Commit 358034dc authored by Jim Fulton's avatar Jim Fulton

Added locking support for use by storages.

Added a working newTid that replaces the non-working newTimeStamp.

Removed WeakSet, which is moved to the transaction package.
parent dcfb60ab
......@@ -16,6 +16,7 @@
import random
import unittest
from persistent import Persistent
from zope.testing import doctest
NUM = 100
......@@ -89,9 +90,7 @@ class TestUtils(unittest.TestCase):
def test_suite():
return unittest.makeSuite(TestUtils, 'check')
if __name__ == "__main__":
loader = unittest.TestLoader()
loader.testMethodPrefix = "check"
unittest.main(testLoader=loader)
suite = unittest.TestSuite()
suite.addTest(unittest.makeSuite(TestUtils, 'check'))
suite.addTest(doctest.DocFileSuite('../utils.txt'))
return suite
......@@ -31,17 +31,17 @@ __all__ = ['z64',
'u64',
'U64',
'cp',
'newTimeStamp',
'newTid',
'oid_repr',
'serial_repr',
'tid_repr',
'positive_id',
'readable_tid_repr',
'WeakSet',
'DEPRECATED_ARGUMENT',
'deprecated37',
'deprecated38',
'get_pickle_metadata',
'locked',
]
# A unique marker to give as the default value for a deprecated argument.
......@@ -113,14 +113,12 @@ def cp(f1, f2, length=None):
write(data)
length -= len(data)
def newTimeStamp(old=None,
TimeStamp=TimeStamp,
time=time.time, gmtime=time.gmtime):
t = time()
ts = TimeStamp(gmtime(t)[:5]+(t%60,))
def newTid(old):
t = time.time()
ts = TimeStamp(*time.gmtime(t)[:5]+(t%60,))
if old is not None:
return ts.laterThan(old)
return ts
ts = ts.laterThan(TimeStamp(old))
return `ts`
def oid_repr(oid):
......@@ -223,75 +221,52 @@ def get_pickle_metadata(data):
classname = ''
return modname, classname
# A simple implementation of weak sets, supplying just enough of Python's
# sets.Set interface for our needs.
class WeakSet(object):
"""A set of objects that doesn't keep its elements alive.
The objects in the set must be weakly referencable.
The objects need not be hashable, and need not support comparison.
Two objects are considered to be the same iff their id()s are equal.
When the only references to an object are weak references (including
those from WeakSets), the object can be garbage-collected, and
will vanish from any WeakSets it may be a member of at that time.
"""
def __init__(self):
# Map id(obj) to obj. By using ids as keys, we avoid requiring
# that the elements be hashable or comparable.
self.data = weakref.WeakValueDictionary()
def __len__(self):
return len(self.data)
def __contains__(self, obj):
return id(obj) in self.data
# Same as a Set, add obj to the collection.
def add(self, obj):
self.data[id(obj)] = obj
# Same as a Set, remove obj from the collection, and raise
# KeyError if obj not in the collection.
def remove(self, obj):
del self.data[id(obj)]
# f is a one-argument function. Execute f(elt) for each elt in the
# set. f's return value is ignored.
def map(self, f):
for wr in self.as_weakref_list():
elt = wr()
if elt is not None:
f(elt)
# Return a list of weakrefs to all the objects in the collection.
# Because a weak dict is used internally, iteration is dicey (the
# underlying dict may change size during iteration, due to gc or
# activity from other threads). as_weakef_list() is safe.
#
# Something like this should really be a method of Python's weak dicts.
# If we invoke self.data.values() instead, we get back a list of live
# objects instead of weakrefs. If gc occurs while this list is alive,
# all the objects move to an older generation (because they're strongly
# referenced by the list!). They can't get collected then, until a
# less frequent collection of the older generation. Before then, if we
# invoke self.data.values() again, they're still alive, and if gc occurs
# while that list is alive they're all moved to yet an older generation.
# And so on. Stress tests showed that it was easy to get into a state
# where a WeakSet grows without bounds, despite that almost all its
# elements are actually trash. By returning a list of weakrefs instead,
# we avoid that, although the decision to use weakrefs is now# very
# visible to our clients.
def as_weakref_list(self):
# We're cheating by breaking into the internals of Python's
# WeakValueDictionary here (accessing its .data attribute).
return self.data.data.values()
def mktemp(dir=None):
"""Create a temp file, known by name, in a semi-secure manner."""
handle, filename = mkstemp(dir=dir)
os.close(handle)
return filename
class Locked(object):
def __init__(self, func, inst=None, class_=None, preconditions=()):
self.im_func = func
self.im_self = inst
self.im_class = class_
self.preconditions = preconditions
def __get__(self, inst, class_):
return self.__class__(self.im_func, inst, class_, self.preconditions)
def __call__(self, *args, **kw):
inst = self.im_self
if inst is None:
inst = args[0]
func = self.im_func.__get__(self.im_self, self.im_class)
inst._lock_acquire()
try:
for precondition in self.preconditions:
if not precondition(inst):
raise AssertionError(
"Failed precondition: ",
precondition.__doc__.strip())
return func(*args, **kw)
finally:
inst._lock_release()
class locked(object):
def __init__(self, *preconditions):
self.preconditions = preconditions
def __get__(self, inst, class_):
# We didn't get any preconditions, so we have a single "precondition",
# which is actually the function to call.
func, = self.preconditions
return Locked(func, inst, class_)
def __call__(self, func):
return Locked(func, preconditions=self.preconditions)
ZODB Utilits Module
===================
The ZODB.utils module provides a number of helpful, somewhat random
:), utility functions.
>>> import ZODB.utils
This document documents a few of them. Over time, it may document
more.
64-bit integers and strings
---------------------------------
ZODB uses 64-bit transaction ids that are typically represented as
strings, but are sometimes manipulated as integers. Object ids are
strings too and it is common to ise 64-bit strings that are just
packed integers.
Functions p64 and u64 pack and unpack integers as strings:
>>> ZODB.utils.p64(250347764455111456)
'\x03yi\xf7"\xa8\xfb '
>>> print ZODB.utils.u64('\x03yi\xf7"\xa8\xfb ')
250347764455111456
The contant z64 has zero packed as a 64-bit string:
>>> ZODB.utils.z64
'\x00\x00\x00\x00\x00\x00\x00\x00'
Transaction id generation
-------------------------
Storages assign transaction ids as transactions are committed. These
are based on UTC time, but must be strictly increasing. The
newTid function akes this pretty easy.
To see this work (in a predictable way), we'll first hack time.time:
>>> import time
>>> old_time = time.time
>>> time.time = lambda : 1224825068.12
Now, if we ask for a new time stamp, we'll get one based on our faux
time:
>>> tid = ZODB.utils.newTid(None)
>>> tid
'\x03yi\xf7"\xa54\x88'
newTid requires an old tid as an argument. The old tid may be None, if
we don't have a previous transaction id.
This time is based on the current time, which we can see by converting
it to a time stamp.
>>> import ZODB.TimeStamp
>>> print ZODB.TimeStamp.TimeStamp(tid)
2008-10-24 05:11:08.120000
To assure that we get a new tid that is later than the old, we can
pass an existing tid. Let's pass the tid we just got.
>>> tid2 = ZODB.utils.newTid(tid)
>>> ZODB.utils.u64(tid), ZODB.utils.u64(tid2)
(250347764454864008L, 250347764454864009L)
Here, since we called it at the same time, we got a time stamp that
was only slightly larger than the previos one. Of course, at a later
time, the time stamp we get will be based on the time:
>>> time.time = lambda : 1224825069.12
>>> tid = ZODB.utils.newTid(tid2)
>>> print ZODB.TimeStamp.TimeStamp(tid)
2008-10-24 05:11:09.120000
>>> time.time = old_time
Locking support
---------------
Storages are required to be thread safe. The locking descriptor helps
automate that. It arranges for a lock to be acquired when a function
is called and released when a function exits. To demonstrate this,
we'll create a "lock" type that simply prints when it is called:
>>> class Lock:
... def acquire(self):
... print 'acquire'
... def release(self):
... print 'release'
Now we'll demonstrate the descriptor:
>>> class C:
... _lock = Lock()
... _lock_acquire = _lock.acquire
... _lock_release = _lock.release
...
... @ZODB.utils.locked
... def meth(self, *args, **kw):
... print 'meth', args, kw
The descriptor expects the instance it wraps to have a '_lock
attribute.
>>> C().meth(1, 2, a=3)
acquire
meth (1, 2) {'a': 3}
release
.. Edge cases
We can get the method from the class:
>>> C.meth # doctest: +ELLIPSIS
<ZODB.utils.Locked object at ...>
>>> C.meth(C())
acquire
meth () {}
release
>>> class C2:
... _lock = Lock()
... _lock_acquire = _lock.acquire
... _lock_release = _lock.release
>>> C.meth(C2()) # doctest: +NORMALIZE_WHITESPACE
Traceback (most recent call last):
...
TypeError: unbound method meth() must be called with C instance
as first argument (got C2 instance instead)
Preconditions
-------------
Often, we want to supply method preconditions. The locking descriptor
supports optional method preconditions [1]_.
>>> class C:
... def __init__(self):
... _lock = Lock()
... self._lock_acquire = _lock.acquire
... self._lock_release = _lock.release
... self._opened = True
... self._transaction = None
...
... def opened(self):
... """The object is open
... """
... print 'checking if open'
... return self._opened
...
... def not_in_transaction(self):
... """The object is not in a transaction
... """
... print 'checking if in a transaction'
... return self._transaction is None
...
... @ZODB.utils.locked(opened, not_in_transaction)
... def meth(self, *args, **kw):
... print 'meth', args, kw
>>> c = C()
>>> c.meth(1, 2, a=3)
acquire
checking if open
checking if in a transaction
meth (1, 2) {'a': 3}
release
>>> c._transaction = 1
>>> c.meth(1, 2, a=3) # doctest: +NORMALIZE_WHITESPACE
Traceback (most recent call last):
...
AssertionError:
('Failed precondition: ', 'The object is not in a transaction')
>>> c._opened = False
>>> c.meth(1, 2, a=3) # doctest: +NORMALIZE_WHITESPACE
Traceback (most recent call last):
...
AssertionError: ('Failed precondition: ', 'The object is open')
.. [1] Arguably, preconditions should be handled via separate
descriptors, but for ZODB storages, almost all methods need to be
locked. Combining preconditions with locking provides both
efficiency and concise expressions. A more general-purpose
facility would almost certainly provide separate descriptors for
preconditions.
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