Merge pull request pandas-dev#4755 from jreback/pickle_compat

BUG: TimeSeries compat from < 0.13

Author: jreback

pandas/compat/pickle_compat.py

@@ -1,62 +1,103 @@
 """ support pre 0.12 series pickle compatibility """
 
 import sys
-import pickle
 import numpy as np
 import pandas
+import pickle as pkl
 from pandas import compat
-from pandas.core.series import Series
-from pandas.sparse.series import SparseSeries
+from pandas.compat import u, string_types
+from pandas.core.series import Series, TimeSeries
+from pandas.sparse.series import SparseSeries, SparseTimeSeries
 
 def load_reduce(self):
     stack = self.stack
     args = stack.pop()
     func = stack[-1]
     if type(args[0]) is type:
         n = args[0].__name__
-        if n == 'DeprecatedSeries':
+        if n == u('DeprecatedSeries') or n == u('DeprecatedTimeSeries'):
             stack[-1] = object.__new__(Series)
             return
-        elif n == 'DeprecatedSparseSeries':
+        elif n == u('DeprecatedSparseSeries') or n == u('DeprecatedSparseTimeSeries'):
             stack[-1] = object.__new__(SparseSeries)
             return
 
     try:
         value = func(*args)
     except:
-        print(sys.exc_info())
-        print(func, args)
+
+        # try to reencode the arguments
+        if self.encoding 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:
+                pass
+
+        if self.is_verbose:
+            print(sys.exc_info())
+            print(func, args)
         raise
 
     stack[-1] = value
 
 if compat.PY3:
-    class Unpickler(pickle._Unpickler):
+    class Unpickler(pkl._Unpickler):
         pass
 else:
-    class Unpickler(pickle.Unpickler):
+    class Unpickler(pkl.Unpickler):
         pass
 
-Unpickler.dispatch[pickle.REDUCE[0]] = load_reduce
+Unpickler.dispatch[pkl.REDUCE[0]] = load_reduce
+
+def load(fh, encoding=None, compat=False, is_verbose=False):
+    """
+    load a pickle, with a provided encoding
 
-def load(file):
-    # try to load a compatibility pickle
-    # fake the old class hierarchy
-    # if it works, then return the new type objects
+    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:
-        pandas.core.series.Series = DeprecatedSeries
-        pandas.sparse.series.SparseSeries = DeprecatedSparseSeries
-        with open(file,'rb') as fh:
-            return Unpickler(fh).load()
+        if compat:
+            pandas.core.series.Series = DeprecatedSeries
+            pandas.core.series.TimeSeries = DeprecatedTimeSeries
+            pandas.sparse.series.SparseSeries = DeprecatedSparseSeries
+            pandas.sparse.series.SparseTimeSeries = DeprecatedSparseTimeSeries
+        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:
         raise
     finally:
-        pandas.core.series.Series = Series
-        pandas.sparse.series.SparseSeries = SparseSeries
+        if compat:
+            pandas.core.series.Series = Series
+            pandas.core.series.Series = TimeSeries
+            pandas.sparse.series.SparseSeries = SparseSeries
+            pandas.sparse.series.SparseTimeSeries = SparseTimeSeries
 
-class DeprecatedSeries(Series, np.ndarray):
+class DeprecatedSeries(np.ndarray, Series):
+    pass
+
+class DeprecatedTimeSeries(DeprecatedSeries):
     pass
 
 class DeprecatedSparseSeries(DeprecatedSeries):
     pass
+
+class DeprecatedSparseTimeSeries(DeprecatedSparseSeries):
+    pass

pandas/core/internals.py

@@ -1845,6 +1845,11 @@ def __setstate__(self, state):
 
         blocks = []
         for values, items in zip(bvalues, bitems):
+
+            # numpy < 1.7 pickle compat
+            if values.dtype == 'M8[us]':
+                values = values.astype('M8[ns]')
+
             blk = make_block(values, items, self.axes[0])
             blocks.append(blk)
         self.blocks = blocks

pandas/io/pickle.py

@@ -1,4 +1,4 @@
-from pandas.compat import cPickle as pkl, PY3
+from pandas.compat import cPickle as pkl, pickle_compat as pc, PY3
 
 def to_pickle(obj, path):
     """
@@ -31,11 +31,23 @@ def read_pickle(path):
     -------
     unpickled : type of object stored in file
     """
+
+    def try_read(path, encoding=None):
+        # try with current pickle, if we have a Type Error then
+        # try with the compat pickle to handle subclass changes
+        # pass encoding only if its not None as py2 doesn't handle
+        # the param
+        try:
+            with open(path,'rb') as fh:
+                with open(path,'rb') as fh:
+                    return pc.load(fh, encoding=encoding, compat=False)
+        except:
+            with open(path,'rb') as fh:
+                return pc.load(fh, encoding=encoding, compat=True)
+
     try:
-        with open(path, 'rb') as fh:
-            return pkl.load(fh)
+        return try_read(path)
     except:
         if PY3:
-            with open(path, 'rb') as fh:
-                return pkl.load(fh, encoding='latin1')
+            return try_read(path, encoding='latin1')
         raise

pandas/io/tests/data/legacy_pickle/0.11.0/0.11.0_x86_64_linux_3.3.0.pickle

@@ -1,26 +1,47 @@
 """ self-contained to write legacy pickle files """
 from __future__ import print_function
 
-from pandas.compat import zip, cPickle as pickle
+# make sure we are < 0.13 compat (in py3)
+try:
+    from pandas.compat import zip, cPickle as pickle
+except:
+    import pickle
 
 def _create_sp_series():
 
     import numpy as np
-    from pandas import bdate_range, SparseSeries
+    from pandas import SparseSeries
 
     nan = np.nan
 
     # nan-based
-    arr = np.arange(15, dtype=float)
+    arr = np.arange(15, dtype=np.float64)
     index = np.arange(15)
     arr[7:12] = nan
     arr[-1:] = nan
 
-    date_index = bdate_range('1/1/2011', periods=len(index))
-    bseries = SparseSeries(arr, index=index, kind='block')
+    bseries = SparseSeries(arr, kind='block')
     bseries.name = 'bseries'
     return bseries
 
+def _create_sp_tsseries():
+
+    import numpy as np
+    from pandas import bdate_range, SparseTimeSeries
+
+    nan = np.nan
+
+    # nan-based
+    arr = np.arange(15, dtype=np.float64)
+    index = np.arange(15)
+    arr[7:12] = nan
+    arr[-1:] = nan
+
+    date_index = bdate_range('1/1/2011', periods=len(index))
+    bseries = SparseTimeSeries(arr, index=date_index, kind='block')
+    bseries.name = 'btsseries'
+    return bseries
+
 def _create_sp_frame():
     import numpy as np
     from pandas import bdate_range, SparseDataFrame
@@ -29,7 +50,7 @@ def _create_sp_frame():
 
     data = {'A': [nan, nan, nan, 0, 1, 2, 3, 4, 5, 6],
             'B': [0, 1, 2, nan, nan, nan, 3, 4, 5, 6],
-            'C': np.arange(10),
+            'C': np.arange(10).astype(np.int64),
             'D': [0, 1, 2, 3, 4, 5, nan, nan, nan, nan]}
 
     dates = bdate_range('1/1/2011', periods=10)
@@ -40,8 +61,8 @@ def create_data():
 
     import numpy as np
     import pandas
-    from pandas import (Series,DataFrame,Panel,
-                        SparseSeries,SparseDataFrame,SparsePanel,
+    from pandas import (Series,TimeSeries,DataFrame,Panel,
+                        SparseSeries,SparseTimeSeries,SparseDataFrame,SparsePanel,
                         Index,MultiIndex,PeriodIndex,
                         date_range,bdate_range,Timestamp)
     nan = np.nan
@@ -61,10 +82,11 @@ def create_data():
                                                  names=['first', 'second']))
     series = dict(float = Series(data['A']),
                   int = Series(data['B']),
-                  mixed = Series(data['E']))
+                  mixed = Series(data['E']),
+                  ts = TimeSeries(np.arange(10).astype(np.int64),index=date_range('20130101',periods=10)))
     frame = dict(float = DataFrame(dict(A = series['float'], B = series['float'] + 1)),
-                  int = DataFrame(dict(A = series['int']  , B = series['int']   + 1)),
-                  mixed = DataFrame(dict([ (k,data[k]) for k in ['A','B','C','D']])))
+                 int = DataFrame(dict(A = series['int']  , B = series['int']   + 1)),
+                 mixed = DataFrame(dict([ (k,data[k]) for k in ['A','B','C','D']])))
     panel = dict(float = Panel(dict(ItemA = frame['float'], ItemB = frame['float']+1)))
 
 
@@ -74,7 +96,8 @@ def create_data():
                  panel = panel,
                  index = index,
                  mi = mi,
-                 sp_series = dict(float = _create_sp_series()),
+                 sp_series = dict(float = _create_sp_series(),
+                                  ts = _create_sp_tsseries()),
                  sp_frame = dict(float = _create_sp_frame())
                  )
 
@@ -92,24 +115,11 @@ def write_legacy_pickles():
 
     print("This script generates a pickle file for the current arch, system, and python version")
 
-    base_dir, _ = os.path.split(os.path.abspath(__file__))
-    base_dir = os.path.join(base_dir,'data/legacy_pickle')
-
-    # could make this a parameter?
-    version = None
-
-
-    if version is None:
-        version = pandas.__version__
-    pth = os.path.join(base_dir, str(version))
-    try:
-        os.mkdir(pth)
-    except:
-        pass
+    version = pandas.__version__
 
     # construct a reasonable platform name
-    f = '_'.join([ str(pl.machine()), str(pl.system().lower()), str(pl.python_version()) ])
-    pth = os.path.abspath(os.path.join(pth,'%s.pickle' % f))
+    f = '_'.join([ str(version), str(pl.machine()), str(pl.system().lower()), str(pl.python_version()) ])
+    pth = '{0}.pickle'.format(f)
 
     fh = open(pth,'wb')
     pickle.dump(create_data(),fh,pickle.HIGHEST_PROTOCOL)

pandas/io/tests/data/legacy_pickle/0.12.0/0.12.0_i686_linux_2.7.3.pickle

@@ -4,7 +4,7 @@
 
 from datetime import datetime, timedelta
 import operator
-import pickle
+import pickle as pkl
 import unittest
 import nose
 import os
@@ -29,25 +29,11 @@ def compare(self, vf):
 
         # py3 compat when reading py2 pickle
         try:
-            with open(vf,'rb') as fh:
-                data = pickle.load(fh)
-        except ValueError as detail:
-
-            # we are trying to read a py3 pickle in py2.....
+            data = pandas.read_pickle(vf)
+        except (ValueError) as detail:
+            # trying to read a py3 pickle in py2
             return
 
-        # we have a deprecated klass
-        except TypeError as detail:
-
-            from pandas.compat.pickle_compat import load
-            data = load(vf)
-
-        except:
-            if not compat.PY3:
-                raise
-            with open(vf,'rb') as fh:
-                data = pickle.load(fh, encoding='latin1')
-
         for typ, dv in data.items():
             for dt, result in dv.items():
 
@@ -64,23 +50,26 @@ def compare(self, vf):
                     comparator = getattr(tm,"assert_%s_equal" % typ)
                     comparator(result,expected)
 
-    def test_read_pickles_0_10_1(self):
+    def read_pickles(self, version):
         if not is_little_endian():
-            raise nose.SkipTest("known failure of test_read_pickles_0_10_1 on non-little endian")
+            raise nose.SkipTest("known failure on non-little endian")
 
-        pth = tm.get_data_path('legacy_pickle/0.10.1')
+        pth = tm.get_data_path('legacy_pickle/{0}'.format(str(version)))
         for f in os.listdir(pth):
             vf = os.path.join(pth,f)
             self.compare(vf)
 
+    def test_read_pickles_0_10_1(self):
+        self.read_pickles('0.10.1')
+
     def test_read_pickles_0_11_0(self):
-        if not is_little_endian():
-            raise nose.SkipTest("known failure of test_read_pickles_0_11_0 on non-little endian")
+        self.read_pickles('0.11.0')
 
-        pth = tm.get_data_path('legacy_pickle/0.11.0')
-        for f in os.listdir(pth):
-            vf = os.path.join(pth,f)
-            self.compare(vf)
+    def test_read_pickles_0_12_0(self):
+        self.read_pickles('0.12.0')
+
+    def test_read_pickles_0_13_0(self):
+        self.read_pickles('0.13.0')
 
 if __name__ == '__main__':
     import nose

pandas/io/tests/data/legacy_pickle/0.12.0/0.12.0_x86_64_linux_2.7.3.pickle

@@ -533,6 +533,12 @@ def __setstate__(self, state):
             self.offset = own_state[1]
             self.tz = own_state[2]
             np.ndarray.__setstate__(self, nd_state)
+
+            # provide numpy < 1.7 compat
+            if nd_state[2] == 'M8[us]':
+                new_state = np.ndarray.__reduce__(self.values.astype('M8[ns]'))
+                np.ndarray.__setstate__(self, new_state[2])
+
         else:  # pragma: no cover
             np.ndarray.__setstate__(self, state)
 

pandas/io/tests/data/legacy_pickle/0.12.0/x86_64_linux_2.7.3.pickle

@@ -526,6 +526,8 @@ def pxd(name):
       package_data={'pandas.io': ['tests/data/legacy_hdf/*.h5',
                                   'tests/data/legacy_pickle/0.10.1/*.pickle',
                                   'tests/data/legacy_pickle/0.11.0/*.pickle',
+                                  'tests/data/legacy_pickle/0.12.0/*.pickle',
+                                  'tests/data/legacy_pickle/0.13.0/*.pickle',
                                   'tests/data/*.csv',
                                   'tests/data/*.dta',
                                   'tests/data/*.txt',