merge develop

1 files changed, 0 insertions, 271 deletions

diff --git a/synapse/metrics/metric.py b/synapse/metrics/metric.py
deleted file mode 100644
index ff5aa8c0e1..0000000000
--- a/synapse/metrics/metric.py
+++ /dev/null
@@ -1,271 +0,0 @@
-# -*- coding: utf-8 -*-
-# Copyright 2015, 2016 OpenMarket Ltd
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-
-from itertools import chain
-import logging
-
-logger = logging.getLogger(__name__)
-
-
-def flatten(items):
-    """Flatten a list of lists
-
-    Args:
-        items: iterable[iterable[X]]
-
-    Returns:
-        list[X]: flattened list
-    """
-    return list(chain.from_iterable(items))
-
-
-class BaseMetric(object):
-    """Base class for metrics which report a single value per label set
-    """
-
-    def __init__(self, name, labels=[], alternative_names=[]):
-        """
-        Args:
-            name (str): principal name for this metric
-            labels (list(str)): names of the labels which will be reported
-                for this metric
-            alternative_names (iterable(str)): list of alternative names for
-                 this metric. This can be useful to provide a migration path
-                when renaming metrics.
-        """
-        self._names = [name] + list(alternative_names)
-        self.labels = labels  # OK not to clone as we never write it
-
-    def dimension(self):
-        return len(self.labels)
-
-    def is_scalar(self):
-        return not len(self.labels)
-
-    def _render_labelvalue(self, value):
-        # TODO: escape backslashes, quotes and newlines
-        return '"%s"' % (value)
-
-    def _render_key(self, values):
-        if self.is_scalar():
-            return ""
-        return "{%s}" % (
-            ",".join(["%s=%s" % (k, self._render_labelvalue(v))
-                      for k, v in zip(self.labels, values)])
-        )
-
-    def _render_for_labels(self, label_values, value):
-        """Render this metric for a single set of labels
-
-        Args:
-            label_values (list[str]): values for each of the labels
-            value: value of the metric at with these labels
-
-        Returns:
-            iterable[str]: rendered metric
-        """
-        rendered_labels = self._render_key(label_values)
-        return (
-            "%s%s %.12g" % (name, rendered_labels, value)
-            for name in self._names
-        )
-
-    def render(self):
-        """Render this metric
-
-        Each metric is rendered as:
-
-            name{label1="val1",label2="val2"} value
-
-        https://prometheus.io/docs/instrumenting/exposition_formats/#text-format-details
-
-        Returns:
-            iterable[str]: rendered metrics
-        """
-        raise NotImplementedError()
-
-
-class CounterMetric(BaseMetric):
-    """The simplest kind of metric; one that stores a monotonically-increasing
-    value that counts events or running totals.
-
-    Example use cases for Counters:
-    - Number of requests processed
-    - Number of items that were inserted into a queue
-    - Total amount of data that a system has processed
-    Counters can only go up (and be reset when the process restarts).
-    """
-
-    def __init__(self, *args, **kwargs):
-        super(CounterMetric, self).__init__(*args, **kwargs)
-
-        # dict[list[str]]: value for each set of label values. the keys are the
-        # label values, in the same order as the labels in self.labels.
-        #
-        # (if the metric is a scalar, the (single) key is the empty list).
-        self.counts = {}
-
-        # Scalar metrics are never empty
-        if self.is_scalar():
-            self.counts[()] = 0.
-
-    def inc_by(self, incr, *values):
-        if len(values) != self.dimension():
-            raise ValueError(
-                "Expected as many values to inc() as labels (%d)" % (self.dimension())
-            )
-
-        # TODO: should assert that the tag values are all strings
-
-        if values not in self.counts:
-            self.counts[values] = incr
-        else:
-            self.counts[values] += incr
-
-    def inc(self, *values):
-        self.inc_by(1, *values)
-
-    def render(self):
-        return flatten(
-            self._render_for_labels(k, self.counts[k])
-            for k in sorted(self.counts.keys())
-        )
-
-
-class CallbackMetric(BaseMetric):
-    """A metric that returns the numeric value returned by a callback whenever
-    it is rendered. Typically this is used to implement gauges that yield the
-    size or other state of some in-memory object by actively querying it."""
-
-    def __init__(self, name, callback, labels=[]):
-        super(CallbackMetric, self).__init__(name, labels=labels)
-
-        self.callback = callback
-
-    def render(self):
-        try:
-            value = self.callback()
-        except Exception:
-            logger.exception("Failed to render %s", self.name)
-            return ["# FAILED to render " + self.name]
-
-        if self.is_scalar():
-            return list(self._render_for_labels([], value))
-
-        return flatten(
-            self._render_for_labels(k, value[k])
-            for k in sorted(value.keys())
-        )
-
-
-class DistributionMetric(object):
-    """A combination of an event counter and an accumulator, which counts
-    both the number of events and accumulates the total value. Typically this
-    could be used to keep track of method-running times, or other distributions
-    of values that occur in discrete occurances.
-
-    TODO(paul): Try to export some heatmap-style stats?
-    """
-
-    def __init__(self, name, *args, **kwargs):
-        self.counts = CounterMetric(name + ":count", **kwargs)
-        self.totals = CounterMetric(name + ":total", **kwargs)
-
-    def inc_by(self, inc, *values):
-        self.counts.inc(*values)
-        self.totals.inc_by(inc, *values)
-
-    def render(self):
-        return self.counts.render() + self.totals.render()
-
-
-class CacheMetric(object):
-    __slots__ = (
-        "name", "cache_name", "hits", "misses", "evicted_size", "size_callback",
-    )
-
-    def __init__(self, name, size_callback, cache_name):
-        self.name = name
-        self.cache_name = cache_name
-
-        self.hits = 0
-        self.misses = 0
-        self.evicted_size = 0
-
-        self.size_callback = size_callback
-
-    def inc_hits(self):
-        self.hits += 1
-
-    def inc_misses(self):
-        self.misses += 1
-
-    def inc_evictions(self, size=1):
-        self.evicted_size += size
-
-    def render(self):
-        size = self.size_callback()
-        hits = self.hits
-        total = self.misses + self.hits
-
-        return [
-            """%s:hits{name="%s"} %d""" % (self.name, self.cache_name, hits),
-            """%s:total{name="%s"} %d""" % (self.name, self.cache_name, total),
-            """%s:size{name="%s"} %d""" % (self.name, self.cache_name, size),
-            """%s:evicted_size{name="%s"} %d""" % (
-                self.name, self.cache_name, self.evicted_size
-            ),
-        ]
-
-
-class MemoryUsageMetric(object):
-    """Keeps track of the current memory usage, using psutil.
-
-    The class will keep the current min/max/sum/counts of rss over the last
-    WINDOW_SIZE_SEC, by polling UPDATE_HZ times per second
-    """
-
-    UPDATE_HZ = 2  # number of times to get memory per second
-    WINDOW_SIZE_SEC = 30  # the size of the window in seconds
-
-    def __init__(self, hs, psutil):
-        clock = hs.get_clock()
-        self.memory_snapshots = []
-
-        self.process = psutil.Process()
-
-        clock.looping_call(self._update_curr_values, 1000 / self.UPDATE_HZ)
-
-    def _update_curr_values(self):
-        max_size = self.UPDATE_HZ * self.WINDOW_SIZE_SEC
-        self.memory_snapshots.append(self.process.memory_info().rss)
-        self.memory_snapshots[:] = self.memory_snapshots[-max_size:]
-
-    def render(self):
-        if not self.memory_snapshots:
-            return []
-
-        max_rss = max(self.memory_snapshots)
-        min_rss = min(self.memory_snapshots)
-        sum_rss = sum(self.memory_snapshots)
-        len_rss = len(self.memory_snapshots)
-
-        return [
-            "process_psutil_rss:max %d" % max_rss,
-            "process_psutil_rss:min %d" % min_rss,
-            "process_psutil_rss:total %d" % sum_rss,
-            "process_psutil_rss:count %d" % len_rss,
-        ]