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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.

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decorators.py
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# -*- coding: utf-8 -*-
"""Decorators for labeling test objects.
Decorators that merely return a modified version of the original function
object are straightforward. Decorators that return a new function object need
to use nose.tools.make_decorator(original_function)(decorator) in returning the
decorator, in order to preserve metadata such as function name, setup and
teardown functions and so on - see nose.tools for more information.
This module provides a set of useful decorators meant to be ready to use in
your own tests. See the bottom of the file for the ready-made ones, and if you
find yourself writing a new one that may be of generic use, add it here.
Included decorators:
Lightweight testing that remains unittest-compatible.
- An @as_unittest decorator can be used to tag any normal parameter-less
function as a unittest TestCase. Then, both nose and normal unittest will
recognize it as such. This will make it easier to migrate away from Nose if
we ever need/want to while maintaining very lightweight tests.
NOTE: This file contains IPython-specific decorators. Using the machinery in
IPython.external.decorators, we import either numpy.testing.decorators if numpy is
available, OR use equivalent code in IPython.external._decorators, which
we've copied verbatim from numpy.
Authors
-------
- Fernando Perez <Fernando.Perez@berkeley.edu>
"""
#-----------------------------------------------------------------------------
# Copyright (C) 2009-2011 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
#-----------------------------------------------------------------------------
# Stdlib imports
import sys
import os
import tempfile
import unittest
# Third-party imports
# This is Michele Simionato's decorator module, kept verbatim.
from IPython.external.decorator import decorator
# Expose the unittest-driven decorators
from .ipunittest import ipdoctest, ipdocstring
# Grab the numpy-specific decorators which we keep in a file that we
# occasionally update from upstream: decorators.py is a copy of
# numpy.testing.decorators, we expose all of it here.
from IPython.external.decorators import *
# For onlyif_cmd_exists decorator
from IPython.utils.process import is_cmd_found
from IPython.utils.py3compat import string_types
#-----------------------------------------------------------------------------
# Classes and functions
#-----------------------------------------------------------------------------
# Simple example of the basic idea
def as_unittest(func):
"""Decorator to make a simple function into a normal test via unittest."""
class Tester(unittest.TestCase):
def test(self):
func()
Tester.__name__ = func.__name__
return Tester
# Utility functions
def apply_wrapper(wrapper,func):
"""Apply a wrapper to a function for decoration.
This mixes Michele Simionato's decorator tool with nose's make_decorator,
to apply a wrapper in a decorator so that all nose attributes, as well as
function signature and other properties, survive the decoration cleanly.
This will ensure that wrapped functions can still be well introspected via
IPython, for example.
"""
import nose.tools
return decorator(wrapper,nose.tools.make_decorator(func)(wrapper))
def make_label_dec(label,ds=None):
"""Factory function to create a decorator that applies one or more labels.
Parameters
----------
label : string or sequence
One or more labels that will be applied by the decorator to the functions
it decorates. Labels are attributes of the decorated function with their
value set to True.
ds : string
An optional docstring for the resulting decorator. If not given, a
default docstring is auto-generated.
Returns
-------
A decorator.
Examples
--------
A simple labeling decorator:
>>> slow = make_label_dec('slow')
>>> slow.__doc__
"Labels a test as 'slow'."
And one that uses multiple labels and a custom docstring:
>>> rare = make_label_dec(['slow','hard'],
... "Mix labels 'slow' and 'hard' for rare tests.")
>>> rare.__doc__
"Mix labels 'slow' and 'hard' for rare tests."
Now, let's test using this one:
>>> @rare
... def f(): pass
...
>>>
>>> f.slow
True
>>> f.hard
True
"""
if isinstance(label, string_types):
labels = [label]
else:
labels = label
# Validate that the given label(s) are OK for use in setattr() by doing a
# dry run on a dummy function.
tmp = lambda : None
for label in labels:
setattr(tmp,label,True)
# This is the actual decorator we'll return
def decor(f):
for label in labels:
setattr(f,label,True)
return f
# Apply the user's docstring, or autogenerate a basic one
if ds is None:
ds = "Labels a test as %r." % label
decor.__doc__ = ds
return decor
# Inspired by numpy's skipif, but uses the full apply_wrapper utility to
# preserve function metadata better and allows the skip condition to be a
# callable.
def skipif(skip_condition, msg=None):
''' Make function raise SkipTest exception if skip_condition is true
Parameters
----------
skip_condition : bool or callable
Flag to determine whether to skip test. If the condition is a
callable, it is used at runtime to dynamically make the decision. This
is useful for tests that may require costly imports, to delay the cost
until the test suite is actually executed.
msg : string
Message to give on raising a SkipTest exception.
Returns
-------
decorator : function
Decorator, which, when applied to a function, causes SkipTest
to be raised when the skip_condition was True, and the function
to be called normally otherwise.
Notes
-----
You will see from the code that we had to further decorate the
decorator with the nose.tools.make_decorator function in order to
transmit function name, and various other metadata.
'''
def skip_decorator(f):
# Local import to avoid a hard nose dependency and only incur the
# import time overhead at actual test-time.
import nose
# Allow for both boolean or callable skip conditions.
if callable(skip_condition):
skip_val = skip_condition
else:
skip_val = lambda : skip_condition
def get_msg(func,msg=None):
"""Skip message with information about function being skipped."""
if msg is None: out = 'Test skipped due to test condition.'
else: out = msg
return "Skipping test: %s. %s" % (func.__name__,out)
# We need to define *two* skippers because Python doesn't allow both
# return with value and yield inside the same function.
def skipper_func(*args, **kwargs):
"""Skipper for normal test functions."""
if skip_val():
raise nose.SkipTest(get_msg(f,msg))
else:
return f(*args, **kwargs)
def skipper_gen(*args, **kwargs):
"""Skipper for test generators."""
if skip_val():
raise nose.SkipTest(get_msg(f,msg))
else:
for x in f(*args, **kwargs):
yield x
# Choose the right skipper to use when building the actual generator.
if nose.util.isgenerator(f):
skipper = skipper_gen
else:
skipper = skipper_func
return nose.tools.make_decorator(f)(skipper)
return skip_decorator
# A version with the condition set to true, common case just to attach a message
# to a skip decorator
def skip(msg=None):
"""Decorator factory - mark a test function for skipping from test suite.
Parameters
----------
msg : string
Optional message to be added.
Returns
-------
decorator : function
Decorator, which, when applied to a function, causes SkipTest
to be raised, with the optional message added.
"""
return skipif(True,msg)
def onlyif(condition, msg):
"""The reverse from skipif, see skipif for details."""
if callable(condition):
skip_condition = lambda : not condition()
else:
skip_condition = lambda : not condition
return skipif(skip_condition, msg)
#-----------------------------------------------------------------------------
# Utility functions for decorators
def module_not_available(module):
"""Can module be imported? Returns true if module does NOT import.
This is used to make a decorator to skip tests that require module to be
available, but delay the 'import numpy' to test execution time.
"""
try:
mod = __import__(module)
mod_not_avail = False
except ImportError:
mod_not_avail = True
return mod_not_avail
def decorated_dummy(dec, name):
"""Return a dummy function decorated with dec, with the given name.
Examples
--------
import IPython.testing.decorators as dec
setup = dec.decorated_dummy(dec.skip_if_no_x11, __name__)
"""
dummy = lambda: None
dummy.__name__ = name
return dec(dummy)
#-----------------------------------------------------------------------------
# Decorators for public use
# Decorators to skip certain tests on specific platforms.
skip_win32 = skipif(sys.platform == 'win32',
"This test does not run under Windows")
skip_linux = skipif(sys.platform.startswith('linux'),
"This test does not run under Linux")
skip_osx = skipif(sys.platform == 'darwin',"This test does not run under OS X")
# Decorators to skip tests if not on specific platforms.
skip_if_not_win32 = skipif(sys.platform != 'win32',
"This test only runs under Windows")
skip_if_not_linux = skipif(not sys.platform.startswith('linux'),
"This test only runs under Linux")
skip_if_not_osx = skipif(sys.platform != 'darwin',
"This test only runs under OSX")
_x11_skip_cond = (sys.platform not in ('darwin', 'win32') and
os.environ.get('DISPLAY', '') == '')
_x11_skip_msg = "Skipped under *nix when X11/XOrg not available"
skip_if_no_x11 = skipif(_x11_skip_cond, _x11_skip_msg)
# not a decorator itself, returns a dummy function to be used as setup
def skip_file_no_x11(name):
return decorated_dummy(skip_if_no_x11, name) if _x11_skip_cond else None
# Other skip decorators
# generic skip without module
skip_without = lambda mod: skipif(module_not_available(mod), "This test requires %s" % mod)
skipif_not_numpy = skip_without('numpy')
skipif_not_matplotlib = skip_without('matplotlib')
skipif_not_sympy = skip_without('sympy')
skip_known_failure = knownfailureif(True,'This test is known to fail')
known_failure_py3 = knownfailureif(sys.version_info[0] >= 3,
'This test is known to fail on Python 3.')
# A null 'decorator', useful to make more readable code that needs to pick
# between different decorators based on OS or other conditions
null_deco = lambda f: f
# Some tests only run where we can use unicode paths. Note that we can't just
# check os.path.supports_unicode_filenames, which is always False on Linux.
try:
f = tempfile.NamedTemporaryFile(prefix=u"tmp€")
except UnicodeEncodeError:
unicode_paths = False
else:
unicode_paths = True
f.close()
onlyif_unicode_paths = onlyif(unicode_paths, ("This test is only applicable "
"where we can use unicode in filenames."))
def onlyif_cmds_exist(*commands):
"""
Decorator to skip test when at least one of `commands` is not found.
"""
for cmd in commands:
try:
if not is_cmd_found(cmd):
return skip("This test runs only if command '{0}' "
"is installed".format(cmd))
except ImportError as e:
# is_cmd_found uses pywin32 on windows, which might not be available
if sys.platform == 'win32' and 'pywin32' in str(e):
return skip("This test runs only if pywin32 and command '{0}' "
"is installed".format(cmd))
raise e
return null_deco
def onlyif_any_cmd_exists(*commands):
"""
Decorator to skip test unless at least one of `commands` is found.
"""
for cmd in commands:
try:
if is_cmd_found(cmd):
return null_deco
except ImportError as e:
# is_cmd_found uses pywin32 on windows, which might not be available
if sys.platform == 'win32' and 'pywin32' in str(e):
return skip("This test runs only if pywin32 and commands '{0}' "
"are installed".format(commands))
raise e
return skip("This test runs only if one of the commands {0} "
"is installed".format(commands))