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agriconnect / pandas   python

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Version: 0.24.2 

/ compat / pickle_compat.py

"""
Support pre-0.12 series pickle compatibility.
"""

import copy
import pickle as pkl
import sys

from pandas.compat import string_types, u  # noqa

import pandas  # noqa
from pandas import Index, compat


def load_reduce(self):
    stack = self.stack
    args = stack.pop()
    func = stack[-1]

    if len(args) and type(args[0]) is type:
        n = args[0].__name__  # noqa

    try:
        stack[-1] = func(*args)
        return
    except Exception as e:

        # If we have a deprecated function,
        # try to replace and try again.

        msg = '_reconstruct: First argument must be a sub-type of ndarray'

        if msg in str(e):
            try:
                cls = args[0]
                stack[-1] = object.__new__(cls)
                return
            except TypeError:
                pass

        # try to re-encode the arguments
        if getattr(self, 'encoding', None) is not None:
            args = tuple(arg.encode(self.encoding)
                         if isinstance(arg, string_types)
                         else arg for arg in args)
            try:
                stack[-1] = func(*args)
                return
            except TypeError:
                pass

        # unknown exception, re-raise
        if getattr(self, 'is_verbose', None):
            print(sys.exc_info())
            print(func, args)
        raise


# If classes are moved, provide compat here.
_class_locations_map = {
    ('pandas.core.sparse.array', 'SparseArray'):
        ('pandas.core.arrays', 'SparseArray'),

    # 15477
    #
    # TODO: When FrozenNDArray is removed, add
    # the following lines for compat:
    #
    # ('pandas.core.base', 'FrozenNDArray'):
    #     ('numpy', 'ndarray'),
    # ('pandas.core.indexes.frozen', 'FrozenNDArray'):
    #     ('numpy', 'ndarray'),
    #
    # Afterwards, remove the current entry
    # for `pandas.core.base.FrozenNDArray`.
    ('pandas.core.base', 'FrozenNDArray'):
        ('pandas.core.indexes.frozen', 'FrozenNDArray'),
    ('pandas.core.base', 'FrozenList'):
        ('pandas.core.indexes.frozen', 'FrozenList'),

    # 10890
    ('pandas.core.series', 'TimeSeries'):
        ('pandas.core.series', 'Series'),
    ('pandas.sparse.series', 'SparseTimeSeries'):
        ('pandas.core.sparse.series', 'SparseSeries'),

    # 12588, extensions moving
    ('pandas._sparse', 'BlockIndex'):
        ('pandas._libs.sparse', 'BlockIndex'),
    ('pandas.tslib', 'Timestamp'):
        ('pandas._libs.tslib', 'Timestamp'),

    # 18543 moving period
    ('pandas._period', 'Period'): ('pandas._libs.tslibs.period', 'Period'),
    ('pandas._libs.period', 'Period'):
        ('pandas._libs.tslibs.period', 'Period'),

    # 18014 moved __nat_unpickle from _libs.tslib-->_libs.tslibs.nattype
    ('pandas.tslib', '__nat_unpickle'):
        ('pandas._libs.tslibs.nattype', '__nat_unpickle'),
    ('pandas._libs.tslib', '__nat_unpickle'):
        ('pandas._libs.tslibs.nattype', '__nat_unpickle'),

    # 15998 top-level dirs moving
    ('pandas.sparse.array', 'SparseArray'):
        ('pandas.core.arrays.sparse', 'SparseArray'),
    ('pandas.sparse.series', 'SparseSeries'):
        ('pandas.core.sparse.series', 'SparseSeries'),
    ('pandas.sparse.frame', 'SparseDataFrame'):
        ('pandas.core.sparse.frame', 'SparseDataFrame'),
    ('pandas.indexes.base', '_new_Index'):
        ('pandas.core.indexes.base', '_new_Index'),
    ('pandas.indexes.base', 'Index'):
        ('pandas.core.indexes.base', 'Index'),
    ('pandas.indexes.numeric', 'Int64Index'):
        ('pandas.core.indexes.numeric', 'Int64Index'),
    ('pandas.indexes.range', 'RangeIndex'):
        ('pandas.core.indexes.range', 'RangeIndex'),
    ('pandas.indexes.multi', 'MultiIndex'):
        ('pandas.core.indexes.multi', 'MultiIndex'),
    ('pandas.tseries.index', '_new_DatetimeIndex'):
        ('pandas.core.indexes.datetimes', '_new_DatetimeIndex'),
    ('pandas.tseries.index', 'DatetimeIndex'):
        ('pandas.core.indexes.datetimes', 'DatetimeIndex'),
    ('pandas.tseries.period', 'PeriodIndex'):
        ('pandas.core.indexes.period', 'PeriodIndex'),

    # 19269, arrays moving
    ('pandas.core.categorical', 'Categorical'):
        ('pandas.core.arrays', 'Categorical'),

    # 19939, add timedeltaindex, float64index compat from 15998 move
    ('pandas.tseries.tdi', 'TimedeltaIndex'):
        ('pandas.core.indexes.timedeltas', 'TimedeltaIndex'),
    ('pandas.indexes.numeric', 'Float64Index'):
        ('pandas.core.indexes.numeric', 'Float64Index'),
}


# our Unpickler sub-class to override methods and some dispatcher
# functions for compat

if compat.PY3:
    class Unpickler(pkl._Unpickler):

        def find_class(self, module, name):
            # override superclass
            key = (module, name)
            module, name = _class_locations_map.get(key, key)
            return super(Unpickler, self).find_class(module, name)

else:

    class Unpickler(pkl.Unpickler):

        def find_class(self, module, name):
            # override superclass
            key = (module, name)
            module, name = _class_locations_map.get(key, key)
            __import__(module)
            mod = sys.modules[module]
            klass = getattr(mod, name)
            return klass

Unpickler.dispatch = copy.copy(Unpickler.dispatch)
Unpickler.dispatch[pkl.REDUCE[0]] = load_reduce


def load_newobj(self):
    args = self.stack.pop()
    cls = self.stack[-1]

    # compat
    if issubclass(cls, Index):
        obj = object.__new__(cls)
    else:
        obj = cls.__new__(cls, *args)

    self.stack[-1] = obj


Unpickler.dispatch[pkl.NEWOBJ[0]] = load_newobj


def load_newobj_ex(self):
    kwargs = self.stack.pop()
    args = self.stack.pop()
    cls = self.stack.pop()

    # compat
    if issubclass(cls, Index):
        obj = object.__new__(cls)
    else:
        obj = cls.__new__(cls, *args, **kwargs)
    self.append(obj)


try:
    Unpickler.dispatch[pkl.NEWOBJ_EX[0]] = load_newobj_ex
except (AttributeError, KeyError):
    pass


def load(fh, encoding=None, compat=False, is_verbose=False):
    """load a pickle, with a provided encoding

    if compat is True:
       fake the old class hierarchy
       if it works, then return the new type objects

    Parameters
    ----------
    fh : a filelike object
    encoding : an optional encoding
    compat : provide Series compatibility mode, boolean, default False
    is_verbose : show exception output
    """

    try:
        fh.seek(0)
        if encoding is not None:
            up = Unpickler(fh, encoding=encoding)
        else:
            up = Unpickler(fh)
        up.is_verbose = is_verbose

        return up.load()
    except (ValueError, TypeError):
        raise