Metadata-Version: 1.1
Name: zc.queue
Version: 2.0.0a1
Summary: Queues that are optimized for persistency via the ZODB.

Home-page: http://pypi.python.org/pypi/zc.queue
Author: Zope Project
Author-email: zope-dev@zope.org
License: ZPL 2.1
Description: =================
        Persistent Queues
        =================
        
        Persistent queues are simply queues that are optimized for persistency via the
        ZODB. They assume that the ZODB is using MVCC to avoid read conflicts. They
        attempt to resolve write conflicts so that transactions that add and remove
        objects simultaneously are merged, unless the transactions are trying to
        remove the same value from the queue.
        
        An important characteristic of these queues is that they do not expect to
        hold more than one reference to any given equivalent item at a time.  For
        instance, some of the conflict resolution features will not perform
        desirably if it is reasonable for your application to hold two copies of the
        string "hello" within the same queue at once [#why]_.
        
        The module provides two flavors: a simple persistent queue that keeps all
        contained objects in one persistent object (`Queue`), and a
        persistent queue that divides up its contents into multiple composite
        elements (`CompositeQueue`). They should be equivalent in terms of
        API and so are mostly examined in the abstract in this document: we'll generate
        instances with a representative `Queue` factory, that could be either class.
        They only differ in an aspect of their write conflict resolution behavior,
        which is discussed below.
        
        Queues can be instantiated with no arguments.
        
            >>> q = Queue()
            >>> from zc.queue.interfaces import IQueue
            >>> from zope.interface.verify import verifyObject
            >>> verifyObject(IQueue, q)
            True
        
        The basic API is simple: use `put` to add items to the back of the queue, and
        `pull` to pull things off the queue, defaulting to the front of the queue.
        Note that `Item` could be either persistent or non persistent object.
        
            >>> q.put(Item(1))
            >>> q.put(Item(2))
            >>> q.pull()
            1
            >>> q.put(Item(3))
            >>> q.pull()
            2
            >>> q.pull()
            3
        
        The `pull` method takes an optional zero-based index argument, and can accept
        negative values.
        
            >>> q.put(Item(4))
            >>> q.put(Item(5))
            >>> q.put(Item(6))
            >>> q.pull(-1)
            6
            >>> q.pull(1)
            5
            >>> q.pull(0)
            4
        
        Requesting an item from an empty queue raises an IndexError.
        
            >>> q.pull() # doctest: +ELLIPSIS
            Traceback (most recent call last):
            ...
            IndexError: ...
        
        Requesting an invalid index value does the same.
        
            >>> q.put(Item(7))
            >>> q.put(Item(8))
            >>> q.pull(2) # doctest: +ELLIPSIS
            Traceback (most recent call last):
            ...
            IndexError: ...
        
        Beyond these core queue operations, queues support len...
        
            >>> len(q)
            2
            >>> q.pull()
            7
            >>> len(q)
            1
            >>> q.pull()
            8
            >>> len(q)
            0
        
        ...iter (which does *not* empty the queue)...
        
            >>> next(iter(q))
            Traceback (most recent call last):
            ...
            StopIteration
            >>> q.put(Item(9))
            >>> q.put(Item(10))
            >>> q.put(Item(11))
            >>> next(iter(q))
            9
            >>> [i for i in q]
            [9, 10, 11]
            >>> q.pull()
            9
            >>> [i for i in q]
            [10, 11]
        
        ...bool...
        
            >>> bool(q)
            True
            >>> q.pull()
            10
            >>> q.pull()
            11
            >>> bool(q)
            False
        
        ...and list-like bracket access (which again does *not* empty the queue).
        
            >>> q.put(Item(12))
            >>> q[0]
            12
            >>> q.pull()
            12
            >>> q[0] # doctest: +ELLIPSIS
            Traceback (most recent call last):
            ...
            IndexError: ...
            >>> for i in range (13, 23):
            ...     q.put(Item(i))
            ...
            >>> q[0]
            13
            >>> q[1]
            14
            >>> q[2]
            15
            >>> q[-1]
            22
            >>> q[-10]
            13
        
        That's it--there's no additional way to add anything beyond `put`, and no
        additional way to remove anything beyond `pull`.
        
        The only other wrinkle is the conflict resolution code.  Conflict
        resolution in ZODB has some general caveats of which you should be aware
        [#caveats]_.
        
        These general caveats aside, we'll now examine some examples of zc.queue
        conflict resolution at work.  To show this, we will have to have two
        copies of the same queue, from two different connections.
        
        NOTE: this testing approach has known weaknesses.  See discussion in tests.py.
        
            >>> import transaction
            >>> from zc.queue.tests import ConflictResolvingMappingStorage
            >>> from ZODB import DB
            >>> db = DB(ConflictResolvingMappingStorage('test'))
            >>> transactionmanager_1 = transaction.TransactionManager()
            >>> transactionmanager_2 = transaction.TransactionManager()
            >>> connection_1 = db.open(transaction_manager=transactionmanager_1)
            >>> root_1 = connection_1.root()
        
            >>> q_1 = root_1["queue"] = Queue()
            >>> transactionmanager_1.commit()
        
            >>> transactionmanager_2 = transaction.TransactionManager()
            >>> connection_2 = db.open(transaction_manager=transactionmanager_2)
            >>> root_2 = connection_2.root()
            >>> q_2 = root_2['queue']
        
        Now we have two copies of the same queue, with separate transaction managers
        and connections about the same way two threads would have them. The '_1'
        suffix identifies the objects for user 1, in thread 1; and the '_2' suffix
        identifies the objects for user 2, in a concurrent thread 2.
        
        First, let's have the two users add some items to the queue concurrently.
        For concurrent commits of only putting a single new item (one each in two
        transactions), in both types of queue the user who commits first gets the
        lower position in the queue--that is, the position that will leave the queue
        sooner using default `pull` calls.
        
        In this example, even though q_1 is modified first, q_2's transaction is
        committed first, so q_2's addition is first after the merge.
        
            >>> q_1.put(Item(1001))
            >>> q_2.put(Item(1000))
            >>> transactionmanager_2.commit()
            >>> transactionmanager_1.commit()
            >>> connection_1.sync()
            >>> connection_2.sync()
            >>> list(q_1)
            [1000, 1001]
            >>> list(q_2)
            [1000, 1001]
        
        For commits of more than one additions per connection of two, or of more than
        two concurrent adding transactions, the behavior is the same for the
        Queue: the first commit's additions will go before the second
        commit's.
        
            >>> from zc import queue
            >>> if isinstance(q_1, queue.Queue):
            ...     for i in range(5):
            ...         q_1.put(Item(i))
            ...     for i in range(1002, 1005):
            ...         q_2.put(Item(i))
            ...     transactionmanager_2.commit()
            ...     transactionmanager_1.commit()
            ...     connection_1.sync()
            ...     connection_2.sync()
            ...
        
        As we'll see below, that will again reliably put all the values from the first
        commit earlier in the queue, to result in
        [1000, 1001, 1002, 1003, 1004, 0, 1, 2, 3, 4].
        
        For the CompositeQueue, the behavior is different.  The order
        will be maintained with a set of additions in a transaction, but the values
        may be merged between the two transactions' additions.  We will compensate
        for that here to get a reliable queue state.
        
            >>> if isinstance(q_1, queue.CompositeQueue):
            ...     for i1, i2 in ((1002, 1003), (1004, 0), (1, 2), (3, 4)):
            ...         q_1.put(Item(i1))
            ...         q_2.put(Item(i2))
            ...         transactionmanager_1.commit()
            ...         transactionmanager_2.commit()
            ...         connection_1.sync()
            ...         connection_2.sync()
            ...
        
        Whichever kind of queue we have, we now have the following values.
        
            >>> list(q_1)
            [1000, 1001, 1002, 1003, 1004, 0, 1, 2, 3, 4]
            >>> list(q_2)
            [1000, 1001, 1002, 1003, 1004, 0, 1, 2, 3, 4]
        
        If two users try to add the same item, then a conflict error is raised.
        
            >>> five = Item(5)
            >>> q_1.put(five)
            >>> q_2.put(five)
            >>> transactionmanager_1.commit()
            >>> from ZODB.POSException import ConflictError, InvalidObjectReference
            >>> try:
            ...     transactionmanager_2.commit() # doctest: +ELLIPSIS
            ... except (ConflictError, InvalidObjectReference):
            ...     print("Conflict Error")
            Conflict Error
            >>> transactionmanager_2.abort()
            >>> connection_1.sync()
            >>> connection_2.sync()
            >>> list(q_1)
            [1000, 1001, 1002, 1003, 1004, 0, 1, 2, 3, 4, 5]
            >>> list(q_2)
            [1000, 1001, 1002, 1003, 1004, 0, 1, 2, 3, 4, 5]
        
        Users can also concurrently remove items from a queue...
        
            >>> q_1.pull()
            1000
            >>> q_1[0]
            1001
        
            >>> q_2.pull(5)
            0
            >>> q_2[5]
            1
        
            >>> q_2[0] # 1000 value still there in this connection
            1000
        
            >>> q_1[4] # 0 value still there in this connection.
            0
        
            >>> transactionmanager_1.commit()
            >>> transactionmanager_2.commit()
            >>> connection_1.sync()
            >>> connection_2.sync()
            >>> list(q_1)
            [1001, 1002, 1003, 1004, 1, 2, 3, 4, 5]
            >>> list(q_2)
            [1001, 1002, 1003, 1004, 1, 2, 3, 4, 5]
        
        ...as long as they don't remove the same item.
        
            >>> q_1.pull()
            1001
            >>> q_2.pull()
            1001
            >>> transactionmanager_1.commit()
            >>> transactionmanager_2.commit() # doctest: +ELLIPSIS
            Traceback (most recent call last):
            ...
            ConflictError: ...
            >>> transactionmanager_2.abort()
            >>> connection_1.sync()
            >>> connection_2.sync()
            >>> list(q_1)
            [1002, 1003, 1004, 1, 2, 3, 4, 5]
            >>> list(q_2)
            [1002, 1003, 1004, 1, 2, 3, 4, 5]
        
        There's actually a special case: the composite queue's buckets will refuse to
        merge if they started with a non-empty state, and one of the two new states
        is empty.  This is to prevent the loss of an addition to the queue.  See
        tests.py for an example.
        
        Also importantly, users can concurrently remove and add items to a queue.
        
            >>> q_1.pull()
            1002
            >>> q_1.pull()
            1003
            >>> q_1.pull()
            1004
            >>> q_2.put(Item(6))
            >>> q_2.put(Item(7))
            >>> transactionmanager_1.commit()
            >>> transactionmanager_2.commit()
            >>> connection_1.sync()
            >>> connection_2.sync()
            >>> list(q_1)
            [1, 2, 3, 4, 5, 6, 7]
            >>> list(q_2)
            [1, 2, 3, 4, 5, 6, 7]
        
        As a final example, we'll show the conflict resolution code under extreme
        duress, with multiple simultaneous puts and pulls.
        
            >>> res_1 = []
            >>> for i in range(6, -1, -2):
            ...     res_1.append(q_1.pull(i))
            ...
            >>> res_1
            [7, 5, 3, 1]
            >>> res_2 = []
            >>> for i in range(5, 0, -2):
            ...     res_2.append(q_2.pull(i))
            ...
            >>> res_2
            [6, 4, 2]
            >>> for i in range(8, 12):
            ...     q_1.put(Item(i))
            ...
            >>> for i in range(12, 16):
            ...     q_2.put(Item(i))
            ...
            >>> list(q_1)
            [2, 4, 6, 8, 9, 10, 11]
            >>> list(q_2)
            [1, 3, 5, 7, 12, 13, 14, 15]
            >>> transactionmanager_1.commit()
            >>> transactionmanager_2.commit()
            >>> connection_1.sync()
            >>> connection_2.sync()
        
        After these commits, if the queue is a Queue, the new values are
        in the order of their commit.  However, as discussed above, if the queue is
        a CompositeQueue the behavior is different. While the order will be
        maintained comparitively--so if object `A` is ahead of object `B` in the queue
        on commit then `A` will still be ahead of `B` after a merge of the conflicting
        transactions--values may be interspersed between the two transactions.
        
        For instance, if our example queue were a Queue, the values would
        be [8, 9, 10, 11, 12, 13, 14, 15].  However, if it were a
        CompositeQueue, the values might be the same, or might be any
        combination in which [8, 9, 10, 11] and [12, 13, 14, 15], from the two
        transactions, are still in order.  One ordering might be
        [8, 9, 12, 13, 10, 11, 14, 15], for instance.
        
            >>> if isinstance(q_1, queue.Queue):
            ...     res_1 = list(q_1)
            ...     res_2 = list(q_2)
            ... elif isinstance(q_1, queue.CompositeQueue):
            ...     firstsrc_1 = list(q_1)
            ...     firstsrc_2 = list(q_2)
            ...     secondsrc_1 = firstsrc_1[:]
            ...     secondsrc_2 = firstsrc_2[:]
            ...     for val in [12, 13, 14, 15]:
            ...         firstsrc_1.remove(Item(val))
            ...         firstsrc_2.remove(Item(val))
            ...     for val in [8, 9, 10, 11]:
            ...         secondsrc_1.remove(Item(val))
            ...         secondsrc_2.remove(Item(val))
            ...     res_1 = firstsrc_1 + secondsrc_1
            ...     res_2 = firstsrc_2 + secondsrc_2
            ...
            >>> res_1
            [8, 9, 10, 11, 12, 13, 14, 15]
            >>> res_2
            [8, 9, 10, 11, 12, 13, 14, 15]
        
            >>> db.close() # cleanup
        
        
        ========================
        PersistentReferenceProxy
        ========================
        
        As `ZODB.ConflictResolution.PersistentReference` doesn't get handled
        properly in `set` due to lack of `__hash__` method, we define a class
        utilizing `__cmp__` method of contained items [#workaround]_.
        
        
        Let's make some stub persistent reference objects. Also make some
        objects that have same oid to simulate different transaction states.
        
            >>> from zc.queue.tests import StubPersistentReference
            >>> pr1 = StubPersistentReference(1)
            >>> pr2 = StubPersistentReference(2)
            >>> pr3 = StubPersistentReference(3)
            >>> pr_c1 = StubPersistentReference(1)
            >>> pr_c2 = StubPersistentReference(2)
            >>> pr_c3 = StubPersistentReference(3)
        
            >>> pr1 == pr_c1
            True
            >>> pr2 == pr_c2
            True
            >>> pr3 == pr_c3
            True
            >>> id(pr1) == id(pr_c1)
            False
            >>> id(pr2) == id(pr_c2)
            False
            >>> id(pr3) == id(pr_c3)
            False
        
            >>> set1 = set((pr1, pr2))
            >>> set1
            set([SPR (1), SPR (2)])
            >>> len(set1)
            2
            >>> set2 = set((pr_c1, pr_c3))
            >>> set2
            set([SPR (1), SPR (3)])
            >>> len(set2)
            2
            >>> set_c1 = set((pr_c1, pr_c2))
            >>> set_c1
            set([SPR (1), SPR (2)])
            >>> len(set_c1)
            2
        
        `set` doesn't handle persistent reference objects properly. All
        following set operations produce wrong results.
        
        Deduplication:
        
            >>> set((pr1, pr_c1))
            set([SPR (1), SPR (1)])
            >>> set((pr2, pr_c2))
            set([SPR (2), SPR (2)])
            >>> set((pr1, pr_c1, pr2))
            set([SPR (1), SPR (1), SPR (2)])
            >>> set4 = set((pr1, pr2, pr3, pr_c1, pr_c2, pr_c3))
            >>> len(set4)
            6
        
        Minus operation:
        
            >>> set3 = set1 - set2
            >>> len(set3)
            2
            >>> set3
            set([SPR (1), SPR (2)])
        
        Contains:
        
            >>> pr3 in set2
            False
        
        Intersection:
        
            >>> set1 & set2
            set([])
        
        Compare:
        
            >>> set1 == set_c1
            False
        
        So we made `PersistentReferenceProxy` wrapping `PersistentReference`
        to work with sets.
        
            >>> from zc.queue._queue import PersistentReferenceProxy
            >>> prp1 = PersistentReferenceProxy(pr1)
            >>> prp2 = PersistentReferenceProxy(pr2)
            >>> prp3 = PersistentReferenceProxy(pr3)
            >>> prp_c1 = PersistentReferenceProxy(pr_c1)
            >>> prp_c2 = PersistentReferenceProxy(pr_c2)
            >>> prp_c3 = PersistentReferenceProxy(pr_c3)
            >>> prp1 == prp_c1
            True
            >>> prp2 == prp_c2
            True
            >>> prp3 == prp_c3
            True
            >>> id(prp1) == id(prp_c1)
            False
            >>> id(prp2) == id(prp_c2)
            False
            >>> id(prp3) == id(prp_c3)
            False
        
            >>> set1 = set((prp1, prp2))
            >>> set1
            set([SPR (1), SPR (2)])
            >>> len(set1)
            2
            >>> set2 = set((prp_c1, prp_c3))
            >>> set2
            set([SPR (1), SPR (3)])
            >>> len(set2)
            2
            >>> set_c1 = set((prp_c1, prp_c2))
            >>> set_c1
            set([SPR (1), SPR (2)])
            >>> len(set_c1)
            2
        
        `set` handles persistent reference properly now. All following set
        operations produce correct results.
        
        Deduplication:
        
            >>> set4 = set((prp1, prp2, prp3, prp_c1, prp_c2, prp_c3))
            >>> len(set4)
            3
            >>> set((prp1, prp_c1))
            set([SPR (1)])
            >>> set((prp2, prp_c2))
            set([SPR (2)])
            >>> set((prp1, prp_c1, prp2))
            set([SPR (1), SPR (2)])
        
        Minus operation:
        
            >>> set3 = set1 - set2
            >>> len(set3)
            1
            >>> set3
            set([SPR (2)])
            >>> set1 - set1
            set([])
            >>> set2 - set3
            set([SPR (1), SPR (3)])
            >>> set3 - set2
            set([SPR (2)])
        
        Contains:
        
            >>> prp3 in set2
            True
            >>> prp1 in set2
            True
            >>> prp_c1 in set2
            True
            >>> prp2 not in set2
            True
        
        Intersection:
        
            >>> set1 & set2
            set([SPR (1)])
            >>> set1 & set_c1
            set([SPR (1), SPR (2)])
            >>> set2 & set3
            set([])
        
        Compare:
        
            >>> set1 == set_c1
            True
            >>> set1 == set2
            False
            >>> set1 == set4
            False
        
        
        -----
        
        .. [#why] The queue's `pull` method is actually the interesting part in why
            this constraint is used, and it becomes more so when you allow an
            arbitrary pull.  By asserting that you do not support having equal
            items in the queue at once, you can simply say that when you remove
            equal objects in the current state and the contemporary, conflicting
            state, it's a conflict error.  Ideally you don't enter another equal
            item in that queue again, or else in fact this is still an
            error-prone heuristic:
        
              - start queue == [X];
              - begin transactions A and B;
              - B removes X and commits;
              - transaction C adds X and Y and commits;
              - transaction A removes X and tries to commit, and conflict resolution
                code believes that it is ok to remove the new X from transaction C
                because it looks like it was just an addition of Y).  Commit succeeds,
                and should not.
        
            If you don't assert that you can use equality to examine conflicts,
            then you have to come up with another heuristic.  Given that the
            conflict resolution code only gets three states to resolve, I don't
            know of a reliable one.
        
            Therefore, zc.queue has a policy of assuming that it can use
            equality to distinguish items.  It's limiting, but the code can have
            a better confidence of doing the right thing.
        
            Also, FWIW, this is policy I want: for my use cases, it would be
            possible to put in two items in a queue that handle the same issue.
            With the right equality code, this can be avoided with the policy
            the queue has now.
        
        .. [#caveats] Here are a few caveats about the state (as of this
            writing) of ZODB conflict resolution in general.
        
            The biggest is that, if you store persistent.Persistent subclass
            objects in a queue (or any other collection with conflict resolution
            code, such as a BTree), the collection will get a placeholder object
            (ZODB.ConflictResolution.PersistentReference), rather than the real
            contained object.  This object has __cmp__ method, but doesn't have
            __hash__ method, The same oid will get different placeholder in the
            different states because of different identity in memory (e.g. `id(obj)`)
            for conflict resolution, which is wrong behavior in a queue.
        
            Another is that, in ZEO, conflict resolution is currently done on
            the server, so the ZEO server must have a copy of the classes
            (software) necessary to instantiate any non-persistent object in the
            collection.
        
            A corollary to the above is that objects such as
            zope.app.keyreference.persistent, which are not persistent
            themselves but rely on a persistent object for their __cmp__, will
            fail during conflict resolution.  A reasonable solution in the case
            of zope.app.keyreference.persistent code is to have the object store
            the information it needs to do the comparison on itself, so the
            absence of the persistent object during conflict resolution is
            unimportant.
        
        .. [#workaround] The reason why we defined
            `PersistentReferenceProxy` is that there would be a significant risk
            of unintended consequenses for some ZODB users if we add __hash__
            method to PersistentReference.
        
        
        =======
        CHANGES
        =======
        
        2.0.0a1 (2013-03-01)
        ====================
        
        - Added support for Python 3.3.
        
        - Replaced deprecated ``zope.interface.implements`` usage with equivalent
          ``zope.interface.implementer`` decorator.
        
        - Dropped support for Python 2.4 and 2.5.
        
        - Fixed an issue where slicing a composite queue would fail due to a
          programming error.
          [malthe]
        
        
        1.3 (2012-01-11)
        ================
        
        - Fixed a conflict resolution bug that didn't handle
          `ZODB.ConflictResolution.PersistentReference` correctly.
          Note that due to syntax we require Python 2.5 or higher now.
        
        
        1.2.1 (2011-12-17)
        ==================
        
        - Fixed ImportError in setup.py.
          [maurits]
        
        
        1.2 (2011-12-17)
        ================
        
        - Fixed undefined ZODB.POSException.StorageTransactionError in tests.
        
        - Let tests pass with ZODB 3.8 and ZODB 3.9.
        
        - Added test extra to declare test dependency on ``zope.testing``.
        
        - Using Python's ``doctest`` module instead of deprecated
          ``zope.testing.doctest``.
        
        - Clean up the generation of reST docs.
        
        
        1.1
        ===
        
        - Fixed a conflict resolution bug in CompositeQueue
        
        - Renamed PersistentQueue to Queue, CompositePersistentQueue to
          CompositeQueue. The old names are nominally deprecated, although no
          warnings are generated and there are no current plans to eliminate
          them.  The PersistentQueue class has more conservative conflict
          resolution than it used to.  (The Queue class has the same conflict
          resolution as the PersistentQueue used to have.)
        
        1.0.1
        =====
        
        - Minor buildout changes
        
        - Initial release to PyPI
        
        1.0
        ===
        
        - Initial release to zope.org
        
Keywords: zope zope3
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Zope Public License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Framework :: Zope3
