def testBatching_BatchCount(self):
"""Tests the GetBatchCount() debugging function."""
count = -1
with UsdMaya.DiagnosticBatchContext():
with UsdMaya.DiagnosticBatchContext():
count = UsdMaya.DiagnosticDelegate.GetBatchCount()
self.assertEqual(count, 2)
count = UsdMaya.DiagnosticDelegate.GetBatchCount()
self.assertEqual(count, 0)
def testBatching(self):
self._StartRecording()
with UsdMaya.DiagnosticBatchContext():
Tf.Warn("spooky warning")
Tf.Status("informative status")
for i in xrange(5):
Tf.Status("repeated status %d" % i)
for i in xrange(3):
Tf.Warn("spam warning %d" % i)
try:
Tf.RaiseCodingError("coding error!")
except:
pass
log = self._StopRecording()
# Note: we use assertItemsEqual because coalescing may re-order the
# diagnostic messages.
self.assertItemsEqual(
log,
[("spooky warning", OM.MCommandMessage.kWarning),
("informative status", OM.MCommandMessage.kInfo),
("repeated status 0 -- and 4 similar", OM.MCommandMessage.kInfo),
("spam warning 0 -- and 2 similar", OM.MCommandMessage.kWarning)])
def testBatching_DelegateRemoved(self):
"""Tests removing the diagnostic delegate when the batch context is
still open."""
self._StartRecording()
with UsdMaya.DiagnosticBatchContext():
Tf.Warn("this warning won't be lost")
Tf.Status("this status won't be lost")
cmds.unloadPlugin('pxrUsd', force=True)
for i in xrange(5):
Tf.Status("no delegate, this will be lost %d" % i)
log = self._StopRecording()
# Note: we use assertItemsEqual because coalescing may re-order the
# diagnostic messages.
self.assertItemsEqual(log, [
("this warning won't be lost", OM.MCommandMessage.kWarning),
("this status won't be lost", OM.MCommandMessage.kInfo),
])
