369 lines
12 KiB
Python
369 lines
12 KiB
Python
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# Copyright 2013 The Chromium Authors. All rights reserved.
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# Use of this source code is governed by a BSD-style license that can be
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# found in the LICENSE file.
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"""Extract histogram names from the description XML file.
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For more information on the format of the XML file, which is self-documenting,
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see histograms.xml; however, here is a simple example to get you started. The
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XML below will generate the following five histograms:
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HistogramTime
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HistogramEnum
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HistogramEnum_Chrome
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HistogramEnum_IE
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HistogramEnum_Firefox
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<histogram-configuration>
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<histograms>
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<histogram name="HistogramTime" units="milliseconds">
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<summary>A brief description.</summary>
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<details>This is a more thorough description of this histogram.</details>
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</histogram>
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<histogram name="HistogramEnum" enum="MyEnumType">
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<summary>This histogram sports an enum value type.</summary>
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</histogram>
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</histograms>
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<enums>
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<enum name="MyEnumType">
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<summary>This is an example enum type, where the values mean little.</summary>
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<int value="1" label="FIRST_VALUE">This is the first value.</int>
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<int value="2" label="SECOND_VALUE">This is the second value.</int>
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</enum>
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</enums>
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<fieldtrials>
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<fieldtrial name="BrowserType">
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<group name="Chrome"/>
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<group name="IE"/>
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<group name="Firefox"/>
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<affected-histogram name="HistogramEnum"/>
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</fieldtrial>
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</fieldtrials>
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</histogram-configuration>
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"""
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import copy
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import logging
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import xml.dom.minidom
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MAX_FIELDTRIAL_DEPENDENCY_DEPTH = 5
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class Error(Exception):
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pass
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def JoinChildNodes(tag):
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return ''.join([c.toxml() for c in tag.childNodes]).strip()
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def NormalizeAttributeValue(s):
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"""Normalizes an attribute value (which might be wrapped over multiple lines)
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by replacing each whitespace sequence with a single space.
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Args:
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s: The string to normalize, e.g. ' \n a b c\n d '
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Returns:
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The normalized string, e.g. 'a b c d'
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"""
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return ' '.join(s.split())
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def NormalizeAllAttributeValues(node):
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"""Recursively normalizes all tag attribute values in the given tree.
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Args:
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node: The minidom node to be normalized.
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Returns:
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The normalized minidom node.
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"""
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if node.nodeType == xml.dom.minidom.Node.ELEMENT_NODE:
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for a in node.attributes.keys():
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node.attributes[a].value = NormalizeAttributeValue(
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node.attributes[a].value)
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for c in node.childNodes: NormalizeAllAttributeValues(c)
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return node
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def _ExpandHistogramNameWithFieldTrial(group_name, histogram_name, fieldtrial):
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"""Creates a new histogram name based on the field trial group.
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Args:
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group_name: The name of the field trial group. May be empty.
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histogram_name: The name of the histogram. May be of the form
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Group.BaseName or BaseName
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field_trial: The FieldTrial XML element.
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Returns:
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A string with the expanded histogram name.
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Raises:
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Error if the expansion can't be done.
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"""
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if fieldtrial.hasAttribute('separator'):
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separator = fieldtrial.getAttribute('separator')
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else:
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separator = '_'
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if fieldtrial.hasAttribute('ordering'):
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ordering = fieldtrial.getAttribute('ordering')
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else:
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ordering = 'suffix'
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if ordering not in ['prefix', 'suffix']:
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logging.error('ordering needs to be prefix or suffix, value is %s' %
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ordering)
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raise Error()
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if not group_name:
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return histogram_name
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if ordering == 'suffix':
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return histogram_name + separator + group_name
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# For prefixes, the group_name is inserted between the "cluster" and the
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# "remainder", e.g. Foo.BarHist expanded with gamma becomes Foo.gamma_BarHist.
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sections = histogram_name.split('.')
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if len(sections) <= 1:
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logging.error(
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'Prefix Field Trial expansions require histogram names which include a '
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'dot separator. Histogram name is %s, and Field Trial is %s' %
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(histogram_name, fieldtrial.getAttribute('name')))
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raise Error()
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cluster = sections[0] + '.'
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remainder = '.'.join(sections[1:])
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return cluster + group_name + separator + remainder
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def ExtractHistograms(filename):
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"""Compute the histogram names and descriptions from the XML representation.
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Args:
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filename: The path to the histograms XML file.
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Returns:
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{ 'histogram_name': 'histogram_description', ... }
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Raises:
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Error if the file is not well-formatted.
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"""
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# Slurp in histograms.xml
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raw_xml = ''
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with open(filename, 'r') as f:
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raw_xml = f.read()
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# Parse the XML into a tree
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tree = xml.dom.minidom.parseString(raw_xml)
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NormalizeAllAttributeValues(tree)
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histograms = {}
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have_errors = False
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# Load the enums.
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enums = {}
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last_name = None
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for enum in tree.getElementsByTagName("enum"):
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if enum.getAttribute('type') != 'int':
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logging.error('Unknown enum type %s' % enum.getAttribute('type'))
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have_errors = True
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continue
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name = enum.getAttribute('name')
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if last_name is not None and name.lower() < last_name.lower():
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logging.error('Enums %s and %s are not in alphabetical order'
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% (last_name, name))
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have_errors = True
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last_name = name
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if name in enums:
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logging.error('Duplicate enum %s' % name)
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have_errors = True
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continue
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last_int_value = None
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enum_dict = {}
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enum_dict['name'] = name
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enum_dict['values'] = {}
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for int_tag in enum.getElementsByTagName("int"):
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value_dict = {}
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int_value = int(int_tag.getAttribute('value'))
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if last_int_value is not None and int_value < last_int_value:
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logging.error('Enum %s int values %d and %d are not in numerical order'
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% (name, last_int_value, int_value))
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have_errors = True
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last_int_value = int_value
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if int_value in enum_dict['values']:
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logging.error('Duplicate enum value %d for enum %s' % (int_value, name))
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have_errors = True
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continue
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value_dict['label'] = int_tag.getAttribute('label')
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value_dict['summary'] = JoinChildNodes(int_tag)
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enum_dict['values'][int_value] = value_dict
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summary_nodes = enum.getElementsByTagName("summary")
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if len(summary_nodes) > 0:
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enum_dict['summary'] = JoinChildNodes(summary_nodes[0])
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enums[name] = enum_dict
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# Process the histograms. The descriptions can include HTML tags.
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last_name = None
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for histogram in tree.getElementsByTagName("histogram"):
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name = histogram.getAttribute('name')
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if last_name is not None and name.lower() < last_name.lower():
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logging.error('Histograms %s and %s are not in alphabetical order'
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% (last_name, name))
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have_errors = True
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last_name = name
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if name in histograms:
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logging.error('Duplicate histogram definition %s' % name)
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have_errors = True
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continue
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histograms[name] = {}
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# Find <summary> tag.
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summary_nodes = histogram.getElementsByTagName("summary")
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if len(summary_nodes) > 0:
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histograms[name]['summary'] = JoinChildNodes(summary_nodes[0])
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else:
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histograms[name]['summary'] = 'TBD'
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# Find <obsolete> tag.
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obsolete_nodes = histogram.getElementsByTagName("obsolete")
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if len(obsolete_nodes) > 0:
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reason = JoinChildNodes(obsolete_nodes[0])
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histograms[name]['obsolete'] = reason
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# Handle units.
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if histogram.hasAttribute('units'):
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histograms[name]['units'] = histogram.getAttribute('units')
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# Find <details> tag.
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details_nodes = histogram.getElementsByTagName("details")
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if len(details_nodes) > 0:
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histograms[name]['details'] = JoinChildNodes(details_nodes[0])
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# Handle enum types.
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if histogram.hasAttribute('enum'):
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enum_name = histogram.getAttribute('enum')
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if not enum_name in enums:
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logging.error('Unknown enum %s in histogram %s' % (enum_name, name))
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have_errors = True
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else:
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histograms[name]['enum'] = enums[enum_name]
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# Process the field trials and compute the combinations with their affected
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# histograms.
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last_name = None
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for fieldtrial in tree.getElementsByTagName("fieldtrial"):
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name = fieldtrial.getAttribute('name')
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if last_name is not None and name.lower() < last_name.lower():
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logging.error('Field trials %s and %s are not in alphabetical order'
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% (last_name, name))
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have_errors = True
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last_name = name
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# Field trials can depend on other field trials, so we need to be careful.
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# Make a temporary copy of the list of field trials to use as a queue.
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# Field trials whose dependencies have not yet been processed will get
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# relegated to the back of the queue to be processed later.
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reprocess_queue = []
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def GenerateFieldTrials():
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for f in tree.getElementsByTagName("fieldtrial"): yield 0, f
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for r, f in reprocess_queue: yield r, f
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for reprocess_count, fieldtrial in GenerateFieldTrials():
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# Check dependencies first
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dependencies_valid = True
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affected_histograms = fieldtrial.getElementsByTagName('affected-histogram')
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for affected_histogram in affected_histograms:
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histogram_name = affected_histogram.getAttribute('name')
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if not histogram_name in histograms:
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# Base histogram is missing
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dependencies_valid = False
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missing_dependency = histogram_name
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break
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if not dependencies_valid:
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if reprocess_count < MAX_FIELDTRIAL_DEPENDENCY_DEPTH:
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reprocess_queue.append( (reprocess_count + 1, fieldtrial) )
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continue
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else:
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logging.error('Field trial %s is missing its dependency %s'
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% (fieldtrial.getAttribute('name'),
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missing_dependency))
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have_errors = True
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continue
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name = fieldtrial.getAttribute('name')
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groups = fieldtrial.getElementsByTagName('group')
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group_labels = {}
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for group in groups:
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group_labels[group.getAttribute('name')] = group.getAttribute('label')
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last_histogram_name = None
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for affected_histogram in affected_histograms:
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histogram_name = affected_histogram.getAttribute('name')
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if (last_histogram_name is not None
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and histogram_name.lower() < last_histogram_name.lower()):
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logging.error('Affected histograms %s and %s of field trial %s are not '
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'in alphabetical order'
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% (last_histogram_name, histogram_name, name))
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have_errors = True
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last_histogram_name = histogram_name
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base_description = histograms[histogram_name]
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with_groups = affected_histogram.getElementsByTagName('with-group')
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if len(with_groups) > 0:
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histogram_groups = with_groups
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else:
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histogram_groups = groups
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for group in histogram_groups:
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group_name = group.getAttribute('name')
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try:
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new_histogram_name = _ExpandHistogramNameWithFieldTrial(
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group_name, histogram_name, fieldtrial)
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if new_histogram_name != histogram_name:
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histograms[new_histogram_name] = copy.deepcopy(
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histograms[histogram_name])
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group_label = group_labels.get(group_name, '')
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if not 'fieldtrial_groups' in histograms[new_histogram_name]:
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histograms[new_histogram_name]['fieldtrial_groups'] = []
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histograms[new_histogram_name]['fieldtrial_groups'].append(group_name)
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if not 'fieldtrial_names' in histograms[new_histogram_name]:
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histograms[new_histogram_name]['fieldtrial_names'] = []
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histograms[new_histogram_name]['fieldtrial_names'].append(name)
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if not 'fieldtrial_labels' in histograms[new_histogram_name]:
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histograms[new_histogram_name]['fieldtrial_labels'] = []
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histograms[new_histogram_name]['fieldtrial_labels'].append(
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group_label)
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except Error:
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have_errors = True
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if have_errors:
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logging.error('Error parsing %s' % filename)
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raise Error()
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return histograms
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def ExtractNames(histograms):
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return sorted(histograms.keys())
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