##// END OF EJS Templates
Make 'Paste Above' the default paste behavior....
Make 'Paste Above' the default paste behavior. Destructive paste mapped to Ctrl-M V is a surprising choice given that there was no drag-to-select on the area being replaced (there is a weaker notion of "selected cell" but this does not map to will-be-replaced- by-paste in the minds of participants in an unscientific poll at PyConCA). Destructive paste is still available as the last paste option in the Edit menu, qualified as "Paste Cell Replace".

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test_serialize.py
168 lines | 5.3 KiB | text/x-python | PythonLexer
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r7967 """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
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r7972 #-------------------------------------------------------------------------------
# Globals and Utilities
#-------------------------------------------------------------------------------
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r7967 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)
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r7972 SHAPES = ((100,), (1024,10), (10,8,6,5), (), (0,))
DTYPES = ('uint8', 'float64', 'int32', [('g', 'float32')], '|S10')
#-------------------------------------------------------------------------------
# Tests
#-------------------------------------------------------------------------------
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r7967 @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)
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r7972 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
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r7975 except (TypeError, NotImplementedError):
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r7972 # e.g. str dtype
pass
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r7967 @dec.parametric
@dec.skip_without('numpy')
def test_numpy():
import numpy
from numpy.testing.utils import assert_array_equal
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r7972 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')],
]:
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r7967 A = numpy.empty(shape, dtype=dtype)
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r7972 _scrub_nan(A)
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r7967 bufs = serialize_object(A)
B, r = unserialize_object(bufs)
yield nt.assert_equals(r, [])
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r7972 yield nt.assert_equals(A.shape, B.shape)
yield nt.assert_equals(A.dtype, B.dtype)
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r7967 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
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r7972 for shape in SHAPES:
for dtype in DTYPES:
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r7967 A = numpy.empty(shape, dtype=dtype)
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r7972 _scrub_nan(A)
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r7967 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, [])
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r7972 yield nt.assert_equals(A.shape, B.shape)
yield nt.assert_equals(A.dtype, B.dtype)
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r7967 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
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r7972 for shape in SHAPES:
for dtype in DTYPES:
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r7967 A = numpy.empty(shape, dtype=dtype)
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r7972 _scrub_nan(A)
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r7967 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, [])
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r7972 yield nt.assert_equals(A.shape, B.shape)
yield nt.assert_equals(A.dtype, B.dtype)
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r7967 yield assert_array_equal(A,B)