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ProcessPoolExecutor().map() fails following an identical map() #68401
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Attached file runs fine. Uncommenting line 19 makes python crash. Also, no crash happens if order of execution of map() and executor.map() is switched. This problem seems to be related to numpy in some way, the code does not crash if the commented return of function user_square is substituted for numpy functions. Using a mac with Yosemite 10.10.3. When program crashed I get window that says: " Click Reopen to open the application again. Click Report to see more detailed information and send a report to Apple. This is the traceback: Traceback (most recent call last):
File "processExample.py", line 27, in <module>
main()
File "processExample.py", line 22, in main
result3 = list(executor.map(user_square, nums))
File "/usr/local/Cellar/python3/3.4.3/Frameworks/Python.framework/Versions/3.4/lib/python3.4/concurrent/futures/_base.py", line 549, in result_iterator
yield future.result()
File "/usr/local/Cellar/python3/3.4.3/Frameworks/Python.framework/Versions/3.4/lib/python3.4/concurrent/futures/_base.py", line 402, in result
return self.__get_result()
File "/usr/local/Cellar/python3/3.4.3/Frameworks/Python.framework/Versions/3.4/lib/python3.4/concurrent/futures/_base.py", line 354, in __get_result
raise self._exception
concurrent.futures.process.BrokenProcessPool: A process in the process pool was terminated abruptly while the future was running or pending. |
I can reproduce a crash with your sample program using the current numpy wheel (1.9.2) and the python.org 3.4.3. The significant parts of the OS X crash dump: Crashed Thread: 0 Dispatch queue: com.apple.main-thread Exception Type: EXC_BAD_ACCESS (SIGSEGV) VM Regions Near 0x110: Application Specific Information: Thread 0 Crashed:: Dispatch queue: com.apple.main-thread Thread 0 crashed with X86 Thread State (64-bit): Logical CPU: 2 So the crash is occurring as a result of a call from NumPy's _dotblas extension module to OS X's libBLAS. There's nothing obvious here that would indicate this is a problem in Python itself. Suggest you pursue this in the NumPy community and, if necessary, open an issue there: |
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