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<title>Dejavu: Introduction</title> |
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<h2>Introduction</h2> |
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<p>Dejavu is an Object-Relational Mapper for Python applications. It is |
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designed to provide the "Model" third of an MVC application. When you build |
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an application using Dejavu, you must supply the Controller(s) and View(s) |
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yourself. Dejavu does not provide these, and does its best to not limit |
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your choices regarding them.</p> |
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<p>If you're familiar with Martin Fowler's work <a href='#fowler'>[1]</a>, |
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you can think of Dejavu as providing a Data Source layer, plus the tools |
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to write your own Domain layer. For the Presentation layer, you're on your |
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own. ;)</p> |
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<h3>Basic Structure</h3> |
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<p>Developers build their Model by creating classes which subclass |
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the class <tt>dejavu.Unit</tt>; for those of you stuck in RDBMS |
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mindsets, each Unit subclass corresponds to a table; instances of the class |
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correspond to the rows. Each subclass possesses a set of attributes known |
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as "properties", which you can think of as columns in your database |
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table. These attributes are generally formed from a <tt>UnitProperty</tt> |
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descriptor. Any Unit data which needs to be persisted ought to be contained |
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in a Unit Property. However, Unit classes can also possess arbitrary |
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methods and attributes which aid their use within the application.</p> |
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|
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<p>Unit classes can be <i>associated</i> to other Unit classes. This means |
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that one of the properties of UnitA maps to one of the properties of UnitB. |
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Related objects may then be looked up more easily.</p> |
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<p>Units are managed in memory by <tt>Sandbox</tt> objects, which function |
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as "Identity Maps" <a href='#fowler'>[1]</a>: in-memory caches of Units |
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which keep commit conflicts to a minimum. Unit objects can be "memorized" |
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and "recalled" from a <tt>Sandbox</tt>, using pure Python lambda expressions |
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<a href='#cpython'>[2]</a> as a query language. The lambda is wrapped |
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in an <tt>Expression</tt> object to make it portable.</p> |
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<p>Sandboxes persist Unit data by <tt>StorageManager</tt> objects. Each |
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persistence mechanism has its own subclass of the <tt>StorageManager</tt> |
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class; for example, persisting Unit data to a Microsoft SQL Server database |
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requires a <tt>StorageManagerADO_SQLServer</tt> object. When recalling data, |
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Storage Managers receive Expression objects; database SM's, for example, |
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will typically examine these Expressions and produce SQL statements from |
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them, which they then use to retrieve data. Storage Managers also handle |
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the creation of new Units, and their destruction.</p> |
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<p>Finally, Dejavu provides a core <tt>Arena</tt> class which you should be |
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able to leverage for any sort of application you are building. The Arena |
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object functions as a top-level "Application" object, collecting the global |
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settings for an application into one place. It doles out Sandboxes, |
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maintains a registry of Units and their associations, and manages startup |
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and shutdown operations.</p> |
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<h3>Simple Example</h3> |
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<p>Since a block of code is often worth a thousand words, here's a minimal |
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example of a Dejavu application:</p> |
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zookeeper.py |
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<pre>import dejavu |
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class Zoo(dejavu.Unit): |
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Name = dejavu.UnitProperty() |
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Size = dejavu.UnitProperty(int) |
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def total_legs(self): |
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return sum([x.Legs for x in self.Animal()]) |
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class Animal(dejavu.Unit): |
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Legs = dejavu.UnitProperty(int, default=4) |
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Animal.set_properties({"Name": unicode, |
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"ZooID": int, |
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}) |
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Animal.many_to_one('ZooID', Zoo, 'ID') |
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# Set up a global Arena object. |
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arena = dejavu.Arena() |
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conf = {u'Connect': |
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r"PROVIDER=MICROSOFT.JET.OLEDB.4.0;DATA SOURCE=C:\zookeeper.mdb;"} |
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arena.add_store("main", "dejavu.storage.storeado.StorageManagerADO_MSAccess", conf)) |
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arena.register_all(globals())</pre> |
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<p>The above creates the model for the zookeeper application. |
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There are three basic things happening: |
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<ol> |
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<li>The <tt>Zoo</tt> and <tt>Animal</tt> classes, which subclass |
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<tt>dejavu.Unit</tt>. These will correspond to the Zoo and |
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Animal tables within the database. Notice the two different |
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methods of declaring Unit properties. Each class also inherits |
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an 'ID' property (an int) from <tt>dejavu.Unit</tt>.</li> |
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<li>The association between the Animal class and the Zoo class |
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(many-to-one).</li> |
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<li>The setup of a dejavu <tt>Arena</tt> object, including a Storage |
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Manager which uses a Microsoft Access (Jet) database.</li> |
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</ol> |
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</p> |
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<p>Here's a simple interactive session which uses the above (assume that |
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tables have been created and populated elsewhere):</p> |
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<pre>>>> import zookeeper |
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>>> box = zookeeper.arena.new_sandbox() |
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>>> box.recall(zookeeper.Animal) |
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[<zookeeper.Animal object at 0x013281F0>, <zookeeper.Animal object at 0x01328150>, |
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<zookeeper.Animal object at 0x01328130>, <zookeeper.Animal object at 0x01328230>] |
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>>> box.recall(zookeeper.Zoo) |
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[] |
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>>> zoo = zookeeper.Zoo(Name='San Diego Zoo', Size='38') |
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>>> box.memorize(zoo) |
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>>> zoo.ID |
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1 |
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>>> box.unit(zookeeper.Zoo, ID=1) is zoo |
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True |
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>>> for creature in box.recall(zookeeper.Animal): |
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zoo.add(creature) |
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>>> len(zoo.Animal()) |
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4</pre> |
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<h3>Design Goals</h3> |
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<p>Dejavu is designed to function in environments with complex integration |
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needs, and tends to separate concerns as much as possible. In particular, |
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Dejavu tries to avoid making decisions in the framework which are better |
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left to developers. Some of those decisions are: |
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<ul> |
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<li>Which user interface style to use.</li> |
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<li>Application package architecture. You can place your application |
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within a single Python module, or develop complete packages.</li> |
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<li>Which types to use for <tt>Unit</tt> properties.</li> |
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<li>Which keys to use when associating <tt>Unit</tt> classes.</li> |
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</ul> |
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In the same way, Dejavu tries to avoid having developers make decisions |
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which are better left to deployers. Some of those decisions are: |
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<ul> |
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<li>Where (and how) to log error messages.</li> |
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<li>Which storage mechanism (database or ...?) to use. In particular, |
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deployers are allowed to mix and match stores, including how |
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and when to cache objects in memory. Dejavu tries to make |
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it easy for <i>deployers</i> to tune applications to their |
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particular environment.</li> |
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</ul> |
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</p> |
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<p>Unlike most generic storage wrappers, Dejavu does not <i>require</i> you |
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to have complete control of your back end. For example, consider Mission |
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Control, the first application built on Dejavu. Mission Control required |
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an ORM which transparently supported two very different backends. Half of |
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the data was to be stored in an MS Access database (which is being migrated |
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to SQL Server), over which the application developers had full control. |
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But half of the data was stored in a third-party application, "The Raiser's |
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Edge" (RE) from Blackbaud. RE provides read-only database access; all writes |
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must go through their object-oriented API. Further, reading via that API was |
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found to be too slow. Therefore, a custom Storage Manager (about 2500 lines |
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of code) was developed, which searches for and loads objects via SQL, but |
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writes Unit data via the REAPI. Dejavu allows the application logic to be |
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completely ignorant of this complex mass of storage details. If Blackbaud |
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closed its doors tomorrow, the solution could be quickly migrated to another |
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data store; business downtime is reduced in the face of inevitable change.<p> |
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<h3>Obtaining and Installing</h3> |
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<p>You can obtain Dejavu from its Subversion repository at |
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<tt>http://projects.amor.org/dejavu/svn/trunk</tt>. Dejavu is designed to be |
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installed in <tt>site-packages/dejavu</tt> or some other root python |
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path.</p> |
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<p>Dejavu was built using Python 2.3.2. You should probably use |
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at least 2.3; Dejavu depends upon the <tt>datetime</tt> module. |
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Although Dejavu <i>supports</i> additional modules like |
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<tt>fixedpoint</tt> and <tt>decimal</tt>, it does not <i>require</i> |
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them.</p> |
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<p>Dejavu uses bytecode hacks, and therefore requires CPython |
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<a href='#cpython'>[2]</a>.</p> |
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<h3>Compared To Other Database Wrappers</h3> |
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<h4>SQLObject</h4> |
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<p>No matter what project I start on, odds are I'll discover that Ian |
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Bicking has already done the same thing, usually better. |
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<br />See http://blog.ianbicking.org/another-less-sleepy-alternative-to-hibernate.html |
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<br />Which was a reply to Ruby's ActiveRecord: |
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http://www.loudthinking.com/arc/000297.html |
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<br />Which was a reply to Java's Hibernate: |
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http://informit.com/guides/content.asp?g=java&seqNum=127&f1=rss</p> |
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<p>Using dejavu, the application developer supplies the following code |
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to define the Units and their relationships:</p> |
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<pre>from dejavu import * |
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import fixedpoint # or decimal, for Python 2.4+ |
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import datetime |
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class Book(Unit): |
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# The ID field is already set to 'int' for all Unit subclasses. |
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title = UnitProperty(str) |
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price = UnitProperty(fixedpoint.Fixedpoint) |
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publishDate = UnitProperty(datetime.datetime) |
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publisher = UnitProperty(int) |
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def addAuthor(self, author): |
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a = Authorship() |
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a.authorID = author.ID |
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a.bookID = self.ID |
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self.sandbox.memorize(a) |
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def author_names(self): |
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names = [] |
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for authorship in self.Authorship(): |
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author = authorship.Author() |
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if author: |
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names.append(author.name) |
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return u', '.join(names) |
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class Publisher(Unit): |
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name = UnitProperty(str) |
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class Author(Unit): |
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name = UnitProperty(str) |
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class Authorship(Unit): |
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authorID = UnitProperty(int) |
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bookID = UnitProperty(int) |
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Book.many_to_one('publisher', Publisher, 'ID') |
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Authorship.many_to_one('bookID', Book, 'ID') |
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Authorship.many_to_one('authorID', Author, 'ID') |
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arena = Arena() |
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arena.register_all(globals()) |
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</pre> |
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<p>The deployer would write in a .conf file:</p> |
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<pre>[Books] |
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Class: dejavu.storage.storepypgsql.StorageManagerPgSQL |
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Connect: host=localhost dbname=bookstore user=postgres password=**** |
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Create If Missing: True</pre> |
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<p>To create the tables:</p> |
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<pre>for cls in (Author, Publisher, Book): |
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arena.create_storage(cls)</pre> |
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<p>The app developer's runtime code reads as follows:</p> |
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<pre> |
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box = arena.new_sandbox() |
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ppython = Book() |
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ppython.title = 'Programming Python' |
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ppython.price = 20 |
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ppython.publishDate = datetime.datetime(2001, 3, 1) |
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# This next line is redundant; all properties default to None. |
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# But explicitness is rarely a bad thing. |
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ppython.publisher = None |
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box.memorize(ppython) |
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print ppython.title # output: 'Programming Python' |
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mlutz = Author(name = 'Mark Lutz') |
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box.memorize(mlutz) # give mlutz an ID |
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ppython.addAuthor(mlutz) |
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print len(ppython.Authorship()) # output: 1 |
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print ppython.author_names() # output: 'Mark Lutz' |
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oreilly = Publisher(name="O'Reilly") |
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box.memorize(oreilly) # give oreilly an ID |
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ppython.publisher = oreilly.ID |
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print ppython.Publisher().name # output: "O'Reilly" |
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print len(oreilly.Book()) # output: 1 |
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print 'Hi,', oreilly.Book().author_names() # output: "Hi, Mark Lutz" |
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</pre> |
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</p> |
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<hr /> |
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|
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<p><a name='fowler'>[1]</a> Fowler, |
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<a href='http://www.martinfowler.com/eaaCatalog/identityMap.html'>Patterns |
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of Enterprise Application Architecture</a>.<br /> |
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<a name='cpython'>[2]</a> Dejavu relies upon bytecode hacking to achieve |
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its clean lambda syntax for data queries. Therefore, it is CPython-specific. |
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In addition, the bytecode of Python may change from one version of Python |
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to another; if you find your version of Python does not work with Dejavu's |
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<tt>codewalk</tt> and <tt>logic</tt> modules, please let me know.<br /> |
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</p> |
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</body> |
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</html> |
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