pickleとjsonモジュール

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jsonモジュール
jsonモジュールはシーケンス化と逆シーケンス化を実現し、主なユーザーの異なるプログラム間のデータ交換をまず見てみましょう.
dumps()シーケンス化
import json
'''json                '''
users = ["alex","tom","wupeiqi","sb","   "]
mes = json.dumps(users)    #   ,   
print(mes)

["alex", "tom", "wupeiqi", "sb", "\u803f\u957f\u5b66"]

以上から分かるように、dumpsは実はシーケンス化されたインスタンスを生成し、この後dumpと区別され、漢字が英語ではなくバイトコードに変換される.
loads()逆シーケンス化
import json
'''json                '''
users = ["alex","tom","wupeiqi","sb","   "]
mes = json.dumps(users)    #   ,   
print("   :",mes)

data = json.loads(mes)
print("",data)

: ["alex", "tom", "wupeiqi", "sb", "\u803f\u957f\u5b66"]
: ['alex', 'tom', 'wupeiqi', 'sb', ' ']

上記dumps()とloads()のシーケンス化と逆シーケンス化は、プログラム間で相互作用する、すなわちファイルを通過せず、jsonのみである.dumps()はインスタンスをシーケンス化し、その後jsonを受信する.loads()は逆シーケンス化され,プログラム間のインタラクションが順次実現される.では、ファイルでどのように対話しますか?
ファイル内のインタラクション:
import json
'''json                '''
users = ["alex","tom","wupeiqi","sb","   "]
mes = json.dumps(users)    #   ,   
''' mes         '''
with open("users",'w+') as fw:
    fw.write(mes)

上記のコードでは、シーケンス化されたインスタンスをファイルに書き込み、jsonを使用します.dumps()生成例,fw.write()ファイルに書き込むには、ファイルのwrite()で書き込む必要があります.
ファイルの逆シーケンス化:
import json
with open('users','r+') as fr:
    mess = json.loads(fr.read())
    print(mess)
      :
['alex', 'tom', 'wupeiqi', 'sb', '   ']

上のファイルの逆シーケンス化では、まずファイルの内容を読み出し、write()を使用して書き込まれるのでread()を出てから逆シーケンス化してインスタンスを生成します.
次にload()とdump()のシーケンス化と逆シーケンス化を見てみましょう.
dump()シーケンス化
import json
users = {"alex":"sb","wupeiqi":666,"   ":6969}
with open("users","w+") as fw:
    json.dump(users,fw)

上から見えますjsondump()は、インスタンス化された情報を直接指定ファイルにシーケンス化し、write()を必要とせず、直接自分で書き込むことができますが、dumps()はシーケンス化されたインスタンスにすぎず、自分でwrite()をファイルに追加する必要があります.
load()逆シーケンス化
import json
with open('users','r+') as fr:
    users = json.load(fr)
    print(users)

      :
{'alex': 'sb', '   ': 6969, 'wupeiqi': 666}

load()逆シーケンス化は読み取り後に逆シーケンス化する必要はありません.dump()に入っているので、ファイルから直接逆シーケンス化できます.
まとめ:
上記のdumps()、loads()およびdump()、load()のシーケンス化および逆シーケンス化から、dumps()はシーケンス化によって生成されたインスタンスであり、loads()は読み書きされたインスタンスであり、dumps()およびloads()は主に異なるプログラムまたはインタフェース間のデータ交換伝送に用いられ、dump()およびload()はファイルレベル間の読み取りおよび書き込みに適しており、両者の間には重点がある.
これは両者の機能が同じで、使い方が違うというわけではありませんが、実際に設計するときに方向を重視するのは違います.
jsonソースコード
r"""JSON (JavaScript Object Notation)  is a subset of
JavaScript syntax (ECMA-262 3rd edition) used as a lightweight data
interchange format.

:mod:`json` exposes an API familiar to users of the standard library
:mod:`marshal` and :mod:`pickle` modules.  It is derived from a
version of the externally maintained simplejson library.

Encoding basic Python object hierarchies::

    >>> import json
    >>> json.dumps(['foo', {'bar': ('baz', None, 1.0, 2)}])
    '["foo", {"bar": ["baz", null, 1.0, 2]}]'
    >>> print(json.dumps("\"foo\bar"))
    "\"foo\bar"
    >>> print(json.dumps('\u1234'))
    "\u1234"
    >>> print(json.dumps('\\'))
    "\\"
    >>> print(json.dumps({"c": 0, "b": 0, "a": 0}, sort_keys=True))
    {"a": 0, "b": 0, "c": 0}
    >>> from io import StringIO
    >>> io = StringIO()
    >>> json.dump(['streaming API'], io)
    >>> io.getvalue()
    '["streaming API"]'

Compact encoding::

    >>> import json
    >>> from collections import OrderedDict
    >>> mydict = OrderedDict([('4', 5), ('6', 7)])
    >>> json.dumps([1,2,3,mydict], separators=(',', ':'))
    '[1,2,3,{"4":5,"6":7}]'

Pretty printing::

    >>> import json
    >>> print(json.dumps({'4': 5, '6': 7}, sort_keys=True, indent=4))
    {
        "4": 5,
        "6": 7
    }

Decoding JSON::

    >>> import json
    >>> obj = ['foo', {'bar': ['baz', None, 1.0, 2]}]
    >>> json.loads('["foo", {"bar":["baz", null, 1.0, 2]}]') == obj
    True
    >>> json.loads('"\\"foo\\bar"') == '"foo\x08ar'
    True
    >>> from io import StringIO
    >>> io = StringIO('["streaming API"]')
    >>> json.load(io)[0] == 'streaming API'
    True

Specializing JSON object decoding::

    >>> import json
    >>> def as_complex(dct):
    ...     if '__complex__' in dct:
    ...         return complex(dct['real'], dct['imag'])
    ...     return dct
    ...
    >>> json.loads('{"__complex__": true, "real": 1, "imag": 2}',
    ...     object_hook=as_complex)
    (1+2j)
    >>> from decimal import Decimal
    >>> json.loads('1.1', parse_float=Decimal) == Decimal('1.1')
    True

Specializing JSON object encoding::

    >>> import json
    >>> def encode_complex(obj):
    ...     if isinstance(obj, complex):
    ...         return [obj.real, obj.imag]
    ...     raise TypeError(repr(o) + " is not JSON serializable")
    ...
    >>> json.dumps(2 + 1j, default=encode_complex)
    '[2.0, 1.0]'
    >>> json.JSONEncoder(default=encode_complex).encode(2 + 1j)
    '[2.0, 1.0]'
    >>> ''.join(json.JSONEncoder(default=encode_complex).iterencode(2 + 1j))
    '[2.0, 1.0]'


Using json.tool from the shell to validate and pretty-print::

    $ echo '{"json":"obj"}' | python -m json.tool
    {
        "json": "obj"
    }
    $ echo '{ 1.2:3.4}' | python -m json.tool
    Expecting property name enclosed in double quotes: line 1 column 3 (char 2)
"""
__version__ = '2.0.9'
__all__ = [
    'dump', 'dumps', 'load', 'loads',
    'JSONDecoder', 'JSONDecodeError', 'JSONEncoder',
]

__author__ = 'Bob Ippolito '

from .decoder import JSONDecoder, JSONDecodeError
from .encoder import JSONEncoder

_default_encoder = JSONEncoder(
    skipkeys=False,
    ensure_ascii=True,
    check_circular=True,
    allow_nan=True,
    indent=None,
    separators=None,
    default=None,
)

def dump(obj, fp, skipkeys=False, ensure_ascii=True, check_circular=True,
        allow_nan=True, cls=None, indent=None, separators=None,
        default=None, sort_keys=False, **kw):
    """Serialize ``obj`` as a JSON formatted stream to ``fp`` (a
    ``.write()``-supporting file-like object).

    If ``skipkeys`` is true then ``dict`` keys that are not basic types
    (``str``, ``int``, ``float``, ``bool``, ``None``) will be skipped
    instead of raising a ``TypeError``.

    If ``ensure_ascii`` is false, then the strings written to ``fp`` can
    contain non-ASCII characters if they appear in strings contained in
    ``obj``. Otherwise, all such characters are escaped in JSON strings.

    If ``check_circular`` is false, then the circular reference check
    for container types will be skipped and a circular reference will
    result in an ``OverflowError`` (or worse).

    If ``allow_nan`` is false, then it will be a ``ValueError`` to
    serialize out of range ``float`` values (``nan``, ``inf``, ``-inf``)
    in strict compliance of the JSON specification, instead of using the
    JavaScript equivalents (``NaN``, ``Infinity``, ``-Infinity``).

    If ``indent`` is a non-negative integer, then JSON array elements and
    object members will be pretty-printed with that indent level. An indent
    level of 0 will only insert newlines. ``None`` is the most compact
    representation.

    If specified, ``separators`` should be an ``(item_separator, key_separator)``
    tuple.  The default is ``(', ', ': ')`` if *indent* is ``None`` and
    ``(',', ': ')`` otherwise.  To get the most compact JSON representation,
    you should specify ``(',', ':')`` to eliminate whitespace.

    ``default(obj)`` is a function that should return a serializable version
    of obj or raise TypeError. The default simply raises TypeError.

    If *sort_keys* is ``True`` (default: ``False``), then the output of
    dictionaries will be sorted by key.

    To use a custom ``JSONEncoder`` subclass (e.g. one that overrides the
    ``.default()`` method to serialize additional types), specify it with
    the ``cls`` kwarg; otherwise ``JSONEncoder`` is used.

    """
    # cached encoder
    if (not skipkeys and ensure_ascii and
        check_circular and allow_nan and
        cls is None and indent is None and separators is None and
        default is None and not sort_keys and not kw):
        iterable = _default_encoder.iterencode(obj)
    else:
        if cls is None:
            cls = JSONEncoder
        iterable = cls(skipkeys=skipkeys, ensure_ascii=ensure_ascii,
            check_circular=check_circular, allow_nan=allow_nan, indent=indent,
            separators=separators,
            default=default, sort_keys=sort_keys, **kw).iterencode(obj)
    # could accelerate with writelines in some versions of Python, at
    # a debuggability cost
    for chunk in iterable:
        fp.write(chunk)


def dumps(obj, skipkeys=False, ensure_ascii=True, check_circular=True,
        allow_nan=True, cls=None, indent=None, separators=None,
        default=None, sort_keys=False, **kw):
    """Serialize ``obj`` to a JSON formatted ``str``.

    If ``skipkeys`` is true then ``dict`` keys that are not basic types
    (``str``, ``int``, ``float``, ``bool``, ``None``) will be skipped
    instead of raising a ``TypeError``.

    If ``ensure_ascii`` is false, then the return value can contain non-ASCII
    characters if they appear in strings contained in ``obj``. Otherwise, all
    such characters are escaped in JSON strings.

    If ``check_circular`` is false, then the circular reference check
    for container types will be skipped and a circular reference will
    result in an ``OverflowError`` (or worse).

    If ``allow_nan`` is false, then it will be a ``ValueError`` to
    serialize out of range ``float`` values (``nan``, ``inf``, ``-inf``) in
    strict compliance of the JSON specification, instead of using the
    JavaScript equivalents (``NaN``, ``Infinity``, ``-Infinity``).

    If ``indent`` is a non-negative integer, then JSON array elements and
    object members will be pretty-printed with that indent level. An indent
    level of 0 will only insert newlines. ``None`` is the most compact
    representation.

    If specified, ``separators`` should be an ``(item_separator, key_separator)``
    tuple.  The default is ``(', ', ': ')`` if *indent* is ``None`` and
    ``(',', ': ')`` otherwise.  To get the most compact JSON representation,
    you should specify ``(',', ':')`` to eliminate whitespace.

    ``default(obj)`` is a function that should return a serializable version
    of obj or raise TypeError. The default simply raises TypeError.

    If *sort_keys* is ``True`` (default: ``False``), then the output of
    dictionaries will be sorted by key.

    To use a custom ``JSONEncoder`` subclass (e.g. one that overrides the
    ``.default()`` method to serialize additional types), specify it with
    the ``cls`` kwarg; otherwise ``JSONEncoder`` is used.

    """
    # cached encoder
    if (not skipkeys and ensure_ascii and
        check_circular and allow_nan and
        cls is None and indent is None and separators is None and
        default is None and not sort_keys and not kw):
        return _default_encoder.encode(obj)
    if cls is None:
        cls = JSONEncoder
    return cls(
        skipkeys=skipkeys, ensure_ascii=ensure_ascii,
        check_circular=check_circular, allow_nan=allow_nan, indent=indent,
        separators=separators, default=default, sort_keys=sort_keys,
        **kw).encode(obj)


_default_decoder = JSONDecoder(object_hook=None, object_pairs_hook=None)


def load(fp, cls=None, object_hook=None, parse_float=None,
        parse_int=None, parse_constant=None, object_pairs_hook=None, **kw):
    """Deserialize ``fp`` (a ``.read()``-supporting file-like object containing
    a JSON document) to a Python object.

    ``object_hook`` is an optional function that will be called with the
    result of any object literal decode (a ``dict``). The return value of
    ``object_hook`` will be used instead of the ``dict``. This feature
    can be used to implement custom decoders (e.g. JSON-RPC class hinting).

    ``object_pairs_hook`` is an optional function that will be called with the
    result of any object literal decoded with an ordered list of pairs.  The
    return value of ``object_pairs_hook`` will be used instead of the ``dict``.
    This feature can be used to implement custom decoders that rely on the
    order that the key and value pairs are decoded (for example,
    collections.OrderedDict will remember the order of insertion). If
    ``object_hook`` is also defined, the ``object_pairs_hook`` takes priority.

    To use a custom ``JSONDecoder`` subclass, specify it with the ``cls``
    kwarg; otherwise ``JSONDecoder`` is used.

    """
    return loads(fp.read(),
        cls=cls, object_hook=object_hook,
        parse_float=parse_float, parse_int=parse_int,
        parse_constant=parse_constant, object_pairs_hook=object_pairs_hook, **kw)


def loads(s, encoding=None, cls=None, object_hook=None, parse_float=None,
        parse_int=None, parse_constant=None, object_pairs_hook=None, **kw):
    """Deserialize ``s`` (a ``str`` instance containing a JSON
    document) to a Python object.

    ``object_hook`` is an optional function that will be called with the
    result of any object literal decode (a ``dict``). The return value of
    ``object_hook`` will be used instead of the ``dict``. This feature
    can be used to implement custom decoders (e.g. JSON-RPC class hinting).

    ``object_pairs_hook`` is an optional function that will be called with the
    result of any object literal decoded with an ordered list of pairs.  The
    return value of ``object_pairs_hook`` will be used instead of the ``dict``.
    This feature can be used to implement custom decoders that rely on the
    order that the key and value pairs are decoded (for example,
    collections.OrderedDict will remember the order of insertion). If
    ``object_hook`` is also defined, the ``object_pairs_hook`` takes priority.

    ``parse_float``, if specified, will be called with the string
    of every JSON float to be decoded. By default this is equivalent to
    float(num_str). This can be used to use another datatype or parser
    for JSON floats (e.g. decimal.Decimal).

    ``parse_int``, if specified, will be called with the string
    of every JSON int to be decoded. By default this is equivalent to
    int(num_str). This can be used to use another datatype or parser
    for JSON integers (e.g. float).

    ``parse_constant``, if specified, will be called with one of the
    following strings: -Infinity, Infinity, NaN, null, true, false.
    This can be used to raise an exception if invalid JSON numbers
    are encountered.

    To use a custom ``JSONDecoder`` subclass, specify it with the ``cls``
    kwarg; otherwise ``JSONDecoder`` is used.

    The ``encoding`` argument is ignored and deprecated.

    """
    if not isinstance(s, str):
        raise TypeError('the JSON object must be str, not {!r}'.format(
                            s.__class__.__name__))
    if s.startswith(u'\ufeff'):
        raise JSONDecodeError("Unexpected UTF-8 BOM (decode using utf-8-sig)",
                              s, 0)
    if (cls is None and object_hook is None and
            parse_int is None and parse_float is None and
            parse_constant is None and object_pairs_hook is None and not kw):
        return _default_decoder.decode(s)
    if cls is None:
        cls = JSONDecoder
    if object_hook is not None:
        kw['object_hook'] = object_hook
    if object_pairs_hook is not None:
        kw['object_pairs_hook'] = object_pairs_hook
    if parse_float is not None:
        kw['parse_float'] = parse_float
    if parse_int is not None:
        kw['parse_int'] = parse_int
    if parse_constant is not None:
        kw['parse_constant'] = parse_constant
    return cls(**kw).decode(s)

pickleソースコード
"""Create portable serialized representations of Python objects.

See module copyreg for a mechanism for registering custom picklers.
See module pickletools source for extensive comments.

Classes:

    Pickler
    Unpickler

Functions:

    dump(object, file)
    dumps(object) -> string
    load(file) -> object
    loads(string) -> object

Misc variables:

    __version__
    format_version
    compatible_formats

"""

from types import FunctionType
from copyreg import dispatch_table
from copyreg import _extension_registry, _inverted_registry, _extension_cache
from itertools import islice
import sys
from sys import maxsize
from struct import pack, unpack
import re
import io
import codecs
import _compat_pickle

__all__ = ["PickleError", "PicklingError", "UnpicklingError", "Pickler",
           "Unpickler", "dump", "dumps", "load", "loads"]

# Shortcut for use in isinstance testing
bytes_types = (bytes, bytearray)

# These are purely informational; no code uses these.
format_version = "4.0"                  # 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
                      "2.0",            # Protocol 2
                      "3.0",            # Protocol 3
                      "4.0",            # Protocol 4
                      ]                 # Old format versions we can read

# This is the highest protocol number we know how to read.
HIGHEST_PROTOCOL = 4

# The protocol we write by default.  May be less than HIGHEST_PROTOCOL.
# We intentionally write a protocol that Python 2.x cannot read;
# there are too many issues with that.
DEFAULT_PROTOCOL = 3

class PickleError(Exception):
    """A common base class for the other pickling exceptions."""
    pass

class PicklingError(PickleError):
    """This exception is raised when an unpicklable object is passed to the
    dump() method.

    """
    pass

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,
    and IndexError.

    """
    pass

# 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.
class _Stop(Exception):
    def __init__(self, value):
        self.value = value

# Jython has PyStringMap; it's a dict subclass with string keys
try:
    from org.python.core import PyStringMap
except ImportError:
    PyStringMap = None

# 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           = b'('   # push special markobject on stack
STOP           = b'.'   # every pickle ends with STOP
POP            = b'0'   # discard topmost stack item
POP_MARK       = b'1'   # discard stack top through topmost markobject
DUP            = b'2'   # duplicate top stack item
FLOAT          = b'F'   # push float object; decimal string argument
INT            = b'I'   # push integer or bool; decimal string argument
BININT         = b'J'   # push four-byte signed int
BININT1        = b'K'   # push 1-byte unsigned int
LONG           = b'L'   # push long; decimal string argument
BININT2        = b'M'   # push 2-byte unsigned int
NONE           = b'N'   # push None
PERSID         = b'P'   # push persistent object; id is taken from string arg
BINPERSID      = b'Q'   #  "       "         "  ;  "  "   "     "  stack
REDUCE         = b'R'   # apply callable to argtuple, both on stack
STRING         = b'S'   # push string; NL-terminated string argument
BINSTRING      = b'T'   # push string; counted binary string argument
SHORT_BINSTRING= b'U'   #  "     "   ;    "      "       "      " < 256 bytes
UNICODE        = b'V'   # push Unicode string; raw-unicode-escaped'd argument
BINUNICODE     = b'X'   #   "     "       "  ; counted UTF-8 string argument
APPEND         = b'a'   # append stack top to list below it
BUILD          = b'b'   # call __setstate__ or __dict__.update()
GLOBAL         = b'c'   # push self.find_class(modname, name); 2 string args
DICT           = b'd'   # build a dict from stack items
EMPTY_DICT     = b'}'   # push empty dict
APPENDS        = b'e'   # extend list on stack by topmost stack slice
GET            = b'g'   # push item from memo on stack; index is string arg
BINGET         = b'h'   #   "    "    "    "   "   "  ;   "    " 1-byte arg
INST           = b'i'   # build & push class instance
LONG_BINGET    = b'j'   # push item from memo on stack; index is 4-byte arg
LIST           = b'l'   # build list from topmost stack items
EMPTY_LIST     = b']'   # push empty list
OBJ            = b'o'   # build & push class instance
PUT            = b'p'   # store stack top in memo; index is string arg
BINPUT         = b'q'   #   "     "    "   "   " ;   "    " 1-byte arg
LONG_BINPUT    = b'r'   #   "     "    "   "   " ;   "    " 4-byte arg
SETITEM        = b's'   # add key+value pair to dict
TUPLE          = b't'   # build tuple from topmost stack items
EMPTY_TUPLE    = b')'   # push empty tuple
SETITEMS       = b'u'   # modify dict by adding topmost key+value pairs
BINFLOAT       = b'G'   # push float; arg is 8-byte float encoding

TRUE           = b'I01
' # not an opcode; see INT docs in pickletools.py FALSE = b'I00
' # not an opcode; see INT docs in pickletools.py # Protocol 2 PROTO = b'\x80' # identify pickle protocol NEWOBJ = b'\x81' # build object by applying cls.__new__ to argtuple EXT1 = b'\x82' # push object from extension registry; 1-byte index EXT2 = b'\x83' # ditto, but 2-byte index EXT4 = b'\x84' # ditto, but 4-byte index TUPLE1 = b'\x85' # build 1-tuple from stack top TUPLE2 = b'\x86' # build 2-tuple from two topmost stack items TUPLE3 = b'\x87' # build 3-tuple from three topmost stack items NEWTRUE = b'\x88' # push True NEWFALSE = b'\x89' # push False LONG1 = b'\x8a' # push long from < 256 bytes LONG4 = b'\x8b' # push really big long _tuplesize2code = [EMPTY_TUPLE, TUPLE1, TUPLE2, TUPLE3] # Protocol 3 (Python 3.x) BINBYTES = b'B' # push bytes; counted binary string argument SHORT_BINBYTES = b'C' # " " ; " " " " < 256 bytes # Protocol 4 SHORT_BINUNICODE = b'\x8c' # push short string; UTF-8 length < 256 bytes BINUNICODE8 = b'\x8d' # push very long string BINBYTES8 = b'\x8e' # push very long bytes string EMPTY_SET = b'\x8f' # push empty set on the stack ADDITEMS = b'\x90' # modify set by adding topmost stack items FROZENSET = b'\x91' # build frozenset from topmost stack items NEWOBJ_EX = b'\x92' # like NEWOBJ but work with keyword only arguments STACK_GLOBAL = b'\x93' # same as GLOBAL but using names on the stacks MEMOIZE = b'\x94' # store top of the stack in memo FRAME = b'\x95' # indicate the beginning of a new frame __all__.extend([x for x in dir() if re.match("[A-Z][A-Z0-9_]+$", x)]) class _Framer: _FRAME_SIZE_TARGET = 64 * 1024 def __init__(self, file_write): self.file_write = file_write self.current_frame = None def start_framing(self): self.current_frame = io.BytesIO() def end_framing(self): if self.current_frame and self.current_frame.tell() > 0: self.commit_frame(force=True) self.current_frame = None def commit_frame(self, force=False): if self.current_frame: f = self.current_frame if f.tell() >= self._FRAME_SIZE_TARGET or force: with f.getbuffer() as data: n = len(data) write = self.file_write write(FRAME) write(pack("", n)) write(data) f.seek(0) f.truncate() def write(self, data): if self.current_frame: return self.current_frame.write(data) else: return self.file_write(data) class _Unframer: def __init__(self, file_read, file_readline, file_tell=None): self.file_read = file_read self.file_readline = file_readline self.current_frame = None def read(self, n): if self.current_frame: data = self.current_frame.read(n) if not data and n != 0: self.current_frame = None return self.file_read(n) if len(data) < n: raise UnpicklingError( "pickle exhausted before end of frame") return data else: return self.file_read(n) def readline(self): if self.current_frame: data = self.current_frame.readline() if not data: self.current_frame = None return self.file_readline() if data[-1] != b'
'[0]: raise UnpicklingError( "pickle exhausted before end of frame") return data else: return self.file_readline() def load_frame(self, frame_size): if self.current_frame and self.current_frame.read() != b'': raise UnpicklingError( "beginning of a new frame before end of current frame") self.current_frame = io.BytesIO(self.file_read(frame_size)) # Tools used for pickling. def _getattribute(obj, name): for subpath in name.split('.'): if subpath == '': raise AttributeError("Can't get local attribute {!r} on {!r}" .format(name, obj)) try: parent = obj obj = getattr(obj, subpath) except AttributeError: raise AttributeError("Can't get attribute {!r} on {!r}" .format(name, obj)) return obj, parent def whichmodule(obj, name): """Find the module an object belong to.""" module_name = getattr(obj, '__module__', None) if module_name is not None: return module_name # Protect the iteration by using a list copy of sys.modules against dynamic # modules that trigger imports of other modules upon calls to getattr. for module_name, module in list(sys.modules.items()): if module_name == '__main__' or module is None: continue try: if _getattribute(module, name)[0] is obj: return module_name except AttributeError: pass return '__main__' def encode_long(x): r"""Encode a long to a two's complement little-endian binary string. Note that 0 is a special case, returning an empty string, to save a byte in the LONG1 pickling context. >>> encode_long(0) b'' >>> encode_long(255) b'\xff\x00' >>> encode_long(32767) b'\xff\x7f' >>> encode_long(-256) b'\x00\xff' >>> encode_long(-32768) b'\x00\x80' >>> encode_long(-128) b'\x80' >>> encode_long(127) b'\x7f' >>> """ if x == 0: return b'' nbytes = (x.bit_length() >> 3) + 1 result = x.to_bytes(nbytes, byteorder='little', signed=True) if x < 0 and nbytes > 1: if result[-1] == 0xff and (result[-2] & 0x80) != 0: result = result[:-1] return result def decode_long(data): r"""Decode a long from a two's complement little-endian binary string. >>> decode_long(b'') 0 >>> decode_long(b"\xff\x00") 255 >>> decode_long(b"\xff\x7f") 32767 >>> decode_long(b"\x00\xff") -256 >>> decode_long(b"\x00\x80") -32768 >>> decode_long(b"\x80") -128 >>> decode_long(b"\x7f") 127 """ return int.from_bytes(data, byteorder='little', signed=True) # Pickling machinery class _Pickler: def __init__(self, file, protocol=None, *, fix_imports=True): """This takes a binary file for writing a pickle data stream. The optional *protocol* argument tells the pickler to use the given protocol; supported protocols are 0, 1, 2, 3 and 4. The default protocol is 3; a backward-incompatible protocol designed for Python 3. 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 produced. The *file* argument must have a write() method that accepts a single bytes argument. It can thus be a file object opened for binary writing, an io.BytesIO instance, or any other custom object that meets this interface. If *fix_imports* is True and *protocol* is less than 3, pickle will try to map the new Python 3 names to the old module names used in Python 2, so that the pickle data stream is readable with Python 2. """ if protocol is None: protocol = DEFAULT_PROTOCOL if protocol < 0: protocol = HIGHEST_PROTOCOL elif not 0 <= protocol <= HIGHEST_PROTOCOL: raise ValueError("pickle protocol must be <= %d" % HIGHEST_PROTOCOL) try: self._file_write = file.write except AttributeError: raise TypeError("file must have a 'write' attribute") self.framer = _Framer(self._file_write) self.write = self.framer.write self.memo = {} self.proto = int(protocol) self.bin = protocol >= 1 self.fast = 0 self.fix_imports = fix_imports and protocol < 3 def clear_memo(self): """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 re-using picklers. """ self.memo.clear() def dump(self, obj): """Write a pickled representation of obj to the open file.""" # Check whether Pickler was initialized correctly. This is # only needed to mimic the behavior of _pickle.Pickler.dump(). if not hasattr(self, "_file_write"): raise PicklingError("Pickler.__init__() was not called by " "%s.__init__()" % (self.__class__.__name__,)) if self.proto >= 2: self.write(PROTO + pack("", self.proto)) if self.proto >= 4: self.framer.start_framing() self.save(obj) self.write(STOP) self.framer.end_framing() def memoize(self, obj): """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 # pickling. # 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. if self.fast: return assert id(obj) not in self.memo idx = len(self.memo) self.write(self.put(idx)) self.memo[id(obj)] = idx, obj # Return a PUT (BINPUT, LONG_BINPUT) opcode string, with argument i. def put(self, idx): if self.proto >= 4: return MEMOIZE elif self.bin: if idx < 256: return BINPUT + pack("", idx) else: return LONG_BINPUT + pack("", idx) else: return PUT + repr(idx).encode("ascii") + b'
' # Return a GET (BINGET, LONG_BINGET) opcode string, with argument i. def get(self, i): if self.bin: if i < 256: return BINGET + pack("", i) else: return LONG_BINGET + pack("", i) return GET + repr(i).encode("ascii") + b'
' def save(self, obj, save_persistent_id=True): self.framer.commit_frame() # Check for persistent id (defined by a subclass) pid = self.persistent_id(obj) if pid is not None and save_persistent_id: self.save_pers(pid) return # Check the memo x = self.memo.get(id(obj)) if x is not None: self.write(self.get(x[0])) return # Check the type dispatch table t = type(obj) f = self.dispatch.get(t) if f is not None: f(self, obj) # Call unbound method with explicit self return # Check private dispatch table if any, or else copyreg.dispatch_table reduce = getattr(self, 'dispatch_table', dispatch_table).get(t) if reduce is not None: rv = reduce(obj) else: # Check for a class with a custom metaclass; treat as regular class try: issc = issubclass(t, type) except TypeError: # t is not a class (old Boost; see SF #502085) issc = False if issc: self.save_global(obj) return # Check for a __reduce_ex__ method, fall back to __reduce__ reduce = getattr(obj, "__reduce_ex__", None) if reduce is not None: rv = reduce(self.proto) else: reduce = getattr(obj, "__reduce__", None) if reduce is not None: rv = reduce() else: raise PicklingError("Can't pickle %r object: %r" % (t.__name__, obj)) # Check for string returned by reduce(), meaning "save as global" if isinstance(rv, str): self.save_global(obj, rv) return # Assert that reduce() returned a tuple if not isinstance(rv, tuple): raise PicklingError("%s must return string or tuple" % reduce) # Assert that it returned an appropriately sized tuple l = len(rv) if not (2 <= l <= 5): 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 return None def save_pers(self, pid): # Save a persistent id reference if self.bin: self.save(pid, save_persistent_id=False) self.write(BINPERSID) else: self.write(PERSID + str(pid).encode("ascii") + b'
') def save_reduce(self, func, args, state=None, listitems=None, dictitems=None, obj=None): # This API is called by some subclasses if not isinstance(args, tuple): raise PicklingError("args from save_reduce() must be a tuple") if not callable(func): raise PicklingError("func from save_reduce() must be callable") save = self.save write = self.write func_name = getattr(func, "__name__", "") if self.proto >= 4 and func_name == "__newobj_ex__": cls, args, kwargs = args if not hasattr(cls, "__new__"): raise PicklingError("args[0] from {} args has no __new__" .format(func_name)) if obj is not None and cls is not obj.__class__: raise PicklingError("args[0] from {} args has the wrong class" .format(func_name)) save(cls) save(args) save(kwargs) write(NEWOBJ_EX) elif self.proto >= 2 and func_name == "__newobj__": # A __reduce__ implementation can direct protocol 2 or newer 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 # class. The implementation for __newobj__ # should be as follows, although pickle has no way to # verify this: # # 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 # Python 2.2). cls = args[0] if not hasattr(cls, "__new__"): raise PicklingError( "args[0] from __newobj__ args has no __new__") if obj is not None and cls is not obj.__class__: raise PicklingError( "args[0] from __newobj__ args has the wrong class") args = args[1:] save(cls) save(args) write(NEWOBJ) else: save(func) save(args) write(REDUCE) if obj is not None: # 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. if id(obj) in self.memo: write(POP + self.get(self.memo[id(obj)][0])) else: self.memoize(obj) # 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) if state is not None: save(state) write(BUILD) # Methods below this point are dispatched through the dispatch table dispatch = {} def save_none(self, obj): self.write(NONE) dispatch[type(None)] = save_none def save_bool(self, obj): if self.proto >= 2: self.write(NEWTRUE if obj else NEWFALSE) else: self.write(TRUE if obj else FALSE) dispatch[bool] = save_bool def save_long(self, obj): if self.bin: # 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 # case. # First one- and two-byte unsigned ints: if obj >= 0: if obj <= 0xff: self.write(BININT1 + pack("", obj)) return if obj <= 0xffff: self.write(BININT2 + pack("", obj)) return # Next check for 4-byte signed ints: if -0x80000000 <= obj <= 0x7fffffff: self.write(BININT + pack("", obj)) return if self.proto >= 2: encoded = encode_long(obj) n = len(encoded) if n < 256: self.write(LONG1 + pack("", n) + encoded) else: self.write(LONG4 + pack("", n) + encoded) return self.write(LONG + repr(obj).encode("ascii") + b'L
') dispatch[int] = save_long def save_float(self, obj): if self.bin: self.write(BINFLOAT + pack('>d', obj)) else: self.write(FLOAT + repr(obj).encode("ascii") + b'
') dispatch[float] = save_float def save_bytes(self, obj): if self.proto < 3: if not obj: # bytes object is empty self.save_reduce(bytes, (), obj=obj) else: self.save_reduce(codecs.encode, (str(obj, 'latin1'), 'latin1'), obj=obj) return n = len(obj) if n <= 0xff: self.write(SHORT_BINBYTES + pack("", n) + obj) elif n > 0xffffffff and self.proto >= 4: self.write(BINBYTES8 + pack("", n) + obj) else: self.write(BINBYTES + pack("", n) + obj) self.memoize(obj) dispatch[bytes] = save_bytes def save_str(self, obj): if self.bin: encoded = obj.encode('utf-8', 'surrogatepass') n = len(encoded) if n <= 0xff and self.proto >= 4: self.write(SHORT_BINUNICODE + pack("", n) + encoded) elif n > 0xffffffff and self.proto >= 4: self.write(BINUNICODE8 + pack("", n) + encoded) else: self.write(BINUNICODE + pack("", n) + encoded) else: obj = obj.replace("\\", "\\u005c") obj = obj.replace("
", "\\u000a") self.write(UNICODE + obj.encode('raw-unicode-escape') + b'
') self.memoize(obj) dispatch[str] = save_str def save_tuple(self, obj): if not obj: # tuple is empty if self.bin: self.write(EMPTY_TUPLE) else: self.write(MARK + TUPLE) return n = len(obj) save = self.save memo = self.memo if n <= 3 and self.proto >= 2: for element in obj: save(element) # Subtle. Same as in the big comment below. if id(obj) in memo: get = self.get(memo[id(obj)][0]) self.write(POP * n + get) else: self.write(_tuplesize2code[n]) self.memoize(obj) return # proto 0 or proto 1 and tuple isn't empty, or proto > 1 and tuple # has more than 3 elements. write = self.write write(MARK) for element in obj: save(element) if id(obj) in memo: # Subtle. d was not in memo when we entered save_tuple(), so # the process of saving the tuple's elements must have saved # the tuple itself: the tuple is recursive. The proper action # now is to throw away everything we put on the stack, and # simply GET the tuple (it's already constructed). This check # could have been done in the "for element" loop instead, but # recursive tuples are a rare thing. get = self.get(memo[id(obj)][0]) if self.bin: write(POP_MARK + get) else: # proto 0 -- POP_MARK not available write(POP * (n+1) + get) return # No recursion. write(TUPLE) self.memoize(obj) dispatch[tuple] = save_tuple def save_list(self, obj): if self.bin: self.write(EMPTY_LIST) else: # proto 0 -- can't use EMPTY_LIST self.write(MARK + LIST) self.memoize(obj) self._batch_appends(obj) dispatch[list] = save_list _BATCHSIZE = 1000 def _batch_appends(self, items): # Helper to batch up APPENDS sequences save = self.save write = self.write if not self.bin: for x in items: save(x) write(APPEND) return it = iter(items) while True: tmp = list(islice(it, self._BATCHSIZE)) n = len(tmp) if n > 1: write(MARK) for x in tmp: save(x) write(APPENDS) elif n: save(tmp[0]) write(APPEND) # else tmp is empty, and we're done if n < self._BATCHSIZE: return def save_dict(self, obj): if self.bin: self.write(EMPTY_DICT) else: # proto 0 -- can't use EMPTY_DICT self.write(MARK + DICT) self.memoize(obj) self._batch_setitems(obj.items()) dispatch[dict] = save_dict if PyStringMap is not None: dispatch[PyStringMap] = save_dict def _batch_setitems(self, items): # Helper to batch up SETITEMS sequences; proto >= 1 only save = self.save write = self.write if not self.bin: for k, v in items: save(k) save(v) write(SETITEM) return it = iter(items) while True: tmp = list(islice(it, self._BATCHSIZE)) n = len(tmp) if n > 1: write(MARK) for k, v in tmp: save(k) save(v) write(SETITEMS) elif n: k, v = tmp[0] save(k) save(v) write(SETITEM) # else tmp is empty, and we're done if n < self._BATCHSIZE: return def save_set(self, obj): save = self.save write = self.write if self.proto < 4: self.save_reduce(set, (list(obj),), obj=obj) return write(EMPTY_SET) self.memoize(obj) it = iter(obj) while True: batch = list(islice(it, self._BATCHSIZE)) n = len(batch) if n > 0: write(MARK) for item in batch: save(item) write(ADDITEMS) if n < self._BATCHSIZE: return dispatch[set] = save_set def save_frozenset(self, obj): save = self.save write = self.write if self.proto < 4: self.save_reduce(frozenset, (list(obj),), obj=obj) return write(MARK) for item in obj: save(item) if id(obj) in self.memo: # 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_MARK + self.get(self.memo[id(obj)][0])) return write(FROZENSET) self.memoize(obj) dispatch[frozenset] = save_frozenset def save_global(self, obj, name=None): write = self.write memo = self.memo if name is None: name = getattr(obj, '__qualname__', None) if name is None: name = obj.__name__ module_name = whichmodule(obj, name) try: __import__(module_name, level=0) module = sys.modules[module_name] obj2, parent = _getattribute(module, name) except (ImportError, KeyError, AttributeError): raise PicklingError( "Can't pickle %r: it's not found as %s.%s" % (obj, module_name, name)) else: if obj2 is not obj: raise PicklingError( "Can't pickle %r: it's not the same object as %s.%s" % (obj, module_name, name)) if self.proto >= 2: code = _extension_registry.get((module_name, name)) if code: assert code > 0 if code <= 0xff: write(EXT1 + pack("", code)) elif code <= 0xffff: write(EXT2 + pack("", code)) else: write(EXT4 + pack("", code)) return lastname = name.rpartition('.')[2] if parent is module: name = lastname # Non-ASCII identifiers are supported only with protocols >= 3. if self.proto >= 4: self.save(module_name) self.save(name) write(STACK_GLOBAL) elif parent is not module: self.save_reduce(getattr, (parent, lastname)) elif self.proto >= 3: write(GLOBAL + bytes(module_name, "utf-8") + b'
' + bytes(name, "utf-8") + b'
') else: if self.fix_imports: r_name_mapping = _compat_pickle.REVERSE_NAME_MAPPING r_import_mapping = _compat_pickle.REVERSE_IMPORT_MAPPING if (module_name, name) in r_name_mapping: module_name, name = r_name_mapping[(module_name, name)] elif module_name in r_import_mapping: module_name = r_import_mapping[module_name] try: write(GLOBAL + bytes(module_name, "ascii") + b'
' + bytes(name, "ascii") + b'
') except UnicodeEncodeError: raise PicklingError( "can't pickle global identifier '%s.%s' using " "pickle protocol %i" % (module, name, self.proto)) self.memoize(obj) def save_type(self, obj): if obj is type(None): return self.save_reduce(type, (None,), obj=obj) elif obj is type(NotImplemented): return self.save_reduce(type, (NotImplemented,), obj=obj) elif obj is type(...): return self.save_reduce(type, (...,), obj=obj) return self.save_global(obj) dispatch[FunctionType] = save_global dispatch[type] = save_type # Unpickling machinery class _Unpickler: def __init__(self, file, *, fix_imports=True, encoding="ASCII", errors="strict"): """This takes a binary file for reading a pickle data stream. The protocol version of the pickle is detected automatically, so no proto argument is needed. The argument *file* must have two methods, a read() method that takes an integer argument, and a readline() method that requires no arguments. Both methods should return bytes. Thus *file* can be a binary file object opened for reading, an io.BytesIO object, or any other custom object that meets this interface. The file-like object must have two methods, a read() method that takes an integer argument, and a readline() method that requires no arguments. Both methods should return bytes. Thus file-like object can be a binary file object opened for reading, a BytesIO object, or any other custom object that meets this interface. Optional keyword arguments are *fix_imports*, *encoding* and *errors*, which are used to control compatibility support for pickle stream generated by Python 2. If *fix_imports* is True, pickle will try to map the old Python 2 names to the new names used in Python 3. The *encoding* and *errors* tell pickle how to decode 8-bit string instances pickled by Python 2; these default to 'ASCII' and 'strict', respectively. *encoding* can be 'bytes' to read theses 8-bit string instances as bytes objects. """ self._file_readline = file.readline self._file_read = file.read self.memo = {} self.encoding = encoding self.errors = errors self.proto = 0 self.fix_imports = fix_imports def load(self): """Read a pickled object representation from the open file. Return the reconstituted object hierarchy specified in the file. """ # Check whether Unpickler was initialized correctly. This is # only needed to mimic the behavior of _pickle.Unpickler.dump(). if not hasattr(self, "_file_read"): raise UnpicklingError("Unpickler.__init__() was not called by " "%s.__init__()" % (self.__class__.__name__,)) self._unframer = _Unframer(self._file_read, self._file_readline) self.read = self._unframer.read self.readline = self._unframer.readline self.mark = object() # any new unique object self.stack = [] self.append = self.stack.append self.proto = 0 read = self.read dispatch = self.dispatch try: while True: key = read(1) if not key: raise EOFError assert isinstance(key, bytes_types) dispatch[key[0]](self) except _Stop as stopinst: return stopinst.value # Return largest index k such that self.stack[k] is self.mark. # If the stack doesn't contain a mark, eventually raises IndexError. # This could be sped by maintaining another stack, of indices at which # the mark appears. For that matter, the latter stack would suffice, # and we wouldn't need to push mark objects on self.stack at all. # Doing so is probably a good thing, though, since if the pickle is # corrupt (or hostile) we may get a clue from finding self.mark embedded # in unpickled objects. def marker(self): stack = self.stack mark = self.mark k = len(stack)-1 while stack[k] is not mark: k = k-1 return k def persistent_load(self, pid): raise UnpicklingError("unsupported persistent id encountered") dispatch = {} def load_proto(self): proto = self.read(1)[0] if not 0 <= proto <= HIGHEST_PROTOCOL: raise ValueError("unsupported pickle protocol: %d" % proto) self.proto = proto dispatch[PROTO[0]] = load_proto def load_frame(self): frame_size, = unpack('', self.read(8)) if frame_size > sys.maxsize: raise ValueError("frame size > sys.maxsize: %d" % frame_size) self._unframer.load_frame(frame_size) dispatch[FRAME[0]] = load_frame def load_persid(self): pid = self.readline()[:-1].decode("ascii") self.append(self.persistent_load(pid)) dispatch[PERSID[0]] = load_persid def load_binpersid(self): pid = self.stack.pop() self.append(self.persistent_load(pid)) dispatch[BINPERSID[0]] = load_binpersid def load_none(self): self.append(None) dispatch[NONE[0]] = load_none def load_false(self): self.append(False) dispatch[NEWFALSE[0]] = load_false def load_true(self): self.append(True) dispatch[NEWTRUE[0]] = load_true def load_int(self): data = self.readline() if data == FALSE[1:]: val = False elif data == TRUE[1:]: val = True else: val = int(data, 0) self.append(val) dispatch[INT[0]] = load_int def load_binint(self): self.append(unpack('', self.read(4))[0]) dispatch[BININT[0]] = load_binint def load_binint1(self): self.append(self.read(1)[0]) dispatch[BININT1[0]] = load_binint1 def load_binint2(self): self.append(unpack('', self.read(2))[0]) dispatch[BININT2[0]] = load_binint2 def load_long(self): val = self.readline()[:-1] if val and val[-1] == b'L'[0]: val = val[:-1] self.append(int(val, 0)) dispatch[LONG[0]] = load_long def load_long1(self): n = self.read(1)[0] data = self.read(n) self.append(decode_long(data)) dispatch[LONG1[0]] = load_long1 def load_long4(self): n, = unpack('', self.read(4)) if n < 0: # Corrupt or hostile pickle -- we never write one like this raise UnpicklingError("LONG pickle has negative byte count") data = self.read(n) self.append(decode_long(data)) dispatch[LONG4[0]] = load_long4 def load_float(self): self.append(float(self.readline()[:-1])) dispatch[FLOAT[0]] = load_float def load_binfloat(self): self.append(unpack('>d', self.read(8))[0]) dispatch[BINFLOAT[0]] = load_binfloat def _decode_string(self, value): # Used to allow strings from Python 2 to be decoded either as # bytes or Unicode strings. This should be used only with the # STRING, BINSTRING and SHORT_BINSTRING opcodes. if self.encoding == "bytes": return value else: return value.decode(self.encoding, self.errors) def load_string(self): data = self.readline()[:-1] # Strip outermost quotes if len(data) >= 2 and data[0] == data[-1] and data[0] in b'"\'': data = data[1:-1] else: raise UnpicklingError("the STRING opcode argument must be quoted") self.append(self._decode_string(codecs.escape_decode(data)[0])) dispatch[STRING[0]] = load_string def load_binstring(self): # Deprecated BINSTRING uses signed 32-bit length len, = unpack('', self.read(4)) if len < 0: raise UnpicklingError("BINSTRING pickle has negative byte count") data = self.read(len) self.append(self._decode_string(data)) dispatch[BINSTRING[0]] = load_binstring def load_binbytes(self): len, = unpack('', self.read(4)) if len > maxsize: raise UnpicklingError("BINBYTES exceeds system's maximum size " "of %d bytes" % maxsize) self.append(self.read(len)) dispatch[BINBYTES[0]] = load_binbytes def load_unicode(self): self.append(str(self.readline()[:-1], 'raw-unicode-escape')) dispatch[UNICODE[0]] = load_unicode def load_binunicode(self): len, = unpack('', self.read(4)) if len > maxsize: raise UnpicklingError("BINUNICODE exceeds system's maximum size " "of %d bytes" % maxsize) self.append(str(self.read(len), 'utf-8', 'surrogatepass')) dispatch[BINUNICODE[0]] = load_binunicode def load_binunicode8(self): len, = unpack('', self.read(8)) if len > maxsize: raise UnpicklingError("BINUNICODE8 exceeds system's maximum size " "of %d bytes" % maxsize) self.append(str(self.read(len), 'utf-8', 'surrogatepass')) dispatch[BINUNICODE8[0]] = load_binunicode8 def load_binbytes8(self): len, = unpack('', self.read(8)) if len > maxsize: raise UnpicklingError("BINBYTES8 exceeds system's maximum size " "of %d bytes" % maxsize) self.append(self.read(len)) dispatch[BINBYTES8[0]] = load_binbytes8 def load_short_binstring(self): len = self.read(1)[0] data = self.read(len) self.append(self._decode_string(data)) dispatch[SHORT_BINSTRING[0]] = load_short_binstring def load_short_binbytes(self): len = self.read(1)[0] self.append(self.read(len)) dispatch[SHORT_BINBYTES[0]] = load_short_binbytes def load_short_binunicode(self): len = self.read(1)[0] self.append(str(self.read(len), 'utf-8', 'surrogatepass')) dispatch[SHORT_BINUNICODE[0]] = load_short_binunicode def load_tuple(self): k = self.marker() self.stack[k:] = [tuple(self.stack[k+1:])] dispatch[TUPLE[0]] = load_tuple def load_empty_tuple(self): self.append(()) dispatch[EMPTY_TUPLE[0]] = load_empty_tuple def load_tuple1(self): self.stack[-1] = (self.stack[-1],) dispatch[TUPLE1[0]] = load_tuple1 def load_tuple2(self): self.stack[-2:] = [(self.stack[-2], self.stack[-1])] dispatch[TUPLE2[0]] = load_tuple2 def load_tuple3(self): self.stack[-3:] = [(self.stack[-3], self.stack[-2], self.stack[-1])] dispatch[TUPLE3[0]] = load_tuple3 def load_empty_list(self): self.append([]) dispatch[EMPTY_LIST[0]] = load_empty_list def load_empty_dictionary(self): self.append({}) dispatch[EMPTY_DICT[0]] = load_empty_dictionary def load_empty_set(self): self.append(set()) dispatch[EMPTY_SET[0]] = load_empty_set def load_frozenset(self): k = self.marker() self.stack[k:] = [frozenset(self.stack[k+1:])] dispatch[FROZENSET[0]] = load_frozenset def load_list(self): k = self.marker() self.stack[k:] = [self.stack[k+1:]] dispatch[LIST[0]] = load_list def load_dict(self): k = self.marker() items = self.stack[k+1:] d = {items[i]: items[i+1] for i in range(0, len(items), 2)} self.stack[k:] = [d] dispatch[DICT[0]] = load_dict # INST and OBJ differ only in how they get a class object. It's not # only sensible to do the rest in a common routine, the two routines # previously diverged and grew different bugs. # klass is the class to instantiate, and k points to the topmost mark # object, following which are the arguments for klass.__init__. def _instantiate(self, klass, k): args = tuple(self.stack[k+1:]) del self.stack[k:] if (args or not isinstance(klass, type) or hasattr(klass, "__getinitargs__")): try: value = klass(*args) except TypeError as err: raise TypeError("in constructor for %s: %s" % (klass.__name__, str(err)), sys.exc_info()[2]) else: value = klass.__new__(klass) self.append(value) def load_inst(self): module = self.readline()[:-1].decode("ascii") name = self.readline()[:-1].decode("ascii") klass = self.find_class(module, name) self._instantiate(klass, self.marker()) dispatch[INST[0]] = load_inst def load_obj(self): # Stack is ... markobject classobject arg1 arg2 ... k = self.marker() klass = self.stack.pop(k+1) self._instantiate(klass, k) dispatch[OBJ[0]] = load_obj def load_newobj(self): args = self.stack.pop() cls = self.stack.pop() obj = cls.__new__(cls, *args) self.append(obj) dispatch[NEWOBJ[0]] = load_newobj def load_newobj_ex(self): kwargs = self.stack.pop() args = self.stack.pop() cls = self.stack.pop() obj = cls.__new__(cls, *args, **kwargs) self.append(obj) dispatch[NEWOBJ_EX[0]] = load_newobj_ex def load_global(self): module = self.readline()[:-1].decode("utf-8") name = self.readline()[:-1].decode("utf-8") klass = self.find_class(module, name) self.append(klass) dispatch[GLOBAL[0]] = load_global def load_stack_global(self): name = self.stack.pop() module = self.stack.pop() if type(name) is not str or type(module) is not str: raise UnpicklingError("STACK_GLOBAL requires str") self.append(self.find_class(module, name)) dispatch[STACK_GLOBAL[0]] = load_stack_global def load_ext1(self): code = self.read(1)[0] self.get_extension(code) dispatch[EXT1[0]] = load_ext1 def load_ext2(self): code, = unpack('', self.read(2)) self.get_extension(code) dispatch[EXT2[0]] = load_ext2 def load_ext4(self): code, = unpack('', self.read(4)) self.get_extension(code) dispatch[EXT4[0]] = load_ext4 def get_extension(self, code): nil = [] obj = _extension_cache.get(code, nil) if obj is not nil: self.append(obj) return key = _inverted_registry.get(code) if not key: if code <= 0: # note that 0 is forbidden # Corrupt or hostile pickle. raise UnpicklingError("EXT specifies code <= 0") raise ValueError("unregistered extension code %d" % code) obj = self.find_class(*key) _extension_cache[code] = obj self.append(obj) def find_class(self, module, name): # Subclasses may override this. if self.proto < 3 and self.fix_imports: if (module, name) in _compat_pickle.NAME_MAPPING: module, name = _compat_pickle.NAME_MAPPING[(module, name)] elif module in _compat_pickle.IMPORT_MAPPING: module = _compat_pickle.IMPORT_MAPPING[module] __import__(module, level=0) if self.proto >= 4: return _getattribute(sys.modules[module], name)[0] else: return getattr(sys.modules[module], name) def load_reduce(self): stack = self.stack args = stack.pop() func = stack[-1] stack[-1] = func(*args) dispatch[REDUCE[0]] = load_reduce def load_pop(self): del self.stack[-1] dispatch[POP[0]] = load_pop def load_pop_mark(self): k = self.marker() del self.stack[k:] dispatch[POP_MARK[0]] = load_pop_mark def load_dup(self): self.append(self.stack[-1]) dispatch[DUP[0]] = load_dup def load_get(self): i = int(self.readline()[:-1]) self.append(self.memo[i]) dispatch[GET[0]] = load_get def load_binget(self): i = self.read(1)[0] self.append(self.memo[i]) dispatch[BINGET[0]] = load_binget def load_long_binget(self): i, = unpack('', self.read(4)) self.append(self.memo[i]) dispatch[LONG_BINGET[0]] = load_long_binget def load_put(self): i = int(self.readline()[:-1]) if i < 0: raise ValueError("negative PUT argument") self.memo[i] = self.stack[-1] dispatch[PUT[0]] = load_put def load_binput(self): i = self.read(1)[0] if i < 0: raise ValueError("negative BINPUT argument") self.memo[i] = self.stack[-1] dispatch[BINPUT[0]] = load_binput def load_long_binput(self): i, = unpack('', self.read(4)) if i > maxsize: raise ValueError("negative LONG_BINPUT argument") self.memo[i] = self.stack[-1] dispatch[LONG_BINPUT[0]] = load_long_binput def load_memoize(self): memo = self.memo memo[len(memo)] = self.stack[-1] dispatch[MEMOIZE[0]] = load_memoize def load_append(self): stack = self.stack value = stack.pop() list = stack[-1] list.append(value) dispatch[APPEND[0]] = load_append def load_appends(self): stack = self.stack mark = self.marker() list_obj = stack[mark - 1] items = stack[mark + 1:] if isinstance(list_obj, list): list_obj.extend(items) else: append = list_obj.append for item in items: append(item) del stack[mark:] dispatch[APPENDS[0]] = load_appends def load_setitem(self): stack = self.stack value = stack.pop() key = stack.pop() dict = stack[-1] dict[key] = value dispatch[SETITEM[0]] = load_setitem def load_setitems(self): stack = self.stack mark = self.marker() dict = stack[mark - 1] for i in range(mark + 1, len(stack), 2): dict[stack[i]] = stack[i + 1] del stack[mark:] dispatch[SETITEMS[0]] = load_setitems def load_additems(self): stack = self.stack mark = self.marker() set_obj = stack[mark - 1] items = stack[mark + 1:] if isinstance(set_obj, set): set_obj.update(items) else: add = set_obj.add for item in items: add(item) del stack[mark:] dispatch[ADDITEMS[0]] = load_additems def load_build(self): stack = self.stack state = stack.pop() inst = stack[-1] setstate = getattr(inst, "__setstate__", None) if setstate is not None: setstate(state) return slotstate = None if isinstance(state, tuple) and len(state) == 2: state, slotstate = state if state: inst_dict = inst.__dict__ intern = sys.intern for k, v in state.items(): if type(k) is str: inst_dict[intern(k)] = v else: inst_dict[k] = v if slotstate: for k, v in slotstate.items(): setattr(inst, k, v) dispatch[BUILD[0]] = load_build def load_mark(self): self.append(self.mark) dispatch[MARK[0]] = load_mark def load_stop(self): value = self.stack.pop() raise _Stop(value) dispatch[STOP[0]] = load_stop # Shorthands def _dump(obj, file, protocol=None, *, fix_imports=True): _Pickler(file, protocol, fix_imports=fix_imports).dump(obj) def _dumps(obj, protocol=None, *, fix_imports=True): f = io.BytesIO() _Pickler(f, protocol, fix_imports=fix_imports).dump(obj) res = f.getvalue() assert isinstance(res, bytes_types) return res def _load(file, *, fix_imports=True, encoding="ASCII", errors="strict"): return _Unpickler(file, fix_imports=fix_imports, encoding=encoding, errors=errors).load() def _loads(s, *, fix_imports=True, encoding="ASCII", errors="strict"): if isinstance(s, str): raise TypeError("Can't load pickle from unicode string") file = io.BytesIO(s) return _Unpickler(file, fix_imports=fix_imports, encoding=encoding, errors=errors).load() # Use the faster _pickle if possible try: from _pickle import ( PickleError, PicklingError, UnpicklingError, Pickler, Unpickler, dump, dumps, load, loads ) except ImportError: Pickler, Unpickler = _Pickler, _Unpickler dump, dumps, load, loads = _dump, _dumps, _load, _loads # Doctest def _test(): import doctest return doctest.testmod() if __name__ == "__main__": import argparse parser = argparse.ArgumentParser( description='display contents of the pickle files') parser.add_argument( 'pickle_file', type=argparse.FileType('br'), nargs='*', help='the pickle file') parser.add_argument( '-t', '--test', action='store_true', help='run self-test suite') parser.add_argument( '-v', action='store_true', help='run verbosely; only affects self-test run') args = parser.parse_args() if args.test: _test() else: if not args.pickle_file: parser.print_help() else: import pprint for f in args.pickle_file: obj = load(f) pprint.pprint(obj)

転載先:https://www.cnblogs.com/gengcx/p/7331120.html