Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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58 lines
1.4 KiB
58 lines
1.4 KiB
import threading
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import scipy._lib.decorator
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__all__ = ['ReentrancyError', 'ReentrancyLock', 'non_reentrant']
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class ReentrancyError(RuntimeError):
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pass
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class ReentrancyLock(object):
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"""
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Threading lock that raises an exception for reentrant calls.
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Calls from different threads are serialized, and nested calls from the
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same thread result to an error.
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The object can be used as a context manager or to decorate functions
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via the decorate() method.
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"""
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def __init__(self, err_msg):
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self._rlock = threading.RLock()
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self._entered = False
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self._err_msg = err_msg
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def __enter__(self):
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self._rlock.acquire()
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if self._entered:
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self._rlock.release()
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raise ReentrancyError(self._err_msg)
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self._entered = True
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def __exit__(self, type, value, traceback):
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self._entered = False
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self._rlock.release()
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def decorate(self, func):
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def caller(func, *a, **kw):
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with self:
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return func(*a, **kw)
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return scipy._lib.decorator.decorate(func, caller)
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def non_reentrant(err_msg=None):
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"""
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Decorate a function with a threading lock and prevent reentrant calls.
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"""
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def decorator(func):
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msg = err_msg
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if msg is None:
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msg = "%s is not re-entrant" % func.__name__
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lock = ReentrancyLock(msg)
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return lock.decorate(func)
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return decorator
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