Source code for fastr.core.target

# Copyright 2011-2014 Biomedical Imaging Group Rotterdam, Departments of
# Medical Informatics and Radiology, Erasmus MC, Rotterdam, The Netherlands
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

"""
The module containing the classes describing the targets.
"""

from abc import ABCMeta, abstractmethod
from collections import deque, namedtuple, Sequence
import datetime
import platform
import psutil
import time
import threading
import shellescape
import subprocess

import fastr
from fastr.core.baseplugin import Plugin
from fastr.core.pluginmanager import PluginSubManager
from fastr import exceptions

SystemUsageInfo = namedtuple('SystemUsageInfo', ['timestamp',
                                                 'cpu_percent',
                                                 'vmem',
                                                 'rmem',
                                                 'read_bytes',
                                                 'write_bytes'])


[docs]class ProcessUsageCollection(Sequence): # It has to be defined in module for pickling purposes usage_type = SystemUsageInfo
[docs] def __init__(self): self.seconds_info = deque() self.minutes_info = []
[docs] def __len__(self): return len(self.seconds_info) + len(self.minutes_info)
[docs] def __getitem__(self, item): # First look in minutes, then in seconds if item < len(self.minutes_info): return self.minutes_info[item]._asdict() else: return self.seconds_info[item - len(self.minutes_info)]._asdict()
[docs] def append(self, value): if not isinstance(value, self.usage_type): raise ValueError('Cannot add a non {}.usage_type'.format(type(self).__name__)) self.seconds_info.append(value) if len(self.seconds_info) >= 120: self.aggregate(60)
[docs] def aggregate(self, number_of_points): oldest_data = [self.seconds_info.popleft() for _ in range(number_of_points)] timestamp = oldest_data[-1].timestamp cpu_percent = sum(x.cpu_percent for x in oldest_data) / len(oldest_data) vmem = max(x.vmem for x in oldest_data) rmem = max(x.rmem for x in oldest_data) read_bytes = oldest_data[-1].read_bytes write_bytes = oldest_data[-1].write_bytes self.minutes_info.append(self.usage_type(timestamp=timestamp, cpu_percent=cpu_percent, vmem=vmem, rmem=rmem, read_bytes=read_bytes, write_bytes=write_bytes))
[docs]class Target(Plugin): """ The abstract base class for all targets. Execution with a target should follow the following pattern: >>> with Target() as target: ... target.run_commmand(['sleep', '10']) The Target context operator will set the correct paths/initialization. Within the context command can be ran and when leaving the context the target reverts the state before. """ __metaclass__ = ABCMeta # Monitor interval for profiling _MONITOR_INTERVAL = 1.0
[docs] def __enter__(self): """ Set the environment in such a way that the target will be on the path. """ return self
[docs] def __exit__(self, exc_type, exc_value, traceback): """ Cleanup the environment where needed """
[docs] @abstractmethod def run_command(self, command): pass
[docs] @classmethod def test(cls): """ Test the plugin, interfaces do not need to be tested on import """ pass
[docs]class SubprocessBasedTarget(Target): """ Abstract based class for targets which call the target via a subprocess. Supplies a call_subprocess which executes the command and profiles the resulting subprocess. """
[docs] def call_subprocess(self, command): """ Call a subprocess with logging/timing/profiling :param list command: the command to execute :return: execution info :rtype: dict """ sysuse = ProcessUsageCollection() start_time = time.time() fastr.log.info('Calling command arguments: {}'.format(command)) printable_command = [] for item in command: printable_command.append(shellescape.quote(item)) fastr.log.info('Calling command: "{}"'.format(' '.join(printable_command))) try: process = subprocess.Popen(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, universal_newlines=True) except OSError as exception: if exception.errno == 2: raise exceptions.FastrExecutableNotFoundError(command[0]) elif exception.errno == 13: # Permission denied raise exceptions.FastrNotExecutableError('Cannot execute {}, permission denied!'.format(command[0])) else: raise exception monitor_thread = threading.Thread(target=self.monitor_process, name='SubprocessMonitor', args=(process, sysuse)) monitor_thread.daemon = True # Make sure this Thread does not block exiting the script monitor_thread.start() stdout, stderr = process.communicate() return_code = process.poll() end_time = time.time() if monitor_thread.is_alive(): monitor_thread.join(2 * self._MONITOR_INTERVAL) if monitor_thread.is_alive(): fastr.log.warning('Ignoring unresponsive monitor thread!') return {'returncode': return_code, 'stdout': stdout, 'stderr': stderr, 'command': command, 'resource_usage': list(sysuse), 'time_elapsed': end_time - start_time}
[docs] def monitor_process(self, process, resources): """ Monitor a process and profile the cpu, memory and io use. Register the resource use every _MONITOR_INTERVAL seconds. :param subproces.Popen process: process to monitor :param ProcessUsageCollection resources: list to append measurements to """ psproc = psutil.Process(process.pid) current_platform = platform.system().lower() # Loop initialization psproc.cpu_percent() # Get rid of meaningless 0.0 at start last_timestamp = datetime.datetime.utcnow() while process.poll() is None: try: # The sleep duration is adapted to loop duration so aggregation will not cause # extended intervals sleep_duration = self._MONITOR_INTERVAL - (datetime.datetime.utcnow() - last_timestamp).total_seconds() sleep_duration = 0.0 if sleep_duration < 0.0 else sleep_duration time.sleep(sleep_duration) # Get process usage information memory_info = psproc.memory_info() if current_platform == 'darwin': io_read = None io_write = None else: try: io_info = psproc.io_counters() io_read = io_info.read_bytes io_write = io_info.write_bytes except psutil.AccessDenied: io_read = None io_write = None last_timestamp = datetime.datetime.utcnow() usage = resources.usage_type(timestamp=last_timestamp.isoformat(), cpu_percent=psproc.cpu_percent(), vmem=memory_info.vms, rmem=memory_info.rss, read_bytes=io_read, write_bytes=io_write) resources.append(usage) except psutil.Error: # If the error occured because during the interval of meassuring the CPU use # the process stopped, we do not mind if process.poll() is None: raise
[docs]class TargetManager(PluginSubManager): """ Container holding all the ExecutionPlugins known to the Fastr system """
[docs] def __init__(self): """ Initialize a ExecutionPluginManager and load plugins. :param path: path to search for plugins :param recursive: flag for searching recursively :return: newly created ExecutionPluginManager """ super(TargetManager, self).__init__(parent=fastr.plugin_manager, plugin_class=Target)