# # Copyright (C) 2007-2016 CEA/DAM # Copyright (C) 2015-2017 Stephane Thiell # # This file is part of ClusterShell. # # ClusterShell is free software; you can redistribute it and/or # modify it under the terms of the GNU Lesser General Public # License as published by the Free Software Foundation; either # version 2.1 of the License, or (at your option) any later version. # # ClusterShell is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU # Lesser General Public License for more details. # # You should have received a copy of the GNU Lesser General Public # License along with ClusterShell; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA """ ClusterShell Task module. Simple example of use: >>> from ClusterShell.Task import task_self, NodeSet >>> >>> # get task associated with calling thread ... task = task_self() >>> >>> # add a command to execute on distant nodes ... task.shell("/bin/uname -r", nodes="tiger[1-30,35]") >>> >>> # run task in calling thread ... task.run() >>> >>> # get results ... for output, nodelist in task.iter_buffers(): ... print '%s: %s' % (NodeSet.fromlist(nodelist), output) ... """ from __future__ import print_function import logging from operator import itemgetter import os import socket import sys import threading from time import sleep import traceback try: basestring except NameError: # Python 3 compat basestring = str from ClusterShell.Defaults import config_paths, DEFAULTS from ClusterShell.Defaults import _local_workerclass, _distant_workerclass, _load_workerclass from ClusterShell.Engine.Engine import EngineAbortException from ClusterShell.Engine.Engine import EngineTimeoutException from ClusterShell.Engine.Engine import EngineAlreadyRunningError from ClusterShell.Engine.Engine import EngineTimer from ClusterShell.Engine.Factory import PreferredEngine from ClusterShell.Worker.EngineClient import EnginePort, EngineClientError from ClusterShell.Worker.Popen import WorkerPopen from ClusterShell.Worker.Tree import TreeWorker from ClusterShell.Worker.Worker import FANOUT_UNLIMITED from ClusterShell.Event import EventHandler from ClusterShell.MsgTree import MsgTree from ClusterShell.NodeSet import NodeSet from ClusterShell.Topology import TopologyParser, TopologyError from ClusterShell.Propagation import PropagationTreeRouter, PropagationChannel class TaskException(Exception): """Base task exception.""" class TaskError(TaskException): """Base task error exception.""" class TimeoutError(TaskError): """Raised when the task timed out.""" class AlreadyRunningError(TaskError): """Raised when trying to resume an already running task.""" class TaskMsgTreeError(TaskError): """Raised when trying to access disabled MsgTree.""" def _getshorthostname(): """Get short hostname (host name cut at the first dot)""" return socket.gethostname().split('.')[0] class Task(object): """ The Task class defines an essential ClusterShell object which aims to execute commands in parallel and easily get their results. More precisely, a Task object manages a coordinated (ie. with respect of its current parameters) collection of independent parallel Worker objects. See ClusterShell.Worker.Worker for further details on ClusterShell Workers. Always bound to a specific thread, a Task object acts like a "thread singleton". So most of the time, and even more for single-threaded applications, you can get the current task object with the following top-level Task module function: >>> task = task_self() However, if you want to create a task in a new thread, use: >>> task = Task() To create or get the instance of the task associated with the thread object thr (threading.Thread): >>> task = Task(thread=thr) To submit a command to execute locally within task, use: >>> task.shell("/bin/hostname") To submit a command to execute to some distant nodes in parallel, use: >>> task.shell("/bin/hostname", nodes="tiger[1-20]") The previous examples submit commands to execute but do not allow result interaction during their execution. For your program to interact during command execution, it has to define event handlers that will listen for local or remote events. These handlers are based on the EventHandler class, defined in ClusterShell.Event. The following example shows how to submit a command on a cluster with a registered event handler: >>> task.shell("uname -r", nodes="node[1-9]", handler=MyEventHandler()) Run task in its associated thread (will block only if the calling thread is the task associated thread): >>> task.resume() or: >>> task.run() You can also pass arguments to task.run() to schedule a command exactly like in task.shell(), and run it: >>> task.run("hostname", nodes="tiger[1-20]", handler=MyEventHandler()) A common need is to set a maximum delay for command execution, especially when the command time is not known. Doing this with ClusterShell Task is very straightforward. To limit the execution time on each node, use the timeout parameter of shell() or run() methods to set a delay in seconds, like: >>> task.run("check_network.sh", nodes="tiger[1-20]", timeout=30) You can then either use Task's iter_keys_timeout() method after execution to see on what nodes the command has timed out, or listen for ev_close() events in your event handler and check the timedout boolean. To get command result, you can either use Task's iter_buffers() method for standard output, iter_errors() for standard error after command execution (common output contents are automatically gathered), or you can listen for ev_read() events in your event handler and get live command output. To get command return codes, you can either use Task's iter_retcodes(), node_retcode() and max_retcode() methods after command execution, or listen for ev_hup() events in your event handler. """ # topology.conf file path list TOPOLOGY_CONFIGS = config_paths('topology.conf') _tasks = {} _taskid_max = 0 _task_lock = threading.Lock() class _SyncMsgHandler(EventHandler): """Special task control port event handler. When a message is received on the port, call appropriate task method.""" def __init__(self, task): EventHandler.__init__(self) self.task = task def ev_msg(self, port, msg): """Message received: call appropriate task method.""" # pull out function and its arguments from message func, (args, kwargs) = msg[0], msg[1:] # call task method func(self.task, *args, **kwargs) class tasksyncmethod(object): """Class encapsulating a function that checks if the calling task is running or is the current task, and allowing it to be used as a decorator making the wrapped task method thread-safe.""" def __call__(self, f): def taskfunc(*args, **kwargs): # pull out the class instance task, fargs = args[0], args[1:] # check if the calling task is the current thread task if task._is_task_self(): return f(task, *fargs, **kwargs) elif task._dispatch_port: # no, safely call the task method by message # through the task special dispatch port task._dispatch_port.msg_send((f, fargs, kwargs)) else: task.info("print_debug")(task, "%s: dropped call: %s" % \ (task, str(fargs))) # modify the decorator meta-data for pydoc # Note: should be later replaced by @wraps (functools) # as of Python 2.5 taskfunc.__name__ = f.__name__ taskfunc.__doc__ = f.__doc__ taskfunc.__dict__ = f.__dict__ taskfunc.__module__ = f.__module__ return taskfunc class _SuspendCondition(object): """Special class to manage task suspend condition.""" def __init__(self, lock=threading.RLock(), initial=0): self._cond = threading.Condition(lock) self.suspend_count = initial def atomic_inc(self): """Increase suspend count.""" self._cond.acquire() self.suspend_count += 1 self._cond.release() def atomic_dec(self): """Decrease suspend count.""" self._cond.acquire() self.suspend_count -= 1 self._cond.release() def wait_check(self, release_lock=None): """Wait for condition if needed.""" self._cond.acquire() try: if self.suspend_count > 0: if release_lock: release_lock.release() self._cond.wait() finally: self._cond.release() def notify_all(self): """Signal all threads waiting for condition.""" self._cond.acquire() try: self.suspend_count = min(self.suspend_count, 0) self._cond.notify_all() finally: self._cond.release() def __new__(cls, thread=None, defaults=None): """ For task bound to a specific thread, this class acts like a "thread singleton", so new style class is used and new object are only instantiated if needed. """ if thread: if thread not in cls._tasks: cls._tasks[thread] = object.__new__(cls) return cls._tasks[thread] return object.__new__(cls) def __init__(self, thread=None, defaults=None): """Initialize a Task, creating a new non-daemonic thread if needed.""" if not getattr(self, "_engine", None): # first time called self._default_lock = threading.Lock() if defaults is None: defaults = DEFAULTS self._default = defaults._task_default.copy() self._default.update( {"local_worker": _local_workerclass(defaults), "distant_worker": _distant_workerclass(defaults)}) self._info = defaults._task_info.copy() # use factory class PreferredEngine that gives the proper # engine instance self._engine = PreferredEngine(self.default("engine"), self._info) self.timeout = None # task synchronization objects self._run_lock = threading.Lock() # primitive lock self._suspend_lock = threading.RLock() # reentrant lock # both join and suspend conditions share the same underlying lock self._suspend_cond = Task._SuspendCondition(self._suspend_lock, 1) self._join_cond = threading.Condition(self._suspend_lock) self._suspended = False self._quit = False self._terminated = False # Default router self.topology = None self.router = None self.gateways = {} # dict of MsgTree by sname self._msgtrees = {} # dict of sources to return codes self._d_source_rc = {} # dict of return codes to sources self._d_rc_sources = {} # keep max rc self._max_rc = None # keep timeout'd sources self._timeout_sources = set() # allow no-op call to getters before resume() self._reset() # special engine port for task method dispatching self._dispatch_port = EnginePort(handler=Task._SyncMsgHandler(self), autoclose=True) self._engine.add(self._dispatch_port) # set taskid used as Thread name Task._task_lock.acquire() Task._taskid_max += 1 self._taskid = Task._taskid_max Task._task_lock.release() # create new thread if needed self._thread_foreign = bool(thread) if self._thread_foreign: self.thread = thread else: self.thread = thread = \ threading.Thread(None, Task._thread_start, "Task-%d" % self._taskid, args=(self,)) Task._tasks[thread] = self thread.start() def _is_task_self(self): """Private method used by the library to check if the task is task_self(), but do not create any task_self() instance.""" return self.thread == threading.current_thread() def default_excepthook(self, exc_type, exc_value, tb): """Default excepthook for a newly Task. When an exception is raised and uncaught on Task thread, excepthook is called, which is default_excepthook by default. Once excepthook overridden, you can still call default_excepthook if needed.""" print('Exception in thread %s:' % self.thread, file=sys.stderr) traceback.print_exception(exc_type, exc_value, tb, file=sys.stderr) _excepthook = default_excepthook def _getexcepthook(self): return self._excepthook def _setexcepthook(self, hook): self._excepthook = hook # If thread has not been created by us, install sys.excepthook which # might handle uncaught exception. if self._thread_foreign: sys.excepthook = self._excepthook # When an exception is raised and uncaught on Task's thread, # excepthook is called. You may want to override this three # arguments method (very similar of what you can do with # sys.excepthook).""" excepthook = property(_getexcepthook, _setexcepthook) def _thread_start(self): """Task-managed thread entry point""" while not self._quit: self._suspend_cond.wait_check() if self._quit: # may be set by abort() break try: self._resume() except: self.excepthook(*sys.exc_info()) self._quit = True self._terminate(kill=True) def _run(self, timeout): """Run task (always called from its self thread).""" # check if task is already running if self._run_lock.locked(): raise AlreadyRunningError("task is already running") # use with statement later try: self._run_lock.acquire() self._engine.run(timeout) finally: self._run_lock.release() def _default_tree_is_enabled(self): """Return whether default tree is enabled (load topology_file btw)""" if self.topology is None: for topology_file in self.TOPOLOGY_CONFIGS[::-1]: if os.path.exists(topology_file): self.load_topology(topology_file) break return (self.topology is not None) and self.default("auto_tree") def load_topology(self, topology_file): """Load propagation topology from provided file. On success, task.topology is set to a corresponding TopologyTree instance. On failure, task.topology is left untouched and a TopologyError exception is raised. """ self.topology = TopologyParser(topology_file).tree(_getshorthostname()) def _default_router(self, router=None): """ Helper to instantiate or bind a default PropagationTreeRouter for the task which can then be shared by multiple workers. Called by a TreeWorker when it is scheduled with this task. """ if router is None: if self.router is None: # Init router with the task's topology (e.g. root node) self.router = \ PropagationTreeRouter(str(self.topology.root.nodeset), self.topology) else: if self.router is not None: # Update default router if a different one is used by a worker. logger = logging.getLogger(__name__) logger.debug("_default_router: overriding previous default " \ "router %s with %s", self.router, router) self.router = router return self.router def default(self, default_key, def_val=None): """ Return per-task value for key from the "default" dictionary. See set_default() for a list of reserved task default_keys. """ self._default_lock.acquire() try: return self._default.get(default_key, def_val) finally: self._default_lock.release() def set_default(self, default_key, value): """ Set task value for specified key in the dictionary "default". Users may store their own task-specific key, value pairs using this method and retrieve them with default(). Task default_keys are: - "stderr": Boolean value indicating whether to enable stdout/stderr separation when using task.shell(), if not specified explicitly (default: False). - "stdin": Boolean value indicating whether to enable stdin when using task.shell(), if not explicitly specified (default: True) - "stdout_msgtree": Whether to instantiate standard output MsgTree for automatic internal gathering of result messages coming from Workers (default: True). - "stderr_msgtree": Same for stderr (default: True). - "engine": Used to specify an underlying Engine explicitly (default: "auto"). - "port_qlimit": Size of port messages queue (default: 32). - "worker": Worker-based class used when spawning workers through shell()/run(). Threading considerations: Unlike set_info(), when called from the task's thread or not, set_default() immediately updates the underlying dictionary in a thread-safe manner. This method doesn't wake up the engine when called. """ self._default_lock.acquire() try: self._default[default_key] = value if default_key == 'local_workername': self._default['local_worker'] = _load_workerclass(value) elif default_key == 'distant_workername': self._default['distant_worker'] = _load_workerclass(value) finally: self._default_lock.release() def info(self, info_key, def_val=None): """ Return per-task information. See set_info() for a list of reserved task info_keys. """ return self._info.get(info_key, def_val) @tasksyncmethod() def set_info(self, info_key, value): """ Set task value for a specific key information. Key, value pairs can be passed to the engine and/or workers. Users may store their own task-specific info key, value pairs using this method and retrieve them with info(). The following example changes the fanout value to 128: >>> task.set_info('fanout', 128) The following example enables debug messages: >>> task.set_info('debug', True) Task info_keys are: - "debug": Boolean value indicating whether to enable library debugging messages (default: False). - "print_debug": Debug messages processing function. This function takes 2 arguments: the task instance and the message string (default: an internal function doing standard print). - "fanout": Max number of registered clients in Engine at a time (default: 64). - "grooming_delay": Message maximum end-to-end delay requirement used for traffic grooming, in seconds as float (default: 0.5). - "connect_timeout": Time in seconds to wait for connecting to remote host before aborting (default: 10). - "command_timeout": Time in seconds to wait for a command to complete before aborting (default: 0, which means unlimited). - "tree_default:": In tree mode, overrides the key in Defaults (settings normally set in defaults.conf) Threading considerations: Unlike set_default(), the underlying info dictionary is only modified from the task's thread. So calling set_info() from another thread leads to queueing the request for late apply (at run time) using the task dispatch port. When received, the request wakes up the engine when the task is running and the info dictionary is then updated. """ self._info[info_key] = value def shell(self, command, **kwargs): """ Schedule a shell command for local or distant parallel execution. This essential method creates a local or remote Worker (depending on the presence of the nodes parameter) and immediately schedules it for execution in task's runloop. So, if the task is already running (ie. called from an event handler), the command is started immediately, assuming current execution constraints are met (eg. fanout value). If the task is not running, the command is not started but scheduled for late execution. See resume() to start task runloop. The following optional parameters are passed to the underlying local or remote Worker constructor: - handler: EventHandler instance to notify (on event) -- default is no handler (None) - timeout: command timeout delay expressed in second using a floating point value -- default is unlimited (None) - autoclose: if set to True, the underlying Worker is automatically aborted as soon as all other non-autoclosing task objects (workers, ports, timers) have finished -- default is False - stderr: separate stdout/stderr if set to True -- default is False. - stdin: enable stdin if set to True or prevent its use otherwise -- default is True. Local usage: task.shell(command [, key=key] [, handler=handler] [, timeout=secs] [, autoclose=enable_autoclose] [, stderr=enable_stderr][, stdin=enable_stdin])) Distant usage: task.shell(command, nodes=nodeset [, handler=handler] [, timeout=secs], [, autoclose=enable_autoclose] [, tree=None|False|True] [, remote=False|True] [, stderr=enable_stderr][, stdin=enable_stdin])) Example: >>> task = task_self() >>> task.shell("/bin/date", nodes="node[1-2345]") >>> task.resume() """ handler = kwargs.get("handler", None) timeo = kwargs.get("timeout", None) autoclose = kwargs.get("autoclose", False) stderr = kwargs.get("stderr", self.default("stderr")) stdin = kwargs.get("stdin", self.default("stdin")) remote = kwargs.get("remote", True) if kwargs.get("nodes", None): assert kwargs.get("key", None) is None, \ "'key' argument not supported for distant command" tree = kwargs.get("tree") # tree == None means auto if tree != False and self._default_tree_is_enabled(): # fail if tree is forced without any topology if tree and self.topology is None: raise TaskError("tree mode required for distant shell " "command with unknown topology!") # create tree worker wrkcls = TreeWorker elif not remote: # create local worker wrkcls = self.default('local_worker') else: # create distant worker wrkcls = self.default('distant_worker') worker = wrkcls(NodeSet(kwargs["nodes"]), command=command, handler=handler, stderr=stderr, timeout=timeo, autoclose=autoclose, remote=remote) else: # create old fashioned local worker worker = WorkerPopen(command, key=kwargs.get("key", None), handler=handler, stderr=stderr, timeout=timeo, autoclose=autoclose) if not stdin: try: worker.set_write_eof() # prevent reading from stdin except EngineClientError: # not all workers support writing pass # schedule worker for execution in this task self.schedule(worker) return worker def copy(self, source, dest, nodes, **kwargs): """ Copy local file to distant nodes. """ assert nodes != None, "local copy not supported" handler = kwargs.get("handler", None) stderr = kwargs.get("stderr", self.default("stderr")) timeo = kwargs.get("timeout", None) preserve = kwargs.get("preserve", None) reverse = kwargs.get("reverse", False) tree = kwargs.get("tree") # tree == None means auto if tree != False and self._default_tree_is_enabled(): # fail if tree is forced without any topology if tree and self.topology is None: raise TaskError("tree mode required for distant shell " "command with unknown topology!") # create tree worker wrkcls = TreeWorker else: # create a new copy worker wrkcls = self.default('distant_worker') worker = wrkcls(nodes, source=source, dest=dest, handler=handler, stderr=stderr, timeout=timeo, preserve=preserve, reverse=reverse) self.schedule(worker) return worker def rcopy(self, source, dest, nodes, **kwargs): """ Copy distant file or directory to local node. """ kwargs['reverse'] = True return self.copy(source, dest, nodes, **kwargs) @tasksyncmethod() def _add_port(self, port): """Add an EnginePort instance to Engine (private method).""" self._engine.add(port) @tasksyncmethod() def remove_port(self, port): """Close and remove a port from task previously created with port().""" self._engine.remove(port) def port(self, handler=None, autoclose=False): """ Create a new task port. A task port is an abstraction object to deliver messages reliably between tasks. Basic rules: - A task can send messages to another task port (thread safe). - A task can receive messages from an acquired port either by setting up a notification mechanism or using a polling mechanism that may block the task waiting for a message sent on the port. - A port can be acquired by one task only. If handler is set to a valid EventHandler object, the port is a send-once port, ie. a message sent to this port generates an ev_msg event notification issued the port's task. If handler is not set, the task can only receive messages on the port by calling port.msg_recv(). """ port = EnginePort(handler, autoclose) self._add_port(port) return port def timer(self, fire, handler, interval=-1.0, autoclose=False): """ Create a timer bound to this task that fires at a preset time in the future by invoking the ev_timer() method of *handler* (provided EventHandler object). Timers can fire either only once or repeatedly at fixed time intervals. Repeating timers can also have their next firing time manually adjusted. The mandatory parameter *fire* sets the firing delay in seconds. The optional parameter *interval* sets the firing interval of the timer. If not specified, the timer fires once and then is automatically invalidated. Time values are expressed in second using floating point values. Precision is implementation (and system) dependent. The optional parameter *autoclose*, if set to True, creates an "autoclosing" timer: it will be automatically invalidated as soon as all other non-autoclosing task's objects (workers, ports, timers) have finished. Default value is False, which means the timer will retain task's runloop until it is invalidated. Return a new EngineTimer instance. See ClusterShell.Engine.Engine.EngineTimer for more details. """ assert fire >= 0.0, \ "timer's relative fire time must be a positive floating number" timer = EngineTimer(fire, interval, autoclose, handler) # The following method may be sent through msg port (async # call) if called from another task. self._add_timer(timer) # always return new timer (sync) return timer @tasksyncmethod() def _add_timer(self, timer): """Add a timer to task engine (thread-safe).""" self._engine.add_timer(timer) @tasksyncmethod() def schedule(self, worker): """ Schedule a worker for execution, ie. add worker in task running loop. Worker will start processing immediately if the task is running (eg. called from an event handler) or as soon as the task is started otherwise. Only useful for manually instantiated workers, for example: >>> task = task_self() >>> worker = WorkerSsh("node[2-3]", None, 10, command="/bin/ls") >>> task.schedule(worker) >>> task.resume() """ assert self in Task._tasks.values(), \ "deleted task instance, call task_self() again!" # bind worker to task self worker._set_task(self) # add worker clients to engine for client in worker._engine_clients(): self._engine.add(client) def _resume_thread(self): """Resume task - called from another thread.""" self._suspend_cond.notify_all() def _resume(self): """Resume task - called from self thread.""" assert self.thread == threading.current_thread() try: try: self._reset() self._run(self.timeout) except EngineTimeoutException: raise TimeoutError() except EngineAbortException as exc: self._terminate(exc.kill) except EngineAlreadyRunningError: raise AlreadyRunningError("task engine is already running") finally: # task becomes joinable self._join_cond.acquire() self._suspend_cond.atomic_inc() self._join_cond.notify_all() self._join_cond.release() def resume(self, timeout=None): """ Resume task. If task is task_self(), workers are executed in the calling thread so this method will block until all (non-autoclosing) workers have finished. This is always the case for a single-threaded application (eg. which doesn't create other Task() instance than task_self()). Otherwise, the current thread doesn't block. In that case, you may then want to call task_wait() to wait for completion. Warning: the timeout parameter can be used to set an hard limit of task execution time (in seconds). In that case, a TimeoutError exception is raised if this delay is reached. Its value is 0 by default, which means no task time limit (TimeoutError is never raised). In order to set a maximum delay for individual command execution, you should use Task.shell()'s timeout parameter instead. """ # If you change options here, check Task.run() compatibility. self.timeout = timeout self._suspend_cond.atomic_dec() if self._is_task_self(): self._resume() else: self._resume_thread() def run(self, command=None, **kwargs): """ With arguments, it will schedule a command exactly like a Task.shell() would have done it and run it. This is the easiest way to simply run a command. >>> task.run("hostname", nodes="foo") Without argument, it starts all outstanding actions. It behaves like Task.resume(). >>> task.shell("hostname", nodes="foo") >>> task.shell("hostname", nodes="bar") >>> task.run() When used with a command, you can set a maximum delay of individual command execution with the help of the timeout parameter (see Task.shell's parameters). You can then listen for ev_close() events and check the timedout boolean in your Worker event handlers, or use num_timeout() or iter_keys_timeout() afterwards. But, when used as an alias to Task.resume(), the timeout parameter sets an hard limit of task execution time. In that case, a TimeoutError exception is raised if this delay is reached. """ worker = None timeout = None # Both resume() and shell() support a 'timeout' parameter. We need a # trick to behave correctly for both cases. # # Here, we mock: task.resume(10) if type(command) in (int, float): timeout = command command = None # Here, we mock: task.resume(timeout=10) elif 'timeout' in kwargs and command is None: timeout = kwargs.pop('timeout') # All other cases mean a classical: shell(...) # we mock: task.shell("mycommand", [timeout=..., ...]) elif command is not None: worker = self.shell(command, **kwargs) self.resume(timeout) return worker @tasksyncmethod() def _suspend_wait(self): """Suspend request received.""" assert task_self() == self # atomically set suspend state self._suspend_lock.acquire() self._suspended = True self._suspend_lock.release() # wait for special suspend condition, while releasing l_run self._suspend_cond.wait_check(self._run_lock) # waking up, atomically unset suspend state self._suspend_lock.acquire() self._suspended = False self._suspend_lock.release() def suspend(self): """ Suspend task execution. This method may be called from another task (thread-safe). The function returns False if the task cannot be suspended (eg. it's not running), or returns True if the task has been successfully suspended. To resume a suspended task, use task.resume(). """ # first of all, increase suspend count self._suspend_cond.atomic_inc() # call synchronized suspend method self._suspend_wait() # wait for stopped task self._run_lock.acquire() # run_lock ownership transfer # get result: are we really suspended or just stopped? result = True self._suspend_lock.acquire() if not self._suspended: # not acknowledging suspend state, task is stopped result = False self._run_lock.release() self._suspend_lock.release() return result @tasksyncmethod() def _abort(self, kill=False): """Abort request received.""" assert task_self() == self # raise an EngineAbortException when task is running self._quit = True self._engine.abort(kill) def abort(self, kill=False): """ Abort a task. Aborting a task removes (and stops when needed) all workers. If optional parameter kill is True, the task object is unbound from the current thread, so calling task_self() creates a new Task object. """ if not self._run_lock.acquire(0): # self._run_lock is locked, try to call synchronized method self._abort(kill) # but there is no guarantee that it has really been called, as the # task could have aborted during the same time, so we use polling while not self._run_lock.acquire(0): sleep(0.001) # in any case, once _run_lock has been acquired, confirm abort self._quit = True self._run_lock.release() if self._is_task_self(): self._terminate(kill) else: # abort on stopped/suspended task self._suspend_cond.notify_all() def _terminate(self, kill): """ Abort completion subroutine. """ assert self._quit == True self._terminated = True if kill: # invalidate dispatch port self._dispatch_port = None # clear engine self._engine.clear(clear_ports=kill) if kill: self._engine.release() self._engine = None # clear result objects self._reset() # unlock any remaining threads that are waiting for our # termination (late join()s) # must be called after _terminated is set to True self._join_cond.acquire() self._join_cond.notify_all() self._join_cond.release() # destroy task if needed if kill: Task._task_lock.acquire() try: del Task._tasks[threading.current_thread()] finally: Task._task_lock.release() def join(self): """ Suspend execution of the calling thread until the target task terminates, unless the target task has already terminated. """ self._join_cond.acquire() try: if self._suspend_cond.suspend_count > 0 and not self._suspended: # ignore stopped task return if self._terminated: # ignore join() on dead task return self._join_cond.wait() finally: self._join_cond.release() def running(self): """ Return True if the task is running. """ return self._engine and self._engine.running def _reset(self): """ Reset buffers and retcodes management variables. """ # reinit MsgTree dict self._msgtrees = {} # other re-init's self._d_source_rc = {} self._d_rc_sources = {} self._max_rc = None self._timeout_sources.clear() def _msgtree(self, sname, strict=True): """Helper method to return msgtree instance by sname if allowed.""" if self.default("%s_msgtree" % sname): if sname not in self._msgtrees: self._msgtrees[sname] = MsgTree() return self._msgtrees[sname] elif strict: raise TaskMsgTreeError("%s_msgtree not set" % sname) def _msg_add(self, worker, node, sname, msg): """ Process a new message into Task's MsgTree that is coming from: - a worker instance of this task - a node - a stream name sname (string identifier) """ assert worker.task == self, "better to add messages from my workers" msgtree = self._msgtree(sname, strict=False) # As strict=False, if msgtree is None, this means task is set to NOT # record messages... in that case we ignore this request, still # keeping possible existing MsgTree, thus allowing temporarily # disabled ones. if msgtree is not None: msgtree.add((worker, node), msg) def _rc_set(self, worker, node, rc): """ Add a worker return code (rc) that is coming from a node of a worker instance. """ assert rc is not None source = (worker, node) # store rc by source self._d_source_rc[source] = rc # store source by rc self._d_rc_sources.setdefault(rc, set()).add(source) # update max rc if self._max_rc is None or rc > self._max_rc: self._max_rc = rc def _timeout_add(self, worker, node): """ Add a timeout indicator that is coming from a node of a worker instance. """ # store source in timeout set self._timeout_sources.add((worker, node)) def _msg_by_source(self, worker, node, sname): """Get a message by its worker instance, node and stream name.""" msg = self._msgtree(sname).get((worker, node)) if msg is None: return None return bytes(msg) def _call_tree_matcher(self, tree_match_func, match_keys=None, worker=None): """Call identified tree matcher (items, walk) method with options.""" if isinstance(match_keys, basestring): # change to str for Python 3 raise TypeError("Sequence of keys/nodes expected for 'match_keys'.") # filter by worker and optionally by matching keys if worker and match_keys is None: match = lambda k: k[0] is worker elif worker and match_keys is not None: match = lambda k: k[0] is worker and k[1] in match_keys elif match_keys: match = lambda k: k[1] in match_keys else: match = None # Call tree matcher function (items or walk) return tree_match_func(match, itemgetter(1)) def _rc_by_source(self, worker, node): """Get a return code by worker instance and node.""" return self._d_source_rc[(worker, node)] def _rc_iter_by_key(self, key): """ Return an iterator over return codes for the given key. """ for (w, k), rc in self._d_source_rc.items(): if k == key: yield rc def _rc_iter_by_worker(self, worker, match_keys=None): """ Return an iterator over return codes and keys list for a specific worker and optional matching keys. """ if match_keys: # Use the items iterator for the underlying dict. for rc, src in self._d_rc_sources.items(): keys = [t[1] for t in src if t[0] is worker and \ t[1] in match_keys] if len(keys) > 0: yield rc, keys else: for rc, src in self._d_rc_sources.items(): keys = [t[1] for t in src if t[0] is worker] if len(keys) > 0: yield rc, keys def _krc_iter_by_worker(self, worker): """ Return an iterator over key, rc for a specific worker. """ for rc, src in self._d_rc_sources.items(): for w, k in src: if w is worker: yield k, rc def _num_timeout_by_worker(self, worker): """ Return the number of timed out "keys" for a specific worker. """ cnt = 0 for (w, k) in self._timeout_sources: if w is worker: cnt += 1 return cnt def _iter_keys_timeout_by_worker(self, worker): """ Iterate over timed out keys (ie. nodes) for a specific worker. """ for (w, k) in self._timeout_sources: if w is worker: yield k def _flush_buffers_by_worker(self, worker): """ Remove any messages from specified worker. """ msgtree = self._msgtree('stdout', strict=False) if msgtree is not None: msgtree.remove(lambda k: k[0] == worker) def _flush_errors_by_worker(self, worker): """ Remove any error messages from specified worker. """ errtree = self._msgtree('stderr', strict=False) if errtree is not None: errtree.remove(lambda k: k[0] == worker) def key_buffer(self, key): """ Get buffer for a specific key. When the key is associated to multiple workers, the resulting buffer will contain all workers content that may overlap. This method returns an empty buffer if key is not found in any workers. """ msgtree = self._msgtree('stdout') select_key = lambda k: k[1] == key return b''.join(bytes(msg) for msg in msgtree.messages(select_key)) node_buffer = key_buffer def key_error(self, key): """ Get error buffer for a specific key. When the key is associated to multiple workers, the resulting buffer will contain all workers content that may overlap. This method returns an empty error buffer if key is not found in any workers. """ errtree = self._msgtree('stderr') select_key = lambda k: k[1] == key return b''.join(bytes(msg) for msg in errtree.messages(select_key)) node_error = key_error def key_retcode(self, key): """ Return return code for a specific key. When the key is associated to multiple workers, return the max return code from these workers. Raises a KeyError if key is not found in any finished workers. """ codes = list(self._rc_iter_by_key(key)) if not codes: raise KeyError(key) return max(codes) node_retcode = key_retcode def max_retcode(self): """ Get max return code encountered during last run or None in the following cases: - all commands timed out - no command-based worker was executed How do retcodes work? If the process exits normally, the return code is its exit status. If the process is terminated by a signal, the return code is 128 + signal number. """ return self._max_rc def _iter_msgtree(self, sname, match_keys=None): """Helper method to iterate over recorded buffers by sname.""" try: msgtree = self._msgtrees[sname] return self._call_tree_matcher(msgtree.walk, match_keys) except KeyError: if not self.default("%s_msgtree" % sname): raise TaskMsgTreeError("%s_msgtree not set" % sname) return iter([]) def iter_buffers(self, match_keys=None): """ Iterate over buffers, returns a tuple (buffer, keys). For remote workers (Ssh), keys are list of nodes. In that case, you should use NodeSet.fromlist(keys) to get a NodeSet instance (which is more convenient and efficient): Optional parameter match_keys add filtering on these keys. Usage example: >>> for buffer, nodelist in task.iter_buffers(): ... print NodeSet.fromlist(nodelist) ... print buffer """ return self._iter_msgtree('stdout', match_keys) def iter_errors(self, match_keys=None): """ Iterate over error buffers, returns a tuple (buffer, keys). See iter_buffers(). """ return self._iter_msgtree('stderr', match_keys) def iter_retcodes(self, match_keys=None): """ Iterate over return codes of command-based workers, returns a tuple (rc, keys). Optional parameter *match_keys* add filtering on these keys. How do retcodes work? If the process exits normally, the return code is its exit status. If the process is terminated by a signal, the return code is 128 + signal number. """ if match_keys: # Use the items iterator for the underlying dict. for rc, src in self._d_rc_sources.items(): keys = [t[1] for t in src if t[1] in match_keys] yield rc, keys else: for rc, src in self._d_rc_sources.items(): yield rc, [t[1] for t in src] def num_timeout(self): """ Return the number of timed out "keys" (ie. nodes). """ return len(self._timeout_sources) def iter_keys_timeout(self): """ Iterate over timed out keys (ie. nodes). """ for (w, k) in self._timeout_sources: yield k def flush_buffers(self): """ Flush all task messages (from all task workers). """ msgtree = self._msgtree('stdout', strict=False) if msgtree is not None: msgtree.clear() def flush_errors(self): """ Flush all task error messages (from all task workers). """ errtree = self._msgtree('stderr', strict=False) if errtree is not None: errtree.clear() @classmethod def wait(cls, from_thread): """ Class method that blocks calling thread until all tasks have finished (from a ClusterShell point of view, for instance, their task.resume() return). It doesn't necessarily mean that associated threads have finished. """ Task._task_lock.acquire() try: tasks = Task._tasks.copy() finally: Task._task_lock.release() for thread, task in tasks.items(): if thread != from_thread: task.join() def _pchannel(self, gateway, metaworker): """Get propagation channel for gateway (create one if needed). Use self.gateways dictionary that allows lookup like: gateway (string) => (worker channel, set of metaworkers) """ gwstr = str(gateway) # create gateway channel if needed if gwstr not in self.gateways: chan = PropagationChannel(self, gateway) logger = logging.getLogger(__name__) logger.debug("pchannel: creating new channel %s", chan) # invoke gateway timeout = None # FIXME: handle timeout for gateway channels wrkcls = self.default('distant_worker') chanworker = wrkcls(gateway, command=metaworker.invoke_gateway, handler=chan, stderr=True, timeout=timeout) chanworker._update_task_rc = False # gateway is special! define worker._fanout to not rely on the # engine's fanout, and use the special value FANOUT_UNLIMITED to # always allow registration of gateways chanworker._fanout = FANOUT_UNLIMITED # change default stream names to avoid internal task buffering # and conform with channel stream names chanworker.SNAME_STDIN = chan.SNAME_WRITER chanworker.SNAME_STDOUT = chan.SNAME_READER chanworker.SNAME_STDERR = chan.SNAME_ERROR self.schedule(chanworker) # update gateways dict self.gateways[gwstr] = (chanworker, set([metaworker])) else: # TODO: assert chanworker is running (need Worker.running()) chanworker, metaworkers = self.gateways[gwstr] metaworkers.add(metaworker) return chanworker.eh def _pchannel_release(self, gateway, metaworker): """Release propagation channel associated to gateway. Lookup by gateway, decref associated metaworker set and release channel worker if needed. """ logger = logging.getLogger(__name__) logger.debug("pchannel_release %s %s", gateway, metaworker) gwstr = str(gateway) if gwstr not in self.gateways: logger.error("pchannel_release: no pchannel found for gateway %s", gwstr) else: # TODO: delay gateway closing when other gateways are running chanworker, metaworkers = self.gateways[gwstr] metaworkers.remove(metaworker) if len(metaworkers) == 0: logger.debug("pchannel_release: destroying channel %s", chanworker.eh) chanworker.abort() # delete gateway reference del self.gateways[gwstr] def task_self(defaults=None): """ Return the current Task object, corresponding to the caller's thread of control (a Task object is always bound to a specific thread). This function provided as a convenience is available in the top-level ClusterShell.Task package namespace. """ return Task(thread=threading.current_thread(), defaults=defaults) def task_wait(): """ Suspend execution of the calling thread until all tasks terminate, unless all tasks have already terminated. This function is provided as a convenience and is available in the top-level ClusterShell.Task package namespace. """ Task.wait(threading.current_thread()) def task_terminate(): """ Destroy the Task instance bound to the current thread. A next call to task_self() will create a new Task object. Not to be called from a signal handler. This function provided as a convenience is available in the top-level ClusterShell.Task package namespace. """ task_self().abort(kill=True) def task_cleanup(): """ Cleanup routine to destroy all created tasks. This function provided as a convenience is available in the top-level ClusterShell.Task package namespace. This is mainly used for testing purposes and should be avoided otherwise. task_cleanup() may be called from any threads but not from a signal handler. """ # be sure to return to a clean state (no task at all) while True: Task._task_lock.acquire() try: tasks = Task._tasks.copy() if len(tasks) == 0: break finally: Task._task_lock.release() # send abort to all known tasks (it's needed to retry as we may have # missed the engine notification window (it was just exiting, which is # quite a common case if we didn't task_join() previously), or we may # have lost some task's dispatcher port messages. for task in tasks.values(): task.abort(kill=True) # also, for other task than self, task.abort() is async and performed # through an EngineAbortException, so tell the Python scheduler to give # up control to raise this exception (handled by task._terminate())... sleep(0.001)