Python WorkUnit.start方法代码示例

# 需要导入模块: from pants.base.workunit import WorkUnit [as 别名]
# 或者: from pants.base.workunit.WorkUnit import start [as 别名]
  def new_workunit_under_parent(self, name, parent, labels=None, cmd='', log_config=None):
    """Creates a (hierarchical) subunit of work for the purpose of timing and reporting.

    - name: A short name for this work. E.g., 'resolve', 'compile', 'scala', 'zinc'.
    - parent: The new workunit is created under this parent.
    - labels: An optional iterable of labels. The reporters can use this to decide how to
              display information about this work.
    - cmd: An optional longer string representing this work.
           E.g., the cmd line of a compiler invocation.

    Task code should not typically call this directly.
    """
    workunit = WorkUnit(run_info_dir=self.run_info_dir, parent=parent, name=name, labels=labels,
                        cmd=cmd, log_config=log_config)
    workunit.start()

    outcome = WorkUnit.FAILURE  # Default to failure we will override if we get success/abort.
    try:
      self.report.start_workunit(workunit)
      yield workunit
    except KeyboardInterrupt:
      outcome = WorkUnit.ABORTED
      self._aborted = True
      raise
    else:
      outcome = WorkUnit.SUCCESS
    finally:
      workunit.set_outcome(outcome)
      self.end_workunit(workunit)

# 需要导入模块: from pants.base.workunit import WorkUnit [as 别名]
# 或者: from pants.base.workunit.WorkUnit import start [as 别名]
  def new_workunit_under_parent(self, name, parent, labels=None, cmd=''):
    """Creates a (hierarchical) subunit of work for the purpose of timing and reporting.

    - name: A short name for this work. E.g., 'resolve', 'compile', 'scala', 'zinc'.
    - parent: The new workunit is created under this parent.
    - labels: An optional iterable of labels. The reporters can use this to decide how to
              display information about this work.
    - cmd: An optional longer string representing this work.
           E.g., the cmd line of a compiler invocation.

    Task code should not typically call this directly.
    """
    workunit = WorkUnit(run_tracker=self, parent=parent, name=name, labels=labels, cmd=cmd)
    workunit.start()
    try:
      self.report.start_workunit(workunit)
      yield workunit
    except KeyboardInterrupt:
      workunit.set_outcome(WorkUnit.ABORTED)
      self._aborted = True
      raise
    except:
      workunit.set_outcome(WorkUnit.FAILURE)
      raise
    else:
      workunit.set_outcome(WorkUnit.SUCCESS)
    finally:
      self.report.end_workunit(workunit)
      workunit.end()

# 需要导入模块: from pants.base.workunit import WorkUnit [as 别名]
# 或者: from pants.base.workunit.WorkUnit import start [as 别名]
class RunTracker(Subsystem):
  """Tracks and times the execution of a pants run.

  Also manages background work.

  Use like this:

  run_tracker.start()
  with run_tracker.new_workunit('compile'):
    with run_tracker.new_workunit('java'):
      ...
    with run_tracker.new_workunit('scala'):
      ...
  run_tracker.close()

  Can track execution against multiple 'roots', e.g., one for the main thread and another for
  background threads.
  """
  options_scope = 'run-tracker'

  # The name of the tracking root for the main thread (and the foreground worker threads).
  DEFAULT_ROOT_NAME = 'main'

  # The name of the tracking root for the background worker threads.
  BACKGROUND_ROOT_NAME = 'background'

  @classmethod
  def subsystem_dependencies(cls):
    return (StatsDBFactory,)

  @classmethod
  def register_options(cls, register):
    register('--stats-upload-url', advanced=True, default=None,
             help='Upload stats to this URL on run completion.')
    register('--stats-upload-timeout', advanced=True, type=int, default=2,
             help='Wait at most this many seconds for the stats upload to complete.')
    register('--num-foreground-workers', advanced=True, type=int, default=8,
             help='Number of threads for foreground work.')
    register('--num-background-workers', advanced=True, type=int, default=8,
             help='Number of threads for background work.')

  def __init__(self, *args, **kwargs):
    super(RunTracker, self).__init__(*args, **kwargs)
    run_timestamp = time.time()
    cmd_line = ' '.join(['pants'] + sys.argv[1:])

    # run_id is safe for use in paths.
    millis = int((run_timestamp * 1000) % 1000)
    run_id = 'pants_run_{}_{}_{}'.format(
               time.strftime('%Y_%m_%d_%H_%M_%S', time.localtime(run_timestamp)), millis,
               uuid.uuid4().hex)

    info_dir = os.path.join(self.get_options().pants_workdir, self.options_scope)
    self.run_info_dir = os.path.join(info_dir, run_id)
    self.run_info = RunInfo(os.path.join(self.run_info_dir, 'info'))
    self.run_info.add_basic_info(run_id, run_timestamp)
    self.run_info.add_info('cmd_line', cmd_line)

    # Create a 'latest' symlink, after we add_infos, so we're guaranteed that the file exists.
    link_to_latest = os.path.join(os.path.dirname(self.run_info_dir), 'latest')

    relative_symlink(self.run_info_dir, link_to_latest)

    # Time spent in a workunit, including its children.
    self.cumulative_timings = AggregatedTimings(os.path.join(self.run_info_dir,
                                                             'cumulative_timings'))

    # Time spent in a workunit, not including its children.
    self.self_timings = AggregatedTimings(os.path.join(self.run_info_dir, 'self_timings'))

    # Hit/miss stats for the artifact cache.
    self.artifact_cache_stats = \
      ArtifactCacheStats(os.path.join(self.run_info_dir, 'artifact_cache_stats'))

    # Number of threads for foreground work.
    self._num_foreground_workers = self.get_options().num_foreground_workers

    # Number of threads for background work.
    self._num_background_workers = self.get_options().num_background_workers

    # We report to this Report.
    self.report = None

    # self._threadlocal.current_workunit contains the current workunit for the calling thread.
    # Note that multiple threads may share a name (e.g., all the threads in a pool).
    self._threadlocal = threading.local()

    # For main thread work. Created on start().
    self._main_root_workunit = None

    # For background work.  Created lazily if needed.
    self._background_worker_pool = None
    self._background_root_workunit = None

    # Trigger subproc pool init while our memory image is still clean (see SubprocPool docstring).
    SubprocPool.foreground()

    self._aborted = False

  def register_thread(self, parent_workunit):
#.........这里部分代码省略.........

# 需要导入模块: from pants.base.workunit import WorkUnit [as 别名]
# 或者: from pants.base.workunit.WorkUnit import start [as 别名]
class RunTracker(object):
  """Tracks and times the execution of a pants run.

  Also manages background work.

  Use like this:

  run_tracker.start()
  with run_tracker.new_workunit('compile'):
    with run_tracker.new_workunit('java'):
      ...
    with run_tracker.new_workunit('scala'):
      ...
  run_tracker.close()

  Can track execution against multiple 'roots', e.g., one for the main thread and another for
  background threads.
  """

  # The name of the tracking root for the main thread (and the foreground worker threads).
  DEFAULT_ROOT_NAME = 'main'

  # The name of the tracking root for the background worker threads.
  BACKGROUND_ROOT_NAME = 'background'

  @classmethod
  def from_config(cls, config):
    if not isinstance(config, Config):
      raise ValueError('Expected a Config object, given %s of type %s' % (config, type(config)))
    info_dir = RunInfo.dir(config)
    stats_upload_url = config.getdefault('stats_upload_url', default=None)
    num_foreground_workers = config.getdefault('num_foreground_workers', default=8)
    num_background_workers = config.getdefault('num_background_workers', default=8)
    return cls(info_dir,
               stats_upload_url=stats_upload_url,
               num_foreground_workers=num_foreground_workers,
               num_background_workers=num_background_workers)

  def __init__(self,
               info_dir,
               stats_upload_url=None,
               num_foreground_workers=8,
               num_background_workers=8):
    self.run_timestamp = time.time()  # A double, so we get subsecond precision for ids.
    cmd_line = ' '.join(['./pants'] + sys.argv[1:])

    # run_id is safe for use in paths.
    millis = (self.run_timestamp * 1000) % 1000
    run_id = 'pants_run_%s_%d' % \
             (time.strftime('%Y_%m_%d_%H_%M_%S', time.localtime(self.run_timestamp)), millis)

    self.info_dir = os.path.join(info_dir, run_id)
    self.run_info = RunInfo(os.path.join(self.info_dir, 'info'))
    self.run_info.add_basic_info(run_id, self.run_timestamp)
    self.run_info.add_info('cmd_line', cmd_line)
    self.stats_url = stats_upload_url

    # Create a 'latest' symlink, after we add_infos, so we're guaranteed that the file exists.
    link_to_latest = os.path.join(os.path.dirname(self.info_dir), 'latest')
    if os.path.exists(link_to_latest):
      os.unlink(link_to_latest)
    os.symlink(self.info_dir, link_to_latest)

    # Time spent in a workunit, including its children.
    self.cumulative_timings = AggregatedTimings(os.path.join(self.info_dir, 'cumulative_timings'))

    # Time spent in a workunit, not including its children.
    self.self_timings = AggregatedTimings(os.path.join(self.info_dir, 'self_timings'))

    # Hit/miss stats for the artifact cache.
    self.artifact_cache_stats = \
      ArtifactCacheStats(os.path.join(self.info_dir, 'artifact_cache_stats'))

    # Number of threads for foreground work.
    self._num_foreground_workers = num_foreground_workers

    # Number of threads for background work.
    self._num_background_workers = num_background_workers

    # We report to this Report.
    self.report = None

    # self._threadlocal.current_workunit contains the current workunit for the calling thread.
    # Note that multiple threads may share a name (e.g., all the threads in a pool).
    self._threadlocal = threading.local()

    # For main thread work. Created on start().
    self._main_root_workunit = None

    # For concurrent foreground work.  Created lazily if needed.
    # Associated with the main thread's root workunit.
    self._foreground_worker_pool = None

    # For background work.  Created lazily if needed.
    self._background_worker_pool = None
    self._background_root_workunit = None

    self._aborted = False

  def register_thread(self, parent_workunit):
#.........这里部分代码省略.........

# 需要导入模块: from pants.base.workunit import WorkUnit [as 别名]
# 或者: from pants.base.workunit.WorkUnit import start [as 别名]
class RunTracker(Subsystem):
  """Tracks and times the execution of a pants run.

  Also manages background work.

  Use like this:

  run_tracker.start()
  with run_tracker.new_workunit('compile'):
    with run_tracker.new_workunit('java'):
      ...
    with run_tracker.new_workunit('scala'):
      ...
  run_tracker.close()

  Can track execution against multiple 'roots', e.g., one for the main thread and another for
  background threads.

  :API: public
  """
  options_scope = 'run-tracker'

  # The name of the tracking root for the main thread (and the foreground worker threads).
  DEFAULT_ROOT_NAME = 'main'

  # The name of the tracking root for the background worker threads.
  BACKGROUND_ROOT_NAME = 'background'

  @classmethod
  def subsystem_dependencies(cls):
    return (StatsDBFactory,)

  @classmethod
  def register_options(cls, register):
    register('--stats-upload-url', advanced=True, default=None,
             help='Upload stats to this URL on run completion.')
    register('--stats-upload-timeout', advanced=True, type=int, default=2,
             help='Wait at most this many seconds for the stats upload to complete.')
    register('--num-foreground-workers', advanced=True, type=int,
             default=multiprocessing.cpu_count(),
             help='Number of threads for foreground work.')
    register('--num-background-workers', advanced=True, type=int,
             default=multiprocessing.cpu_count(),
             help='Number of threads for background work.')
    register('--stats-local-json-file', advanced=True, default=None,
             help='Write stats to this local json file on run completion.')

  def __init__(self, *args, **kwargs):
    """
    :API: public
    """
    super(RunTracker, self).__init__(*args, **kwargs)
    self._run_timestamp = time.time()
    self._cmd_line = ' '.join(['pants'] + sys.argv[1:])
    self._sorted_goal_infos = tuple()

    # Initialized in `initialize()`.
    self.run_info_dir = None
    self.run_info = None
    self.cumulative_timings = None
    self.self_timings = None
    self.artifact_cache_stats = None
    self.pantsd_stats = None

    # Initialized in `start()`.
    self.report = None
    self._main_root_workunit = None

    # A lock to ensure that adding to stats at the end of a workunit
    # operates thread-safely.
    self._stats_lock = threading.Lock()

    # Log of success/failure/aborted for each workunit.
    self.outcomes = {}

    # Number of threads for foreground work.
    self._num_foreground_workers = self.get_options().num_foreground_workers

    # Number of threads for background work.
    self._num_background_workers = self.get_options().num_background_workers

    # self._threadlocal.current_workunit contains the current workunit for the calling thread.
    # Note that multiple threads may share a name (e.g., all the threads in a pool).
    self._threadlocal = threading.local()

    # For background work.  Created lazily if needed.
    self._background_worker_pool = None
    self._background_root_workunit = None

    # Trigger subproc pool init while our memory image is still clean (see SubprocPool docstring).
    SubprocPool.set_num_processes(self._num_foreground_workers)
    SubprocPool.foreground()

    self._aborted = False

    # Data will be organized first by target and then scope.
    # Eg:
    # {
    #   'target/address:name': {
    #     'running_scope': {
#.........这里部分代码省略.........

# 需要导入模块: from pants.base.workunit import WorkUnit [as 别名]
# 或者: from pants.base.workunit.WorkUnit import start [as 别名]
class RunTracker(Subsystem):
  """Tracks and times the execution of a pants run.

  Also manages background work.

  Use like this:

  run_tracker.start()
  with run_tracker.new_workunit('compile'):
    with run_tracker.new_workunit('java'):
      ...
    with run_tracker.new_workunit('scala'):
      ...
  run_tracker.close()

  Can track execution against multiple 'roots', e.g., one for the main thread and another for
  background threads.

  :API: public
  """
  options_scope = 'run-tracker'

  # The name of the tracking root for the main thread (and the foreground worker threads).
  DEFAULT_ROOT_NAME = 'main'

  # The name of the tracking root for the background worker threads.
  BACKGROUND_ROOT_NAME = 'background'

  @classmethod
  def subsystem_dependencies(cls):
    return super(RunTracker, cls).subsystem_dependencies() + (Cookies,)

  @classmethod
  def register_options(cls, register):
    register('--stats-upload-urls', advanced=True, type=dict, default={},
             help='Upload stats to these URLs on run completion.  Value is a map from URL to the '
                  'name of the auth provider the user must auth against in order to upload stats '
                  'to that URL, or None/empty string if no auth is required.  Currently the '
                  'auth provider name is only used to provide a more helpful error message.')
    register('--stats-upload-timeout', advanced=True, type=int, default=2,
             help='Wait at most this many seconds for the stats upload to complete.')
    register('--stats-version', advanced=True, type=int, default=1, choices=[1, 2],
             help='Format of stats JSON for uploads and local json file.')
    register('--num-foreground-workers', advanced=True, type=int,
             default=multiprocessing.cpu_count(),
             help='Number of threads for foreground work.')
    register('--num-background-workers', advanced=True, type=int,
             default=multiprocessing.cpu_count(),
             help='Number of threads for background work.')
    register('--stats-local-json-file', advanced=True, default=None,
             help='Write stats to this local json file on run completion.')
    register('--stats-option-scopes-to-record', advanced=True, type=list, default=[],
             help="Option scopes to record in stats on run completion. "
                  "Options may be selected by joining the scope and the option with a ^ character, "
                  "i.e. to get option enable_pantsd in the GLOBAL scope, you'd pass "
                  "GLOBAL^enable_pantsd")

  def __init__(self, *args, **kwargs):
    """
    :API: public
    """
    super(RunTracker, self).__init__(*args, **kwargs)
    self._run_timestamp = time.time()
    self._cmd_line = ' '.join(['pants'] + sys.argv[1:])
    self._sorted_goal_infos = tuple()

    # Initialized in `initialize()`.
    self.run_info_dir = None
    self.run_info = None
    self.cumulative_timings = None
    self.self_timings = None
    self.artifact_cache_stats = None
    self.pantsd_stats = None

    # Initialized in `start()`.
    self.report = None
    self.json_reporter = None
    self._main_root_workunit = None
    self._all_options = None

    # A lock to ensure that adding to stats at the end of a workunit
    # operates thread-safely.
    self._stats_lock = threading.Lock()

    # Log of success/failure/aborted for each workunit.
    self.outcomes = {}

    # Number of threads for foreground work.
    self._num_foreground_workers = self.get_options().num_foreground_workers

    # Number of threads for background work.
    self._num_background_workers = self.get_options().num_background_workers

    # self._threadlocal.current_workunit contains the current workunit for the calling thread.
    # Note that multiple threads may share a name (e.g., all the threads in a pool).
    self._threadlocal = threading.local()

    # A logger facade that logs into this RunTracker.
    self._logger = RunTrackerLogger(self)

#.........这里部分代码省略.........

# 需要导入模块: from pants.base.workunit import WorkUnit [as 别名]
# 或者: from pants.base.workunit.WorkUnit import start [as 别名]
class RunTracker(Subsystem):
  """Tracks and times the execution of a pants run.

  Also manages background work.

  Use like this:

  run_tracker.start()
  with run_tracker.new_workunit('compile'):
    with run_tracker.new_workunit('java'):
      ...
    with run_tracker.new_workunit('scala'):
      ...
  run_tracker.close()

  Can track execution against multiple 'roots', e.g., one for the main thread and another for
  background threads.
  """
  @classmethod
  def scope_qualifier(cls):
    return 'run-tracker'

  # The name of the tracking root for the main thread (and the foreground worker threads).
  DEFAULT_ROOT_NAME = 'main'

  # The name of the tracking root for the background worker threads.
  BACKGROUND_ROOT_NAME = 'background'

  @classmethod
  def register_options(cls, register):
    register('--stats-upload-url', advanced=True, default=None,
             help='Upload stats to this URL on run completion.')
    register('--stats-upload-timeout', advanced=True, type=int, default=2,
             help='Wait at most this many seconds for the stats upload to complete.')
    register('--num-foreground-workers', advanced=True, type=int, default=8,
             help='Number of threads for foreground work.')
    register('--num-background-workers', advanced=True, type=int, default=8,
             help='Number of threads for background work.')

  def __init__(self, *args, **kwargs):
    super(RunTracker, self).__init__(*args, **kwargs)
    self.run_timestamp = time.time()  # A double, so we get subsecond precision for ids.
    cmd_line = ' '.join(['./pants'] + sys.argv[1:])

    # run_id is safe for use in paths.
    millis = int((self.run_timestamp * 1000) % 1000)
    run_id = 'pants_run_{}_{}'.format(
               time.strftime('%Y_%m_%d_%H_%M_%S', time.localtime(self.run_timestamp)), millis)

    info_dir = os.path.join(self.get_options().pants_workdir, self.options_scope)
    self.run_info_dir = os.path.join(info_dir, run_id)
    self.run_info = RunInfo(os.path.join(self.run_info_dir, 'info'))
    self.run_info.add_basic_info(run_id, self.run_timestamp)
    self.run_info.add_info('cmd_line', cmd_line)
    self.stats_url = self.get_options().stats_upload_url
    self.stats_timeout = self.get_options().stats_upload_timeout

    # Create a 'latest' symlink, after we add_infos, so we're guaranteed that the file exists.
    link_to_latest = os.path.join(os.path.dirname(self.run_info_dir), 'latest')

    try:
      if os.path.lexists(link_to_latest):
        os.unlink(link_to_latest)
      os.symlink(self.run_info_dir, link_to_latest)
    except OSError as e:
      # Another run may beat us to deletion or creation.
      if not (e.errno == errno.EEXIST or e.errno == errno.ENOENT):
        raise

    # Time spent in a workunit, including its children.
    self.cumulative_timings = AggregatedTimings(os.path.join(self.run_info_dir,
                                                             'cumulative_timings'))

    # Time spent in a workunit, not including its children.
    self.self_timings = AggregatedTimings(os.path.join(self.run_info_dir, 'self_timings'))

    # Hit/miss stats for the artifact cache.
    self.artifact_cache_stats = \
      ArtifactCacheStats(os.path.join(self.run_info_dir, 'artifact_cache_stats'))

    # Number of threads for foreground work.
    self._num_foreground_workers = self.get_options().num_foreground_workers

    # Number of threads for background work.
    self._num_background_workers = self.get_options().num_background_workers

    # We report to this Report.
    self.report = None

    # self._threadlocal.current_workunit contains the current workunit for the calling thread.
    # Note that multiple threads may share a name (e.g., all the threads in a pool).
    self._threadlocal = threading.local()

    # For main thread work. Created on start().
    self._main_root_workunit = None

    # For background work.  Created lazily if needed.
    self._background_worker_pool = None
    self._background_root_workunit = None

#.........这里部分代码省略.........