__name__ + "(id: '%s'')>" % (self.getId())
>>> Base = sqlalchemy.ext.declarative.declarative_base()

>>> from sparc.cache import ICachedItem
>>> import sqlalchemy
>>> from datetime import date, timedelta
>>> class myCachedItem(myBaseMixin, Base):
... implements(ICachedItem)
... entry_number = sqlalchemy.Column(sqlalchemy.BigInteger(), primary_key=True)
... logged_date = sqlalchemy.Column(sqlalchemy.DateTime(),nullable=True)
... def getId(self):
... return self.entry_number
... def __eq__(self, instance):
... if not isinstance(instance, self.__class__):
... return False
... if self.entry_number != instance.entry_number:
... return False
... if self.logged_date - instance.logged_date != timedelta(0):
... return False
... return True
... def __ne__(self, instance):
... return not self.__eq__(instance)

This implementation is a bit more tricky than our myItem object from above.
First thing to note is our dependency on sqlalchmeny. This is an
implementation-specific dependency...driven by our base requirement to allow
information to be stored in a DB via the sqlalchemy abstraction layer. Other
than conformance to the ICachedItem interface requirements, this acts like a
normal SQL Alchemy persistent object class

But once again, the above implementation is not that fun to write out, so we
have a ready-to-use mixin class to help things out.

>>> del(myCachedItem)
>>> from sparc.cache.item import cachedItemMixin
>>> Base = sqlalchemy.ext.declarative.declarative_base() # we need to reset this, cause myCachedItem is already defined above
>>> class myCachedItem(cachedItemMixin, myBaseMixin, Base):
... _key = 'entry_number'
... entry_number = sqlalchemy.Column(sqlalchemy.BigInteger(), primary_key=True)
... logged_date = sqlalchemy.Column(sqlalchemy.DateTime(),nullable=True)

Finally (like above), we created factory...whose responsibility is simply to
generate new instances of our implementation.

>>> from zope.component.factory import IFactory, Factory
>>> myCachedItemFactory = Factory(myCachedItem, 'myCachedItemFactory')

Cached Item Mapper
Now that we have two different classes, one representing information we want to
cache and the other representing the information after it has been cached, we need
a way to relate the 2 different classes. For this task, we have the
ICachedItemMapper interface. This class provides a mechanism to populate
an ICachedItem from information stored in a ICachableItem.

>>> from zope.component import adapts
>>> from sparc.cache.interfaces import ICachedItemMapper, ICachableSource
>>> from sparc.cache.sources import normalizedDateTime, normalizedDateTimeResolver
>>> class myItemCacheMapper(object):
... implements(ICachedItemMapper)
... adapts(ICachableSource)
... mapper = {
... 'entry_number' :'ENTRY #',
... 'logged_date' :normalizedDateTime('LOGGED DATE')
... }
... def __init__(self, CachableSource):
... self.cachableSource = CachableSource
... def key(self):
... for _key, _value in self.mapper.iteritems():
... if _value == self.cachableSource.key():
... return _key
... raise LookupError("expected to find matching cache key for given source key via map lookup")
... def factory(self):
... return myCachedItem()
... def get(self, sourceItem):
... _cachedItem = self.factory()
... _cachedItem.entry_number = int(sourceItem.attributes['ENTRY #'])
... _cachedItem.logged_date = normalizedDateTimeResolver(self.logged_date).manage(sourceItem.attributes['LOGGED DATE'])
... return _cachedItem

For the purpose of illustration, the above class fully implements the
ICachedItemMapper interface. However, since it's not fun to create this
type of class, there's an available mixin class to make things a bit simpler
to read/write

>>> del(myItemCacheMapper)
>>> from sparc.cache.sql import SqlObjectMapperMixin
>>> class myItemCacheMapper(SqlObjectMapperMixin):
... mapper = {
... 'entry_number' :'ENTRY #',
... 'logged_date' :normalizedDateTime('LOGGED DATE')
... }

Much nicer to look at. Also note the normalizedDateTime() reference. This
class is an implementation of the IManagedCachedItemMapperAttributeKeyWrapper
interface. The interface is needs to supply a __call__() method
that returns the string key name.

We've now created classes that represent information in its pre and post
cached state, and also a mapper for the two states. Things are about to get
interesting. Before we move forward, we will configure the ZCA registry
with both our components above and also components that are available in
sparc (defined in the various *.zcml files in the framework).

>>> from sparc.common import Configure
>>> import sparc.cache
>>> Configure([sparc.cache])

We now have populated the global ZCA registry with all available components
in the sparc.cache package. It's a good start, but we also need to register
the ICachableItemMapper adapter implementation components above.
Remember, registration allows these components to be looked up via ZCA calls.

>>> from zope.component import getGlobalSiteManager
>>> gsm = getGlobalSiteManager()
>>> gsm.registerAdapter(myItemCacheMapper, (ICachableSource, IFactory), ICachedItemMapper)

Data Source
Up until now, we've really only dealt with data definitions. You might be
asking..."so where's the data?". We have the ICachableSource interface to
deal with data sources. But first, we need to start with the actual data.
We'll use the test_csvdata.csv file located under the
sparc.cache.sources.tests directory.

>>> import os
>>> csv_file = os.path.dirname(os.path.abspath(__file__)) + os.sep + 'sources' + os.sep + 'tests' + os.sep + 'test_csvdata.csv'

We can now create instances of sparc.cache.sources.csvdata.CSVSource via
its factory. This object will be used to generate ICachableItem objects for
each valid CSV row entry.

>>> from zope.component import createObject
>>> myCSVSource = createObject('cache.sources.CSVSourceFactory', csv_file, myCachableItemFactory)

Let's run a few quick test to make sure the data source is sane

>>> item = myCSVSource.first()
>>> item.attributes['ENTRY #']
>>> item.attributes['LOGGED DATE']
'6/18/2014 16:28'
>>> item.getId()
>>> item.validate()

Database Connection
To work with a database, we need to connect to it per SQLAlchemy instructions.
We'll use a simple SQLite memory database for this example.

>>> from sqlalchemy import create_engine
>>> engine = create_engine('sqlite:///:memory:')
>>> from sqlalchemy.orm import sessionmaker
>>> Session = sessionmaker(bind=engine)
>>> session = Session()

We need to provide the ISqlAlchemySession marker interface to the session
object to enable easy ZCA based component lookup for adapters.

>>> from zope.interface import directlyProvides
>>> from sparc.db import ISqlAlchemySession
>>> directlyProvides(session, ISqlAlchemySession)

Load the Cache!!!
OK, it was a bit complicated to get here...but now we'll see the fruits of
our labor. Our actual caching interface is defined by ICacheArea. We've
implemented this interface via an adapter located at
sparc.cache.sql.SqlObjectCacheArea. This adapter is already registered, so
we can look it up.

>>> from sparc.cache import ICacheArea
>>> from zope.component import getMultiAdapter
>>> myMapper = getMultiAdapter((myCSVSource, myCachedItemFactory), ICachedItemMapper) # get our mapper via our adapter implementation
>>> mySqlObjectCacheArea = getMultiAdapter((session, myMapper), ICacheArea)

One more final activity...we need to initialize (i.e. create the DB tables)
the storage area.

>>> mySqlObjectCacheArea.initialize(Base)

whew...that was a lot of we can finally use it. let's start
by getting one of our cachable items in hand.

>>> item = myCSVSource.first()
>>> item.getId()

Let's make sure our mapper works ok.

>>> myMapper.get(item).getId()

This item hasn't been cached yet

>>> mySqlObjectCacheArea.get(item)
>>> mySqlObjectCacheArea.isDirty(item)
>>> cached = mySqlObjectCacheArea.cache(item)
>>> cached.getId()
>>> mySqlObjectCacheArea.isDirty(item)
>>> item.attributes['LOGGED DATE'] = '6/18/2014 16:28' # same as orig
>>> mySqlObjectCacheArea.isDirty(item)
>>> mySqlObjectCacheArea.cache(item)
>>> item.attributes['LOGGED DATE'] = '6/25/2014 16:28' # new date
>>> mySqlObjectCacheArea.isDirty(item)
>>> myMapper.get(item).getId()

Let's test the transactional features

>>> mySqlObjectCacheArea.rollback()
>>> mySqlObjectCacheArea.isDirty(item)
>>> cached = mySqlObjectCacheArea.cache(item)
>>> cached.getId()
>>> mySqlObjectCacheArea.isDirty(item)
>>> mySqlObjectCacheArea.commit()
>>> mySqlObjectCacheArea.isDirty(item)
>>> item = myCSVSource.first() # this resets the date from above
>>> mySqlObjectCacheArea.isDirty(item)
>>> cached = mySqlObjectCacheArea.cache(item)
>>> cached.getId()
>>> mySqlObjectCacheArea.commit()

Let's get the item directly from the DB and make sure it acts like a

>>> mySqlObjectCacheArea.session.expunge(cached)
>>> cached = mySqlObjectCacheArea.get(item)
>>> cached.getId()

Now lets do a bulk import...when we import it will bring in 1 less
than the total CSV source (because the first entry already done and does not
require an update)

>>> mySqlObjectCacheArea.import_source(myCSVSource)


* pypi packaging update


* include zcml configuration files in packaging


* initial release
Release History

Release History


This version

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

Show More


History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

Show More

Download Files

Download Files

TODO: Brief introduction on what you do with files - including link to relevant help section.

File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
sparc.cache-0.0.3.tar.gz (20.1 kB) Copy SHA256 Checksum SHA256 Source Oct 29, 2015

Supported By

WebFaction WebFaction Technical Writing Elastic Elastic Search Pingdom Pingdom Monitoring Dyn Dyn DNS HPE HPE Development Sentry Sentry Error Logging CloudAMQP CloudAMQP RabbitMQ Heroku Heroku PaaS Kabu Creative Kabu Creative UX & Design Fastly Fastly CDN DigiCert DigiCert EV Certificate Rackspace Rackspace Cloud Servers DreamHost DreamHost Log Hosting