Make IPython work if a recent numpy is not available.

I updated the numpy testing decorators module and didn't notice they
recently introduced dependencies that make it use the rest of numpy.  We may
later want to revisit this, as my solution is ugly, but I simply hacked it
to load locally the code they added, which we now carry as
_numpy_testing_utils.

Ultimately the solution to this should be taken up with upstream numpy, so
that we all agree on a common set of testing decorators with no other
dependencies aside from the stdlib.  But for now, this will let us move
forward as that discussion could take a while.

IPython/external/_numpy_testing_utils.py

@@ -0,0 +1,120 b''
+# IPython: modified copy of numpy.testing.utils, so numpy.testing.decorators
+# works without numpy being installed.
+"""
+Utility function to facilitate testing.
+"""
+
+import os
+import sys
+import re
+import operator
+import types
+import warnings
+
+# The following two classes are copied from python 2.6 warnings module (context
+# manager)
+class WarningMessage(object):
+
+    """
+    Holds the result of a single showwarning() call.
+
+    Notes
+    -----
+    `WarningMessage` is copied from the Python 2.6 warnings module,
+    so it can be used in NumPy with older Python versions.
+
+    """
+
+    _WARNING_DETAILS = ("message", "category", "filename", "lineno", "file",
+                        "line")
+
+    def __init__(self, message, category, filename, lineno, file=None,
+                    line=None):
+        local_values = locals()
+        for attr in self._WARNING_DETAILS:
+            setattr(self, attr, local_values[attr])
+        if category:
+            self._category_name = category.__name__
+        else:
+            self._category_name = None
+
+    def __str__(self):
+        return ("{message : %r, category : %r, filename : %r, lineno : %s, "
+                    "line : %r}" % (self.message, self._category_name,
+                                    self.filename, self.lineno, self.line))
+
+class WarningManager:
+    """
+    A context manager that copies and restores the warnings filter upon
+    exiting the context.
+
+    The 'record' argument specifies whether warnings should be captured by a
+    custom implementation of ``warnings.showwarning()`` and be appended to a
+    list returned by the context manager. Otherwise None is returned by the
+    context manager. The objects appended to the list are arguments whose
+    attributes mirror the arguments to ``showwarning()``.
+
+    The 'module' argument is to specify an alternative module to the module
+    named 'warnings' and imported under that name. This argument is only useful
+    when testing the warnings module itself.
+
+    Notes
+    -----
+    `WarningManager` is a copy of the ``catch_warnings`` context manager
+    from the Python 2.6 warnings module, with slight modifications.
+    It is copied so it can be used in NumPy with older Python versions.
+
+    """
+    def __init__(self, record=False, module=None):
+        self._record = record
+        if module is None:
+            self._module = sys.modules['warnings']
+        else:
+            self._module = module
+        self._entered = False
+
+    def __enter__(self):
+        if self._entered:
+            raise RuntimeError("Cannot enter %r twice" % self)
+        self._entered = True
+        self._filters = self._module.filters
+        self._module.filters = self._filters[:]
+        self._showwarning = self._module.showwarning
+        if self._record:
+            log = []
+            def showwarning(*args, **kwargs):
+                log.append(WarningMessage(*args, **kwargs))
+            self._module.showwarning = showwarning
+            return log
+        else:
+            return None
+
+    def __exit__(self):
+        if not self._entered:
+            raise RuntimeError("Cannot exit %r without entering first" % self)
+        self._module.filters = self._filters
+        self._module.showwarning = self._showwarning
+
+def assert_warns(warning_class, func, *args, **kw):
+    """Fail unless a warning of class warning_class is thrown by callable when
+    invoked with arguments args and keyword arguments kwargs.
+    
+    If a different type of warning is thrown, it will not be caught, and the
+    test case will be deemed to have suffered an error.
+    """
+
+    # XXX: once we may depend on python >= 2.6, this can be replaced by the
+    # warnings module context manager.
+    ctx = WarningManager(record=True)
+    l = ctx.__enter__()
+    warnings.simplefilter('always')
+    try:
+        func(*args, **kw)
+        if not len(l) > 0:
+            raise AssertionError("No warning raised when calling %s"
+                    % func.__name__)
+        if not l[0].category is warning_class:
+            raise AssertionError("First warning for %s is not a " \
+                    "%s( is %s)" % (func.__name__, warning_class, l[0]))
+    finally:
+        ctx.__exit__()

IPython/external/decorators.py

@@ -1,275 +1,284 b''
 """
 Decorators for labeling and modifying behavior of 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 meta-data such as
 function name, setup and teardown functions and so on - see
 ``nose.tools`` for more information.
 
 """
 import warnings
 import sys
 
-from numpy.testing.utils import \
-        WarningManager, WarningMessage
+# IPython changes: make this work if numpy not available
+# Original code:
+#from numpy.testing.utils import \
+#        WarningManager, WarningMessage
+# Our version:
+try:
+    from numpy.testing.utils import WarningManager, WarningMessage
+except ImportError:
+    from _numpy_testing_utils import WarningManager, WarningMessage
+    
+# End IPython changes
 
 def slow(t):
     """
     Label a test as 'slow'.
 
     The exact definition of a slow test is obviously both subjective and
     hardware-dependent, but in general any individual test that requires more
     than a second or two should be labeled as slow (the whole suite consits of
     thousands of tests, so even a second is significant).
 
     Parameters
     ----------
     t : callable
         The test to label as slow.
 
     Returns
     -------
     t : callable
         The decorated test `t`.
 
     Examples
     --------
     The `numpy.testing` module includes ``import decorators as dec``.
     A test can be decorated as slow like this::
 
       from numpy.testing import *
 
       @dec.slow
       def test_big(self):
           print 'Big, slow test'
 
     """
 
     t.slow = True
     return t
 
 def setastest(tf=True):
     """
     Signals to nose that this function is or is not a test.
 
     Parameters
     ----------
     tf : bool
         If True, specifies that the decorated callable is a test.
         If False, specifies that the decorated callable is not a test.
         Default is True.
 
     Notes
     -----
     This decorator can't use the nose namespace, because it can be
     called from a non-test module. See also ``istest`` and ``nottest`` in
     ``nose.tools``.
 
     Examples
     --------
     `setastest` can be used in the following way::
 
       from numpy.testing.decorators import setastest
 
       @setastest(False)
       def func_with_test_in_name(arg1, arg2):
           pass
 
     """
     def set_test(t):
         t.__test__ = tf
         return t
     return set_test
 
 def skipif(skip_condition, msg=None):
     """
     Make function raise SkipTest exception if a given condition is true.
 
     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.
 
     Parameters
     ----------
     skip_condition : bool or callable
         Flag to determine whether to skip the decorated test.
     msg : str, optional
         Message to give on raising a SkipTest exception. Default is None.
 
     Returns
     -------
     decorator : function
         Decorator which, when applied to a function, causes SkipTest
         to be raised when `skip_condition` is True, and the function
         to be called normally otherwise.
 
     Notes
     -----
     The decorator itself is decorated 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 = lambda : 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 = '\n'+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 decorator.
         if nose.util.isgenerator(f):
             skipper = skipper_gen
         else:
             skipper = skipper_func
             
         return nose.tools.make_decorator(f)(skipper)
 
     return skip_decorator
 
 
 def knownfailureif(fail_condition, msg=None):
     """
     Make function raise KnownFailureTest exception if given condition is true.
 
     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.
 
     Parameters
     ----------
     fail_condition : bool or callable
         Flag to determine whether to mark the decorated test as a known
         failure (if True) or not (if False).
     msg : str, optional
         Message to give on raising a KnownFailureTest exception.
         Default is None.
 
     Returns
     -------
     decorator : function
         Decorator, which, when applied to a function, causes SkipTest
         to be raised when `skip_condition` is True, and the function
         to be called normally otherwise.
 
     Notes
     -----
     The decorator itself is decorated with the ``nose.tools.make_decorator``
     function in order to transmit function name, and various other metadata.
 
     """
     if msg is None:
         msg = 'Test skipped due to known failure'
 
     # Allow for both boolean or callable known failure conditions.
     if callable(fail_condition):
         fail_val = lambda : fail_condition()
     else:
         fail_val = lambda : fail_condition
 
     def knownfail_decorator(f):
         # Local import to avoid a hard nose dependency and only incur the
         # import time overhead at actual test-time.
         import nose
         from noseclasses import KnownFailureTest
         def knownfailer(*args, **kwargs):
             if fail_val():
                 raise KnownFailureTest, msg
             else:
                 return f(*args, **kwargs)
         return nose.tools.make_decorator(f)(knownfailer)
 
     return knownfail_decorator
 
 def deprecated(conditional=True):
     """
     Filter deprecation warnings while running the test suite.
 
     This decorator can be used to filter DeprecationWarning's, to avoid
     printing them during the test suite run, while checking that the test
     actually raises a DeprecationWarning.
 
     Parameters
     ----------
     conditional : bool or callable, optional
         Flag to determine whether to mark test as deprecated or not. If the
         condition is a callable, it is used at runtime to dynamically make the
         decision. Default is True.
 
     Returns
     -------
     decorator : function
         The `deprecated` decorator itself.
 
     Notes
     -----
     .. versionadded:: 1.4.0
 
     """
     def deprecate_decorator(f):
         # Local import to avoid a hard nose dependency and only incur the
         # import time overhead at actual test-time.
         import nose
         from noseclasses import KnownFailureTest
 
         def _deprecated_imp(*args, **kwargs):
             # Poor man's replacement for the with statement
             ctx = WarningManager(record=True)
             l = ctx.__enter__()
             warnings.simplefilter('always')
             try:
                 f(*args, **kwargs)
                 if not len(l) > 0:
                     raise AssertionError("No warning raised when calling %s"
                             % f.__name__)
                 if not l[0].category is DeprecationWarning:
                     raise AssertionError("First warning for %s is not a " \
                             "DeprecationWarning( is %s)" % (f.__name__, l[0]))
             finally:
                 ctx.__exit__()
 
         if callable(conditional):
             cond = conditional()
         else:
             cond = conditional
         if cond:
             return nose.tools.make_decorator(f)(_deprecated_imp)
         else:
             return f
     return deprecate_decorator