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# Copyright 2019 The LUCI Authors. All rights reserved.
# Use of this source code is governed under the Apache License, Version 2.0
# that can be found in the LICENSE file.
"""The types that appear as inputs to post-processing hooks."""
import re
from collections import Iterable, OrderedDict
import attr
from .types import ResourceCost
class Command(list):
"""Specialized list enabling enhanced searching in command arguments.
Command is a list of strings that supports searching for individual strings
or subsequences of strings comparing by either string equality or regular
expression. Regular expression elements are compared against strings using the
search method of the regular expression object.
For example, the following all evaluate as True:
'foo' in Command(['foo', 'bar', 'baz'])
re.compile('a') in Command(['foo', 'bar', 'baz'])
['foo', 'bar'] in Command(['foo', 'bar', 'baz'])
[re.compile('o$'), 'bar', re.compile('^b')]
in Command(['foo', 'bar', 'baz'])
You may also provide a literal `Ellipsis` in the list to mean "zero or more
tokens here" to allow matching commands with gaps between matching parts.
For example, this would return True:
['foo', Ellipsis, 'bar'] in Command(['foo', 'monkey', 'stuff, 'bar'])
['foo', Ellipsis, 'bar'] in Command(['foo', 'bar'])
TODO(iannucci): when recipe engine is in python3, update this to specify `...`
def __contains__(self, item):
# Get a function that can be used for matching against an element
# Command's elements will always be strings, so we'll only try to match
# against strings or regexes
def get_matcher(obj):
if isinstance(obj, basestring):
return lambda other: obj == other
if isinstance(obj, re._pattern_type):
if obj is Ellipsis:
return Ellipsis
return None
if isinstance(item, Iterable) and not isinstance(item, basestring):
# Empty iterable is trivially contained
if not item:
return True
matchers = [get_matcher(e) for e in item]
matchers = [get_matcher(item)]
# If None is present in matchers, then that means item is/contains an object
# of a type that we won't use for matching
if any(m is None for m in matchers):
return False
# Compress multiple runs of Ellipsis
compressed_matchers = matchers[:1]
for matcher in matchers[1:]:
if matcher is Ellipsis and compressed_matchers[-1] is Ellipsis:
matchers = compressed_matchers
# Now trim Ellipsis from the beginning and end.
if matchers[:1] == [Ellipsis]:
matchers = matchers[1:]
if matchers[-1:] == [Ellipsis]:
matchers = matchers[:-1]
# At this point, matchers is a list of functions that we can apply against
# the elements of each subsequence in the list; if each matcher matches the
# corresponding element of the subsequence then we say that the sequence of
# strings/regexes is contained in the command
# Ellipsis have a minimum width of 0, everything else has a match size of
# 1 slot. Do a pass over matchers to calculate the number of slots required
# to match `matchers[i:]`.
min_slots_count = 0
min_slots = [None] * len(matchers)
for i, matcher in enumerate(reversed(matchers)):
if matcher is not Ellipsis:
min_slots_count += 1
min_slots[len(min_slots)-1-i] = min_slots_count
# If matchers looked like ['a', 'b', ..., 'c'], min_slots now looks like:
# [3, 2, 1, 1]
def _matches_seq(matchers_offset, self_offset):
max_slot = len(self) - min_slots[matchers_offset]
if max_slot < self_offset:
return False
for self_idx in xrange(self_offset, max_slot + 1):
num_matched = 0
for matchers_idx in xrange(matchers_offset, len(matchers)):
matcher = matchers[matchers_idx]
# If this is Ellipsis we consume it, and try matching the rest of the
# matchers against the rest of the sequence at every offset.
if matcher is Ellipsis:
for start_idx in xrange(self_offset+num_matched, len(self)):
if _cached_matches_seq(matchers_idx+1, start_idx):
return True
return False
if not matcher(self[self_idx + num_matched]):
num_matched += 1
return True
return False
# Since we have Ellipsis which can match any number of positions, including
# zero, we memoize _matches_seq to avoid doing duplicate checks. This caps
# the runtime of this matcher at O(len(matchers) * len(self)); Otherwise
# this would be quadratic on self.
no_entry = object()
cache = {}
def _cached_matches_seq(matchers_offset, self_offset):
key = (matchers_offset, self_offset)
ret = cache.get(key, no_entry)
if ret is not no_entry:
return ret
ret = _matches_seq(matchers_offset, self_offset)
cache[key] = ret
return ret
return _cached_matches_seq(0, 0)
class Step(object):
"""The representation of a step provided to post-process hooks.
A `Step` has fields for all of the details of a step that would be recorded
into the JSON expectation file for this test. Fields set to their default
values will not appear in the expectation file for the test. The defaults for
each field simplify post-processing hooks by allowing the fields to be
accessed without having to specify a default value.
See field definitions and comments for descriptions of the field meanings and
default values.
# **************************** Expectation fields ****************************
# These fields appear directly in the expectations file for a test.
# TODO(iannucci) Use buildbucket step names here, e.g. 'parent|child|leaf'
# instead of buildbot style 'parent.child.leaf' or make tuple
# The name of the step as a string
name = attr.ib()
# The step's command as a sequence of strings
# When initialized in from_step_dict, the sequence will be an instance of
# Command, which supports an enhanced contains check that enables concise
# subsequence and regex checking.
# Implementation note: cmd still appears in expectation files when its empty,
# so distiniguish between an empty cmd list and a cmd that has been filtered
# while still allowing duck-typing a default of () is used which is not equal
# to an empty list but still supports sequence operations
cmd = attr.ib(default=())
# The working directory that the step is executed under as a string, in terms
# of a placeholder e.g. RECIPE_REPO[recipe_engine]
# An empty string is equivalent to start_dir
cwd = attr.ib(default='')
# The resource cost of this Step. Will be None for no-command steps.
cost = attr.ib(default=ResourceCost())
# See //recipe_modules/context/ for information on the precise meaning
# of env, env_prefixes and env_suffixes.
# env will be the env value for the step, a dictionary mapping strings
# containing the environment variable names to strings containing the
# environment variable value.
env = attr.ib(factory=dict)
# env_prefixes and env_suffixes will be the env prefixes and suffixes for the
# step, dictionaries mapping strings containing the environment variable names
# to lists containing strings to be prepended/addended to the environment
# variable.
env_prefixes = attr.ib(factory=dict)
env_suffixes = attr.ib(factory=dict)
# A bool indicating whether a step can emit its own annotations.
allow_subannotations = attr.ib(default=False)
# Either None for no timeout or a numeric type containing the number of
# seconds the step must complete in.
timeout = attr.ib(default=None)
# Mapping of LUCI_CONTEXT section name to the current section value.
luci_context = attr.ib(factory=dict)
# A bool indicating the step is an infrastructure step that should raise
# InfraFailure instead of StepFailure if the step finishes with an exit code
# that is not allowed.
infra_step = attr.ib(default=False)
# String containing the content of the step's stdin if the step's stdin was
# redirected with a PlaceHolder.
stdin = attr.ib(default='')
# ***************************** Annotation fields ****************************
# These fields appear in annotations in the ~followup_annotations field in the
# expectations file for the test
# The nest level of the step: 0 is a top-level step.
# TODO(iannucci) Remove this
nest_level = attr.ib(default=0)
# A string containing the step's step text.
step_text = attr.ib(default='')
# A string containing the step's step summary text.
step_summary_text = attr.ib(default='')
# A dictionary containing the step's logs, mapping strings containing the log
# name to strings containing the full content of the log (the lines of the
# logs in the StepPresentation joined with '\n').
logs = attr.ib(factory=OrderedDict)
# A dictionary containing the step's links, mapping strings containing the
# link name to strings containing the link URL.
links = attr.ib(factory=OrderedDict)
# A dictionary containing the build properties set by the step, mapping
# strings containing the property name to json-ish objects containing the
# value of the property.
output_properties = attr.ib(factory=OrderedDict)
# A string containing the resulting status of the step, one of: 'SUCCESS',
status = attr.ib(default='SUCCESS',
# Arbitrary lines that appear in the annotations.
# The presence of these annotations is an implementation detail and likely to
# change in the future, so tests should avoid operating on this field except
# to set it to default to filter them out.
_raw_annotations = attr.ib(default=[])
def from_step_dict(cls, step_dict):
"""Create a `Step` from a step dictionary.
* step_dict - Dictionary containing the data to be written out to the
expectation file for the step. All keys in the dictionary must match
the name of one of the fields of `Step`.
A `Step` object where for each item in `step_dict`, the field whose name
matches the item's key is set to the item's value.
if 'name' not in step_dict:
raise ValueError("step dict must have 'name' key, step dict keys: %r"
% sorted(step_dict.iterkeys()))
if 'cmd' in step_dict or 'cost' in step_dict:
step_dict = step_dict.copy()
if 'cmd' in step_dict:
step_dict['cmd'] = Command(step_dict['cmd'])
if 'cost' in step_dict and step_dict['cost'] is not None:
step_dict['cost'] = ResourceCost(**step_dict['cost'])
return cls(**step_dict)
def _as_dict(self):
return attr.asdict(self, recurse=False)
def to_step_dict(self):
step_dict = {k: v for k, v in self._as_dict().iteritems()
if k == 'name' or v != PROTOTYPE_STEP[k]}
if step_dict.get('cmd', None) is not None:
step_dict['cmd'] = list(step_dict['cmd'])
if step_dict.get('cost', None) is not None:
cost = step_dict['cost']
step_dict['cost'] = attr.asdict(cost)
for k in step_dict.keys():
if k.startswith('_'):
step_dict[k[1:]] = step_dict.pop(k)
return step_dict
PROTOTYPE_STEP = Step('')._as_dict()