nagai/fune
3
0
Fork 0
forked from mirrors/gecko-dev
Code Pull requests Activity
fune/toolkit/components/telemetry/build_scripts/mozparsers/parse_histograms.py
Marco Castelluccio 76a10c5956 Bug 1790816 - Reformat toolkit/ with isort. r=linter-reviewers,Standard8 DONTBUILD 
# ignore-this-changeset

Differential Revision: https://phabricator.services.mozilla.com/D162670
2022-11-22 18:23:54 +00:00

1009 lines
36 KiB
Python
Raw Blame History

# 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 atexit
import collections
import itertools
import json
import math
import os
import re
import runpy
import sys
from collections import OrderedDict
from ctypes import c_int
from . import shared_telemetry_utils as utils
from .shared_telemetry_utils import ParserError
atexit.register(ParserError.exit_func)
# Constants.
MAX_LABEL_LENGTH = 20
MAX_LABEL_COUNT = 100
MAX_KEY_COUNT = 30
MAX_KEY_LENGTH = 20
MIN_CATEGORICAL_BUCKET_COUNT = 50
CPP_IDENTIFIER_PATTERN = "^[a-z][a-z0-9_]+[a-z0-9]$"
ALWAYS_ALLOWED_KEYS = [
"kind",
"description",
"operating_systems",
"expires_in_version",
"alert_emails",
"keyed",
"releaseChannelCollection",
"bug_numbers",
"keys",
"record_in_processes",
"record_into_store",
"products",
]
BASE_DOC_URL = (
"https://firefox-source-docs.mozilla.org/toolkit/components/" "telemetry/telemetry/"
)
HISTOGRAMS_DOC_URL = BASE_DOC_URL + "collection/histograms.html"
SCALARS_DOC_URL = BASE_DOC_URL + "collection/scalars.html"
GECKOVIEW_STREAMING_SUPPORTED_KINDS = [
"linear",
"exponential",
"categorical",
]
# parse_histograms.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
def linear_buckets(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):
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
allowlists = None
def load_allowlist():
global allowlists
try:
parsers_path = os.path.realpath(os.path.dirname(__file__))
# The parsers live in build_scripts/parsers in the Telemetry module, while
# the histogram-allowlists file lives in the root of the module. Account
# for that when looking for the allowlist.
# NOTE: if the parsers are moved, this logic will need to be updated.
telemetry_module_path = os.path.abspath(
os.path.join(parsers_path, os.pardir, os.pardir)
)
allowlist_path = os.path.join(
telemetry_module_path, "histogram-allowlists.json"
)
with open(allowlist_path, "r") as f:
try:
allowlists = json.load(f)
for name, allowlist in allowlists.items():
allowlists[name] = set(allowlist)
except ValueError:
ParserError("Error parsing allowlist: %s" % allowlist_path).handle_now()
except IOError:
allowlists = None
ParserError("Unable to parse allowlist: %s." % allowlist_path).handle_now()
class Histogram:
"""A class for representing a histogram definition."""
def __init__(self, name, definition, strict_type_checks=False):
"""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.
- 'strict_type_checks': A boolean indicating whether to use the new, stricter type checks.
The server-side still has to deal with old, oddly typed
submissions, so we have to skip them there by default.
"""
self._strict_type_checks = strict_type_checks
self._is_use_counter = name.startswith("USE_COUNTER2_")
if self._is_use_counter:
definition.setdefault("record_in_processes", ["main", "content"])
definition.setdefault("releaseChannelCollection", "opt-out")
definition.setdefault("products", ["firefox", "fennec"])
self.verify_attributes(name, definition)
self._name = name
self._description = definition["description"]
self._kind = definition["kind"]
self._keys = definition.get("keys", [])
self._keyed = definition.get("keyed", False)
self._expiration = definition.get("expires_in_version")
self._labels = definition.get("labels", [])
self._record_in_processes = definition.get("record_in_processes")
self._record_into_store = definition.get("record_into_store", ["main"])
self._products = definition.get("products")
self._operating_systems = definition.get("operating_systems", ["all"])
self.compute_bucket_parameters(definition)
self.set_nsITelemetry_kind()
self.set_dataset(definition)
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', 'categorical', '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 low(self):
"""Return the lower bound of the histogram."""
return self._low
def high(self):
"""Return the high bound of the histogram."""
return self._high
def n_buckets(self):
"""Return the number of buckets in the histogram."""
return self._n_buckets
def keyed(self):
"""Returns True if this a keyed histogram, false otherwise."""
return self._keyed
def keys(self):
"""Returns a list of allowed keys for keyed histogram, [] for others."""
return self._keys
def dataset(self):
"""Returns the dataset this histogram belongs into."""
return self._dataset
def labels(self):
"""Returns a list of labels for a categorical histogram, [] for others."""
return self._labels
def record_in_processes(self):
"""Returns a list of processes this histogram is permitted to record in."""
return self._record_in_processes
def record_in_processes_enum(self):
"""Get the non-empty list of flags representing the processes to record data in"""
return [utils.process_name_to_enum(p) for p in self.record_in_processes()]
def products(self):
"""Get the non-empty list of products to record data on"""
return self._products
def products_enum(self):
"""Get the non-empty list of flags representing products to record data on"""
return [utils.product_name_to_enum(p) for p in self.products()]
def operating_systems(self):
"""Get the list of operating systems to record data on"""
return self._operating_systems
def record_on_os(self, target_os):
"""Check if this probe should be recorded on the passed os."""
os = self.operating_systems()
if "all" in os:
return True
canonical_os = utils.canonical_os(target_os)
if "unix" in os and canonical_os in utils.UNIX_LIKE_OS:
return True
return canonical_os in os
def record_into_store(self):
"""Get the non-empty list of stores to record into"""
return self._record_into_store
def ranges(self):
"""Return an array of lower bounds for each bucket in the histogram."""
bucket_fns = {
"boolean": linear_buckets,
"flag": linear_buckets,
"count": linear_buckets,
"enumerated": linear_buckets,
"categorical": linear_buckets,
"linear": linear_buckets,
"exponential": exponential_buckets,
}
if self._kind not in bucket_fns:
ParserError(
'Unknown kind "%s" for histogram "%s".' % (self._kind, self._name)
).handle_later()
fn = bucket_fns[self._kind]
return fn(self.low(), self.high(), self.n_buckets())
def compute_bucket_parameters(self, definition):
bucket_fns = {
"boolean": Histogram.boolean_flag_bucket_parameters,
"flag": Histogram.boolean_flag_bucket_parameters,
"count": Histogram.boolean_flag_bucket_parameters,
"enumerated": Histogram.enumerated_bucket_parameters,
"categorical": Histogram.categorical_bucket_parameters,
"linear": Histogram.linear_bucket_parameters,
"exponential": Histogram.exponential_bucket_parameters,
}
if self._kind not in bucket_fns:
ParserError(
'Unknown kind "%s" for histogram "%s".' % (self._kind, self._name)
).handle_later()
fn = bucket_fns[self._kind]
self.set_bucket_parameters(*fn(definition))
def verify_attributes(self, name, definition):
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"],
"categorical": ALWAYS_ALLOWED_KEYS + ["labels", "n_values"],
"linear": general_keys,
"exponential": general_keys,
}
# We removed extended_statistics_ok on the client, but the server-side,
# where _strict_type_checks==False, has to deal with historical data.
if not self._strict_type_checks:
table["exponential"].append("extended_statistics_ok")
kind = definition["kind"]
if kind not in table:
ParserError(
'Unknown kind "%s" for histogram "%s".' % (kind, name)
).handle_later()
allowed_keys = table[kind]
self.check_name(name)
self.check_keys(name, definition, allowed_keys)
self.check_keys_field(name, definition)
self.check_field_types(name, definition)
self.check_allowlisted_kind(name, definition)
self.check_allowlistable_fields(name, definition)
self.check_expiration(name, definition)
self.check_label_values(name, definition)
self.check_record_in_processes(name, definition)
self.check_products(name, definition)
self.check_operating_systems(name, definition)
self.check_record_into_store(name, definition)
def check_name(self, name):
if "#" in name:
ParserError(
'Error for histogram name "%s": "#" is not allowed.' % (name)
).handle_later()
# Avoid C++ identifier conflicts between histogram enums and label enum names.
if name.startswith("LABELS_"):
ParserError(
'Error for histogram name "%s": can not start with "LABELS_".' % (name)
).handle_later()
# To make it easier to generate C++ identifiers from this etc., we restrict
# the histogram names to a strict pattern.
# We skip this on the server to avoid failures with old Histogram.json revisions.
if self._strict_type_checks:
if not re.match(CPP_IDENTIFIER_PATTERN, name, re.IGNORECASE):
ParserError(
'Error for histogram name "%s": name does not conform to "%s"'
% (name, CPP_IDENTIFIER_PATTERN)
).handle_later()
def check_expiration(self, name, definition):
field = "expires_in_version"
expiration = definition.get(field)
if not expiration:
return
# We forbid new probes from using "expires_in_version" : "default" field/value pair.
# Old ones that use this are added to the allowlist.
if (
expiration == "default"
and allowlists is not None
and name not in allowlists["expiry_default"]
):
ParserError(
'New histogram "%s" cannot have "default" %s value.' % (name, field)
).handle_later()
# Historical editions of Histograms.json can have the deprecated
# expiration format 'N.Na1'. Fortunately, those scripts set
# self._strict_type_checks to false.
if (
expiration != "default"
and not utils.validate_expiration_version(expiration)
and self._strict_type_checks
):
ParserError(
(
"Error for histogram {} - invalid {}: {}."
"\nSee: {}#expires-in-version"
).format(name, field, expiration, HISTOGRAMS_DOC_URL)
).handle_later()
expiration = utils.add_expiration_postfix(expiration)
definition[field] = expiration
def check_label_values(self, name, definition):
labels = definition.get("labels")
if not labels:
return
invalid = filter(lambda l: len(l) > MAX_LABEL_LENGTH, labels)
if len(list(invalid)) > 0:
ParserError(
'Label values for "%s" exceed length limit of %d: %s'
% (name, MAX_LABEL_LENGTH, ", ".join(invalid))
).handle_later()
if len(labels) > MAX_LABEL_COUNT:
ParserError(
'Label count for "%s" exceeds limit of %d' % (name, MAX_LABEL_COUNT)
).handle_now()
# To make it easier to generate C++ identifiers from this etc., we restrict
# the label values to a strict pattern.
invalid = filter(
lambda l: not re.match(CPP_IDENTIFIER_PATTERN, l, re.IGNORECASE), labels
)
if len(list(invalid)) > 0:
ParserError(
'Label values for %s are not matching pattern "%s": %s'
% (name, CPP_IDENTIFIER_PATTERN, ", ".join(invalid))
).handle_later()
def check_record_in_processes(self, name, definition):
if not self._strict_type_checks:
return
field = "record_in_processes"
rip = definition.get(field)
DOC_URL = HISTOGRAMS_DOC_URL + "#record-in-processes"
if not rip:
ParserError(
'Histogram "%s" must have a "%s" field:\n%s' % (name, field, DOC_URL)
).handle_later()
for process in rip:
if not utils.is_valid_process_name(process):
ParserError(
'Histogram "%s" has unknown process "%s" in %s.\n%s'
% (name, process, field, DOC_URL)
).handle_later()
def check_products(self, name, definition):
if not self._strict_type_checks:
return
field = "products"
products = definition.get(field)
DOC_URL = HISTOGRAMS_DOC_URL + "#products"
if not products:
ParserError(
'Histogram "%s" must have a "%s" field:\n%s' % (name, field, DOC_URL)
).handle_now()
for product in products:
if not utils.is_valid_product(product):
ParserError(
'Histogram "%s" has unknown product "%s" in %s.\n%s'
% (name, product, field, DOC_URL)
).handle_later()
if utils.is_geckoview_streaming_product(product):
kind = definition.get("kind")
if kind not in GECKOVIEW_STREAMING_SUPPORTED_KINDS:
ParserError(
(
'Histogram "%s" is of kind "%s" which is unsupported for '
'product "%s".'
)
% (name, kind, product)
).handle_later()
keyed = definition.get("keyed")
if keyed:
ParserError(
'Keyed histograms like "%s" are unsupported for product "%s"'
% (name, product)
).handle_later()
def check_operating_systems(self, name, definition):
if not self._strict_type_checks:
return
field = "operating_systems"
operating_systems = definition.get(field)
DOC_URL = HISTOGRAMS_DOC_URL + "#operating-systems"
if not operating_systems:
# operating_systems is optional
return
for operating_system in operating_systems:
if not utils.is_valid_os(operating_system):
ParserError(
'Histogram "%s" has unknown operating system "%s" in %s.\n%s'
% (name, operating_system, field, DOC_URL)
).handle_later()
def check_record_into_store(self, name, definition):
if not self._strict_type_checks:
return
field = "record_into_store"
DOC_URL = HISTOGRAMS_DOC_URL + "#record-into-store"
if field not in definition:
# record_into_store is optional
return
record_into_store = definition.get(field)
# record_into_store should not be empty
if not record_into_store:
ParserError(
'Histogram "%s" has empty list of stores, which is not allowed.\n%s'
% (name, DOC_URL)
).handle_later()
def check_keys_field(self, name, definition):
keys = definition.get("keys")
if not self._strict_type_checks or keys is None:
return
if not definition.get("keyed", False):
raise ValueError(
"'keys' field is not valid for %s; only allowed for keyed histograms."
% (name)
)
if len(keys) == 0:
raise ValueError("The key list for %s cannot be empty" % (name))
if len(keys) > MAX_KEY_COUNT:
raise ValueError(
"Label count for %s exceeds limit of %d" % (name, MAX_KEY_COUNT)
)
invalid = filter(lambda k: len(k) > MAX_KEY_LENGTH, keys)
if len(list(invalid)) > 0:
raise ValueError(
'"keys" values for %s are exceeding length "%d": %s'
% (name, MAX_KEY_LENGTH, ", ".join(invalid))
)
def check_allowlisted_kind(self, name, definition):
# We don't need to run any of these checks on the server.
if not self._strict_type_checks or allowlists is None:
return
# Disallow "flag" and "count" histograms on desktop, suggest to use
# scalars instead. Allow using these histograms on Android, as we
# don't support scalars there yet.
hist_kind = definition.get("kind")
android_target = "android" in definition.get("operating_systems", [])
if (
not android_target
and hist_kind in ["flag", "count"]
and name not in allowlists["kind"]
):
ParserError(
(
'Unsupported kind "%s" for histogram "%s":\n'
'New "%s" histograms are not supported on Desktop, you should'
" use scalars instead:\n"
"%s\n"
"Are you trying to add a histogram on Android?"
' Add "operating_systems": ["android"] to your histogram definition.'
)
% (hist_kind, name, hist_kind, SCALARS_DOC_URL)
).handle_now()
# Check for the presence of fields that old histograms are allowlisted for.
def check_allowlistable_fields(self, name, definition):
# Use counters don't have any mechanism to add the fields checked here,
# so skip the check for them.
# We also don't need to run any of these checks on the server.
if self._is_use_counter or not self._strict_type_checks:
return
# In the pipeline we don't have allowlists available.
if allowlists is None:
return
for field in ["alert_emails", "bug_numbers"]:
if field not in definition and name not in allowlists[field]:
ParserError(
'New histogram "%s" must have a "%s" field.' % (name, field)
).handle_later()
if field in definition and name in allowlists[field]:
msg = (
'Histogram "%s" should be removed from the allowlist for "%s" in '
"histogram-allowlists.json."
)
ParserError(msg % (name, field)).handle_later()
def check_field_types(self, name, definition):
# Define expected types for the histogram properties.
type_checked_fields = {
"n_buckets": int,
"n_values": int,
"low": int,
"high": int,
"keyed": bool,
"expires_in_version": str,
"kind": str,
"description": str,
"releaseChannelCollection": str,
}
# For list fields we check the items types.
type_checked_list_fields = {
"bug_numbers": int,
"alert_emails": str,
"labels": str,
"record_in_processes": str,
"keys": str,
"products": str,
"operating_systems": str,
"record_into_store": str,
}
# For the server-side, where _strict_type_checks==False, we want to
# skip the stricter type checks for these fields for dealing with
# historical data.
coerce_fields = ["low", "high", "n_values", "n_buckets"]
if not self._strict_type_checks:
# This handles some old non-numeric expressions.
EXPRESSIONS = {
"JS::GCReason::NUM_TELEMETRY_REASONS": 101,
"mozilla::StartupTimeline::MAX_EVENT_ID": 12,
}
def try_to_coerce_to_number(v):
if v in EXPRESSIONS:
return EXPRESSIONS[v]
try:
return eval(v, {})
except Exception:
return v
for key in [k for k in coerce_fields if k in definition]:
definition[key] = try_to_coerce_to_number(definition[key])
# This handles old "keyed":"true" definitions (bug 1271986).
if definition.get("keyed", None) == "true":
definition["keyed"] = True
def nice_type_name(t):
if t is str:
return "string"
return t.__name__
for key, key_type in type_checked_fields.items():
if key not in definition:
continue
if not isinstance(definition[key], key_type):
ParserError(
'Value for key "{0}" in histogram "{1}" should be {2}.'.format(
key, name, nice_type_name(key_type)
)
).handle_later()
# Make sure the max range is lower than or equal to INT_MAX
if "high" in definition and not c_int(definition["high"]).value > 0:
ParserError(
'Value for high in histogram "{0}" should be lower or equal to INT_MAX.'.format(
nice_type_name(c_int)
)
).handle_later()
for key, key_type in type_checked_list_fields.items():
if key not in definition:
continue
if not all(isinstance(x, key_type) for x in definition[key]):
ParserError(
'All values for list "{0}" in histogram "{1}" should be of type'
" {2}.".format(key, name, nice_type_name(key_type))
).handle_later()
def check_keys(self, name, definition, allowed_keys):
if not self._strict_type_checks:
return
for key in iter(definition.keys()):
if key not in allowed_keys:
ParserError(
'Key "%s" is not allowed for histogram "%s".' % (key, name)
).handle_later()
def set_bucket_parameters(self, low, high, n_buckets):
self._low = low
self._high = high
self._n_buckets = n_buckets
max_n_buckets = 101 if self._kind in ["enumerated", "categorical"] else 100
if (
allowlists is not None
and self._n_buckets > max_n_buckets
and type(self._n_buckets) is int
):
if self._name not in allowlists["n_buckets"]:
ParserError(
'New histogram "%s" is not permitted to have more than 100 buckets.\n'
"Histograms with large numbers of buckets use disproportionately high"
" amounts of resources. Contact a Telemetry peer (e.g. in #telemetry)"
" if you think an exception ought to be made:\n"
"https://wiki.mozilla.org/Modules/Toolkit#Telemetry" % self._name
).handle_later()
@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, n_values + 1)
@staticmethod
def categorical_bucket_parameters(definition):
# Categorical histograms default to 50 buckets to make working with them easier.
# Otherwise when adding labels later we run into problems with the pipeline not
# supporting bucket changes.
# This can be overridden using the n_values field.
n_values = max(
len(definition["labels"]),
definition.get("n_values", 0),
MIN_CATEGORICAL_BUCKET_COUNT,
)
return (1, n_values, n_values + 1)
@staticmethod
def exponential_bucket_parameters(definition):
return (definition.get("low", 1), definition["high"], definition["n_buckets"])
def set_nsITelemetry_kind(self):
# Pick a Telemetry implementation type.
types = {
"boolean": "BOOLEAN",
"flag": "FLAG",
"count": "COUNT",
"enumerated": "LINEAR",
"categorical": "CATEGORICAL",
"linear": "LINEAR",
"exponential": "EXPONENTIAL",
}
if self._kind not in types:
ParserError(
'Unknown kind "%s" for histogram "%s".' % (self._kind, self._name)
).handle_later()
self._nsITelemetry_kind = "nsITelemetry::HISTOGRAM_%s" % types[self._kind]
def set_dataset(self, definition):
datasets = {
"opt-in": "DATASET_PRERELEASE_CHANNELS",
"opt-out": "DATASET_ALL_CHANNELS",
}
value = definition.get("releaseChannelCollection", "opt-in")
if value not in datasets:
ParserError(
"Unknown value for releaseChannelCollection"
' policy for histogram "%s".' % self._name
).handle_later()
self._dataset = "nsITelemetry::" + datasets[value]
# This hook function loads the histograms into an OrderedDict.
# It will raise a ParserError if duplicate keys are found.
def load_histograms_into_dict(ordered_pairs, strict_type_checks):
d = collections.OrderedDict()
for key, value in ordered_pairs:
if strict_type_checks and key in d:
ParserError(
"Found duplicate key in Histograms file: %s" % key
).handle_later()
d[key] = value
return d
# 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_json(filename, strict_type_checks):
with open(filename, "r") as f:
try:
def hook(ps):
return load_histograms_into_dict(ps, strict_type_checks)
histograms = json.load(f, object_pairs_hook=hook)
except ValueError as e:
ParserError(
"error parsing histograms in %s: %s" % (filename, e)
).handle_now()
return histograms
def from_UseCounters_conf(filename, strict_type_checks):
return usecounters.generate_histograms(filename)
def from_UseCountersWorker_conf(filename, strict_type_checks):
return usecounters.generate_histograms(filename, True)
def from_nsDeprecatedOperationList(filename, strict_type_checks):
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
def to_camel_case(property_name):
return re.sub(
"(^|_|-)([a-z0-9])",
lambda m: m.group(2).upper(),
property_name.strip("_").strip("-"),
)
def add_css_property_counters(histograms, property_name):
def add_counter(context):
name = "USE_COUNTER2_CSS_PROPERTY_%s_%s" % (
to_camel_case(property_name),
context.upper(),
)
histograms[name] = {
"expires_in_version": "never",
"kind": "boolean",
"description": "Whether a %s used the CSS property %s"
% (context, property_name),
}
add_counter("document")
add_counter("page")
def from_ServoCSSPropList(filename, strict_type_checks):
histograms = collections.OrderedDict()
properties = runpy.run_path(filename)["data"]
for prop in properties:
add_css_property_counters(histograms, prop.name)
return histograms
def from_counted_unknown_properties(filename, strict_type_checks):
histograms = collections.OrderedDict()
properties = runpy.run_path(filename)["COUNTED_UNKNOWN_PROPERTIES"]
# NOTE(emilio): Unlike ServoCSSProperties, `prop` here is just the property
# name.
#
# We use the same naming as CSS properties so that we don't get
# discontinuity when we implement or prototype them.
for prop in properties:
add_css_property_counters(histograms, prop)
return histograms
# This is only used for probe-scraper.
def from_properties_db(filename, strict_type_checks):
histograms = collections.OrderedDict()
with open(filename, "r") as f:
in_css_properties = False
for line in f:
if not in_css_properties:
if line.startswith("exports.CSS_PROPERTIES = {"):
in_css_properties = True
continue
if line.startswith("};"):
break
if not line.startswith(' "'):
continue
name = line.split('"')[1]
add_css_property_counters(histograms, name)
return histograms
FILENAME_PARSERS = [
(lambda x: from_json if x.endswith(".json") else None),
(
lambda x: from_nsDeprecatedOperationList
if x == "nsDeprecatedOperationList.h"
else None
),
(lambda x: from_ServoCSSPropList if x == "ServoCSSPropList.py" else None),
(
lambda x: from_counted_unknown_properties
if x == "counted_unknown_properties.py"
else None
),
(lambda x: from_properties_db if x == "properties-db.js" else None),
]
# Similarly to the dance above with buildconfig, usecounters may not be
# available, so handle that gracefully.
try:
import usecounters
FILENAME_PARSERS.append(
lambda x: from_UseCounters_conf if x == "UseCounters.conf" else None
)
FILENAME_PARSERS.append(
lambda x: from_UseCountersWorker_conf if x == "UseCountersWorker.conf" else None
)
except ImportError:
pass
def from_files(filenames, strict_type_checks=True):
"""Return an iterator that provides a sequence of Histograms for
the histograms defined in filenames.
"""
if strict_type_checks:
load_allowlist()
all_histograms = OrderedDict()
for filename in filenames:
parser = None
for checkFn in FILENAME_PARSERS:
parser = checkFn(os.path.basename(filename))
if parser is not None:
break
if parser is None:
ParserError("Don't know how to parse %s." % filename).handle_now()
histograms = parser(filename, strict_type_checks)
# 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):
ParserError("Histogram parser did not provide an OrderedDict.").handle_now()
for (name, definition) in histograms.items():
if name in all_histograms:
ParserError('Duplicate histogram name "%s".' % name).handle_later()
all_histograms[name] = definition
def check_continuity(iterable, filter_function, name):
indices = list(filter(filter_function, enumerate(iter(iterable.keys()))))
if indices:
lower_bound = indices[0][0]
upper_bound = indices[-1][0]
n_counters = upper_bound - lower_bound + 1
if n_counters != len(indices):
ParserError(
"Histograms %s must be defined in a contiguous block." % name
).handle_later()
# We require that all USE_COUNTER2_*_WORKER histograms be defined in a contiguous
# block.
check_continuity(
all_histograms,
lambda x: x[1].startswith("USE_COUNTER2_") and x[1].endswith("_WORKER"),
"use counter worker",
)
# And all other USE_COUNTER2_* histograms be defined in a contiguous
# block.
check_continuity(
all_histograms,
lambda x: x[1].startswith("USE_COUNTER2_") and not x[1].endswith("_WORKER"),
"use counter",
)
# Check that histograms that were removed from Histograms.json etc.
# are also removed from the allowlists.
if allowlists is not None:
all_allowlist_entries = itertools.chain.from_iterable(iter(allowlists.values()))
orphaned = set(all_allowlist_entries) - set(all_histograms.keys())
if len(orphaned) > 0:
msg = (
"The following entries are orphaned and should be removed from "
"histogram-allowlists.json:\n%s"
)
ParserError(msg % (", ".join(sorted(orphaned)))).handle_later()
for (name, definition) in all_histograms.items():
yield Histogram(name, definition, strict_type_checks=strict_type_checks)
View git blame Copy permalink