from __future__ import absolute_import
import logging
import sys
import threading
import traceback
logger = logging.getLogger('pykka')
__all__ = ['log_thread_tracebacks']
[docs]def log_thread_tracebacks(*args, **kwargs):
"""Logs at :attr:`logging.CRITICAL` level a traceback for each running
thread.
This can be a convenient tool for debugging deadlocks.
The function accepts any arguments so that it can easily be used as e.g. a
signal handler, but it does not use the arguments for anything.
To use this function as a signal handler, setup logging with a
:attr:`logging.CRITICAL` threshold or lower and make your main thread
register this with the :mod:`signal` module::
import logging
import signal
import pykka.debug
logging.basicConfig(level=logging.DEBUG)
signal.signal(signal.SIGUSR1, pykka.debug.log_thread_tracebacks)
If your application deadlocks, send the `SIGUSR1` signal to the process::
kill -SIGUSR1 <pid of your process>
Signal handler caveats:
- The function *must* be registered as a signal handler by your main
thread. If not, :func:`signal.signal` will raise a :exc:`ValueError`.
- All signals in Python are handled by the main thread. Thus, the signal
will only be handled, and the tracebacks logged, if your main thread is
available to do some work. Making your main thread idle using
:func:`time.sleep` is OK. The signal will awaken your main thread.
Blocking your main thread on e.g. :func:`queue.Queue.get` or
:meth:`pykka.Future.get` will break signal handling, and thus you won't
be able to signal your process to print the thread tracebacks.
The morale is: setup signals using your main thread, start your actors,
then let your main thread relax for the rest of your application's life
cycle.
.. versionadded:: 1.1
"""
thread_names = dict((t.ident, t.name) for t in threading.enumerate())
for ident, frame in sys._current_frames().items():
name = thread_names.get(ident, '?')
stack = ''.join(traceback.format_stack(frame))
logger.critical(
'Current state of {} (ident: {}):\n{}'.format(name, ident, stack)
)