# This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this # file, You can obtain one at http://mozilla.org/MPL/2.0/. import collections import json import math import os import re import sys # histogram_tools.py is used by scripts from a mozilla-central build tree # and also by outside consumers, such as the telemetry server. We need # to ensure that importing things works in both contexts. Therefore, # unconditionally importing things that are local to the build tree, such # as buildconfig, is a no-no. try: import buildconfig # Need to update sys.path to be able to find usecounters. sys.path.append(os.path.join(buildconfig.topsrcdir, 'dom/base/')) except ImportError: # Must be in an out-of-tree usage scenario. Trust that whoever is # running this script knows we need the usecounters module and has # ensured it's in our sys.path. pass from collections import OrderedDict def table_dispatch(kind, table, body): """Call body with table[kind] if it exists. Raise an error otherwise.""" if kind in table: return body(table[kind]) else: raise BaseException, "don't know how to handle a histogram of kind %s" % kind class DefinitionException(BaseException): pass def check_numeric_limits(dmin, dmax, n_buckets): if type(dmin) != int: raise DefinitionException, "minimum is not a number" if type(dmax) != int: raise DefinitionException, "maximum is not a number" if type(n_buckets) != int: raise DefinitionException, "number of buckets is not a number" def linear_buckets(dmin, dmax, n_buckets): check_numeric_limits(dmin, dmax, n_buckets) ret_array = [0] * n_buckets dmin = float(dmin) dmax = float(dmax) for i in range(1, n_buckets): linear_range = (dmin * (n_buckets - 1 - i) + dmax * (i - 1)) / (n_buckets - 2) ret_array[i] = int(linear_range + 0.5) return ret_array def exponential_buckets(dmin, dmax, n_buckets): check_numeric_limits(dmin, dmax, n_buckets) log_max = math.log(dmax); bucket_index = 2; ret_array = [0] * n_buckets current = dmin ret_array[1] = current for bucket_index in range(2, n_buckets): log_current = math.log(current) log_ratio = (log_max - log_current) / (n_buckets - bucket_index) log_next = log_current + log_ratio next_value = int(math.floor(math.exp(log_next) + 0.5)) if next_value > current: current = next_value else: current = current + 1 ret_array[bucket_index] = current return ret_array always_allowed_keys = ['kind', 'description', 'cpp_guard', 'expires_in_version', 'alert_emails', 'keyed', 'releaseChannelCollection', 'bug_numbers'] n_buckets_whitelist = None; try: whitelist_path = os.path.join(os.path.abspath(os.path.realpath(os.path.dirname(__file__))), 'bucket-whitelist.json') with open(whitelist_path, 'r') as f: try: n_buckets_whitelist = set(json.load(f)) except ValueError, e: raise BaseException, 'error parsing bucket whitelist (%s)' % whitelist_path except IOError: n_buckets_whitelist = None print 'Unable to parse whitelist (%s). Assuming all histograms are acceptable.' % whitelist_path class Histogram: """A class for representing a histogram definition.""" def __init__(self, name, definition): """Initialize a histogram named name with the given definition. definition is a dict-like object that must contain at least the keys: - 'kind': The kind of histogram. Must be one of 'boolean', 'flag', 'count', 'enumerated', 'linear', or 'exponential'. - 'description': A textual description of the histogram. The key 'cpp_guard' is optional; if present, it denotes a preprocessor symbol that should guard C/C++ definitions associated with the histogram.""" self.check_name(name) self.verify_attributes(name, definition) self._name = name self._description = definition['description'] self._kind = definition['kind'] self._cpp_guard = definition.get('cpp_guard') self._keyed = definition.get('keyed', False) self._extended_statistics_ok = definition.get('extended_statistics_ok', False) self._expiration = definition.get('expires_in_version') self.compute_bucket_parameters(definition) table = { 'boolean': 'BOOLEAN', 'flag': 'FLAG', 'count': 'COUNT', 'enumerated': 'LINEAR', 'linear': 'LINEAR', 'exponential': 'EXPONENTIAL' } table_dispatch(self.kind(), table, lambda k: self._set_nsITelemetry_kind(k)) datasets = { 'opt-in': 'DATASET_RELEASE_CHANNEL_OPTIN', 'opt-out': 'DATASET_RELEASE_CHANNEL_OPTOUT' } value = definition.get('releaseChannelCollection', 'opt-in') if not value in datasets: raise DefinitionException, "unknown release channel collection policy for " + name self._dataset = "nsITelemetry::" + datasets[value] def name(self): """Return the name of the histogram.""" return self._name def description(self): """Return the description of the histogram.""" return self._description def kind(self): """Return the kind of the histogram. Will be one of 'boolean', 'flag', 'count', 'enumerated', 'linear', or 'exponential'.""" return self._kind def expiration(self): """Return the expiration version of the histogram.""" return self._expiration def nsITelemetry_kind(self): """Return the nsITelemetry constant corresponding to the kind of the histogram.""" return self._nsITelemetry_kind def _set_nsITelemetry_kind(self, kind): self._nsITelemetry_kind = "nsITelemetry::HISTOGRAM_%s" % kind def low(self): """Return the lower bound of the histogram. May be a string.""" return self._low def high(self): """Return the high bound of the histogram. May be a string.""" return self._high def n_buckets(self): """Return the number of buckets in the histogram. May be a string.""" return self._n_buckets def cpp_guard(self): """Return the preprocessor symbol that should guard C/C++ definitions associated with the histogram. Returns None if no guarding is necessary.""" return self._cpp_guard def keyed(self): """Returns True if this a keyed histogram, false otherwise.""" return self._keyed def dataset(self): """Returns the dataset this histogram belongs into.""" return self._dataset def extended_statistics_ok(self): """Return True if gathering extended statistics for this histogram is enabled.""" return self._extended_statistics_ok def ranges(self): """Return an array of lower bounds for each bucket in the histogram.""" table = { 'boolean': linear_buckets, 'flag': linear_buckets, 'count': linear_buckets, 'enumerated': linear_buckets, 'linear': linear_buckets, 'exponential': exponential_buckets } return table_dispatch(self.kind(), table, lambda p: p(self.low(), self.high(), self.n_buckets())) def compute_bucket_parameters(self, definition): table = { 'boolean': Histogram.boolean_flag_bucket_parameters, 'flag': Histogram.boolean_flag_bucket_parameters, 'count': Histogram.boolean_flag_bucket_parameters, 'enumerated': Histogram.enumerated_bucket_parameters, 'linear': Histogram.linear_bucket_parameters, 'exponential': Histogram.exponential_bucket_parameters } table_dispatch(self.kind(), table, lambda p: self.set_bucket_parameters(*p(definition))) def verify_attributes(self, name, definition): global always_allowed_keys general_keys = always_allowed_keys + ['low', 'high', 'n_buckets'] table = { 'boolean': always_allowed_keys, 'flag': always_allowed_keys, 'count': always_allowed_keys, 'enumerated': always_allowed_keys + ['n_values'], 'linear': general_keys, 'exponential': general_keys + ['extended_statistics_ok'] } table_dispatch(definition['kind'], table, lambda allowed_keys: Histogram.check_keys(name, definition, allowed_keys)) if ('alert_emails' in definition and not isinstance(definition['alert_emails'], list)): raise KeyError, 'alert_emails must be an array if present (in Histogram %s)' % name Histogram.check_expiration(name, definition) Histogram.check_bug_numbers(name, definition) def check_name(self, name): if '#' in name: raise ValueError, '"#" not permitted for %s' % (name) @staticmethod def check_expiration(name, definition): expiration = definition.get('expires_in_version') if not expiration: return if re.match(r'^[1-9][0-9]*$', expiration): expiration = expiration + ".0a1" elif re.match(r'^[1-9][0-9]*\.0$', expiration): expiration = expiration + "a1" definition['expires_in_version'] = expiration @staticmethod def check_bug_numbers(name, definition): bug_numbers = definition.get('bug_numbers') if not bug_numbers: return if not isinstance(bug_numbers, list): raise ValueError, 'bug_numbers field for "%s" should be an array' % (name) if not all(type(num) is int for num in bug_numbers): raise ValueError, 'bug_numbers array for "%s" should only contain integers' % (name) @staticmethod def check_keys(name, definition, allowed_keys): for key in definition.iterkeys(): if key not in allowed_keys: raise KeyError, '%s not permitted for %s' % (key, name) def set_bucket_parameters(self, low, high, n_buckets): def try_to_coerce_to_number(v): try: return eval(v, {}) except: return v self._low = try_to_coerce_to_number(low) self._high = try_to_coerce_to_number(high) self._n_buckets = try_to_coerce_to_number(n_buckets) if n_buckets_whitelist is not None and self._n_buckets > 100 and type(self._n_buckets) is int: if self._name not in n_buckets_whitelist: raise KeyError, ('New histogram %s is not permitted to have more than 100 buckets. ' 'Histograms with large numbers of buckets use disproportionately high amounts of resources. ' 'Contact :vladan or the Perf team if you think an exception ought to be made.' % self._name) @staticmethod def boolean_flag_bucket_parameters(definition): return (1, 2, 3) @staticmethod def linear_bucket_parameters(definition): return (definition.get('low', 1), definition['high'], definition['n_buckets']) @staticmethod def enumerated_bucket_parameters(definition): n_values = definition['n_values'] return (1, n_values, "%s+1" % n_values) @staticmethod def exponential_bucket_parameters(definition): return (definition.get('low', 1), definition['high'], definition['n_buckets']) # We support generating histograms from multiple different input files, not # just Histograms.json. For each file's basename, we have a specific # routine to parse that file, and return a dictionary mapping histogram # names to histogram parameters. def from_Histograms_json(filename): with open(filename, 'r') as f: try: histograms = json.load(f, object_pairs_hook=OrderedDict) except ValueError, e: raise BaseException, "error parsing histograms in %s: %s" % (filename, e.message) return histograms def from_UseCounters_conf(filename): return usecounters.generate_histograms(filename) def from_nsDeprecatedOperationList(filename): operation_regex = re.compile('^DEPRECATED_OPERATION\\(([^)]+)\\)') histograms = collections.OrderedDict() with open(filename, 'r') as f: for line in f: match = operation_regex.search(line) if not match: continue op = match.group(1) def add_counter(context): name = 'USE_COUNTER2_DEPRECATED_%s_%s' % (op, context.upper()) histograms[name] = { 'expires_in_version': 'never', 'kind': 'boolean', 'description': 'Whether a %s used %s' % (context, op) } add_counter('document') add_counter('page') return histograms FILENAME_PARSERS = { 'Histograms.json': from_Histograms_json, 'nsDeprecatedOperationList.h': from_nsDeprecatedOperationList, } # Similarly to the dance above with buildconfig, usecounters may not be # available, so handle that gracefully. try: import usecounters FILENAME_PARSERS['UseCounters.conf'] = from_UseCounters_conf except ImportError: pass def from_files(filenames): """Return an iterator that provides a sequence of Histograms for the histograms defined in filenames. """ all_histograms = OrderedDict() for filename in filenames: parser = FILENAME_PARSERS[os.path.basename(filename)] histograms = parser(filename) # OrderedDicts are important, because then the iteration order over # the parsed histograms is stable, which makes the insertion into # all_histograms stable, which makes ordering in generated files # stable, which makes builds more deterministic. if not isinstance(histograms, OrderedDict): raise BaseException, "histogram parser didn't provide an OrderedDict" for (name, definition) in histograms.iteritems(): if all_histograms.has_key(name): raise DefinitionException, "duplicate histogram name %s" % name all_histograms[name] = definition # We require that all USE_COUNTER2_* histograms be defined in a contiguous # block. use_counter_indices = filter(lambda x: x[1].startswith("USE_COUNTER2_"), enumerate(all_histograms.iterkeys())); if use_counter_indices: lower_bound = use_counter_indices[0][0] upper_bound = use_counter_indices[-1][0] n_counters = upper_bound - lower_bound + 1 if n_counters != len(use_counter_indices): raise DefinitionException, "use counter histograms must be defined in a contiguous block" for (name, definition) in all_histograms.iteritems(): yield Histogram(name, definition)