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355 lines
13 KiB
Python
355 lines
13 KiB
Python
# This Source Code Form is subject to the terms of the Mozilla Public
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# License, v. 2.0. If a copy of the MPL was not distributed with this
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# file, You can obtain one at http://mozilla.org/MPL/2.0/.
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import collections
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import json
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import math
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import os
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import re
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import sys
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# histogram_tools.py is used by scripts from a mozilla-central build tree
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# and also by outside consumers, such as the telemetry server. We need
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# to ensure that importing things works in both contexts. Therefore,
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# unconditionally importing things that are local to the build tree, such
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# as buildconfig, is a no-no.
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try:
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import buildconfig
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# Need to update sys.path to be able to find usecounters.
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sys.path.append(os.path.join(buildconfig.topsrcdir, 'dom/base/'))
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except ImportError:
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# Must be in an out-of-tree usage scenario. Trust that whoever is
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# running this script knows we need the usecounters module and has
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# ensured it's in our sys.path.
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pass
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from collections import OrderedDict
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def table_dispatch(kind, table, body):
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"""Call body with table[kind] if it exists. Raise an error otherwise."""
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if kind in table:
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return body(table[kind])
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else:
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raise BaseException, "don't know how to handle a histogram of kind %s" % kind
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class DefinitionException(BaseException):
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pass
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def check_numeric_limits(dmin, dmax, n_buckets):
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if type(dmin) != int:
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raise DefinitionException, "minimum is not a number"
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if type(dmax) != int:
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raise DefinitionException, "maximum is not a number"
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if type(n_buckets) != int:
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raise DefinitionException, "number of buckets is not a number"
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def linear_buckets(dmin, dmax, n_buckets):
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check_numeric_limits(dmin, dmax, n_buckets)
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ret_array = [0] * n_buckets
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dmin = float(dmin)
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dmax = float(dmax)
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for i in range(1, n_buckets):
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linear_range = (dmin * (n_buckets - 1 - i) + dmax * (i - 1)) / (n_buckets - 2)
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ret_array[i] = int(linear_range + 0.5)
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return ret_array
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def exponential_buckets(dmin, dmax, n_buckets):
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check_numeric_limits(dmin, dmax, n_buckets)
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log_max = math.log(dmax);
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bucket_index = 2;
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ret_array = [0] * n_buckets
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current = dmin
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ret_array[1] = current
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for bucket_index in range(2, n_buckets):
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log_current = math.log(current)
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log_ratio = (log_max - log_current) / (n_buckets - bucket_index)
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log_next = log_current + log_ratio
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next_value = int(math.floor(math.exp(log_next) + 0.5))
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if next_value > current:
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current = next_value
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else:
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current = current + 1
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ret_array[bucket_index] = current
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return ret_array
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always_allowed_keys = ['kind', 'description', 'cpp_guard', 'expires_in_version',
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'alert_emails', 'keyed', 'releaseChannelCollection']
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class Histogram:
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"""A class for representing a histogram definition."""
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def __init__(self, name, definition):
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"""Initialize a histogram named name with the given definition.
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definition is a dict-like object that must contain at least the keys:
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- 'kind': The kind of histogram. Must be one of 'boolean', 'flag',
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'count', 'enumerated', 'linear', or 'exponential'.
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- 'description': A textual description of the histogram.
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The key 'cpp_guard' is optional; if present, it denotes a preprocessor
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symbol that should guard C/C++ definitions associated with the histogram."""
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self.check_name(name)
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self.verify_attributes(name, definition)
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self._name = name
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self._description = definition['description']
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self._kind = definition['kind']
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self._cpp_guard = definition.get('cpp_guard')
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self._keyed = definition.get('keyed', False)
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self._extended_statistics_ok = definition.get('extended_statistics_ok', False)
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self._expiration = definition.get('expires_in_version')
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self.compute_bucket_parameters(definition)
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table = { 'boolean': 'BOOLEAN',
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'flag': 'FLAG',
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'count': 'COUNT',
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'enumerated': 'LINEAR',
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'linear': 'LINEAR',
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'exponential': 'EXPONENTIAL' }
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table_dispatch(self.kind(), table,
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lambda k: self._set_nsITelemetry_kind(k))
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datasets = { 'opt-in': 'DATASET_RELEASE_CHANNEL_OPTIN',
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'opt-out': 'DATASET_RELEASE_CHANNEL_OPTOUT' }
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value = definition.get('releaseChannelCollection', 'opt-in')
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if not value in datasets:
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raise DefinitionException, "unknown release channel collection policy for " + name
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self._dataset = "nsITelemetry::" + datasets[value]
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def name(self):
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"""Return the name of the histogram."""
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return self._name
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def description(self):
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"""Return the description of the histogram."""
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return self._description
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def kind(self):
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"""Return the kind of the histogram.
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Will be one of 'boolean', 'flag', 'count', 'enumerated', 'linear', or 'exponential'."""
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return self._kind
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def expiration(self):
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"""Return the expiration version of the histogram."""
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return self._expiration
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def nsITelemetry_kind(self):
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"""Return the nsITelemetry constant corresponding to the kind of
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the histogram."""
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return self._nsITelemetry_kind
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def _set_nsITelemetry_kind(self, kind):
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self._nsITelemetry_kind = "nsITelemetry::HISTOGRAM_%s" % kind
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def low(self):
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"""Return the lower bound of the histogram. May be a string."""
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return self._low
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def high(self):
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"""Return the high bound of the histogram. May be a string."""
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return self._high
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def n_buckets(self):
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"""Return the number of buckets in the histogram. May be a string."""
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return self._n_buckets
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def cpp_guard(self):
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"""Return the preprocessor symbol that should guard C/C++ definitions
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associated with the histogram. Returns None if no guarding is necessary."""
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return self._cpp_guard
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def keyed(self):
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"""Returns True if this a keyed histogram, false otherwise."""
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return self._keyed
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def dataset(self):
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"""Returns the dataset this histogram belongs into."""
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return self._dataset
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def extended_statistics_ok(self):
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"""Return True if gathering extended statistics for this histogram
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is enabled."""
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return self._extended_statistics_ok
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def ranges(self):
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"""Return an array of lower bounds for each bucket in the histogram."""
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table = { 'boolean': linear_buckets,
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'flag': linear_buckets,
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'count': linear_buckets,
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'enumerated': linear_buckets,
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'linear': linear_buckets,
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'exponential': exponential_buckets }
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return table_dispatch(self.kind(), table,
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lambda p: p(self.low(), self.high(), self.n_buckets()))
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def compute_bucket_parameters(self, definition):
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table = {
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'boolean': Histogram.boolean_flag_bucket_parameters,
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'flag': Histogram.boolean_flag_bucket_parameters,
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'count': Histogram.boolean_flag_bucket_parameters,
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'enumerated': Histogram.enumerated_bucket_parameters,
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'linear': Histogram.linear_bucket_parameters,
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'exponential': Histogram.exponential_bucket_parameters
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}
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table_dispatch(self.kind(), table,
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lambda p: self.set_bucket_parameters(*p(definition)))
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def verify_attributes(self, name, definition):
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global always_allowed_keys
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general_keys = always_allowed_keys + ['low', 'high', 'n_buckets']
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table = {
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'boolean': always_allowed_keys,
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'flag': always_allowed_keys,
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'count': always_allowed_keys,
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'enumerated': always_allowed_keys + ['n_values'],
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'linear': general_keys,
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'exponential': general_keys + ['extended_statistics_ok']
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}
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table_dispatch(definition['kind'], table,
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lambda allowed_keys: Histogram.check_keys(name, definition, allowed_keys))
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Histogram.check_expiration(name, definition)
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def check_name(self, name):
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if '#' in name:
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raise ValueError, '"#" not permitted for %s' % (name)
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@staticmethod
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def check_expiration(name, definition):
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expiration = definition.get('expires_in_version')
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if not expiration:
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return
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if re.match(r'^[1-9][0-9]*$', expiration):
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expiration = expiration + ".0a1"
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elif re.match(r'^[1-9][0-9]*\.0$', expiration):
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expiration = expiration + "a1"
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definition['expires_in_version'] = expiration
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@staticmethod
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def check_keys(name, definition, allowed_keys):
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for key in definition.iterkeys():
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if key not in allowed_keys:
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raise KeyError, '%s not permitted for %s' % (key, name)
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def set_bucket_parameters(self, low, high, n_buckets):
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def try_to_coerce_to_number(v):
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try:
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return eval(v, {})
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except:
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return v
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self._low = try_to_coerce_to_number(low)
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self._high = try_to_coerce_to_number(high)
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self._n_buckets = try_to_coerce_to_number(n_buckets)
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@staticmethod
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def boolean_flag_bucket_parameters(definition):
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return (1, 2, 3)
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@staticmethod
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def linear_bucket_parameters(definition):
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return (definition.get('low', 1),
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definition['high'],
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definition['n_buckets'])
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@staticmethod
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def enumerated_bucket_parameters(definition):
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n_values = definition['n_values']
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return (1, n_values, "%s+1" % n_values)
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@staticmethod
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def exponential_bucket_parameters(definition):
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return (definition.get('low', 1),
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definition['high'],
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definition['n_buckets'])
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# We support generating histograms from multiple different input files, not
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# just Histograms.json. For each file's basename, we have a specific
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# routine to parse that file, and return a dictionary mapping histogram
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# names to histogram parameters.
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def from_Histograms_json(filename):
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with open(filename, 'r') as f:
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try:
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histograms = json.load(f, object_pairs_hook=OrderedDict)
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except ValueError, e:
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raise BaseException, "error parsing histograms in %s: %s" % (filename, e.message)
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return histograms
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def from_UseCounters_conf(filename):
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return usecounters.generate_histograms(filename)
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def from_nsDeprecatedOperationList(filename):
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operation_regex = re.compile('^DEPRECATED_OPERATION\\(([^)]+)\\)')
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histograms = collections.OrderedDict()
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with open(filename, 'r') as f:
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for line in f:
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match = operation_regex.search(line)
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if not match:
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continue
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op = match.group(1)
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def add_counter(context):
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name = 'USE_COUNTER_DEPRECATED_%s_%s' % (op, context.upper())
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histograms[name] = {
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'expires_in_version': 'never',
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'kind': 'boolean',
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'description': 'Whether a %s used %s' % (context, op)
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}
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add_counter('document')
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add_counter('page')
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return histograms
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FILENAME_PARSERS = {
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'Histograms.json': from_Histograms_json,
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'nsDeprecatedOperationList.h': from_nsDeprecatedOperationList,
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}
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# Similarly to the dance above with buildconfig, usecounters may not be
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# available, so handle that gracefully.
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try:
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import usecounters
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FILENAME_PARSERS['UseCounters.conf'] = from_UseCounters_conf
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except ImportError:
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pass
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def from_files(filenames):
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"""Return an iterator that provides a sequence of Histograms for
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the histograms defined in filenames.
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"""
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all_histograms = OrderedDict()
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for filename in filenames:
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parser = FILENAME_PARSERS[os.path.basename(filename)]
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histograms = parser(filename)
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# OrderedDicts are important, because then the iteration order over
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# the parsed histograms is stable, which makes the insertion into
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# all_histograms stable, which makes ordering in generated files
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# stable, which makes builds more deterministic.
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if not isinstance(histograms, OrderedDict):
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raise BaseException, "histogram parser didn't provide an OrderedDict"
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for (name, definition) in histograms.iteritems():
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if all_histograms.has_key(name):
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raise DefinitionException, "duplicate histogram name %s" % name
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all_histograms[name] = definition
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# We require that all USE_COUNTER_* histograms be defined in a contiguous
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# block.
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use_counter_indices = filter(lambda x: x[1].startswith("USE_COUNTER_"),
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enumerate(all_histograms.iterkeys()));
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if use_counter_indices:
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lower_bound = use_counter_indices[0][0]
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upper_bound = use_counter_indices[-1][0]
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n_counters = upper_bound - lower_bound + 1
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if n_counters != len(use_counter_indices):
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raise DefinitionException, "use counter histograms must be defined in a contiguous block"
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for (name, definition) in all_histograms.iteritems():
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yield Histogram(name, definition)
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