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How to use get_counting method in yandex-tank

Best Python code snippet using yandex-tank

passfail.py

Source:passfail.py

...130                    self.config['subject'],131                    self.config['condition'],132                    self.config['threshold'],133                    self.window_logic,134                    self.get_counting())135            return "%s: %s%s%s %s %d sec" % data136    def process_criteria_logic(self, tstmp, get_value):137        value = self.agg_logic(tstmp, get_value)138        state = self.condition(value, self.threshold)139        if self.window_logic == 'for':140            if state:141                self._start = min(self._start, tstmp)142                self._end = tstmp143            else:144                self._start = sys.maxsize145                self._end = 0146            if self.get_counting() >= self.window:147                self.trigger()148        elif self.window_logic == 'within' and state:149            self._start = tstmp - self.window + 1150            self._end = tstmp151            self.trigger()152        elif self.window_logic == 'over' and state:153            min_buffer_tstmp = min(self.agg_buffer.keys())154            self._start = min_buffer_tstmp155            self._end = tstmp156            if self.get_counting() >= self.window:157                self.trigger()158        logging.debug("%s %s: %s", tstmp, self, state)159    def trigger(self):160        if not self.is_triggered:161            logging.warning("%s", self)162        self.is_triggered = True163    def check(self):164        """165        Interrupt the execution if desired condition occured166        :raise AutomatedShutdown:167        """168        if self.stop and self.is_triggered:169            if self.fail:170                logging.info("Pass/Fail criterion triggered shutdown: %s", self)171                raise AutomatedShutdown("%s" % self)172            else:173                return True174        return False175    @abstractmethod176    def _get_field_functor(self, subject, percentage):177        pass178    def _get_condition_functor(self, cond):179        if cond == '=' or cond == '==':180            return lambda x, y: x == y181        elif cond == '>':182            return lambda x, y: x > y183        elif cond == '>=':184            return lambda x, y: x >= y185        elif cond == '<':186            return lambda x, y: x < y187        elif cond == '<=':188            return lambda x, y: x <= y189        else:190            raise TaurusConfigError("Unsupported fail criteria condition: %s" % cond)191    def _get_aggregator_functor(self, logic, _subject):192        if logic == 'for':193            return lambda tstmp, value: value194        elif logic in ('within', 'over'):195            return self._within_aggregator_avg  # FIXME: having simple average for percented values is a bit wrong196        else:197            raise TaurusConfigError("Unsupported window logic: %s" % logic)198    def _get_windowed_points(self, tstmp, value):199        self.agg_buffer[tstmp] = value200        keys = list(self.agg_buffer.keys())201        for tstmp_old in keys:202            if tstmp_old <= tstmp - self.window:203                del self.agg_buffer[tstmp_old]204                continue205            break206        return viewvalues(self.agg_buffer)207    def _within_aggregator_sum(self, tstmp, value):208        return sum(self._get_windowed_points(tstmp, value))209    def _within_aggregator_avg(self, tstmp, value):210        points = self._get_windowed_points(tstmp, value)211        return sum(points) / len(points)212    def get_counting(self):213        return self._end - self._start + 1214class DataCriterion(FailCriterion):215    """216    errors?217    duration (less or more than expected)218    errors in tools log?219    steady and threshold220    negate condition221    a way to inform other modules about the reason and mark the moment of start counting222    and trigger countdown for windowed223    :type config: dict224    :type owner: bzt.engine.EngineModule225    """226    def __init__(self, config, owner):227        super(DataCriterion, self).__init__(config, owner)228        self.label = config.get('label', '')229        self.selector = DataPoint.CURRENT if self.window > 0 else DataPoint.CUMULATIVE230    def aggregated_second(self, data):231        """232        Main criteria logic contained here233        :type data: bzt.modules.aggregator.DataPoint234        """235        part = data[self.selector]236        if self.label not in part:237            logging.debug("No label %s in %s", self.label, part.keys())238            return239        val = self.get_value(part[self.label])240        self.process_criteria_logic(data[DataPoint.TIMESTAMP], val)241    def _get_field_functor(self, subject, percentage):242        if subject == 'avg-rt':243            if percentage:244                raise TaurusConfigError("Percentage threshold is not applicable for %s" % subject)245            return lambda x: x[KPISet.AVG_RESP_TIME]246        elif subject == 'avg-lt':247            if percentage:248                raise TaurusConfigError("Percentage threshold is not applicable for %s" % subject)249            return lambda x: x[KPISet.AVG_LATENCY]250        elif subject == 'avg-ct':251            if percentage:252                raise TaurusConfigError("Percentage threshold is not applicable for %s" % subject)253            return lambda x: x[KPISet.AVG_CONN_TIME]254        elif subject == 'stdev-rt':255            if percentage:256                raise TaurusConfigError("Percentage threshold is not applicable for %s" % subject)257            return lambda x: x[KPISet.STDEV_RESP_TIME]258        elif subject.startswith('concurr'):259            if percentage:260                raise TaurusConfigError("Percentage threshold is not applicable for %s" % subject)261            return lambda x: x[KPISet.CONCURRENCY]262        elif subject == 'hits':263            if percentage:264                raise TaurusConfigError("Percentage threshold is not applicable for %s" % subject)265            return lambda x: x[KPISet.SAMPLE_COUNT]266        elif subject.startswith('succ'):267            if percentage:268                return lambda x: 100.0 * x[KPISet.SUCCESSES] / x[KPISet.SAMPLE_COUNT]269            else:270                return lambda x: x[KPISet.SUCCESSES]271        elif subject.startswith('fail'):272            if percentage:273                return lambda x: 100.0 * x[KPISet.FAILURES] / x[KPISet.SAMPLE_COUNT]274            else:275                return lambda x: x[KPISet.FAILURES]276        elif subject.startswith('p'):277            if percentage:278                raise TaurusConfigError("Percentage threshold is not applicable for %s" % subject)279            level = str(float(subject[1:]))280            return lambda x: x[KPISet.PERCENTILES][level] if level in x[KPISet.PERCENTILES] else 0281        elif subject.startswith('rc'):282            count = lambda x: sum([283                                      x[KPISet.RESP_CODES][y]284                                      for y in x[KPISet.RESP_CODES].keys()285                                      if fnmatch.fnmatch(y, subject[2:])286                                      ])287            if percentage:288                return lambda x: 100.0 * count(x) / float(x[KPISet.SAMPLE_COUNT])289            else:290                return count291        else:292            raise TaurusConfigError("Unsupported fail criteria subject: %s" % subject)293    def _get_aggregator_functor(self, logic, subj):294        if logic in ('within', "over") and not self.percentage:295            if subj in ('hits',) or subj.startswith('succ') or subj.startswith('fail') or subj.startswith('rc'):296                return self._within_aggregator_sum297        return super(DataCriterion, self)._get_aggregator_functor(logic, subj)298    @staticmethod299    def string_to_config(crit_config):300        """301        Parse string like "avg-rt of label>100ms for 1m, continue as non-failed"302        into config dict303        :type crit_config: str304        :rtype: dict305        """306        res = BetterDict()307        res.merge({308            "subject": None,309            "condition": None,310            "threshold": None,311            "logic": "for",312            "timeframe": 0,313            "label": "",314            "stop": True,315            "fail": True,316            "message": None,317        })318        if ':' in crit_config:319            res['message'] = crit_config[:crit_config.index(':')].strip()320            crit_config = crit_config[crit_config.index(':') + 1:].strip()321        if ',' in crit_config:322            crit_str = crit_config[:crit_config.index(',')].strip()323            action_str = crit_config[crit_config.index(',') + 1:].strip()324        else:325            crit_str = crit_config326            action_str = ""327        crit_pat = re.compile(r"([\w?*.-]+)(\s*of\s*([\S ]+))?\s*([<>=]+)\s*(\S+)(\s+(for|within|over)\s+(\S+))?")328        crit_match = crit_pat.match(crit_str.strip())329        if not crit_match:330            raise TaurusConfigError("Criteria string is malformed in its condition part: %s" % crit_str)331        crit_groups = crit_match.groups()332        res["subject"] = crit_groups[0]333        res["condition"] = crit_groups[3]334        res["threshold"] = crit_groups[4]335        if crit_groups[2]:336            res["label"] = crit_groups[2]337        if crit_groups[6]:338            res["logic"] = crit_groups[6]339        if crit_groups[7]:340            res["timeframe"] = crit_groups[7]341        if action_str:342            action_pat = re.compile(r"(stop|continue)(\s+as\s+(failed|non-failed))?")343            act_match = action_pat.match(action_str.strip())344            if not act_match:345                raise TaurusConfigError("Criteria string is malformed in its action part: %s" % action_str)346            action_groups = act_match.groups()347            res["stop"] = action_groups[0] != "continue"348            res["fail"] = action_groups[2] is None or action_groups[2] == "failed"349        return res350class PassFailWidget(Pile, PrioritizedWidget):351    """352    Represents console widget for pass/fail criteria visualisation353    If criterion is failing, it will be displayed on the widget354    return urwid widget355    :type failing_criteria: list[FailCriterion]356    """357    def __init__(self, pass_fail_reporter):358        self.pass_fail_reporter = pass_fail_reporter359        self.failing_criteria = []360        self.text_widget = Text("")361        super(PassFailWidget, self).__init__([self.text_widget])362        PrioritizedWidget.__init__(self)363    def __prepare_colors(self):364        """365        returns tuple ("color", text)366        :return:367        """368        result = []369        for failing_criterion in self.failing_criteria:370            if failing_criterion.window:371                percent = failing_criterion.get_counting() / failing_criterion.window372            else:373                percent = 1374            color = 'stat-txt'375            if 0.5 <= percent < 0.8:376                color = 'pf-3'377            elif 0.8 <= percent < 1:378                color = 'pf-4'379            elif 1 <= percent:  # pylint: disable=misplaced-comparison-constant380                color = 'pf-5'381            result.append((color, "%s\n" % failing_criterion))382        return result383    def update(self):384        """385        updates widget text386        :return:387        """388        self.text_widget.set_text("")389        self.failing_criteria = [x for x in self.pass_fail_reporter.criteria if x.get_counting() > 0]390        if self.failing_criteria:391            widget_text = self.__prepare_colors()392            self.text_widget.set_text(widget_text)...

object-oriented.py

Source:object-oriented.py

...65    @classmethod66    def how_many(cls):67        return cls.count68    @classmethod69    def get_counting(cls):70        return cls.__counting71print Person.how_many(), Person.get_counting()72bob = Person("Bob")73print Person.how_many(), Person.get_counting()...

strategy.py

Source:strategy.py

1def get_counting(n_train, epoch):2    return StopPolicy(n_train, epoch)3class StopPolicy:4    def __init__(self, n_train, epoch):5        self.epoch = epoch6        self.n_train = n_train7        self.step_loss = None8        self.epoch_losses = []9        self.val_losses=[]10        self.min_val_loss = None11        self.count_epoch=012        self.count_step=013    def update_step(self,loss):14        self.count_step +=115        if self.step_loss == None:16            self.step_loss = loss17        else:18            self.step_loss+=loss19    def update_validation_loss(self,loss):20        self.val_losses.append(loss)21        if self.min_val_loss == None:22            self.min_val_loss = loss23        elif loss < self.min_val_loss:24            self.min_val_loss = loss25    def update_validation(self,sth):26        self.update_validation_loss(sth['loss'])27    def update_epoch(self):28        self.count_epoch+=129        epoch_loss = self.step_loss/self.n_train30        self.epoch_losses.append(epoch_loss)31        self.step_loss = None32        return epoch_loss33    #def check_validation(self):34    #    return self.count_step%(self.n_train//self.bs)==035    def check_continue(self):36        return self.count_epoch < self.epoch37    38if __name__ == '__main__':39    from datasets import *40    import torch.nn as nn41    base_dir = '/mnt/md0/_datasets/OralCavity/TMA_arranged/WU/data4disease/patch10x224s1.0e0.8'42    r=043    f=044    augments='flip,simple_color'45    bs=3246    data = get_loaders(base_dir,r,f,bs,augments)47    train,val=data48    criterion = nn.CrossEntropyLoss()49    # test stop policy50    stopPolicy = get_counting(data, 2, bs)51    while stopPolicy.check_continue():52        for batch in train:53            size = batch['image'].size(0)54            outputs = torch.rand(size,2)55            y = torch.randint(0,2,(size,))56            #outputs = torch.randn(3,5,requires_grad=True)57            #y = torch.empty(3,dtype=torch.long).random_(5)58            loss = criterion(outputs, y)59            stopPolicy.update_step(loss.item()*size)60            if stopPolicy.check_validation():61                print('check validation')...

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