"""Create portable serialized representations of Python objects.
See module cPickle for a (much) faster implementation.
See module copy_reg for a mechanism for registering custom picklers.
See module pickletools source for extensive comments.
__version__ = "$Revision: 72223 $" # Code version
from copy_reg import dispatch_table
from copy_reg import _extension_registry, _inverted_registry, _extension_cache
__all__ = ["PickleError", "PicklingError", "UnpicklingError", "Pickler",
"Unpickler", "dump", "dumps", "load", "loads"]
# These are purely informational; no code uses these.
format_version = "2.0" # File format version we write
compatible_formats = ["1.0", # Original protocol 0
"1.1", # Protocol 0 with INST added
"1.2", # Original protocol 1
"1.3", # Protocol 1 with BINFLOAT added
] # Old format versions we can read
# Keep in synch with cPickle. This is the highest protocol number we
# Why use struct.pack() for pickling but marshal.loads() for
# unpickling? struct.pack() is 40% faster than marshal.dumps(), but
# marshal.loads() is twice as fast as struct.unpack()!
class PickleError(Exception):
"""A common base class for the other pickling exceptions."""
class PicklingError(PickleError):
"""This exception is raised when an unpicklable object is passed to the
class UnpicklingError(PickleError):
"""This exception is raised when there is a problem unpickling an object,
such as a security violation.
Note that other exceptions may also be raised during unpickling, including
(but not necessarily limited to) AttributeError, EOFError, ImportError,
# An instance of _Stop is raised by Unpickler.load_stop() in response to
# the STOP opcode, passing the object that is the result of unpickling.
def __init__(self, value):
# Jython has PyStringMap; it's a dict subclass with string keys
from org.python.core import PyStringMap
# UnicodeType may or may not be exported (normally imported from types)
# Pickle opcodes. See pickletools.py for extensive docs. The listing
# here is in kind-of alphabetical order of 1-character pickle code.
# pickletools groups them by purpose.
MARK = '(' # push special markobject on stack
STOP = '.' # every pickle ends with STOP
POP = '0' # discard topmost stack item
POP_MARK = '1' # discard stack top through topmost markobject
DUP = '2' # duplicate top stack item
FLOAT = 'F' # push float object; decimal string argument
INT = 'I' # push integer or bool; decimal string argument
BININT = 'J' # push four-byte signed int
BININT1 = 'K' # push 1-byte unsigned int
LONG = 'L' # push long; decimal string argument
BININT2 = 'M' # push 2-byte unsigned int
PERSID = 'P' # push persistent object; id is taken from string arg
BINPERSID = 'Q' # " " " ; " " " " stack
REDUCE = 'R' # apply callable to argtuple, both on stack
STRING = 'S' # push string; NL-terminated string argument
BINSTRING = 'T' # push string; counted binary string argument
SHORT_BINSTRING = 'U' # " " ; " " " " < 256 bytes
UNICODE = 'V' # push Unicode string; raw-unicode-escaped'd argument
BINUNICODE = 'X' # " " " ; counted UTF-8 string argument
APPEND = 'a' # append stack top to list below it
BUILD = 'b' # call __setstate__ or __dict__.update()
GLOBAL = 'c' # push self.find_class(modname, name); 2 string args
DICT = 'd' # build a dict from stack items
EMPTY_DICT = '}' # push empty dict
APPENDS = 'e' # extend list on stack by topmost stack slice
GET = 'g' # push item from memo on stack; index is string arg
BINGET = 'h' # " " " " " " ; " " 1-byte arg
INST = 'i' # build & push class instance
LONG_BINGET = 'j' # push item from memo on stack; index is 4-byte arg
LIST = 'l' # build list from topmost stack items
EMPTY_LIST = ']' # push empty list
OBJ = 'o' # build & push class instance
PUT = 'p' # store stack top in memo; index is string arg
BINPUT = 'q' # " " " " " ; " " 1-byte arg
LONG_BINPUT = 'r' # " " " " " ; " " 4-byte arg
SETITEM = 's' # add key+value pair to dict
TUPLE = 't' # build tuple from topmost stack items
EMPTY_TUPLE = ')' # push empty tuple
SETITEMS = 'u' # modify dict by adding topmost key+value pairs
BINFLOAT = 'G' # push float; arg is 8-byte float encoding
TRUE = 'I01\n' # not an opcode; see INT docs in pickletools.py
FALSE = 'I00\n' # not an opcode; see INT docs in pickletools.py
PROTO = '\x80' # identify pickle protocol
NEWOBJ = '\x81' # build object by applying cls.__new__ to argtuple
EXT1 = '\x82' # push object from extension registry; 1-byte index
EXT2 = '\x83' # ditto, but 2-byte index
EXT4 = '\x84' # ditto, but 4-byte index
TUPLE1 = '\x85' # build 1-tuple from stack top
TUPLE2 = '\x86' # build 2-tuple from two topmost stack items
TUPLE3 = '\x87' # build 3-tuple from three topmost stack items
NEWTRUE = '\x88' # push True
NEWFALSE = '\x89' # push False
LONG1 = '\x8a' # push long from < 256 bytes
LONG4 = '\x8b' # push really big long
_tuplesize2code = [EMPTY_TUPLE, TUPLE1, TUPLE2, TUPLE3]
__all__.extend([x for x in dir() if re.match("[A-Z][A-Z0-9_]+$",x)])
def __init__(self, file, protocol=None):
"""This takes a file-like object for writing a pickle data stream.
The optional protocol argument tells the pickler to use the
given protocol; supported protocols are 0, 1, 2. The default
protocol is 0, to be backwards compatible. (Protocol 0 is the
only protocol that can be written to a file opened in text
mode and read back successfully. When using a protocol higher
than 0, make sure the file is opened in binary mode, both when
pickling and unpickling.)
Protocol 1 is more efficient than protocol 0; protocol 2 is
more efficient than protocol 1.
Specifying a negative protocol version selects the highest
protocol version supported. The higher the protocol used, the
more recent the version of Python needed to read the pickle
The file parameter must have a write() method that accepts a single
string argument. It can thus be an open file object, a StringIO
object, or any other custom object that meets this interface.
protocol = HIGHEST_PROTOCOL
elif not 0 <= protocol <= HIGHEST_PROTOCOL:
raise ValueError("pickle protocol must be <= %d" % HIGHEST_PROTOCOL)
self.proto = int(protocol)
"""Clears the pickler's "memo".
The memo is the data structure that remembers which objects the
pickler has already seen, so that shared or recursive objects are
pickled by reference and not by value. This method is useful when
"""Write a pickled representation of obj to the open file."""
self.write(PROTO + chr(self.proto))
"""Store an object in the memo."""
# The Pickler memo is a dictionary mapping object ids to 2-tuples
# that contain the Unpickler memo key and the object being memoized.
# The memo key is written to the pickle and will become
# the key in the Unpickler's memo. The object is stored in the
# Pickler memo so that transient objects are kept alive during
# The use of the Unpickler memo length as the memo key is just a
# convention. The only requirement is that the memo values be unique.
# But there appears no advantage to any other scheme, and this
# scheme allows the Unpickler memo to be implemented as a plain (but
# growable) array, indexed by memo key.
assert id(obj) not in self.memo
memo_len = len(self.memo)
self.write(self.put(memo_len))
self.memo[id(obj)] = memo_len, obj
# Return a PUT (BINPUT, LONG_BINPUT) opcode string, with argument i.
def put(self, i, pack=struct.pack):
return LONG_BINPUT + pack("<i", i)
return PUT + repr(i) + '\n'
# Return a GET (BINGET, LONG_BINGET) opcode string, with argument i.
def get(self, i, pack=struct.pack):
return LONG_BINGET + pack("<i", i)
return GET + repr(i) + '\n'
# Check for persistent id (defined by a subclass)
pid = self.persistent_id(obj)
x = self.memo.get(id(obj))
self.write(self.get(x[0]))
# Check the type dispatch table
f(self, obj) # Call unbound method with explicit self
# Check copy_reg.dispatch_table
reduce = dispatch_table.get(t)
# Check for a class with a custom metaclass; treat as regular class
issc = issubclass(t, TypeType)
except TypeError: # t is not a class (old Boost; see SF #502085)
# Check for a __reduce_ex__ method, fall back to __reduce__
reduce = getattr(obj, "__reduce_ex__", None)
reduce = getattr(obj, "__reduce__", None)
raise PicklingError("Can't pickle %r object: %r" %
# Check for string returned by reduce(), meaning "save as global"
if type(rv) is StringType:
self.save_global(obj, rv)
# Assert that reduce() returned a tuple
if type(rv) is not TupleType:
raise PicklingError("%s must return string or tuple" % reduce)
# Assert that it returned an appropriately sized tuple
raise PicklingError("Tuple returned by %s must have "
"two to five elements" % reduce)
# Save the reduce() output and finally memoize the object
self.save_reduce(obj=obj, *rv)
def persistent_id(self, obj):
# This exists so a subclass can override it
def save_pers(self, pid):
# Save a persistent id reference
self.write(PERSID + str(pid) + '\n')
def save_reduce(self, func, args, state=None,
listitems=None, dictitems=None, obj=None):
# This API is called by some subclasses
# Assert that args is a tuple or None
if not isinstance(args, TupleType):
raise PicklingError("args from reduce() should be a tuple")
# Assert that func is callable
if not hasattr(func, '__call__'):
raise PicklingError("func from reduce should be callable")
# Protocol 2 special case: if func's name is __newobj__, use NEWOBJ
if self.proto >= 2 and getattr(func, "__name__", "") == "__newobj__":
# A __reduce__ implementation can direct protocol 2 to
# use the more efficient NEWOBJ opcode, while still
# allowing protocol 0 and 1 to work normally. For this to
# work, the function returned by __reduce__ should be
# called __newobj__, and its first argument should be a
# new-style class. The implementation for __newobj__
# should be as follows, although pickle has no way to
# def __newobj__(cls, *args):
# return cls.__new__(cls, *args)
# Protocols 0 and 1 will pickle a reference to __newobj__,
# while protocol 2 (and above) will pickle a reference to
# cls, the remaining args tuple, and the NEWOBJ code,
# which calls cls.__new__(cls, *args) at unpickling time
# (see load_newobj below). If __reduce__ returns a
# three-tuple, the state from the third tuple item will be
# pickled regardless of the protocol, calling __setstate__
# at unpickling time (see load_build below).
# Note that no standard __newobj__ implementation exists;
# you have to provide your own. This is to enforce
# compatibility with Python 2.2 (pickles written using
# protocol 0 or 1 in Python 2.3 should be unpicklable by
if not hasattr(cls, "__new__"):
"args[0] from __newobj__ args has no __new__")
if obj is not None and cls is not obj.__class__:
"args[0] from __newobj__ args has the wrong class")
# If the object is already in the memo, this means it is
# recursive. In this case, throw away everything we put on the
# stack, and fetch the object back from the memo.
write(POP + self.get(self.memo[id(obj)][0]))
# More new special cases (that work with older protocols as
# well): when __reduce__ returns a tuple with 4 or 5 items,
# the 4th and 5th item should be iterators that provide list
# items and dict items (as (key, value) tuples), or None.
if listitems is not None:
self._batch_appends(listitems)
if dictitems is not None:
self._batch_setitems(dictitems)
# Methods below this point are dispatched through the dispatch table
def save_none(self, obj):
dispatch[NoneType] = save_none
def save_bool(self, obj):
self.write(obj and NEWTRUE or NEWFALSE)
self.write(obj and TRUE or FALSE)
dispatch[bool] = save_bool
def save_int(self, obj, pack=struct.pack):
# If the int is small enough to fit in a signed 4-byte 2's-comp
# format, we can store it more efficiently than the general
# First one- and two-byte unsigned ints:
self.write(BININT1 + chr(obj))
self.write("%c%c%c" % (BININT2, obj&0xff, obj>>8))
# Next check for 4-byte signed ints:
high_bits = obj >> 31 # note that Python shift sign-extends
if high_bits == 0 or high_bits == -1:
# All high bits are copies of bit 2**31, so the value
# fits in a 4-byte signed int.
self.write(BININT + pack("<i", obj))
# Text pickle, or int too big to fit in signed 4-byte format.
self.write(INT + repr(obj) + '\n')
dispatch[IntType] = save_int
def save_long(self, obj, pack=struct.pack):
self.write(LONG1 + chr(n) + bytes)
self.write(LONG4 + pack("<i", n) + bytes)
self.write(LONG + repr(obj) + '\n')
dispatch[LongType] = save_long
def save_float(self, obj, pack=struct.pack):
self.write(BINFLOAT + pack('>d', obj))
self.write(FLOAT + repr(obj) + '\n')
dispatch[FloatType] = save_float
def save_string(self, obj, pack=struct.pack):
self.write(SHORT_BINSTRING + chr(n) + obj)
self.write(BINSTRING + pack("<i", n) + obj)
self.write(STRING + repr(obj) + '\n')
dispatch[StringType] = save_string
def save_unicode(self, obj, pack=struct.pack):
encoding = obj.encode('utf-8')
It is recommended that you Edit text format, this type of Fix handles quite a lot in one request
