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Merge pull request #2389 from takluyver/catch-histdb-errors...
Merge pull request #2389 from takluyver/catch-histdb-errors Catch sqlite DatabaseErrors in more places when reading the history database It seems sqlite can encounter corruption and throw an error when reading the database, although it has connected successfully. This borrows the move-and-recreate machinery we already had on connecting to the database. If such an error occurs, the corrupted file is moved and the user get warned of the name of the corrupted file.

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test_serialize.py
168 lines | 5.3 KiB | text/x-python | PythonLexer
"""test serialization tools"""
#-------------------------------------------------------------------------------
# Copyright (C) 2011 The IPython Development Team
#
# Distributed under the terms of the BSD License. The full license is in
# the file COPYING, distributed as part of this software.
#-------------------------------------------------------------------------------
#-------------------------------------------------------------------------------
# Imports
#-------------------------------------------------------------------------------
import pickle
import nose.tools as nt
# from unittest import TestCaes
from IPython.zmq.serialize import serialize_object, unserialize_object
from IPython.testing import decorators as dec
from IPython.utils.pickleutil import CannedArray
#-------------------------------------------------------------------------------
# Globals and Utilities
#-------------------------------------------------------------------------------
def roundtrip(obj):
"""roundtrip an object through serialization"""
bufs = serialize_object(obj)
obj2, remainder = unserialize_object(bufs)
nt.assert_equals(remainder, [])
return obj2
class C(object):
"""dummy class for """
def __init__(self, **kwargs):
for key,value in kwargs.iteritems():
setattr(self, key, value)
SHAPES = ((100,), (1024,10), (10,8,6,5), (), (0,))
DTYPES = ('uint8', 'float64', 'int32', [('g', 'float32')], '|S10')
#-------------------------------------------------------------------------------
# Tests
#-------------------------------------------------------------------------------
@dec.parametric
def test_roundtrip_simple():
for obj in [
'hello',
dict(a='b', b=10),
[1,2,'hi'],
(b'123', 'hello'),
]:
obj2 = roundtrip(obj)
yield nt.assert_equals(obj, obj2)
@dec.parametric
def test_roundtrip_nested():
for obj in [
dict(a=range(5), b={1:b'hello'}),
[range(5),[range(3),(1,[b'whoda'])]],
]:
obj2 = roundtrip(obj)
yield nt.assert_equals(obj, obj2)
@dec.parametric
def test_roundtrip_buffered():
for obj in [
dict(a=b"x"*1025),
b"hello"*500,
[b"hello"*501, 1,2,3]
]:
bufs = serialize_object(obj)
yield nt.assert_equals(len(bufs), 2)
obj2, remainder = unserialize_object(bufs)
yield nt.assert_equals(remainder, [])
yield nt.assert_equals(obj, obj2)
def _scrub_nan(A):
"""scrub nans out of empty arrays
since nan != nan
"""
import numpy
if A.dtype.fields and A.shape:
for field in A.dtype.fields.keys():
try:
A[field][numpy.isnan(A[field])] = 0
except (TypeError, NotImplementedError):
# e.g. str dtype
pass
@dec.parametric
@dec.skip_without('numpy')
def test_numpy():
import numpy
from numpy.testing.utils import assert_array_equal
for shape in SHAPES:
for dtype in DTYPES:
A = numpy.empty(shape, dtype=dtype)
_scrub_nan(A)
bufs = serialize_object(A)
B, r = unserialize_object(bufs)
yield nt.assert_equals(r, [])
yield nt.assert_equals(A.shape, B.shape)
yield nt.assert_equals(A.dtype, B.dtype)
yield assert_array_equal(A,B)
@dec.parametric
@dec.skip_without('numpy')
def test_recarray():
import numpy
from numpy.testing.utils import assert_array_equal
for shape in SHAPES:
for dtype in [
[('f', float), ('s', '|S10')],
[('n', int), ('s', '|S1'), ('u', 'uint32')],
]:
A = numpy.empty(shape, dtype=dtype)
_scrub_nan(A)
bufs = serialize_object(A)
B, r = unserialize_object(bufs)
yield nt.assert_equals(r, [])
yield nt.assert_equals(A.shape, B.shape)
yield nt.assert_equals(A.dtype, B.dtype)
yield assert_array_equal(A,B)
@dec.parametric
@dec.skip_without('numpy')
def test_numpy_in_seq():
import numpy
from numpy.testing.utils import assert_array_equal
for shape in SHAPES:
for dtype in DTYPES:
A = numpy.empty(shape, dtype=dtype)
_scrub_nan(A)
bufs = serialize_object((A,1,2,b'hello'))
canned = pickle.loads(bufs[0])
yield nt.assert_true(canned[0], CannedArray)
tup, r = unserialize_object(bufs)
B = tup[0]
yield nt.assert_equals(r, [])
yield nt.assert_equals(A.shape, B.shape)
yield nt.assert_equals(A.dtype, B.dtype)
yield assert_array_equal(A,B)
@dec.parametric
@dec.skip_without('numpy')
def test_numpy_in_dict():
import numpy
from numpy.testing.utils import assert_array_equal
for shape in SHAPES:
for dtype in DTYPES:
A = numpy.empty(shape, dtype=dtype)
_scrub_nan(A)
bufs = serialize_object(dict(a=A,b=1,c=range(20)))
canned = pickle.loads(bufs[0])
yield nt.assert_true(canned['a'], CannedArray)
d, r = unserialize_object(bufs)
B = d['a']
yield nt.assert_equals(r, [])
yield nt.assert_equals(A.shape, B.shape)
yield nt.assert_equals(A.dtype, B.dtype)
yield assert_array_equal(A,B)