Cothread locks up in response to runtime warning from numpy #78

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1. AlexanderWells-diamond commented on Oct 8, 2025

   

   AlexanderWells-diamond

   on Oct 8, 2025

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   There appears to be something wrong with how Cothread handles Numpy's error handling. Whatever interaction is happening is causing this permanent hang. It also seems to somehow be overriding the Numpy error handling setting.

   The below program demonstrates the call inside of numpy.std() that is where the hang is actually happening. Note that we are doing numpy.seterr(all='raise'), which should make all Warnings instead convert into Exceptions. They are not, we just get a hang instead.

   import numpy
   import cothread
   from numpy._core import umath as um
   
   
   def ticker():
       print('Hello')
       numpy.seterr(all='raise')
       arrmean = numpy.zeros(1)
       um.true_divide(arrmean, 0, out=arrmean,
                       casting='unsafe', subok=False)
       print('End')
   
   cothread.Spawn(ticker)
   cothread.Yield()
   print('Bye')
   
   

   Compare this to the same program running outside of a Cothread:

   import numpy
   import cothread
   from numpy._core import umath as um
   
   numpy.seterr(all='raise')
   arrmean = numpy.zeros(1)
   arrmean = um.true_divide(arrmean, 0, out=arrmean,
                                        casting='unsafe', subok=False)
   print(arrmean)
   

   Which yields the expected Exception from Numpy:

   Traceback (most recent call last):
     File "/scratch/eyh46967/dev/cothread/test.py", line 20, in <module>
       arrmean = um.true_divide(arrmean, 0, out=arrmean,
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
   FloatingPointError: invalid value encountered in divide
   
2. Araneidae commented on Oct 9, 2025

   

   Araneidae

   on Oct 9, 2025

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   This seems to be a regression from Python2: I can repeat this test with dls-python and the exception is reported normally. (In my test I'm simply using numpy.std([]) as this is a little less brittle than trying to import from numpy._core, which seems to be quite version specific.)