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How to use describe_limits method in localstack

Best Python code snippet using localstack_python

scan_generator.py

Source:scan_generator.py

...16    def points_for_level(self, level: int, rng=None) -> List[Any]:17        """18        """19        raise NotImplementedError20    def describe_limits(self, target: Dict[str, Any]) -> None:21        """22        """23        raise NotImplementedError24class RefiningGenerator(ScanGenerator):25    """Generates progressively finer grid by halving distance between points each level.26    """27    def __init__(self, lower, upper, randomise_order):28        self.lower = float(min(lower, upper))29        self.upper = float(max(lower, upper))30        self.randomise_order = randomise_order31    def has_level(self, level: int) -> bool:32        ""33        # For floating-point parameters, a refining scan, in practical terms, never runs34        # out of points. Will need to be amended for integer parameters.35        return True36    def points_for_level(self, level: int, rng=None) -> List[Any]:37        ""38        if level == 0:39            return [self.lower, self.upper]40        d = self.upper - self.lower41        num = 2**(level - 1)42        points = np.arange(num) * d / num + d / (2 * num) + self.lower43        if self.randomise_order:44            rng.shuffle(points)45        return points46    def describe_limits(self, target: Dict[str, Any]) -> None:47        ""48        target["min"] = self.lower49        target["max"] = self.upper50class ExpandingGenerator(ScanGenerator):51    """Generates points with given, constant spacing in progressively growing range52    around a given centre.53    """54    def __init__(self,55                 centre,56                 spacing,57                 randomise_order: bool,58                 limit_lower=None,59                 limit_upper=None):60        """61        :param limit_lower: Optional lower limit (inclusive) to the range of generated62            points. Useful for representing scans on parameters the range of which is63            limited (e.g. to be non-negative).64        :param limit_upper: See `limit_lower`.65        """66        self.centre = centre67        self.spacing = abs(spacing)68        self.randomise_order = randomise_order69        self.limit_lower = limit_lower if limit_lower is not None else float("-inf")70        if centre < self.limit_lower:71            raise ValueError("Given scan centre exceeds lower limit")72        self.limit_upper = limit_upper if limit_upper is not None else float("inf")73        if centre > self.limit_upper:74            raise ValueError("Given scan centre exceeds upper limit")75    def has_level(self, level: int) -> bool:76        ""77        def num_points(limit):78            return np.floor(abs(self.centre - limit) / self.spacing)79        return level <= max(num_points(self.limit_lower), num_points(self.limit_upper))80    def points_for_level(self, level: int, rng=None) -> List[Any]:81        ""82        if level == 0:83            return [self.centre]84        points = []85        lower = self.centre - level * self.spacing86        if lower >= self.limit_lower:87            points.append(lower)88        upper = self.centre + level * self.spacing89        if upper <= self.limit_upper:90            points.append(upper)91        if self.randomise_order:92            rng.shuffle(points)93        return points94    def describe_limits(self, target: Dict[str, Any]) -> None:95        ""96        if self.limit_lower > float("-inf"):97            target["min"] = self.limit_lower98        if self.limit_upper < float("inf"):99            target["max"] = self.limit_upper100        target["increment"] = self.spacing101class LinearGenerator(ScanGenerator):102    """Generates equally spaced points between two endpoints."""103    def __init__(self, start, stop, num_points, randomise_order):104        if num_points < 2:105            raise ValueError("Need at least 2 points in linear scan")106        self.start = start107        self.stop = stop108        self.num_points = num_points109        self.randomise_order = randomise_order110    def has_level(self, level: int) -> bool:111        ""112        return level == 0113    def points_for_level(self, level: int, rng=None) -> List[Any]:114        ""115        assert level == 0116        points = np.linspace(start=self.start,117                             stop=self.stop,118                             num=self.num_points,119                             endpoint=True)120        if self.randomise_order:121            rng.shuffle(points)122        return points.tolist()123    def describe_limits(self, target: Dict[str, Any]) -> None:124        ""125        target["min"] = min(self.start, self.stop)126        target["max"] = max(self.start, self.stop)127        target["increment"] = abs(self.stop - self.start) / (self.num_points - 1)128class CentreSpanGenerator(LinearGenerator):129    """Generates equally spaced points in ``centre``Â±``half_span``."""130    def __init__(self,131                 centre,132                 half_span,133                 num_points: int,134                 randomise_order: bool,135                 limit_lower=None,136                 limit_upper=None):137        """138        :param limit_lower: Optional lower limit (inclusive) to the range of generated139            points. Useful for representing scans on parameters the range of which is140            limited (e.g. to be non-negative).141        :param limit_upper: See `limit_lower`.142        """143        if num_points < 1:144            raise ValueError("Need at least one point in centre/span scan")145        self.num_points = num_points146        self.randomise_order = randomise_order147        self.start = centre - half_span148        if limit_lower is not None:149            self.start = max(self.start, limit_lower)150        self.stop = centre + half_span151        if limit_upper is not None:152            self.stop = min(self.stop, limit_upper)153        if self.start > self.stop:154            raise ValueError("Empty centre/span scan (lower limit larger than upper)")155        if num_points == 1:156            self.start = self.stop = centre157class ListGenerator(ScanGenerator):158    """Generates points by reading from an explicitly specified list."""159    def __init__(self, values, randomise_order):160        self.values = values161        self.randomise_order = randomise_order162    def has_level(self, level: int) -> bool:163        ""164        return level == 0165    def points_for_level(self, level: int, rng=None) -> List[Any]:166        ""167        assert level == 0168        values = self.values169        if self.randomise_order:170            values = np.array(self.values)171            rng.shuffle(values)172        return values173    def describe_limits(self, target: Dict[str, Any]) -> None:174        ""175        values = np.array(self.values)176        if np.issubdtype(values.dtype, np.number):177            target["min"] = np.min(values)178            target["max"] = np.max(values)179GENERATORS = {180    "refining": RefiningGenerator,181    "expanding": ExpandingGenerator,182    "linear": LinearGenerator,183    "centre_span": CentreSpanGenerator,184    "list": ListGenerator185}186class ScanOptions:187    """...

dynamo_limit_handler.py

Source:dynamo_limit_handler.py

1class DynamoLimitHandler:2    def __init__(self, attribute):3        self.attribute = attribute4    def handle(self, client, stream_name):5        response = client.describe_limits()6        return attributes.get(self.attribute)7    def handle_response(self, name, value):...

db.describe_limits.py

Source:db.describe_limits.py

1#!/usr/bin/env python2import boto33ddb = boto3.client('dynamodb')...

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