Python gc.disable() Examples

def test_del_newclass(self):
        # __del__ methods can trigger collection, make this to happen
        thresholds = gc.get_threshold()
        gc.enable()
        gc.set_threshold(1)

        class A(object):
            def __del__(self):
                dir(self)
        a = A()
        del a

        gc.disable()
        gc.set_threshold(*thresholds)

    # The following two tests are fragile:
    # They precisely count the number of allocations,
    # which is highly implementation-dependent.
    # For example:
    # - disposed tuples are not freed, but reused
    # - the call to assertEqual somehow avoids building its args tuple 

def test_load_refcount():
    # Check that objects returned by np.load are directly freed based on
    # their refcount, rather than needing the gc to collect them.

    f = BytesIO()
    np.savez(f, [1, 2, 3])
    f.seek(0)

    assert_(gc.isenabled())
    gc.disable()
    try:
        gc.collect()
        np.load(f)
        # gc.collect returns the number of unreachable objects in cycles that
        # were found -- we are checking that no cycles were created by np.load
        n_objects_in_cycles = gc.collect()
    finally:
        gc.enable()
    assert_equal(n_objects_in_cycles, 0) 

def test_circular_references(sentry_init, request):
    sentry_init(default_integrations=False, integrations=[ThreadingIntegration()])

    gc.collect()
    gc.disable()
    request.addfinalizer(gc.enable)

    class MyThread(Thread):
        def run(self):
            pass

    t = MyThread()
    t.start()
    t.join()
    del t

    assert not gc.collect() 

def childConnectionLost(self, childFD):
        """
        Similarly to L{childDataReceived}, disable the automatic dispatch
        provided by the base implementation to verify that the transport is
        calling this method directly.
        """
        if childFD == 1:
            self.stages.append(2)
            if self.data != b"abcd":
                raise RuntimeError(
                    "Data was %r instead of 'abcd'" % (self.data,))
            self.transport.write(b"1234")
        elif childFD == 2:
            self.stages.append(3)
            if self.err != b"1234":
                raise RuntimeError(
                    "Err was %r instead of '1234'" % (self.err,))
            self.transport.write(b"abcd")
            self.stages.append(4)
        elif childFD == 0:
            self.stages.append(5) 

def _assert_valid_refcount(op):
    """
    Check that ufuncs don't mishandle refcount of object `1`.
    Used in a few regression tests.
    """
    if not HAS_REFCOUNT:
        return True
    import numpy as np, gc

    b = np.arange(100*100).reshape(100, 100)
    c = b
    i = 1

    gc.disable()
    try:
        rc = sys.getrefcount(i)
        for j in range(15):
            d = op(b, c)
        assert_(sys.getrefcount(i) >= rc)
    finally:
        gc.enable()
    del d  # for pyflakes 

def setUp(self):
        """
        Replace L{process} os, fcntl, sys, switchUID, fdesc and pty modules
        with the mock class L{MockOS}.
        """
        if gc.isenabled():
            self.addCleanup(gc.enable)
        else:
            self.addCleanup(gc.disable)
        self.mockos = MockOS()
        self.mockos.euid = 1236
        self.mockos.egid = 1234
        self.patch(process, "os", self.mockos)
        self.patch(process, "fcntl", self.mockos)
        self.patch(process, "sys", self.mockos)
        self.patch(process, "switchUID", self.mockos.switchUID)
        self.patch(process, "fdesc", self.mockos)
        self.patch(process.Process, "processReaderFactory", DumbProcessReader)
        self.patch(process.Process, "processWriterFactory", DumbProcessWriter)
        self.patch(process, "pty", self.mockos)

        self.mocksig = MockSignal()
        self.patch(process, "signal", self.mocksig) 

def timeit(self, number=default_number):
        """Time 'number' executions of the main statement.

        To be precise, this executes the setup statement once, and
        then returns the time it takes to execute the main statement
        a number of times, as a float measured in seconds.  The
        argument is the number of times through the loop, defaulting
        to one million.  The main statement, the setup statement and
        the timer function to be used are passed to the constructor.
        """
        if itertools:
            it = itertools.repeat(None, number)
        else:
            it = [None] * number
        gcold = gc.isenabled()
        gc.disable()
        timing = self.inner(it, self.timer)
        if gcold:
            gc.enable()
        return timing 

def _assert_valid_refcount(op):
    """
    Check that ufuncs don't mishandle refcount of object `1`.
    Used in a few regression tests.
    """
    if not HAS_REFCOUNT:
        return True
    import numpy as np, gc

    b = np.arange(100*100).reshape(100, 100)
    c = b
    i = 1

    gc.disable()
    try:
        rc = sys.getrefcount(i)
        for j in range(15):
            d = op(b, c)
        assert_(sys.getrefcount(i) >= rc)
    finally:
        gc.enable()
    del d  # for pyflakes 

def host_memory_usage_in_gb():
    gc.collect()
    gc.disable() # Avoids accessing gc'd objects during traversal.
    objects = gc.get_objects()
    tensors = [obj for obj in objects if torch.is_tensor(obj)] # Debug
    host_tensors = [t for t in tensors if not t.is_cuda]
    total_mem_mb = 0
    visited_data = []

    for tensor in host_tensors:
        if tensor.is_sparse:
            continue
        # a data_ptr indicates a memory block allocated
        data_ptr = tensor.storage().data_ptr()
        if data_ptr in visited_data:
            continue
        visited_data.append(data_ptr)

        numel = tensor.storage().size()
        element_size = tensor.storage().element_size()
        mem_mb = numel*element_size /1024/1024 # 32bit=4Byte, MByte
        total_mem_mb += mem_mb

    gc.enable()
    return total_mem_mb / 1024 # in 

def timeit(self, number=default_number):
        """Time 'number' executions of the main statement.

        To be precise, this executes the setup statement once, and
        then returns the time it takes to execute the main statement
        a number of times, as a float measured in seconds.  The
        argument is the number of times through the loop, defaulting
        to one million.  The main statement, the setup statement and
        the timer function to be used are passed to the constructor.
        """
        if itertools:
            it = itertools.repeat(None, number)
        else:
            it = [None] * number
        gcold = gc.isenabled()
        gc.disable()
        try:
            timing = self.inner(it, self.timer)
        finally:
            if gcold:
                gc.enable()
        return timing 

def sig_vtalrm(self, *args):
        self.hndl_called = True

        if self.hndl_count > 3:
            # it shouldn't be here, because it should have been disabled.
            raise signal.ItimerError("setitimer didn't disable ITIMER_VIRTUAL "
                "timer.")
        elif self.hndl_count == 3:
            # disable ITIMER_VIRTUAL, this function shouldn't be called anymore
            signal.setitimer(signal.ITIMER_VIRTUAL, 0)
            if test_support.verbose:
                print("last SIGVTALRM handler call")

        self.hndl_count += 1

        if test_support.verbose:
            print("SIGVTALRM handler invoked", args) 

def _assert_valid_refcount(op):
    """
    Check that ufuncs don't mishandle refcount of object `1`.
    Used in a few regression tests.
    """
    if not HAS_REFCOUNT:
        return True
    import numpy as np, gc

    b = np.arange(100*100).reshape(100, 100)
    c = b
    i = 1

    gc.disable()
    try:
        rc = sys.getrefcount(i)
        for j in range(15):
            d = op(b, c)
        assert_(sys.getrefcount(i) >= rc)
    finally:
        gc.enable()
    del d  # for pyflakes 

def test_free_from_gc(self):
        # Check that freeing of blocks by the garbage collector doesn't deadlock
        # (issue #12352).
        # Make sure the GC is enabled, and set lower collection thresholds to
        # make collections more frequent (and increase the probability of
        # deadlock).
        if not gc.isenabled():
            gc.enable()
            self.addCleanup(gc.disable)
        thresholds = gc.get_threshold()
        self.addCleanup(gc.set_threshold, *thresholds)
        gc.set_threshold(10)

        # perform numerous block allocations, with cyclic references to make
        # sure objects are collected asynchronously by the gc
        for i in range(5000):
            a = multiprocessing.heap.BufferWrapper(1)
            b = multiprocessing.heap.BufferWrapper(1)
            # circular references
            a.buddy = b
            b.buddy = a

#
#
# 

def test_main():
    enabled = gc.isenabled()
    gc.disable()
    assert not gc.isenabled()
    debug = gc.get_debug()
    gc.set_debug(debug & ~gc.DEBUG_LEAK) # this test is supposed to leak

    try:
        gc.collect() # Delete 2nd generation garbage
        run_unittest(GCTests, GCTogglingTests)
    finally:
        gc.set_debug(debug)
        # test gc.enable() even if GC is disabled by default
        if verbose:
            print "restoring automatic collection"
        # make sure to always test gc.enable()
        gc.enable()
        assert gc.isenabled()
        if not enabled:
            gc.disable() 

def test_del_newclass(self):
        # __del__ methods can trigger collection, make this to happen
        thresholds = gc.get_threshold()
        gc.enable()
        gc.set_threshold(1)

        class A(object):
            def __del__(self):
                dir(self)
        a = A()
        del a

        gc.disable()
        gc.set_threshold(*thresholds)

    # The following two tests are fragile:
    # They precisely count the number of allocations,
    # which is highly implementation-dependent.
    # For example:
    # - disposed tuples are not freed, but reused
    # - the call to assertEqual somehow avoids building its args tuple 

def test_del_newclass(self):
        # __del__ methods can trigger collection, make this to happen
        thresholds = gc.get_threshold()
        gc.enable()
        gc.set_threshold(1)

        class A(object):
            def __del__(self):
                dir(self)
        a = A()
        del a

        gc.disable()
        gc.set_threshold(*thresholds)

    # The following two tests are fragile:
    # They precisely count the number of allocations,
    # which is highly implementation-dependent.
    # For example:
    # - disposed tuples are not freed, but reused
    # - the call to assertEqual somehow avoids building its args tuple 

def test_free_from_gc(self):
        # Check that freeing of blocks by the garbage collector doesn't deadlock
        # (issue #12352).
        # Make sure the GC is enabled, and set lower collection thresholds to
        # make collections more frequent (and increase the probability of
        # deadlock).
        if not gc.isenabled():
            gc.enable()
            self.addCleanup(gc.disable)
        thresholds = gc.get_threshold()
        self.addCleanup(gc.set_threshold, *thresholds)
        gc.set_threshold(10)

        # perform numerous block allocations, with cyclic references to make
        # sure objects are collected asynchronously by the gc
        for i in range(5000):
            a = multiprocessing.heap.BufferWrapper(1)
            b = multiprocessing.heap.BufferWrapper(1)
            # circular references
            a.buddy = b
            b.buddy = a

#
#
# 

def test_load_refcount():
    # Check that objects returned by np.load are directly freed based on
    # their refcount, rather than needing the gc to collect them.

    f = BytesIO()
    np.savez(f, [1, 2, 3])
    f.seek(0)

    assert_(gc.isenabled())
    gc.disable()
    try:
        gc.collect()
        np.load(f)
        # gc.collect returns the number of unreachable objects in cycles that
        # were found -- we are checking that no cycles were created by np.load
        n_objects_in_cycles = gc.collect()
    finally:
        gc.enable()
    assert_equal(n_objects_in_cycles, 0) 

def timeit(self, number=default_number):
        """Time 'number' executions of the main statement.

        To be precise, this executes the setup statement once, and
        then returns the time it takes to execute the main statement
        a number of times, as a float measured in seconds.  The
        argument is the number of times through the loop, defaulting
        to one million.  The main statement, the setup statement and
        the timer function to be used are passed to the constructor.
        """
        if itertools:
            it = itertools.repeat(None, number)
        else:
            it = [None] * number
        gcold = gc.isenabled()
        gc.disable()
        try:
            timing = self.inner(it, self.timer)
        finally:
            if gcold:
                gc.enable()
        return timing 

def sig_vtalrm(self, *args):
        self.hndl_called = True

        if self.hndl_count > 3:
            # it shouldn't be here, because it should have been disabled.
            raise signal.ItimerError("setitimer didn't disable ITIMER_VIRTUAL "
                "timer.")
        elif self.hndl_count == 3:
            # disable ITIMER_VIRTUAL, this function shouldn't be called anymore
            signal.setitimer(signal.ITIMER_VIRTUAL, 0)
            if test_support.verbose:
                print("last SIGVTALRM handler call")

        self.hndl_count += 1

        if test_support.verbose:
            print("SIGVTALRM handler invoked", args) 

def timeit(self, number=default_number):
        """Time 'number' executions of the main statement.

        To be precise, this executes the setup statement once, and
        then returns the time it takes to execute the main statement
        a number of times, as a float measured in seconds.  The
        argument is the number of times through the loop, defaulting
        to one million.  The main statement, the setup statement and
        the timer function to be used are passed to the constructor.
        """
        if itertools:
            it = itertools.repeat(None, number)
        else:
            it = [None] * number
        gcold = gc.isenabled()
        gc.disable()
        try:
            timing = self.inner(it, self.timer)
        finally:
            if gcold:
                gc.enable()
        return timing 

def test_load_refcount():
    # Check that objects returned by np.load are directly freed based on
    # their refcount, rather than needing the gc to collect them.

    f = BytesIO()
    np.savez(f, [1, 2, 3])
    f.seek(0)

    assert_(gc.isenabled())
    gc.disable()
    try:
        gc.collect()
        np.load(f)
        # gc.collect returns the number of unreachable objects in cycles that
        # were found -- we are checking that no cycles were created by np.load
        n_objects_in_cycles = gc.collect()
    finally:
        gc.enable()
    assert_equal(n_objects_in_cycles, 0) 

def load_parser(self, path, original_changed_time):
        try:
            pickle_changed_time = self._index[path]
        except KeyError:
            return None
        if original_changed_time is not None \
                and pickle_changed_time < original_changed_time:
            # the pickle file is outdated
            return None

        with open(self._get_hashed_path(path), 'rb') as f:
            try:
                gc.disable()
                parser_cache_item = pickle.load(f)
            finally:
                gc.enable()

        debug.dbg('pickle loaded: %s', path)
        parser_cache[path] = parser_cache_item
        return parser_cache_item.parser 

def timeit(self, number=default_number):
        """Time 'number' executions of the main statement.

        To be precise, this executes the setup statement once, and
        then returns the time it takes to execute the main statement
        a number of times, as a float measured in seconds.  The
        argument is the number of times through the loop, defaulting
        to one million.  The main statement, the setup statement and
        the timer function to be used are passed to the constructor.
        """
        if itertools:
            it = itertools.repeat(None, number)
        else:
            it = [None] * number
        gcold = gc.isenabled()
        gc.disable()
        try:
            timing = self.inner(it, self.timer)
        finally:
            if gcold:
                gc.enable()
        return timing 

def timeit(self, number=default_number):
        """Time 'number' executions of the main statement.

        To be precise, this executes the setup statement once, and
        then returns the time it takes to execute the main statement
        a number of times, as a float measured in seconds.  The
        argument is the number of times through the loop, defaulting
        to one million.  The main statement, the setup statement and
        the timer function to be used are passed to the constructor.
        """
        if itertools:
            it = itertools.repeat(None, number)
        else:
            it = [None] * number
        gcold = gc.isenabled()
        gc.disable()
        timing = self.inner(it, self.timer)
        if gcold:
            gc.enable()
        return timing 

def sig_vtalrm(self, *args):
        self.hndl_called = True

        if self.hndl_count > 3:
            # it shouldn't be here, because it should have been disabled.
            raise signal.ItimerError("setitimer didn't disable ITIMER_VIRTUAL "
                "timer.")
        elif self.hndl_count == 3:
            # disable ITIMER_VIRTUAL, this function shouldn't be called anymore
            signal.setitimer(signal.ITIMER_VIRTUAL, 0)
            if test_support.verbose:
                print("last SIGVTALRM handler call")

        self.hndl_count += 1

        if test_support.verbose:
            print("SIGVTALRM handler invoked", args) 

def test_free_from_gc(self):
        # Check that freeing of blocks by the garbage collector doesn't deadlock
        # (issue #12352).
        # Make sure the GC is enabled, and set lower collection thresholds to
        # make collections more frequent (and increase the probability of
        # deadlock).
        if not gc.isenabled():
            gc.enable()
            self.addCleanup(gc.disable)
        thresholds = gc.get_threshold()
        self.addCleanup(gc.set_threshold, *thresholds)
        gc.set_threshold(10)

        # perform numerous block allocations, with cyclic references to make
        # sure objects are collected asynchronously by the gc
        for i in range(5000):
            a = multiprocessing.heap.BufferWrapper(1)
            b = multiprocessing.heap.BufferWrapper(1)
            # circular references
            a.buddy = b
            b.buddy = a

#
#
# 

def test_main():
    enabled = gc.isenabled()
    gc.disable()
    assert not gc.isenabled()
    debug = gc.get_debug()
    gc.set_debug(debug & ~gc.DEBUG_LEAK) # this test is supposed to leak

    try:
        gc.collect() # Delete 2nd generation garbage
        run_unittest(GCTests, GCTogglingTests)
    finally:
        gc.set_debug(debug)
        # test gc.enable() even if GC is disabled by default
        if verbose:
            print "restoring automatic collection"
        # make sure to always test gc.enable()
        gc.enable()
        assert gc.isenabled()
        if not enabled:
            gc.disable() 

def timeit(self, number=default_number):
        """Time 'number' executions of the main statement.

        To be precise, this executes the setup statement once, and
        then returns the time it takes to execute the main statement
        a number of times, as a float measured in seconds.  The
        argument is the number of times through the loop, defaulting
        to one million.  The main statement, the setup statement and
        the timer function to be used are passed to the constructor.
        """
        it = itertools.repeat(None, number)
        gcold = gc.isenabled()
        gc.disable()
        try:
            timing = self.inner(it, self.timer)
        finally:
            if gcold:
                gc.enable()
        return timing 

def __init__(self, global_config):
        self.global_config = global_config
        self.ccmap = []
        self.el = Timeout(self.GClector, 60, -1)
        Signal(SIGHUP, self.discAll, SIGHUP)
        Signal(SIGUSR2, self.toggleDebug, SIGUSR2)
        Signal(SIGPROF, self.safeRestart, SIGPROF)
        Signal(SIGTERM, self.safeStop, SIGTERM)
        #gc.disable()
        #gc.set_debug(gc.DEBUG_STATS)
        #gc.set_threshold(0)
        #print gc.collect()