##// END OF EJS Templates
upstream » ipython
RSS

Clone from https://github.com/ipython/ipython.git

Reset the interactive namespace __warningregistry__ before executing code...
Reset the interactive namespace __warningregistry__ before executing code Fixes #6611. Idea: Right now, people often don't see important warnings when running code in IPython, because (to a first approximation) any given warning will only issue once per session. Blink and you'll miss it! This is a very common contributor to confused emails to numpy-discussion. E.g.: In [5]: 1 / my_array_with_random_contents /home/njs/.user-python2.7-64bit-3/bin/ipython:1: RuntimeWarning: divide by zero encountered in divide #!/home/njs/.user-python2.7-64bit-3/bin/python Out[5]: array([ 1.77073316, -2.29765021, -2.01800811, ..., 1.13871243, -1.08302964, -8.6185091 ]) Oo, right, guess I gotta be careful of those zeros -- thanks, numpy, for giving me that warning! A few days later: In [592]: 1 / some_other_array Out[592]: array([ 3.07735763, 0.50769289, 0.83984078, ..., -0.67563917, -0.85736257, -1.36511271]) Oops, it turns out that this array had a zero in it too, and that's going to bite me later. But no warning this time! The effect of this commit is to make it so that warnings triggered by the code in cell 5 do *not* suppress warnings triggered by the code in cell 592. Note that this only applies to warnings triggered *directly* by code entered interactively -- if somepkg.foo() calls anotherpkg.bad_func() which issues a warning, then this warning will still only be displayed once, even if multiple cells call somepkg.foo(). But if cell 5 and cell 592 both call anotherpkg.bad_func() directly, then both will get warnings. (Important exception: if foo() is defined *interactively*, and calls anotherpkg.bad_func(), then every cell that calls foo() will display the warning again. This is unavoidable without fixes to CPython upstream.) Explanation: Python's warning system has some weird quirks. By default, it tries to suppress duplicate warnings, where "duplicate" means the same warning message triggered twice by the same line of code. This requires determining which line of code is responsible for triggering a warning, and this is controlled by the stacklevel= argument to warnings.warn. Basically, though, the idea is that if foo() calls bar() which calls baz() which calls some_deprecated_api(), then baz() will get counted as being "responsible", and the warning system will make a note that the usage of some_deprecated_api() inside baz() has already been warned about and doesn't need to be warned about again. So far so good. To accomplish this, obviously, there has to be a record of somewhere which line this was. You might think that this would be done by recording the filename:linenumber pair in a dict inside the warnings module, or something like that. You would be wrong. What actually happens is that the warnings module will use stack introspection to reach into baz()'s execution environment, create a global (module-level) variable there named __warningregistry__, and then, inside this dictionary, record just the line number. Basically, it assumes that any given module contains only one line 1, only one line 2, etc., so storing the filename is irrelevant. Obviously for interactive code this is totally wrong -- all cells share the same execution environment and global namespace, and they all contain a new line 1. Currently the warnings module treats these as if they were all the same line. In fact they are not the same line; once we have executed a given chunk of code, we will never see those particular lines again. As soon as a given chunk of code finishes executing, its line number labels become meaningless, and the corresponding warning registry entries become meaningless as well. Therefore, with this patch we delete the __warningregistry__ each time we execute a new block of code.
MinRK - - Load All Authors

File last commit:

r17119:103ad648
r18548:61431d7d
Show More
test_serialize.py
208 lines | 6.1 KiB | text/x-python | PythonLexer
/ IPython / kernel / zmq / tests / test_serialize.py
History | Annotation | Raw |Copy content |Copy permalink
"""test serialization tools"""
# Copyright (c) IPython Development Team.
# Distributed under the terms of the Modified BSD License.
import pickle
from collections import namedtuple
import nose.tools as nt
# from unittest import TestCaes
from IPython.kernel.zmq.serialize import serialize_object, unserialize_object
from IPython.testing import decorators as dec
from IPython.utils.pickleutil import CannedArray, CannedClass
from IPython.utils.py3compat import iteritems
from IPython.parallel import interactive
#-------------------------------------------------------------------------------
# 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 iteritems(kwargs):
setattr(self, key, value)
SHAPES = ((100,), (1024,10), (10,8,6,5), (), (0,))
DTYPES = ('uint8', 'float64', 'int32', [('g', 'float32')], '|S10')
#-------------------------------------------------------------------------------
# Tests
#-------------------------------------------------------------------------------
def new_array(shape, dtype):
import numpy
return numpy.random.random(shape).astype(dtype)
def test_roundtrip_simple():
for obj in [
'hello',
dict(a='b', b=10),
[1,2,'hi'],
(b'123', 'hello'),
]:
obj2 = roundtrip(obj)
nt.assert_equal(obj, obj2)
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)
nt.assert_equal(obj, obj2)
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)
nt.assert_equal(len(bufs), 2)
obj2, remainder = unserialize_object(bufs)
nt.assert_equal(remainder, [])
nt.assert_equal(obj, obj2)
@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 = new_array(shape, dtype=dtype)
bufs = serialize_object(A)
B, r = unserialize_object(bufs)
nt.assert_equal(r, [])
nt.assert_equal(A.shape, B.shape)
nt.assert_equal(A.dtype, B.dtype)
assert_array_equal(A,B)
@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 = new_array(shape, dtype=dtype)
bufs = serialize_object(A)
B, r = unserialize_object(bufs)
nt.assert_equal(r, [])
nt.assert_equal(A.shape, B.shape)
nt.assert_equal(A.dtype, B.dtype)
assert_array_equal(A,B)
@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 = new_array(shape, dtype=dtype)
bufs = serialize_object((A,1,2,b'hello'))
canned = pickle.loads(bufs[0])
nt.assert_is_instance(canned[0], CannedArray)
tup, r = unserialize_object(bufs)
B = tup[0]
nt.assert_equal(r, [])
nt.assert_equal(A.shape, B.shape)
nt.assert_equal(A.dtype, B.dtype)
assert_array_equal(A,B)
@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 = new_array(shape, dtype=dtype)
bufs = serialize_object(dict(a=A,b=1,c=range(20)))
canned = pickle.loads(bufs[0])
nt.assert_is_instance(canned['a'], CannedArray)
d, r = unserialize_object(bufs)
B = d['a']
nt.assert_equal(r, [])
nt.assert_equal(A.shape, B.shape)
nt.assert_equal(A.dtype, B.dtype)
assert_array_equal(A,B)
def test_class():
@interactive
class C(object):
a=5
bufs = serialize_object(dict(C=C))
canned = pickle.loads(bufs[0])
nt.assert_is_instance(canned['C'], CannedClass)
d, r = unserialize_object(bufs)
C2 = d['C']
nt.assert_equal(C2.a, C.a)
def test_class_oldstyle():
@interactive
class C:
a=5
bufs = serialize_object(dict(C=C))
canned = pickle.loads(bufs[0])
nt.assert_is_instance(canned['C'], CannedClass)
d, r = unserialize_object(bufs)
C2 = d['C']
nt.assert_equal(C2.a, C.a)
def test_tuple():
tup = (lambda x:x, 1)
bufs = serialize_object(tup)
canned = pickle.loads(bufs[0])
nt.assert_is_instance(canned, tuple)
t2, r = unserialize_object(bufs)
nt.assert_equal(t2[0](t2[1]), tup[0](tup[1]))
point = namedtuple('point', 'x y')
def test_namedtuple():
p = point(1,2)
bufs = serialize_object(p)
canned = pickle.loads(bufs[0])
nt.assert_is_instance(canned, point)
p2, r = unserialize_object(bufs, globals())
nt.assert_equal(p2.x, p.x)
nt.assert_equal(p2.y, p.y)
def test_list():
lis = [lambda x:x, 1]
bufs = serialize_object(lis)
canned = pickle.loads(bufs[0])
nt.assert_is_instance(canned, list)
l2, r = unserialize_object(bufs)
nt.assert_equal(l2[0](l2[1]), lis[0](lis[1]))
def test_class_inheritance():
@interactive
class C(object):
a=5
@interactive
class D(C):
b=10
bufs = serialize_object(dict(D=D))
canned = pickle.loads(bufs[0])
nt.assert_is_instance(canned['D'], CannedClass)
d, r = unserialize_object(bufs)
D2 = d['D']
nt.assert_equal(D2.a, D.a)
nt.assert_equal(D2.b, D.b)