Another extension to reduce(). It can return a 4- or 5-tuple now.
The 4th item can be None or an iterator yielding list items, which are used to append() or extend() the object. The 5th item can be None or an iterator yielding a dict's (key, value) pairs, which are stuffed into the object using __setitem__. Also (as a separate, though related, feature) add "batching" for list and dict items. If you pickled a dict or list with a million items in the past, it would push a million items onto the stack. It now pushes only 1000 items at a time on the stack, using repeated APPENDS or SETITEMS opcodes. (For lists, I hope that using many short extend() calls doesn't exhibit quadratic behavior.)
This commit is contained in:
Guido van Rossum
parent
f9b0cc7df6
commit
25cb7dfb0f
163
Lib/pickle.py
163
Lib/pickle.py
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@ -317,19 +317,14 @@ class Pickler:
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if type(rv) is not TupleType:
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raise PicklingError("%s must return string or tuple" % reduce)
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# Assert that it returned a 2-tuple or 3-tuple, and unpack it
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# Assert that it returned an appropriately sized tuple
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l = len(rv)
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if l == 2:
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func, args = rv
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state = None
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elif l == 3:
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func, args, state = rv
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else:
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if not (2 <= l <= 5):
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raise PicklingError("Tuple returned by %s must have "
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"exactly two or three elements" % reduce)
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"two to five elements" % reduce)
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# Save the reduce() output and finally memoize the object
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self.save_reduce(func, args, state, obj)
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self.save_reduce(obj=obj, *rv)
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def persistent_id(self, obj):
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# This exists so a subclass can override it
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@ -343,7 +338,8 @@ class Pickler:
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else:
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self.write(PERSID + str(pid) + '\n')
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def save_reduce(self, func, args, state=None, obj=None):
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def save_reduce(self, func, args, state=None,
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listitems=None, dictitems=None, obj=None):
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# This API is be called by some subclasses
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# Assert that args is a tuple or None
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@ -411,6 +407,17 @@ class Pickler:
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if obj is not None:
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self.memoize(obj)
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# More new special cases (that work with older protocols as
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# well): when __reduce__ returns a tuple with 4 or 5 items,
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# the 4th and 5th item should be iterators that provide list
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# items and dict items (as (key, value) tuples), or None.
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if listitems is not None:
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self._batch_appends(listitems)
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if dictitems is not None:
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self._batch_setitems(dictitems)
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if state is not None:
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save(state)
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write(BUILD)
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@ -434,28 +441,9 @@ class Pickler:
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self.memoize(obj)
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if isinstance(obj, list):
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n = len(obj)
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if n > 1:
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write(MARK)
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for x in obj:
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save(x)
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write(APPENDS)
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elif n == 1:
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save(obj[0])
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write(APPEND)
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self._batch_appends(iter(obj))
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elif isinstance(obj, dict):
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n = len(obj)
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if n > 1:
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write(MARK)
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for k, v in obj.iteritems():
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save(k)
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save(v)
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write(SETITEMS)
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elif n == 1:
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k, v = obj.items()[0]
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save(k)
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save(v)
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write(SETITEM)
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self._batch_setitems(obj.iteritems())
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getstate = getattr(obj, "__getstate__", None)
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@ -683,63 +671,100 @@ class Pickler:
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def save_list(self, obj):
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write = self.write
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save = self.save
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if self.bin:
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write(EMPTY_LIST)
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self.memoize(obj)
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n = len(obj)
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if n > 1:
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write(MARK)
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for element in obj:
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save(element)
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write(APPENDS)
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elif n:
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assert n == 1
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save(obj[0])
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write(APPEND)
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# else the list is empty, and we're already done
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else: # proto 0 -- can't use EMPTY_LIST or APPENDS
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else: # proto 0 -- can't use EMPTY_LIST
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write(MARK + LIST)
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self.memoize(obj)
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for element in obj:
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save(element)
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write(APPEND)
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self.memoize(obj)
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self._batch_appends(iter(obj))
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dispatch[ListType] = save_list
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_BATCHSIZE = 1000
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def _batch_appends(self, items):
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# Helper to batch up APPENDS sequences
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save = self.save
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write = self.write
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if not self.bin:
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for x in items:
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save(x)
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write(APPEND)
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return
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r = xrange(self._BATCHSIZE)
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while items is not None:
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tmp = []
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for i in r:
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try:
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tmp.append(items.next())
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except StopIteration:
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items = None
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break
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n = len(tmp)
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if n > 1:
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write(MARK)
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for x in tmp:
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save(x)
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write(APPENDS)
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elif n:
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save(tmp[0])
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write(APPEND)
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# else tmp is empty, and we're done
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def save_dict(self, obj):
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write = self.write
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save = self.save
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items = obj.iteritems()
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if self.bin:
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write(EMPTY_DICT)
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self.memoize(obj)
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if len(obj) > 1:
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write(MARK)
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for key, value in items:
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save(key)
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save(value)
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write(SETITEMS)
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return
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# else (dict is empty or a singleton), fall through to the
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# SETITEM code at the end
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else: # proto 0 -- can't use EMPTY_DICT or SETITEMS
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else: # proto 0 -- can't use EMPTY_DICT
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write(MARK + DICT)
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self.memoize(obj)
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# proto 0 or len(obj) < 2
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for key, value in items:
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save(key)
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save(value)
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write(SETITEM)
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self.memoize(obj)
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self._batch_setitems(obj.iteritems())
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dispatch[DictionaryType] = save_dict
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if not PyStringMap is None:
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dispatch[PyStringMap] = save_dict
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def _batch_setitems(self, items):
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# Helper to batch up SETITEMS sequences; proto >= 1 only
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save = self.save
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write = self.write
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if not self.bin:
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for k, v in items:
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save(k)
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save(v)
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write(SETITEM)
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return
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r = xrange(self._BATCHSIZE)
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while items is not None:
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tmp = []
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for i in r:
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try:
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tmp.append(items.next())
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except StopIteration:
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items = None
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break
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n = len(tmp)
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if n > 1:
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write(MARK)
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for k, v in tmp:
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save(k)
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save(v)
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write(SETITEMS)
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elif n:
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k, v = tmp[0]
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save(k)
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save(v)
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write(SETITEM)
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# else tmp is empty, and we're done
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def save_inst(self, obj):
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cls = obj.__class__
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