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def re_escape(pattern, chars=frozenset("()[]{}?*+|^$\\.-#")): escape = '\\{}'.format return ''.join( escape(c) if c in chars or c.isspace() else '\\000' if c == '\x00' else c for c in pattern )
Escape all special regex characters in pattern. Logic taken from regex module. :param pattern: regex pattern to escape :type patterm: str :returns: escaped pattern :rtype: str
def register_plugin(manager): manager.register_blueprint(player) manager.register_mimetype_function(detect_playable_mimetype) # add style tag manager.register_widget( place='styles', type='stylesheet', endpoint='player.static', filename='css/browse.css' ) # r...
Register blueprints and actions using given plugin manager. :param manager: plugin manager :type manager: browsepy.manager.PluginManager
def fmt_size(size, binary=True): if binary: fmt_sizes = binary_units fmt_divider = 1024. else: fmt_sizes = standard_units fmt_divider = 1000. for fmt in fmt_sizes[:-1]: if size < 1000: return (size, fmt) size /= fmt_divider return size, fm...
Get size and unit. :param size: size in bytes :type size: int :param binary: whether use binary or standard units, defaults to True :type binary: bool :return: size and unit :rtype: tuple of int and unit as str
def relativize_path(path, base, os_sep=os.sep): if not check_base(path, base, os_sep): raise OutsideDirectoryBase("%r is not under %r" % (path, base)) prefix_len = len(base) if not base.endswith(os_sep): prefix_len += len(os_sep) return path[prefix_len:]
Make absolute path relative to an absolute base. :param path: absolute path :type path: str :param base: absolute base path :type base: str :param os_sep: path component separator, defaults to current OS separator :type os_sep: str :return: relative path :rtype: str or unicode :rais...
def abspath_to_urlpath(path, base, os_sep=os.sep): return relativize_path(path, base, os_sep).replace(os_sep, '/')
Make filesystem absolute path uri relative using given absolute base path. :param path: absolute path :param base: absolute base path :param os_sep: path component separator, defaults to current OS separator :return: relative uri :rtype: str or unicode :raises OutsideDirectoryBase: if resulting...
def urlpath_to_abspath(path, base, os_sep=os.sep): prefix = base if base.endswith(os_sep) else base + os_sep realpath = os.path.abspath(prefix + path.replace('/', os_sep)) if check_path(base, realpath) or check_under_base(realpath, base): return realpath raise OutsideDirectoryBase("%r is no...
Make uri relative path fs absolute using a given absolute base path. :param path: relative path :param base: absolute base path :param os_sep: path component separator, defaults to current OS separator :return: absolute path :rtype: str or unicode :raises OutsideDirectoryBase: if resulting path...
def generic_filename(path): for sep in common_path_separators: if sep in path: _, path = path.rsplit(sep, 1) return path
Extract filename of given path os-indepently, taking care of known path separators. :param path: path :return: filename :rtype: str or unicode (depending on given path)
def clean_restricted_chars(path, restricted_chars=restricted_chars): for character in restricted_chars: path = path.replace(character, '_') return path
Get path without restricted characters. :param path: path :return: path without restricted characters :rtype: str or unicode (depending on given path)
def check_forbidden_filename(filename, destiny_os=os.name, restricted_names=restricted_names): return ( filename in restricted_names or destiny_os == 'nt' and filename.split('.', 1)[0].upper() in nt_device_names )
Get if given filename is forbidden for current OS or filesystem. :param filename: :param destiny_os: destination operative system :param fs_encoding: destination filesystem filename encoding :return: wether is forbidden on given OS (or filesystem) or not :rtype: bool
def check_path(path, base, os_sep=os.sep): base = base[:-len(os_sep)] if base.endswith(os_sep) else base return os.path.normcase(path) == os.path.normcase(base)
Check if both given paths are equal. :param path: absolute path :type path: str :param base: absolute base path :type base: str :param os_sep: path separator, defaults to os.sep :type base: str :return: wether two path are equal or not :rtype: bool
def check_base(path, base, os_sep=os.sep): return ( check_path(path, base, os_sep) or check_under_base(path, base, os_sep) )
Check if given absolute path is under or given base. :param path: absolute path :type path: str :param base: absolute base path :type base: str :param os_sep: path separator, defaults to os.sep :return: wether path is under given base or not :rtype: bool
def check_under_base(path, base, os_sep=os.sep): prefix = base if base.endswith(os_sep) else base + os_sep return os.path.normcase(path).startswith(os.path.normcase(prefix))
Check if given absolute path is under given base. :param path: absolute path :type path: str :param base: absolute base path :type base: str :param os_sep: path separator, defaults to os.sep :return: wether file is under given base or not :rtype: bool
def secure_filename(path, destiny_os=os.name, fs_encoding=compat.FS_ENCODING): path = generic_filename(path) path = clean_restricted_chars( path, restricted_chars=( nt_restricted_chars if destiny_os == 'nt' else restricted_chars )) path = ...
Get rid of parent path components and special filenames. If path is invalid or protected, return empty string. :param path: unsafe path, only basename will be used :type: str :param destiny_os: destination operative system (defaults to os.name) :type destiny_os: str :param fs_encoding: fs path...
def alternative_filename(filename, attempt=None): filename_parts = filename.rsplit(u'.', 2) name = filename_parts[0] ext = ''.join(u'.%s' % ext for ext in filename_parts[1:]) if attempt is None: choose = random.choice extra = u' %s' % ''.join(choose(fs_safe_characters) for i in rang...
Generates an alternative version of given filename. If an number attempt parameter is given, will be used on the alternative name, a random value will be used otherwise. :param filename: original filename :param attempt: optional attempt number, defaults to null :return: new filename :rtype: s...
def scandir(path, app=None): exclude = app and app.config.get('exclude_fnc') if exclude: return ( item for item in compat.scandir(path) if not exclude(item.path) ) return compat.scandir(path)
Config-aware scandir. Currently, only aware of ``exclude_fnc``. :param path: absolute path :type path: str :param app: flask application :type app: flask.Flask or None :returns: filtered scandir entries :rtype: iterator
def is_excluded(self): exclude = self.app and self.app.config['exclude_fnc'] return exclude and exclude(self.path)
Get if current node shouldn't be shown, using :attt:`app` config's exclude_fnc. :returns: True if excluded, False otherwise
def widgets(self): widgets = [] if self.can_remove: widgets.append( self.plugin_manager.create_widget( 'entry-actions', 'button', file=self, css='remove', endpoint='re...
List widgets with filter return True for this node (or without filter). Remove button is prepended if :property:can_remove returns true. :returns: list of widgets :rtype: list of namedtuple instances
def link(self): link = None for widget in self.widgets: if widget.place == 'entry-link': link = widget return link
Get last widget with place "entry-link". :returns: widget on entry-link (ideally a link one) :rtype: namedtuple instance
def can_remove(self): dirbase = self.app.config["directory_remove"] return bool(dirbase and check_under_base(self.path, dirbase))
Get if current node can be removed based on app config's directory_remove. :returns: True if current node can be removed, False otherwise. :rtype: bool
def parent(self): if check_path(self.path, self.app.config['directory_base']): return None parent = os.path.dirname(self.path) if self.path else None return self.directory_class(parent, self.app) if parent else None
Get parent node if available based on app config's directory_base. :returns: parent object if available :rtype: Node instance or None
def ancestors(self): ancestors = [] parent = self.parent while parent: ancestors.append(parent) parent = parent.parent return ancestors
Get list of ancestors until app config's directory_base is reached. :returns: list of ancestors starting from nearest. :rtype: list of Node objects
def modified(self): try: dt = datetime.datetime.fromtimestamp(self.stats.st_mtime) return dt.strftime('%Y.%m.%d %H:%M:%S') except OSError: return None
Get human-readable last modification date-time. :returns: iso9008-like date-time string (without timezone) :rtype: str
def from_urlpath(cls, path, app=None): app = app or current_app base = app.config['directory_base'] path = urlpath_to_abspath(path, base) if not cls.generic: kls = cls elif os.path.isdir(path): kls = cls.directory_class else: k...
Alternative constructor which accepts a path as taken from URL and uses the given app or the current app config to get the real path. If class has attribute `generic` set to True, `directory_class` or `file_class` will be used as type. :param path: relative path as from URL :pa...
def _find_paths(self, current_dir, patterns): pattern = patterns[0] patterns = patterns[1:] has_wildcard = is_pattern(pattern) using_globstar = pattern == "**" # This avoids os.listdir() for performance if has_wildcard: entries = [x.name for x in scan...
Recursively generates absolute paths whose components underneath current_dir match the corresponding pattern in patterns
def union_overlapping(intervals): disjoint_intervals = [] for interval in intervals: if disjoint_intervals and disjoint_intervals[-1].overlaps(interval): disjoint_intervals[-1] = disjoint_intervals[-1].union(interval) else: disjoint_intervals.append(interval) ret...
Union any overlapping intervals in the given set.
def recurse(query, index): for node in app.store.find(query): if node.is_leaf: index.add(node.path) else: recurse('{0}.*'.format(node.path), index)
Recursively walk across paths, adding leaves to the index as they're found.
def setAggregationMethod(path, aggregationMethod, xFilesFactor=None): fh = None try: fh = open(path,'r+b') if LOCK: fcntl.flock( fh.fileno(), fcntl.LOCK_EX ) packedMetadata = fh.read(metadataSize) try: (aggregationType,maxRetention,xff,archiveCount) = struct.unpack(metadataFormat,pack...
setAggregationMethod(path,aggregationMethod,xFilesFactor=None) path is a string aggregationMethod specifies the method to use when propagating data (see ``whisper.aggregationMethods``) xFilesFactor specifies the fraction of data points in a propagation interval that must have known values for a propagation to occur. ...
def validateArchiveList(archiveList): if not archiveList: raise InvalidConfiguration("You must specify at least one archive configuration!") archiveList = sorted(archiveList, key=lambda a: a[0]) #sort by precision (secondsPerPoint) for i,archive in enumerate(archiveList): if i == len(archiveList) - 1: ...
Validates an archiveList. An ArchiveList must: 1. Have at least one archive config. Example: (60, 86400) 2. No archive may be a duplicate of another. 3. Higher precision archives' precision must evenly divide all lower precision archives' precision. 4. Lower precision archives must cover larger time intervals...
def create(path,archiveList,xFilesFactor=None,aggregationMethod=None,sparse=False,useFallocate=False): # Set default params if xFilesFactor is None: xFilesFactor = 0.5 if aggregationMethod is None: aggregationMethod = 'average' #Validate archive configurations... validateArchiveList(archiveList) ...
create(path,archiveList,xFilesFactor=0.5,aggregationMethod='average') path is a string archiveList is a list of archives, each of which is of the form (secondsPerPoint,numberOfPoints) xFilesFactor specifies the fraction of data points in a propagation interval that must have known values for a propagation to occur agg...
def update(path,value,timestamp=None): value = float(value) fh = None try: fh = open(path,'r+b') return file_update(fh, value, timestamp) finally: if fh: fh.close()
update(path,value,timestamp=None) path is a string value is a float timestamp is either an int or float
def update_many(path,points): if not points: return points = [ (int(t),float(v)) for (t,v) in points] points.sort(key=lambda p: p[0],reverse=True) #order points by timestamp, newest first fh = None try: fh = open(path,'r+b') return file_update_many(fh, points) finally: if fh: fh.close()
update_many(path,points) path is a string points is a list of (timestamp,value) points
def info(path): fh = None try: fh = open(path,'rb') return __readHeader(fh) finally: if fh: fh.close() return None
info(path) path is a string
def fetch(path,fromTime,untilTime=None,now=None): fh = None try: fh = open(path,'rb') return file_fetch(fh, fromTime, untilTime, now) finally: if fh: fh.close()
fetch(path,fromTime,untilTime=None) path is a string fromTime is an epoch time untilTime is also an epoch time, but defaults to now. Returns a tuple of (timeInfo, valueList) where timeInfo is itself a tuple of (fromTime, untilTime, step) Returns None if no data can be returned
def __archive_fetch(fh, archive, fromTime, untilTime): fromInterval = int( fromTime - (fromTime % archive['secondsPerPoint']) ) + archive['secondsPerPoint'] untilInterval = int( untilTime - (untilTime % archive['secondsPerPoint']) ) + archive['secondsPerPoint'] if fromInterval == untilInterval: # Zero-leng...
Fetch data from a single archive. Note that checks for validity of the time period requested happen above this level so it's possible to wrap around the archive on a read and request data older than the archive's retention
def merge(path_from, path_to): fh_from = open(path_from, 'rb') fh_to = open(path_to, 'rb+') return file_merge(fh_from, fh_to)
Merges the data from one whisper file into another. Each file must have the same archive configuration
def diff(path_from, path_to, ignore_empty = False): fh_from = open(path_from, 'rb') fh_to = open(path_to, 'rb') diffs = file_diff(fh_from, fh_to, ignore_empty) fh_to.close() fh_from.close() return diffs
Compare two whisper databases. Each file must have the same archive configuration
def add_data(self, path, time_info, data, exprs): # Dont add if empty if not nonempty(data): for d in self.data[path]: if nonempty(d['values']): return # Add data to path for expr in exprs: self.paths[expr].add(path) ...
Stores data before it can be put into a time series
def extract_variants(pattern): v1, v2 = pattern.find('{'), pattern.find('}') if v1 > -1 and v2 > v1: variations = pattern[v1+1:v2].split(',') variants = [pattern[:v1] + v + pattern[v2+1:] for v in variations] else: variants = [pattern] return list(_deduplicate(variants))
Extract the pattern variants (ie. {foo,bar}baz = foobaz or barbaz).
def match_entries(entries, pattern): matching = [] for variant in expand_braces(pattern): matching.extend(fnmatch.filter(entries, variant)) return list(_deduplicate(matching))
A drop-in replacement for fnmatch.filter that supports pattern variants (ie. {foo,bar}baz = foobaz or barbaz).
def expand_braces(pattern): res = set() # Used instead of s.strip('{}') because strip is greedy. # We want to remove only ONE leading { and ONE trailing }, if both exist def remove_outer_braces(s): if s[0] == '{' and s[-1] == '}': return s[1:-1] return s match = EXPA...
Find the rightmost, innermost set of braces and, if it contains a comma-separated list, expand its contents recursively (any of its items may itself be a list enclosed in braces). Return the full list of expanded strings.
def select_host(self, metric): key = self.keyfunc(metric) nodes = [] servers = set() for node in self.hash_ring.get_nodes(key): server, instance = node if server in servers: continue servers.add(server) nodes.append...
Returns the carbon host that has data for the given metric.
def safeArgs(args): return (arg for arg in args if arg is not None and not math.isnan(arg) and not math.isinf(arg))
Iterate over valid, finite values in an iterable. Skip any items that are None, NaN, or infinite.
def dataLimits(data, drawNullAsZero=False, stacked=False): missingValues = any(None in series for series in data) finiteData = [series for series in data if not series.options.get('drawAsInfinite')] yMinValue = safeMin(safeMin(series) for series in finiteData) if yMinValue is None...
Return the range of values in data as (yMinValue, yMaxValue). data is an array of TimeSeries objects.
def format_units(v, step=None, system="si", units=None): if v is None: return 0, '' for prefix, size in UnitSystems[system]: if condition(v, size, step): v2 = v / size if v2 - math.floor(v2) < 0.00000000001 and v > 1: v2 = float(math.floor(v2)) ...
Format the given value in standardized units. ``system`` is either 'binary' or 'si' For more info, see: http://en.wikipedia.org/wiki/SI_prefix http://en.wikipedia.org/wiki/Binary_prefix
def checkFinite(value, name='value'): if math.isnan(value): raise GraphError('Encountered NaN %s' % (name,)) elif math.isinf(value): raise GraphError('Encountered infinite %s' % (name,)) return value
Check that value is a finite number. If it is, return it. If not, raise GraphError describing the problem, using name in the error message.
def reconcileLimits(self): if self.minValue < self.maxValue: # The limits are already OK. return minFixed = (self.minValueSource in ['min']) maxFixed = (self.maxValueSource in ['max', 'limit']) if minFixed and maxFixed: raise GraphError('The %...
If self.minValue is not less than self.maxValue, fix the problem. If self.minValue is not less than self.maxValue, adjust self.minValue and/or self.maxValue (depending on which was not specified explicitly by the user) to make self.minValue < self.maxValue. If the user specified both li...
def applySettings(self, axisMin=None, axisMax=None, axisLimit=None): if axisMin is not None and not math.isnan(axisMin): self.minValueSource = 'min' self.minValue = self.checkFinite(axisMin, 'axis min') if axisMax == 'max': self.maxValueSource = 'extremum' ...
Apply the specified settings to this axis. Set self.minValue, self.minValueSource, self.maxValue, self.maxValueSource, and self.axisLimit reasonably based on the parameters provided. Arguments: axisMin -- a finite number, or None to choose a round minimum limit tha...
def makeLabel(self, value): value, prefix = format_units(value, self.step, system=self.unitSystem) span, spanPrefix = format_units(self.span, self.step, system=self.unitSystem) if prefix: prefix += ...
Create a label for the specified value. Create a label string containing the value and its units (if any), based on the values of self.step, self.span, and self.unitSystem.
def generateSteps(self, minStep): self.checkFinite(minStep) if self.binary: base = 2.0 mantissas = [1.0] exponent = math.floor(math.log(minStep, 2) - EPSILON) else: base = 10.0 mantissas = [1.0, 2.0, 5.0] exponent =...
Generate allowed steps with step >= minStep in increasing order.
def computeSlop(self, step, divisor): bottom = step * math.floor(self.minValue / float(step) + EPSILON) top = bottom + step * divisor if top >= self.maxValue - EPSILON * step: return max(top - self.maxValue, self.minValue - bottom) else: return None
Compute the slop that would result from step and divisor. Return the slop, or None if this combination can't cover the full range. See chooseStep() for the definition of "slop".
def chooseStep(self, divisors=None, binary=False): self.binary = binary if divisors is None: divisors = [4, 5, 6] else: for divisor in divisors: self.checkFinite(divisor, 'divisor') if divisor < 1: raise GraphEr...
Choose a nice, pretty size for the steps between axis labels. Our main constraint is that the number of divisions must be taken from the divisors list. We pick a number of divisions and a step size that minimizes the amount of whitespace ("slop") that would need to be included outside o...
def formatPathExpressions(seriesList): pathExpressions = sorted(set([s.pathExpression for s in seriesList])) return ','.join(pathExpressions)
Returns a comma-separated list of unique path expressions.
def sumSeries(requestContext, *seriesLists): if not seriesLists or not any(seriesLists): return [] seriesList, start, end, step = normalize(seriesLists) name = "sumSeries(%s)" % formatPathExpressions(seriesList) values = (safeSum(row) for row in zip_longest(*seriesList)) series = TimeSe...
Short form: sum() This will add metrics together and return the sum at each datapoint. (See integral for a sum over time) Example:: &target=sum(company.server.application*.requestsHandled) This would show the sum of all requests handled per minute (provided requestsHandled are collected ...
def sumSeriesWithWildcards(requestContext, seriesList, *positions): newSeries = {} newNames = list() for series in seriesList: newname = '.'.join(map(lambda x: x[1], filter(lambda i: i[0] not in positions, enumerate(series.nam...
Call sumSeries after inserting wildcards at the given position(s). Example:: &target=sumSeriesWithWildcards(host.cpu-[0-7].cpu-{user,system}.value, 1) This would be the equivalent of:: &target=sumSeries(host.*.cpu-user.value)&target=sumSeries( ...
def averageSeriesWithWildcards(requestContext, seriesList, *positions): matchedList = defaultdict(list) for series in seriesList: newname = '.'.join(map(lambda x: x[1], filter(lambda i: i[0] not in positions, enumerate(series.name...
Call averageSeries after inserting wildcards at the given position(s). Example:: &target=averageSeriesWithWildcards( host.cpu-[0-7].cpu-{user,system}.value, 1) This would be the equivalent of:: &target=averageSeries(host.*.cpu-user.value)&target=averageSeries( host.*....
def multiplySeriesWithWildcards(requestContext, seriesList, *position): positions = [position] if isinstance(position, int) else position newSeries = {} newNames = [] for series in seriesList: new_name = ".".join(map(lambda x: x[1], filter(lambda i: i[0] not ...
Call multiplySeries after inserting wildcards at the given position(s). Example:: &target=multiplySeriesWithWildcards( web.host-[0-7].{avg-response,total-request}.value, 2) This would be the equivalent of:: &target=multiplySeries(web.host-0.{avg-response,total-request}.value) ...
def rangeOfSeries(requestContext, *seriesLists): if not seriesLists or not any(seriesLists): return [] seriesList, start, end, step = normalize(seriesLists) name = "rangeOfSeries(%s)" % formatPathExpressions(seriesList) values = (safeSubtract(max(row), min(row)) f...
Takes a wildcard seriesList. Distills down a set of inputs into the range of the series Example:: &target=rangeOfSeries(Server*.connections.total)
def percentileOfSeries(requestContext, seriesList, n, interpolate=False): if n <= 0: raise ValueError( 'The requested percent is required to be greater than 0') if not seriesList: return [] name = 'percentileOfSeries(%s,%g)' % (seriesList[0].pathExpression, n) start, end...
percentileOfSeries returns a single series which is composed of the n-percentile values taken across a wildcard series at each point. Unless `interpolate` is set to True, percentile values are actual values contained in one of the supplied series.
def keepLastValue(requestContext, seriesList, limit=INF): for series in seriesList: series.name = "keepLastValue(%s)" % (series.name) series.pathExpression = series.name consecutiveNones = 0 for i, value in enumerate(series): series[i] = value # No 'keepi...
Takes one metric or a wildcard seriesList, and optionally a limit to the number of 'None' values to skip over. Continues the line with the last received value when gaps ('None' values) appear in your data, rather than breaking your line. Example:: &target=keepLastValue(Server01.connections.han...
def interpolate(requestContext, seriesList, limit=INF): for series in seriesList: series.name = "interpolate(%s)" % (series.name) series.pathExpression = series.name consecutiveNones = 0 for i, value in enumerate(series): series[i] = value # No 'keeping' ...
Takes one metric or a wildcard seriesList, and optionally a limit to the number of 'None' values to skip over. Continues the line with the last received value when gaps ('None' values) appear in your data, rather than breaking your line. Example:: &target=interpolate(Server01.connections.handl...
def changed(requestContext, seriesList): for series in seriesList: series.name = series.pathExpression = 'changed(%s)' % series.name previous = None for index, value in enumerate(series): if previous is None: series[index] = 0 elif value is not No...
Takes one metric or a wildcard seriesList. Output 1 when the value changed, 0 when null or the same Example:: &target=changed(Server01.connections.handled)
def divideSeriesLists(requestContext, dividendSeriesList, divisorSeriesList): if len(dividendSeriesList) != len(divisorSeriesList): raise ValueError("dividendSeriesList and divisorSeriesList argument\ must have equal length") results = [] for dividendSeries, divisorSeri...
Iterates over a two lists and divides list1[0] by list2[0], list1[1] by list2[1] and so on. The lists need to be the same length
def divideSeries(requestContext, dividendSeriesList, divisorSeriesList): if len(divisorSeriesList) == 0: for series in dividendSeriesList: series.name = "divideSeries(%s,MISSING)" % series.name series.pathExpression = series.name for i in range(len(series)): ...
Takes a dividend metric and a divisor metric and draws the division result. A constant may *not* be passed. To divide by a constant, use the scale() function (which is essentially a multiplication operation) and use the inverse of the dividend. (Division by 8 = multiplication by 1/8 or 0.125) Example::...
def multiplySeries(requestContext, *seriesLists): if not seriesLists or not any(seriesLists): return [] seriesList, start, end, step = normalize(seriesLists) if len(seriesList) == 1: return seriesList name = "multiplySeries(%s)" % ','.join([s.name for s in seriesList]) product =...
Takes two or more series and multiplies their points. A constant may not be used. To multiply by a constant, use the scale() function. Example:: &target=multiplySeries(Series.dividends,Series.divisors)
def weightedAverage(requestContext, seriesListAvg, seriesListWeight, *nodes): if isinstance(nodes, int): nodes = [nodes] sortedSeries = {} for seriesAvg, seriesWeight in zip_longest( seriesListAvg, seriesListWeight): key = '' for node in nodes: key += ser...
Takes a series of average values and a series of weights and produces a weighted average for all values. The corresponding values should share one or more zero-indexed nodes. Example:: &target=weightedAverage(*.transactions.mean,*.transactions.count,0) &target=weightedAverage(*.transactio...
def exponentialMovingAverage(requestContext, seriesList, windowSize): # EMA = C * (current_value) + (1 - C) + EMA # C = 2 / (windowSize + 1) # The following was copied from movingAverage, and altered for ema if not seriesList: return [] windowInterval = None if isinstance(windowSize...
Takes a series of values and a window size and produces an exponential moving average utilizing the following formula: ema(current) = constant * (Current Value) + (1 - constant) * ema(previous) The Constant is calculated as: constant = 2 / (windowSize + 1) The first period EMA uses a simple ...
def movingMedian(requestContext, seriesList, windowSize): if not seriesList: return [] windowInterval = None if isinstance(windowSize, six.string_types): delta = parseTimeOffset(windowSize) windowInterval = to_seconds(delta) if windowInterval: previewSeconds = window...
Graphs the moving median of a metric (or metrics) over a fixed number of past points, or a time interval. Takes one metric or a wildcard seriesList followed by a number N of datapoints or a quoted string with a length of time like '1hour' or '5min' (See ``from / until`` in the render\_api_ for examples...
def scale(requestContext, seriesList, factor): for series in seriesList: series.name = "scale(%s,%g)" % (series.name, float(factor)) series.pathExpression = series.name for i, value in enumerate(series): series[i] = safeMul(value, factor) return seriesList
Takes one metric or a wildcard seriesList followed by a constant, and multiplies the datapoint by the constant provided at each point. Example:: &target=scale(Server.instance01.threads.busy,10) &target=scale(Server.instance*.threads.busy,10)
def scaleToSeconds(requestContext, seriesList, seconds): for series in seriesList: series.name = "scaleToSeconds(%s,%d)" % (series.name, seconds) series.pathExpression = series.name factor = seconds * 1.0 / series.step for i, value in enumerate(series): series[i] = s...
Takes one metric or a wildcard seriesList and returns "value per seconds" where seconds is a last argument to this functions. Useful in conjunction with derivative or integral function if you want to normalize its result to a known resolution for arbitrary retentions
def pow(requestContext, seriesList, factor): for series in seriesList: series.name = "pow(%s,%g)" % (series.name, float(factor)) series.pathExpression = series.name for i, value in enumerate(series): series[i] = safePow(value, factor) return seriesList
Takes one metric or a wildcard seriesList followed by a constant, and raises the datapoint by the power of the constant provided at each point. Example:: &target=pow(Server.instance01.threads.busy,10) &target=pow(Server.instance*.threads.busy,10)
def powSeries(requestContext, *seriesLists): if not seriesLists or not any(seriesLists): return [] seriesList, start, end, step = normalize(seriesLists) name = "powSeries(%s)" % ','.join([s.name for s in seriesList]) values = [] for row in zip_longest(*seriesList): first = True ...
Takes two or more series and pows their points. A constant line may be used. Example:: &target=powSeries(Server.instance01.app.requests, Server.instance01.app.replies)
def squareRoot(requestContext, seriesList): for series in seriesList: series.name = "squareRoot(%s)" % (series.name) for i, value in enumerate(series): series[i] = safePow(value, 0.5) return seriesList
Takes one metric or a wildcard seriesList, and computes the square root of each datapoint. Example:: &target=squareRoot(Server.instance01.threads.busy)
def absolute(requestContext, seriesList): for series in seriesList: series.name = "absolute(%s)" % (series.name) series.pathExpression = series.name for i, value in enumerate(series): series[i] = safeAbs(value) return seriesList
Takes one metric or a wildcard seriesList and applies the mathematical abs function to each datapoint transforming it to its absolute value. Example:: &target=absolute(Server.instance01.threads.busy) &target=absolute(Server.instance*.threads.busy)
def offset(requestContext, seriesList, factor): for series in seriesList: series.name = "offset(%s,%g)" % (series.name, float(factor)) series.pathExpression = series.name for i, value in enumerate(series): if value is not None: series[i] = value + factor ...
Takes one metric or a wildcard seriesList followed by a constant, and adds the constant to each datapoint. Example:: &target=offset(Server.instance01.threads.busy,10)
def offsetToZero(requestContext, seriesList): for series in seriesList: series.name = "offsetToZero(%s)" % (series.name) minimum = safeMin(series) for i, value in enumerate(series): if value is not None: series[i] = value - minimum return seriesList
Offsets a metric or wildcard seriesList by subtracting the minimum value in the series from each datapoint. Useful to compare different series where the values in each series may be higher or lower on average but you're only interested in the relative difference. An example use case is for compari...
def movingAverage(requestContext, seriesList, windowSize): if not seriesList: return [] windowInterval = None if isinstance(windowSize, six.string_types): delta = parseTimeOffset(windowSize) windowInterval = to_seconds(delta) if windowInterval: previewSeconds = windo...
Graphs the moving average of a metric (or metrics) over a fixed number of past points, or a time interval. Takes one metric or a wildcard seriesList followed by a number N of datapoints or a quoted string with a length of time like '1hour' or '5min' (See ``from / until`` in the render\_api_ for example...
def movingSum(requestContext, seriesList, windowSize): if not seriesList: return [] windowInterval = None if isinstance(windowSize, six.string_types): delta = parseTimeOffset(windowSize) windowInterval = abs(delta.seconds + (delta.days * 86400)) if windowInterval: pr...
Graphs the moving sum of a metric (or metrics) over a fixed number of past points, or a time interval. Takes one metric or a wildcard seriesList followed by a number N of datapoints or a quoted string with a length of time like '1hour' or '5min' (See ``from / until`` in the render\_api_ for examples of...
def movingMax(requestContext, seriesList, windowSize): if not seriesList: return [] windowInterval = None if isinstance(windowSize, six.string_types): delta = parseTimeOffset(windowSize) windowInterval = abs(delta.seconds + (delta.days * 86400)) if windowInterval: pr...
Graphs the moving maximum of a metric (or metrics) over a fixed number of past points, or a time interval. Takes one metric or a wildcard seriesList followed by a number N of datapoints or a quoted string with a length of time like '1hour' or '5min' (See ``from / until`` in the render\_api_ for example...
def consolidateBy(requestContext, seriesList, consolidationFunc): for series in seriesList: # datalib will throw an exception, so it's not necessary to validate # here series.consolidationFunc = consolidationFunc series.name = 'consolidateBy(%s,"%s")' % (series.name, ...
Takes one metric or a wildcard seriesList and a consolidation function name. Valid function names are 'sum', 'average', 'min', and 'max'. When a graph is drawn where width of the graph size in pixels is smaller than the number of datapoints to be graphed, Graphite consolidates the values to to pre...
def delay(requestContext, seriesList, steps): results = [] for series in seriesList: newValues = [] prev = [] for val in series: if len(prev) < steps: newValues.append(None) prev.append(val) continue newValues.a...
This shifts all samples later by an integer number of steps. This can be used for custom derivative calculations, among other things. Note: this will pad the early end of the data with None for every step shifted. This complements other time-displacement functions such as timeShift and timeSlice, in th...
def integral(requestContext, seriesList): results = [] for series in seriesList: newValues = [] current = 0.0 for val in series: if val is None: newValues.append(None) else: current += val newValues.append(curre...
This will show the sum over time, sort of like a continuous addition function. Useful for finding totals or trends in metrics that are collected per minute. Example:: &target=integral(company.sales.perMinute) This would start at zero on the left side of the graph, adding the sales each mi...
def integralByInterval(requestContext, seriesList, intervalUnit): intervalDuration = int(to_seconds(parseTimeOffset(intervalUnit))) startTime = int(epoch(requestContext['startTime'])) results = [] for series in seriesList: newValues = [] # current time within series iteration ...
This will do the same as integral() funcion, except resetting the total to 0 at the given time in the parameter "from" Useful for finding totals per hour/day/week/.. Example:: &target=integralByInterval(company.sales.perMinute, "1d")&from=midnight-10days Thi...
def nonNegativeDerivative(requestContext, seriesList, maxValue=None): results = [] for series in seriesList: newValues = [] prev = None for val in series: if None in (prev, val): newValues.append(None) prev = val continue ...
Same as the derivative function above, but ignores datapoints that trend down. Useful for counters that increase for a long time, then wrap or reset. (Such as if a network interface is destroyed and recreated by unloading and re-loading a kernel module, common with USB / WiFi cards. Example:: ...
def stacked(requestContext, seriesLists, stackName='__DEFAULT__'): if 'totalStack' in requestContext: totalStack = requestContext['totalStack'].get(stackName, []) else: requestContext['totalStack'] = {} totalStack = [] results = [] for series in seriesLists: newValue...
Takes one metric or a wildcard seriesList and change them so they are stacked. This is a way of stacking just a couple of metrics without having to use the stacked area mode (that stacks everything). By means of this a mixed stacked and non stacked graph can be made It can also take an optional argumen...
def areaBetween(requestContext, *seriesLists): if len(seriesLists) == 1: [seriesLists] = seriesLists assert len(seriesLists) == 2, ("areaBetween series argument must " "reference *exactly* 2 series") lower, upper = seriesLists if len(lower) == 1: [...
Draws the vertical area in between the two series in seriesList. Useful for visualizing a range such as the minimum and maximum latency for a service. areaBetween expects **exactly one argument** that results in exactly two series (see example below). The order of the lower and higher values series doe...
def aliasSub(requestContext, seriesList, search, replace): try: seriesList.name = re.sub(search, replace, seriesList.name) except AttributeError: for series in seriesList: series.name = re.sub(search, replace, series.name) return seriesList
Runs series names through a regex search/replace. Example:: &target=aliasSub(ip.*TCP*,"^.*TCP(\d+)","\\1")
def alias(requestContext, seriesList, newName): try: seriesList.name = newName except AttributeError: for series in seriesList: series.name = newName return seriesList
Takes one metric or a wildcard seriesList and a string in quotes. Prints the string instead of the metric name in the legend. Example:: &target=alias(Sales.widgets.largeBlue,"Large Blue Widgets")
def cactiStyle(requestContext, seriesList, system=None, units=None): def fmt(x): if system: if units: return "%.2f %s" % format_units(x, system=system, units=units) else: return "%.2f%s" % format_units(x, system=system) else: i...
Takes a series list and modifies the aliases to provide column aligned output with Current, Max, and Min values in the style of cacti. Optionally takes a "system" value to apply unit formatting in the same style as the Y-axis, or a "unit" string to append an arbitrary unit suffix. NOTE: column alignment...
def _getFirstPathExpression(name): tokens = grammar.parseString(name) pathExpression = None while pathExpression is None: if tokens.pathExpression: pathExpression = tokens.pathExpression elif tokens.expression: tokens = tokens.expression elif tokens.call:...
Returns the first metric path in an expression.
def aliasByNode(requestContext, seriesList, *nodes): for series in seriesList: pathExpression = _getFirstPathExpression(series.name) metric_pieces = pathExpression.split('.') series.name = '.'.join(metric_pieces[n] for n in nodes) return seriesList
Takes a seriesList and applies an alias derived from one or more "node" portion/s of the target name. Node indices are 0 indexed. Example:: &target=aliasByNode(ganglia.*.cpu.load5,1)
def legendValue(requestContext, seriesList, *valueTypes): valueFuncs = { 'avg': lambda s: safeDiv(safeSum(s), safeLen(s)), 'total': safeSum, 'min': safeMin, 'max': safeMax, 'last': safeLast, } system = None if valueTypes[-1] in ('si', 'binary'): syste...
Takes one metric or a wildcard seriesList and a string in quotes. Appends a value to the metric name in the legend. Currently one or several of: `last`, `avg`, `total`, `min`, `max`. The last argument can be `si` (default) or `binary`, in that case values will be formatted in the corresponding system. ...
def alpha(requestContext, seriesList, alpha): for series in seriesList: series.options['alpha'] = alpha return seriesList
Assigns the given alpha transparency setting to the series. Takes a float value between 0 and 1.
def color(requestContext, seriesList, theColor): for series in seriesList: series.color = theColor return seriesList
Assigns the given color to the seriesList Example:: &target=color(collectd.hostname.cpu.0.user, 'green') &target=color(collectd.hostname.cpu.0.system, 'ff0000') &target=color(collectd.hostname.cpu.0.idle, 'gray') &target=color(collectd.hostname.cpu.0.idle, '6464ffaa')
def substr(requestContext, seriesList, start=0, stop=0): for series in seriesList: left = series.name.rfind('(') + 1 right = series.name.find(')') if right < 0: right = len(series.name)+1 cleanName = series.name[left:right:].split('.') if int(stop) == 0: ...
Takes one metric or a wildcard seriesList followed by 1 or 2 integers. Assume that the metric name is a list or array, with each element separated by dots. Prints n - length elements of the array (if only one integer n is passed) or n - m elements of the array (if two integers n and m are passed). The l...
def logarithm(requestContext, seriesList, base=10): results = [] for series in seriesList: newValues = [] for val in series: if val is None: newValues.append(None) elif val <= 0: newValues.append(None) else: ...
Takes one metric or a wildcard seriesList, a base, and draws the y-axis in logarithmic format. If base is omitted, the function defaults to base 10. Example:: &target=log(carbon.agents.hostname.avgUpdateTime,2)
def maximumBelow(requestContext, seriesList, n): results = [] for series in seriesList: val = safeMax(series) if val is None or val <= n: results.append(series) return results
Takes one metric or a wildcard seriesList followed by a constant n. Draws only the metrics with a maximum value below n. Example:: &target=maximumBelow(system.interface.eth*.packetsSent,1000) This would only display interfaces which always sent less than 1000 packets/min.
def minimumBelow(requestContext, seriesList, n): results = [] for series in seriesList: val = safeMin(series) if val is None or val <= n: results.append(series) return results
Takes one metric or a wildcard seriesList followed by a constant n. Draws only the metrics with a minimum value below n. Example:: &target=minimumBelow(system.interface.eth*.packetsSent,1000) This would only display interfaces which sent at one point less than 1000 packets/min.
def highestMax(requestContext, seriesList, n=1): result_list = sorted(seriesList, key=lambda s: safeMax(s))[-n:] return sorted(result_list, key=lambda s: max(s), reverse=True)
Takes one metric or a wildcard seriesList followed by an integer N. Out of all metrics passed, draws only the N metrics with the highest maximum value in the time period specified. Example:: &target=highestMax(server*.instance*.threads.busy,5) Draws the top 5 servers who have had the most bu...
def currentAbove(requestContext, seriesList, n): results = [] for series in seriesList: val = safeLast(series) if val is not None and val >= n: results.append(series) return results
Takes one metric or a wildcard seriesList followed by an integer N. Out of all metrics passed, draws only the metrics whose value is above N at the end of the time period specified. Example:: &target=currentAbove(server*.instance*.threads.busy,50) Draws the servers with more than 50 busy thre...
def averageAbove(requestContext, seriesList, n): results = [] for series in seriesList: val = safeAvg(series) if val is not None and val >= n: results.append(series) return results
Takes one metric or a wildcard seriesList followed by an integer N. Out of all metrics passed, draws only the metrics with an average value above N for the time period specified. Example:: &target=averageAbove(server*.instance*.threads.busy,25) Draws the servers with average values above 25.