shelve.py: database of persistent objects, on top of pickle.py and anydbm.py

pickle.py: new low-level persistency module (used to be called flatten)
dbmac.py: stupid dbm clone for the Mac
anydbm.py: generic dbm interface (should be extended to support gdbm)

3 files changed, 556 insertions, 0 deletions

diff --git a/Lib/anydbm.py b/Lib/anydbm.py
new file mode 100644
index 0000000..49e819b
--- /dev/null
+++ b/Lib/anydbm.py
@@ -0,0 +1,9 @@
+"""A generic interface to all dbm clones."""
+
+try:
+	import dbm
+	def open(file, mode = 'rw'):
+		return dbm.open(file, mode, 0666)
+except ImportError:
+	import dbmac
+	open = dbmac.open
diff --git a/Lib/pickle.py b/Lib/pickle.py
new file mode 100644
index 0000000..b5ade57
--- /dev/null
+++ b/Lib/pickle.py
@@ -0,0 +1,504 @@
+"""\
+Pickling Algorithm
+------------------
+
+This module implements a basic but powerful algorithm for "pickling" (a.k.a.
+serializing, marshalling or flattening) nearly arbitrary Python objects.
+This is a more primitive notion than persistency -- although pickle
+reads and writes file objects, it does not handle the issue of naming
+persistent objects, nor the (even more complicated) area of concurrent
+access to persistent objects.  The pickle module can transform a complex
+object into a byte stream and it can transform the byte stream into
+an object with the same internal structure.  The most obvious thing to
+do with these byte streams is to write them onto a file, but it is also
+conceivable to send them across a network or store them in a database.
+
+Unlike the built-in marshal module, pickle handles the following correctly:
+
+- recursive objects
+- pointer sharing
+- class instances
+
+Pickle is Python-specific.  This has the advantage that there are no
+restrictions imposed by external standards such as CORBA (which probably
+can't represent pointer sharing or recursive objects); however it means
+that non-Python programs may not be able to reconstruct pickled Python
+objects.
+
+Pickle uses a printable ASCII representation.  This is slightly more
+voluminous than a binary representation.  However, small integers actually
+take *less* space when represented as minimal-size decimal strings than
+when represented as 32-bit binary numbers, and strings are only much longer
+if they contain control characters or 8-bit characters.  The big advantage
+of using printable ASCII (and of some other characteristics of pickle's
+representation) is that for debugging or recovery purposes it is possible
+for a human to read the pickled file with a standard text editor.  (I could
+have gone a step further and used a notation like S-expressions, but the
+parser would have been considerably more complicated and slower, and the
+files would probably have become much larger.)
+
+Pickle doesn't handle code objects, which marshal does.
+I suppose pickle could, and maybe it should, but there's probably no
+great need for it right now (as long as marshal continues to be used
+for reading and writing code objects), and at least this avoids
+the possibility of smuggling Trojan horses into a program.
+
+For the benefit of persistency modules written using pickle, it supports
+the notion of a reference to an object outside the pickled data stream.
+Such objects are referenced by a name, which is an arbitrary string of
+printable ASCII characters.  The resolution of such names is not defined
+by the pickle module -- the persistent object module will have to implement
+a method "persistent_load".  To write references to persistent objects,
+the persistent module must define a method "persistent_id" which returns
+either None or the persistent ID of the object.
+
+There are some restrictions on the pickling of class instances.
+
+First of all, the class must be defined at the top level in a module.
+
+Next, it must normally be possible to create class instances by calling
+the class without arguments.  If this is undesirable, the class can
+define a method __getinitargs__ (XXX not a pretty name!), which should
+return a *tuple* containing the arguments to be passed to the class
+constructor.
+
+Classes can influence how they are pickled -- if the class defines
+the method __getstate__, it is called and the return state is pickled
+as the contents for the instance, and if the class defines the
+method __setstate__, it is called with the unpickled state.  (Note
+that these methods can also be used to implement copying class instances.)
+If there is no __getstate__ method, the instance's __dict__
+is pickled.  If there is no __setstate__ method, the pickled object
+must be a dictionary and its items are assigned to the new instance's
+dictionary.  (If a class defines both __getstate__ and __setstate__,
+the state object needn't be a dictionary -- these methods can do what they
+want.)
+
+Note that when class instances are pickled, their class's code and data
+is not pickled along with them.  Only the instance data is pickled.
+This is done on purpose, so you can fix bugs in a class or add methods and
+still load objects that were created with an earlier version of the
+class.  If you plan to have long-lived objects that will see many versions
+of a class, it may be worth to put a version number in the objects so
+that suitable conversions can be made by the class's __setstate__ method.
+
+The interface is as follows:
+
+To pickle an object x onto a file f. open for writing:
+
+	p = pickle.Pickler(f)
+	p.dump(x)
+
+To unpickle an object x from a file f, open for reading:
+
+	u = pickle.Unpickler(f)
+	x = u.load(x)
+
+The Pickler class only calls the method f.write with a string argument
+(XXX possibly the interface should pass f.write instead of f).
+The Unpickler calls the methods f.read(with an integer argument)
+and f.readline(without argument), both returning a string.
+It is explicitly allowed to pass non-file objects here, as long as they
+have the right methods.
+
+The following types can be pickled:
+
+- None
+- integers, long integers, floating point numbers
+- strings
+- tuples, lists and dictionaries containing picklable objects
+- class instances whose __dict__ or __setstate__() is picklable
+
+Attempts to pickle unpicklable objects will raise an exception
+after having written an unspecified number of bytes to the file argument.
+
+It is possible to make multiple calls to Pickler.dump() or to
+Unpickler.load(), as long as there is a one-to-one correspondence
+betwee pickler and Unpickler objects and between dump and load calls
+for any pair of corresponding Pickler and Unpicklers.  WARNING: this
+is intended for pickleing multiple objects without intervening modifications
+to the objects or their parts.  If you modify an object and then pickle
+it again using the same Pickler instance, the object is not pickled
+again -- a reference to it is pickled and the Unpickler will return
+the old value, not the modified one.  (XXX There are two problems here:
+(a) detecting changes, and (b) marshalling a minimal set of changes.
+I have no answers.  Garbage Collection may also become a problem here.)
+"""
+
+__format_version__ = "1.0"		# File format version
+__version__ = "1.2"			# Code version
+
+from types import *
+import string
+
+AtomicTypes = [NoneType, IntType, FloatType, StringType]
+
+def safe(object):
+	t = type(object)
+	if t in AtomicTypes:
+		return 1
+	if t is TupleType:
+		for item in object:
+			if not safe(item): return 0
+		return 1
+	return 0
+
+MARK = '('
+POP = '0'
+DUP = '2'
+STOP = '.'
+TUPLE = 't'
+LIST = 'l'
+DICT = 'd'
+INST = 'i'
+GET = 'g'
+PUT = 'p'
+APPEND = 'a'
+SETITEM = 's'
+BUILD = 'b'
+NONE = 'N'
+INT = 'I'
+LONG = 'L'
+FLOAT = 'F'
+STRING = 'S'
+PERSID = 'P'
+AtomicKeys = [NONE, INT, LONG, FLOAT, STRING]
+AtomicMap = {
+	NoneType: NONE,
+	IntType: INT,
+	LongType: LONG,
+	FloatType: FLOAT,
+	StringType: STRING,
+}
+
+class Pickler:
+
+	def __init__(self, file):
+		self.write = file.write
+		self.memo = {}
+
+	def dump(self, object):
+		self.save(object)
+		self.write(STOP)
+
+	def save(self, object):
+		pid = self.persistent_id(object)
+		if pid:
+			self.write(PERSID + str(pid) + '\n')
+			return
+		d = id(object)
+		if self.memo.has_key(d):
+			self.write(GET + `d` + '\n')
+			return
+		t = type(object)
+		self.dispatch[t](self, object)
+
+	def persistent_id(self, object):
+		return None
+
+	dispatch = {}
+
+	def save_none(self, object):
+		self.write(NONE)
+	dispatch[NoneType] = save_none
+
+	def save_int(self, object):
+		self.write(INT + `object` + '\n')
+	dispatch[IntType] = save_int
+
+	def save_long(self, object):
+		self.write(LONG + `object` + '\n')
+	dispatch[LongType] = save_long
+
+	def save_float(self, object):
+		self.write(FLOAT + `object` + '\n')
+	dispatch[FloatType] = save_float
+
+	def save_string(self, object):
+		d = id(object)
+		self.write(STRING + `object` + '\n')
+		self.write(PUT + `d` + '\n')
+		self.memo[d] = object
+	dispatch[StringType] = save_string
+
+	def save_tuple(self, object):
+		d = id(object)
+		self.write(MARK)
+		n = len(object)
+		for k in range(n):
+			self.save(object[k])
+			if self.memo.has_key(d):
+				# Saving object[k] has saved us!
+				while k >= 0:
+					self.write(POP)
+					k = k-1
+				self.write(GET + `d` + '\n')
+				break
+		else:
+			self.write(TUPLE + PUT + `d` + '\n')
+			self.memo[d] = object
+	dispatch[TupleType] = save_tuple
+
+	def save_list(self, object):
+		d = id(object)
+		self.write(MARK)
+		n = len(object)
+		for k in range(n):
+			item = object[k]
+			if not safe(item):
+				break
+			self.save(item)
+		else:
+			k = n
+		self.write(LIST + PUT + `d` + '\n')
+		self.memo[d] = object
+		for k in range(k, n):
+			item = object[k]
+			self.save(item)
+			self.write(APPEND)
+	dispatch[ListType] = save_list
+
+	def save_dict(self, object):
+		d = id(object)
+		self.write(MARK)
+		items = object.items()
+		n = len(items)
+		for k in range(n):
+			key, value = items[k]
+			if not safe(key) or not safe(value):
+				break
+			self.save(key)
+			self.save(value)
+		else:
+			k = n
+		self.write(DICT + PUT + `d` + '\n')
+		self.memo[d] = object
+		for k in range(k, n):
+			key, value = items[k]
+			self.save(key)
+			self.save(value)
+			self.write(SETITEM)
+	dispatch[DictionaryType] = save_dict
+
+	def save_inst(self, object):
+		d = id(object)
+		cls = object.__class__
+		module = whichmodule(cls)
+		name = cls.__name__
+		if hasattr(object, '__getinitargs__'):
+			args = object.__getinitargs__()
+			len(args) # XXX Assert it's a sequence
+		else:
+			args = ()
+		self.write(MARK)
+		for arg in args:
+			self.save(arg)
+		self.write(INST + module + '\n' + name + '\n' + 
+			PUT + `d` + '\n')
+		self.memo[d] = object
+		try:
+			getstate = object.__getstate__
+		except AttributeError:
+			stuff = object.__dict__
+		else:
+			stuff = getstate()
+		self.save(stuff)
+		self.write(BUILD)
+	dispatch[InstanceType] = save_inst
+
+
+classmap = {}
+
+def whichmodule(cls):
+	"""Figure out the module in which a class occurs.
+
+	Search sys.modules for the module.
+	Cache in classmap.
+	Return a module name.
+	If the class cannot be found, return __main__.
+	"""
+	if classmap.has_key(cls):
+		return classmap[cls]
+	import sys
+	clsname = cls.__name__
+	for name, module in sys.modules.items():
+		if module.__name__ != '__main__' and \
+		   hasattr(module, clsname) and \
+		   getattr(module, clsname) is cls:
+			break
+	else:
+		name = '__main__'
+	classmap[cls] = name
+	return name
+
+
+class Unpickler:
+
+	def __init__(self, file):
+		self.readline = file.readline
+		self.read = file.read
+		self.memo = {}
+
+	def load(self):
+		self.mark = ['spam'] # Any new unique object
+		self.stack = []
+		try:
+			while 1:
+				key = self.read(1)
+				self.dispatch[key](self)
+		except STOP, value:
+			return value
+
+	def marker(self):
+		k = len(self.stack)-1
+		while self.stack[k] != self.mark: k = k-1
+		return k
+
+	dispatch = {}
+
+	def load_persid(self):
+		pid = self.readline()[:-1]
+		self.stack.append(self.persisent_load(pid))
+	dispatch[PERSID] = load_persid
+
+	def load_none(self):
+		self.stack.append(None)
+	dispatch[NONE] = load_none
+
+	def load_atomic(self):
+		self.stack.append(eval(self.readline()[:-1]))
+	dispatch[INT] = load_atomic
+	dispatch[LONG] = load_atomic
+	dispatch[FLOAT] = load_atomic
+	dispatch[STRING] = load_atomic
+
+	def load_tuple(self):
+		k = self.marker()
+		self.stack[k:] = [tuple(self.stack[k+1:])]
+	dispatch[TUPLE] = load_tuple
+
+	def load_list(self):
+		k = self.marker()
+		self.stack[k:] = [self.stack[k+1:]]
+	dispatch[LIST] = load_list
+
+	def load_dict(self):
+		k = self.marker()
+		d = {}
+		items = self.stack[k+1:]
+		for i in range(0, len(items), 2):
+			key = items[i]
+			value = items[i+1]
+			d[key] = value
+		self.stack[k:] = [d]
+	dispatch[DICT] = load_dict
+
+	def load_inst(self):
+		k = self.marker()
+		args = tuple(self.stack[k+1:])
+		del self.stack[k:]
+		module = self.readline()[:-1]
+		name = self.readline()[:-1]
+		env = {}
+		try:
+			exec 'from %s import %s' % (module, name) in env
+		except ImportError:
+			raise SystemError, \
+			      "Failed to import class %s from module %s" % \
+			      (name, module)
+		else:
+			klass = env[name]
+			if type(klass) != ClassType:
+				raise SystemError, \
+					"imported object %s from module %s is not a class" % \
+					(name, module)
+			value = apply(klass, args)
+		self.stack.append(value)
+	dispatch[INST] = load_inst
+
+	def load_pop(self):
+				del self.stack[-1]
+	dispatch[POP] = load_pop
+
+	def load_dup(self):
+		stack.append(stack[-1])
+	dispatch[DUP] = load_dup
+
+	def load_get(self):
+		self.stack.append(self.memo[string.atoi(self.readline()[:-1])])
+	dispatch[GET] = load_get
+
+	def load_put(self):
+		self.memo[string.atoi(self.readline()[:-1])] = self.stack[-1]
+	dispatch[PUT] = load_put
+
+	def load_append(self):
+		value = self.stack[-1]
+		del self.stack[-1]
+		list = self.stack[-1]
+		list.append(value)
+	dispatch[APPEND] = load_append
+
+	def load_setitem(self):
+		value = self.stack[-1]
+		key = self.stack[-2]
+		del self.stack[-2:]
+		dict = self.stack[-1]
+		dict[key] = value
+	dispatch[SETITEM] = load_setitem
+
+	def load_build(self):
+		value = self.stack[-1]
+		del self.stack[-1]
+		inst = self.stack[-1]
+		try:
+			setstate = inst.__setstate__
+		except AttributeError:
+			for key in value.keys():
+				inst.__dict__[key] = value[key]
+		else:
+			setstate(value)
+	dispatch[BUILD] = load_build
+
+	def load_mark(self):
+		self.stack.append(self.mark)
+	dispatch[MARK] = load_mark
+
+	def load_stop(self):
+		value = self.stack[-1]
+		del self.stack[-1]
+		raise STOP, value
+	dispatch[STOP] = load_stop
+
+
+class C:
+	def __cmp__(self, other):
+		return cmp(self.__dict__, other.__dict__)
+
+def test():
+	fn = 'pickle_tmp'
+	c = C()
+	c.foo = 1
+	c.bar = 2
+	x = [0,1,2,3]
+	y = ('abc', 'abc', c, c)
+	x.append(y)
+	x.append(y)
+	x.append(5)
+	f = open(fn, 'w')
+	F = Pickler(f)
+	F.dump(x)
+	f.close()
+	f = open(fn, 'r')
+	U = Unpickler(f)
+	x2 = U.load()
+	print x
+	print x2
+	print x == x2
+	print map(id, x)
+	print map(id, x2)
+	print F.memo
+	print U.memo
+
+if __name__ == '__main__':
+	test()
diff --git a/Lib/shelve.py b/Lib/shelve.py
new file mode 100644
index 0000000..b90e641
--- /dev/null
+++ b/Lib/shelve.py
@@ -0,0 +1,43 @@
+"""Manage shelves of pickled objects."""
+
+import pickle
+import StringIO
+
+class Shelf:
+
+	def __init__(self, dict):
+		self.dict = dict
+	
+	def keys(self):
+		return self.dict.keys()
+	
+	def __len__(self):
+		return self.dict.len()
+	
+	def has_key(self, key):
+		return self.dict.has_key(key)
+	
+	def __getitem__(self, key):
+		return pickle.Unpickler(StringIO.StringIO(self.dict[key])).load()
+	
+	def __setitem__(self, key, value):
+		f = StringIO.StringIO()
+		p = pickle.Pickler(f)
+		p.dump(value)
+		self.dict[key] = f.getvalue()
+	
+	def __delitem__(self, key):
+		del self.dict[key]
+	
+	def close(self):
+		self.db.close()
+		self.db = None
+
+class DbShelf(Shelf):
+	
+	def __init__(self, file):
+		import anydbm
+		Shelf.__init__(self, anydbm.open(file))
+
+def open(file):
+	return DbShelf(file)