Tests for persistent.Persistent =============================== This document is an extended doc test that covers the basics of the Persistent base class. The test expects a class named 'P' to be provided in its globals. The P class implements the Persistent interface. Test framework -------------- The class P needs to behave like ExampleP. (Note that the code below is *not* part of the tests.) class ExampleP(Persistent): def __init__(self): self.x = 0 def inc(self): self.x += 1 The tests use stub data managers. A data manager is responsible for loading and storing the state of a persistent object. It's stored in the _p_jar attribute of a persistent object. >>> class DM: ... def __init__(self): ... self.called = 0 ... def register(self, ob): ... self.called += 1 ... def setstate(self, ob): ... ob.__setstate__({'x': 42}) >>> class BrokenDM(DM): ... def register(self,ob): ... self.called += 1 ... raise NotImplementedError ... def setstate(self,ob): ... raise NotImplementedError >>> from persistent import Persistent Test Persistent without Data Manager ------------------------------------ First do some simple tests of a Persistent instance that does not have a data manager (_p_jar). >>> p = P() >>> p.x 0 >>> p._p_changed False >>> p._p_state 0 >>> p._p_jar >>> p._p_oid Verify that modifications have no effect on _p_state of _p_changed. >>> p.inc() >>> p.inc() >>> p.x 2 >>> p._p_changed False >>> p._p_state 0 Try all sorts of different ways to change the object's state. >>> p._p_deactivate() >>> p._p_state 0 >>> p._p_changed = True >>> p._p_state 0 >>> del p._p_changed >>> p._p_changed False >>> p._p_state 0 >>> p.x 2 Test Persistent with Data Manager --------------------------------- Next try some tests of an object with a data manager. The DM class is a simple testing stub. >>> p = P() >>> dm = DM() >>> p._p_oid = "00000012" >>> p._p_jar = dm >>> p._p_changed 0 >>> dm.called 0 Modifying the object marks it as changed and registers it with the data manager. Subsequent modifications don't have additional side-effects. >>> p.inc() >>> p._p_changed 1 >>> dm.called 1 >>> p.inc() >>> p._p_changed 1 >>> dm.called 1 It's not possible to deactivate a modified object. >>> p._p_deactivate() >>> p._p_changed 1 It is possible to invalidate it. That's the key difference between deactivation and invalidation. >>> p._p_invalidate() >>> p._p_state -1 Now that the object is a ghost, any attempt to modify it will require that it be unghosted first. The test data manager has the odd property that it sets the object's 'x' attribute to 42 when it is unghosted. >>> p.inc() >>> p.x 43 >>> dm.called 2 You can manually reset the changed field to False, although it's not clear why you would want to do that. The object changes to the UPTODATE state but retains its modifications. >>> p._p_changed = False >>> p._p_state 0 >>> p._p_changed False >>> p.x 43 >>> p.inc() >>> p._p_changed True >>> dm.called 3 __getstate__() and __setstate__() --------------------------------- The next several tests cover the __getstate__() and __setstate__() implementations. >>> p = P() >>> state = p.__getstate__() >>> isinstance(state, dict) True >>> state['x'] 0 >>> p._p_state 0 Calling setstate always leaves the object in the uptodate state? (I'm not entirely clear on this one.) >>> p.__setstate__({'x': 5}) >>> p._p_state 0 Assigning to a volatile attribute has no effect on the object state. >>> p._v_foo = 2 >>> p.__getstate__() {'x': 5} >>> p._p_state 0 The _p_serial attribute is not affected by calling setstate. >>> p._p_serial = "00000012" >>> p.__setstate__(p.__getstate__()) >>> p._p_serial '00000012' Change Ghost test ----------------- If an object is a ghost and it's _p_changed is set to True, it should have no effect. >>> p = P() >>> p._p_jar = DM() >>> p._p_oid = 1 >>> p._p_deactivate() >>> p._p_changed >>> p._p_state -1 >>> p._p_changed = True >>> p._p_changed >>> p._p_state -1 Activate, deactivate, and invalidate ------------------------------------ Some of these tests are redundant, but are included to make sure there are explicit and simple tests of _p_activate(), _p_deactivate(), and _p_invalidate(). >>> p = P() >>> p._p_oid = 1 >>> p._p_jar = DM() >>> p._p_deactivate() >>> p._p_state -1 >>> p._p_activate() >>> p._p_state 0 >>> p.x 42 >>> p.inc() >>> p.x 43 >>> p._p_state 1 >>> p._p_invalidate() >>> p._p_state -1 >>> p.x 42 Test failures ------------- The following tests cover various errors cases. When an object is modified, it registers with its data manager. If that registration fails, the exception is propagated and the object stays in the up-to-date state. It shouldn't change to the modified state, because it won't be saved when the transaction commits. >>> p = P() >>> p._p_oid = 1 >>> p._p_jar = BrokenDM() >>> p._p_state 0 >>> p._p_jar.called 0 >>> p._p_changed = 1 Traceback (most recent call last): ... NotImplementedError >>> p._p_jar.called 1 >>> p._p_state 0 Make sure that exceptions that occur inside the data manager's setstate() method propagate out to the caller. >>> p = P() >>> p._p_oid = 1 >>> p._p_jar = BrokenDM() >>> p._p_deactivate() >>> p._p_state -1 >>> p._p_activate() Traceback (most recent call last): ... NotImplementedError >>> p._p_state -1 Special test to cover layout of __dict__ ---------------------------------------- We once had a bug in the Persistent class that calculated an incorrect offset for the __dict__ attribute. It assigned __dict__ and _p_jar to the same location in memory. This is a simple test to make sure they have different locations. >>> p = P() >>> p.inc() >>> p.inc() >>> 'x' in p.__dict__ True >>> p._p_jar Inheritance and metaclasses --------------------------- Simple tests to make sure it's possible to inherit from the Persistent base class multiple times. There used to be metaclasses involved in Persistent that probably made this a more interesting test. >>> class A(Persistent): ... pass >>> class B(Persistent): ... pass >>> class C(A, B): ... pass >>> class D(object): ... pass >>> class E(D, B): ... pass >>> a = A() >>> b = B() >>> c = C() >>> d = D() >>> e = E() Also make sure that it's possible to define Persistent classes that have a custom metaclass. >>> class alternateMeta(type): ... type >>> class alternate(object): ... __metaclass__ = alternateMeta >>> class mixedMeta(alternateMeta, type): ... pass >>> class mixed(alternate, Persistent): ... pass >>> class mixed(Persistent, alternate): ... pass Basic type structure -------------------- >>> Persistent.__dictoffset__ 0 >>> Persistent.__weakrefoffset__ 0 >>> Persistent.__basicsize__ > object.__basicsize__ True >>> P.__dictoffset__ > 0 True >>> P.__weakrefoffset__ > 0 True >>> P.__dictoffset__ < P.__weakrefoffset__ True >>> P.__basicsize__ > Persistent.__basicsize__ True Slots ----- These are some simple tests of classes that have an __slots__ attribute. Some of the classes should have slots, others shouldn't. >>> class noDict(object): ... __slots__ = ['foo'] >>> class p_noDict(Persistent): ... __slots__ = ['foo'] >>> class p_shouldHaveDict(p_noDict): ... pass >>> p_noDict.__dictoffset__ 0 >>> x = p_noDict() >>> x.foo = 1 >>> x.foo 1 >>> x.bar = 1 Traceback (most recent call last): ... AttributeError: 'p_noDict' object has no attribute 'bar' >>> x._v_bar = 1 Traceback (most recent call last): ... AttributeError: 'p_noDict' object has no attribute '_v_bar' >>> x.__dict__ Traceback (most recent call last): ... AttributeError: 'p_noDict' object has no attribute '__dict__' The various _p_ attributes are unaffected by slots. >>> p._p_oid >>> p._p_jar >>> p._p_state 0 If the most-derived class does not specify >>> p_shouldHaveDict.__dictoffset__ > 0 True >>> x = p_shouldHaveDict() >>> isinstance(x.__dict__, dict) True Pickling -------- There's actually a substantial effort involved in making subclasses of Persistent work with plain-old pickle. The ZODB serialization layer never calls pickle on an object; it pickles the object's class description and its state as two separate pickles. >>> import pickle >>> p = P() >>> p.inc() >>> p2 = pickle.loads(pickle.dumps(p)) >>> p2.__class__ is P True >>> p2.x == p.x True We should also test that pickle works with custom getstate and setstate. Perhaps even reduce. The problem is that pickling depends on finding the class in a particular module, and classes defined here won't appear in any module. We could require each user of the tests to define a base class, but that might be tedious. Interfaces ---------- Some versions of Zope and ZODB have the zope.interfaces package available. If it is available, then persistent will be associated with several interfaces. It's hard to write a doctest test that runs the tests only if zope.interface is available, so this test looks a little unusual. One problem is that the assert statements won't do anything if you run with -O. >>> try: ... import zope.interface ... except ImportError: ... pass ... else: ... from persistent.interfaces import IPersistent ... assert IPersistent.implementedBy(Persistent) ... p = Persistent() ... assert IPersistent.providedBy(p) ... assert IPersistent.implementedBy(P) ... p = P() ... assert IPersistent.providedBy(p)