Python SubprocPool.foreground方法代码示例

# 需要导入模块: from pants.base.worker_pool import SubprocPool [as 别名]
# 或者: from pants.base.worker_pool.SubprocPool import foreground [as 别名]
  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:])

    # 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': {
    #       'run_duration': 356.09
    #     },
    #     'GLOBAL': {
    #       'target_type': 'pants.test'
    #     }
    #   }
    # }
    self._target_to_data = {}

# 需要导入模块: from pants.base.worker_pool import SubprocPool [as 别名]
# 或者: from pants.base.worker_pool.SubprocPool import foreground [as 别名]
  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.set_num_processes(self._num_foreground_workers)
    SubprocPool.foreground()

    self._aborted = False

# 需要导入模块: from pants.base.worker_pool import SubprocPool [as 别名]
# 或者: from pants.base.worker_pool.SubprocPool import foreground [as 别名]
  def subproc_map(self, f, items):
    """Map function `f` over `items` in subprocesses and return the result.

      :param f: A multiproc-friendly (importable) work function.
      :param args: A iterable of pickleable arguments to f.
    """
    try:
      # Pool.map (and async_map().get() w/o timeout) can miss SIGINT.
      # See: http://stackoverflow.com/a/1408476, http://bugs.python.org/issue8844
      # Instead, we map_async(...), wait *with a timeout* until ready, then .get()
      # NB: in 2.x, wait() with timeout wakes up often to check, burning CPU. Oh well.
      res = SubprocPool.foreground().map_async(f, items)
      while not res.ready():
        res.wait(60) # Repeatedly wait for up to a minute.
        if not res.ready():
          self.log.debug('subproc_map result still not ready...')
      return res.get()
    except KeyboardInterrupt:
      SubprocPool.shutdown(True)
      raise

# 需要导入模块: from pants.base.worker_pool import SubprocPool [as 别名]
# 或者: from pants.base.worker_pool.SubprocPool import foreground [as 别名]
  def __init__(self,
               info_dir,
               stats_upload_url=None,
               stats_upload_timeout=2,
               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.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 = stats_upload_url
    self.stats_timeout = 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 = 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

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

    self._aborted = False