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How to use __make_points method in yandex-tank

Best Python code snippet using yandex-tank

decoder.py

Source:decoder.py

...36        points = list()37        for second_data in data:38            for host, host_data in second_data["data"].items():39                points.append(40                    self.__make_points(41                        "monitoring",42                        {"host": host, "comment": host_data.get("comment")},43                        second_data["timestamp"],44                        {45                            # cast int to float. avoid https://github.com/yandex/yandex-tank/issues/77646                            metric: float(value) if isinstance(value, int) else value47                            for metric, value in host_data["metrics"].items()48                        }49                    )50                )51        return points52    def decode_aggregates(self, aggregated_data, gun_stats, prefix):53        ts = aggregated_data["ts"]54        points = list()55        # stats overall w/ __OVERALL__ label56        points += self.__make_points_for_label(57            ts,58            aggregated_data["overall"],59            "__OVERALL__",60            prefix,61            gun_stats62        )63        # detailed stats per tag64        if self.labeled:65            for label, aggregated_data_by_tag in aggregated_data["tagged"].items():66                points += self.__make_points_for_label(67                    ts,68                    aggregated_data_by_tag,69                    label,70                    prefix,71                    gun_stats72                )73        return points74    def __make_points_for_label(self, ts, data, label, prefix, gun_stats):75        """x76        Make a set of points for `this` label77        overall_quantiles, overall_meta, net_codes, proto_codes, histograms78        """79        label_points = list()80        label_points.extend(81            (82                # overall quantiles for label83                self.__make_points(84                    prefix + "overall_quantiles",85                    {"label": label},86                    ts,87                    self.__make_quantile_fields(data)88                ),89                # overall meta (gun status) for label90                self.__make_points(91                    prefix + "overall_meta",92                    {"label": label},93                    ts,94                    self.__make_overall_meta_fields(data, gun_stats)95                ),96                # net codes for label97                self.__make_points(98                    prefix + "net_codes",99                    {"label": label},100                    ts,101                    self.__make_netcodes_fields(data)102                ),103                # proto codes for label104                self.__make_points(105                    prefix + "proto_codes",106                    {"label": label},107                    ts,108                    self.__make_protocodes_fields(data)109                )110            )111        )112        # histograms, one row for each bin113        if self.histograms:114            for bin_, count in zip(data["interval_real"]["hist"]["bins"],115                                   data["interval_real"]["hist"]["data"]):116                label_points.append(117                    self.__make_points(118                        prefix + "histograms",119                        {"label": label},120                        ts,121                        {"bin": bin_, "count": count}122                    )123                )124        return label_points125    @staticmethod126    def __make_quantile_fields(data):127        return {128            'q' + str(q): value / 1000.0129            for q, value in zip(data["interval_real"]["q"]["q"],130                                data["interval_real"]["q"]["value"])131        }132    @staticmethod133    def __make_overall_meta_fields(data, stats):134        return {135            "active_threads": stats["metrics"]["instances"],136            "RPS": data["interval_real"]["len"],137            "planned_requests": float(stats["metrics"]["reqps"]),138        }139    @staticmethod140    def __make_netcodes_fields(data):141        return {142            str(code): int(cnt)143            for code, cnt in data["net_code"]["count"].items()144        }145    @staticmethod146    def __make_protocodes_fields(data):147        return {148            str(code): int(cnt)149            for code, cnt in data["proto_code"]["count"].items()150        }151    def __make_points(self, measurement, additional_tags, ts, fields):152        """153        Parameters154        ----------155        measurement : string156            measurement type (e.g. monitoring, overall_meta, net_codes, proto_codes, overall_quantiles)157        additional_tags : dict158            custom additional tags for this points159        ts : integer160            timestamp161        fields : dict162            influxdb columns163        Returns164        -------165        dict...

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