Python asizeof.asizeof方法代碼示例

# 需要導入模塊: from pympler import asizeof [as 別名]
# 或者: from pympler.asizeof import asizeof [as 別名]
def get_collection_sizes(obj, collections: Optional[Tuple]=None,
                         get_only_non_empty=False):
    """
    Iterates over `collections` of the gives object and gives its byte size
    and number of items in collection
    """
    from pympler import asizeof
    collections = collections or (list, dict, set, deque, abc.Sized)
    if not isinstance(collections, tuple):
        collections = tuple(collections)

    result = []
    for attr_name in dir(obj):
        attr = getattr(obj, attr_name)
        if isinstance(attr, collections) and (
                not get_only_non_empty or len(attr) > 0):
            result.append(
                (attr_name, len(attr), asizeof.asizeof(attr, detail=1)))
    return result 

# 需要導入模塊: from pympler import asizeof [as 別名]
# 或者: from pympler.asizeof import asizeof [as 別名]
def displayMemoryUsage(self, timeDescription):
        r"""
        Print out some information to stdout about the memory usage of ARMI.

        Makes use of the asizeof utility.

        Useful when the debugMem setting is set to True.

        Turn these on as appropriate to find all your problems.
        """
        runLog.important(
            "----- Memory Usage Report at {} -----".format(timeDescription)
        )
        self._printFullMemoryBreakdown(
            startsWith="", reportSize=self.cs["debugMemSize"]
        )
        self._reactorAssemblyTrackingBreakdown()
        runLog.important(
            "----- End Memory Usage Report at {} -----".format(timeDescription)
        ) 

# 需要導入模塊: from pympler import asizeof [as 別名]
# 或者: from pympler.asizeof import asizeof [as 別名]
def __init__(self, instance, resolution_level=0, trace=False):
        """
        Create a weak reference for 'instance' to observe an object but which
        won't prevent its deletion (which is monitored by the finalize
        callback). The size of the object is recorded in 'snapshots' as
        (timestamp, size) tuples.
        """
        self.ref = weakref_ref(instance, self.finalize)
        self.id = id(instance)
        self.repr = ''
        self.name = str(instance.__class__)
        self.birth = _get_time()
        self.death = None
        self._resolution_level = resolution_level
        self.trace = None

        if trace:
            self._save_trace()

        initial_size = asizeof.basicsize(instance) or 0
        size = asizeof.Asized(initial_size, initial_size)
        self.snapshots = [(self.birth, size)] 

# 需要導入模塊: from pympler import asizeof [as 別名]
# 或者: from pympler.asizeof import asizeof [as 別名]
def __store_stats(self):

        st_wr = open(self.__project_path + TornadoDic.get_short_names(self.learner.LEARNER_NAME).lower() + ".txt", "w")

        lrn_error_rate = PredictionEvaluator.calculate_error_rate(self.learner.get_global_confusion_matrix())
        lrn_mem = asizeof.asizeof(self.learner, limit=20)
        lrn_runtime = self.learner.get_total_running_time()

        stats = self.learner.LEARNER_NAME + "\n\t" + \
                "Classifier Error-rate: " + "%0.2f" % (100 * lrn_error_rate) + "%" + "\n\t" + \
                "Classifier Memory Usage (bytes): " + "%0.2f" % lrn_mem + "\n\t" + \
                "Classifier Runtime (ms): " + "%0.2f" % lrn_runtime

        print(stats)

        st_wr.write(stats)
        st_wr.close() 

# 需要導入模塊: from pympler import asizeof [as 別名]
# 或者: from pympler.asizeof import asizeof [as 別名]
def get_memory_usage(obj, get_collections_memory_usage=False,
                     get_only_non_empty=False):
    result = []
    from pympler import asizeof
    result.append(asizeof.asizeof(obj))
    if get_collections_memory_usage:
        result.append(
            get_collection_sizes(
                obj, get_only_non_empty=get_only_non_empty))
    return result 

# 需要導入模塊: from pympler import asizeof [as 別名]
# 或者: from pympler.asizeof import asizeof [as 別名]
def compute_size(obj):
    return asizeof.asizeof(obj) 

# 需要導入模塊: from pympler import asizeof [as 別名]
# 或者: from pympler.asizeof import asizeof [as 別名]
def set_object(self, value):
        if value is not None:
            object_hash = self.compute_hash(value)
            self.object_property = value
            self._hash = object_hash
            self.file_name = object_hash
            self.byte_size = asizeof.asizeof(value) 

# 需要導入模塊: from pympler import asizeof [as 別名]
# 或者: from pympler.asizeof import asizeof [as 別名]
def add(self, item):
        itemId = id(item)
        if itemId in self.ids:
            return False

        self.ids.add(itemId)
        if self.reportSize:
            try:
                self.memSize += asizeof(item)
            except:
                self.memSize = float("nan")
        self.count += 1
        return True 

# 需要導入模塊: from pympler import asizeof [as 別名]
# 或者: from pympler.asizeof import asizeof [as 別名]
def calcSize(self, obj):
        tempAttrs = {}
        try:
            for attrName in self.excludedAttributes:
                if hasattr(obj, attrName):
                    tempAttrs[attrName] = getattr(obj, attrName, None)
                    setattr(obj, attrName, None)
            self.sizes.append(asizeof(obj) / (1024.0 ** 2))
            self._breakdownAttributeSizes(obj)
        finally:
            for attrName, attrObj in tempAttrs.items():
                setattr(obj, attrName, attrObj) 

# 需要導入模塊: from pympler import asizeof [as 別名]
# 或者: from pympler.asizeof import asizeof [as 別名]
def get_obj_referents(oid):
    referents = {}
    obj = get_obj(oid)
    if type(obj) is dict:
        named_objects = asizeof.named_refs(obj)
    else:
        refs = asizeof._getreferents(obj)
        named_objects = [(repr(type(x)), x) for x in refs]
    for name, o in named_objects:
        referents[name] = (get_ref(o), type(o).__name__, safe_repr(o, clip=48), asizeof.asizeof(o))
    return dict(referents=referents) 

# 需要導入模塊: from pympler import asizeof [as 別名]
# 或者: from pympler.asizeof import asizeof [as 別名]
def test_slots_being_used():
    """
    The class is really using __slots__.
    """
    non_slot_instance = C1(x=1, y="test")
    slot_instance = C1Slots(x=1, y="test")

    assert "__dict__" not in dir(slot_instance)
    assert "__slots__" in dir(slot_instance)

    assert "__dict__" in dir(non_slot_instance)
    assert "__slots__" not in dir(non_slot_instance)

    assert set(["__weakref__", "x", "y"]) == set(slot_instance.__slots__)

    if has_pympler:
        assert asizeof(slot_instance) < asizeof(non_slot_instance)

    non_slot_instance.t = "test"
    with pytest.raises(AttributeError):
        slot_instance.t = "test"

    assert 1 == non_slot_instance.method()
    assert 1 == slot_instance.method()

    assert attr.fields(C1Slots) == attr.fields(C1)
    assert attr.asdict(slot_instance) == attr.asdict(non_slot_instance) 

# 需要導入模塊: from pympler import asizeof [as 別名]
# 或者: from pympler.asizeof import asizeof [as 別名]
def test_inheritance_from_slots():
    """
    Inheriting from an attrs slotted class works.
    """

    @attr.s(slots=True, hash=True)
    class C2Slots(C1Slots):
        z = attr.ib()

    @attr.s(slots=True, hash=True)
    class C2(C1):
        z = attr.ib()

    c2 = C2Slots(x=1, y=2, z="test")
    assert 1 == c2.x
    assert 2 == c2.y
    assert "test" == c2.z

    assert set(["z"]) == set(C2Slots.__slots__)

    assert 1 == c2.method()
    assert "clsmethod" == c2.classmethod()
    assert "staticmethod" == c2.staticmethod()

    with pytest.raises(AttributeError):
        c2.t = "test"

    non_slot_instance = C2(x=1, y=2, z="test")
    if has_pympler:
        assert asizeof(c2) < asizeof(non_slot_instance)

    c3 = C2Slots(x=1, y=3, z="test")
    assert c3 > c2
    c2_ = C2Slots(x=1, y=2, z="test")
    assert c2 == c2_

    assert "C2Slots(x=1, y=2, z='test')" == repr(c2)

    hash(c2)  # Just to assert it doesn't raise.

    assert {"x": 1, "y": 2, "z": "test"} == attr.asdict(c2) 

# 需要導入模塊: from pympler import asizeof [as 別名]
# 或者: from pympler.asizeof import asizeof [as 別名]
def calculate_emr(learners, error_weight=1, memory_weight=1, runtime_weight=1, lb=1, ub=10):

        learners_names = []
        learners_errors = []
        learners_runtime = []
        learners_memory_usages = []
        learners_emr_scores = []

        for learner in learners:
            learners_names.append(learner.LEARNER_NAME.title())
            learners_errors.append(PredictionEvaluator.calculate(TornadoDic.ERROR_RATE, learner.get_confusion_matrix()))
            learners_runtime.append(learner.get_total_running_time())
            if memory_weight != -1:
                learners_memory_usages.append(asizeof.asizeof(learner))
            else:
                learners_memory_usages.append(0)

        if len(learners) != 1:
            err_min, err_max = LearnersScoreCalculator.get_min_max(learners_errors)
            run_min, run_max = LearnersScoreCalculator.get_min_max(learners_runtime)
            mem_min, mem_max = LearnersScoreCalculator.get_min_max(learners_memory_usages)

            for i in range(0, len(learners_names)):
                error = LearnersScoreCalculator.scale(learners_errors[i], err_min, err_max, lb, ub)
                runtime = LearnersScoreCalculator.scale(learners_runtime[i], run_min, run_max, lb, ub)
                memory_usage = LearnersScoreCalculator.scale(learners_memory_usages[i], mem_min, mem_max, lb, ub)
                learners_emr_scores.append(LearnersScoreCalculator.__cal_emr(ub, error, runtime, memory_usage, error_weight, runtime_weight, memory_weight))

            return learners_emr_scores, learners_errors, learners_memory_usages, learners_runtime
        else:
            return None, learners_errors, learners_memory_usages, learners_runtime 

# 需要導入模塊: from pympler import asizeof [as 別名]
# 或者: from pympler.asizeof import asizeof [as 別名]
def add_result_data(self, title, key, data):
        if SIZE_CONTROL:
            if not self.MEM_LIMIT:
                mem_size = asizeof(self.current_task.results)
                if mem_size < 15000000:
                    self._add_result(title, key, data)
                else:
                    self.MEM_LIMIT = True
        else:
            self._add_result(title, key, data) 

# 需要導入模塊: from pympler import asizeof [as 別名]
# 或者: from pympler.asizeof import asizeof [as 別名]
def add_results_data(self, results):
        if SIZE_CONTROL:
            if not self.MEM_LIMIT:
                mem_size = asizeof(self.current_task.results)
                add_size = asizeof(results)
                if (mem_size + add_size) < 15000000:
                    self._add_results(results)
                else:
                    self.MEM_LIMIT = True
        else:
            self._add_results(results)