Python JobQueue.close方法代码示例

# 需要导入模块: from fabric.job_queue import JobQueue [as 别名]
# 或者: from fabric.job_queue.JobQueue import close [as 别名]
def execute(task, *args, **kwargs):
    """
    Execute ``task`` (callable or name), honoring host/role decorators, etc.

    ``task`` may be an actual callable object, or it may be a registered task
    name, which is used to look up a callable just as if the name had been
    given on the command line (including :ref:`namespaced tasks <namespaces>`,
    e.g. ``"deploy.migrate"``.

    The task will then be executed once per host in its host list, which is
    (again) assembled in the same manner as CLI-specified tasks: drawing from
    :option:`-H`, :ref:`env.hosts <hosts>`, the `~fabric.decorators.hosts` or
    `~fabric.decorators.roles` decorators, and so forth.

    ``host``, ``hosts``, ``role``, ``roles`` and ``exclude_hosts`` kwargs will
    be stripped out of the final call, and used to set the task's host list, as
    if they had been specified on the command line like e.g. ``fab
    taskname:host=hostname``.

    Any other arguments or keyword arguments will be passed verbatim into
    ``task`` when it is called, so ``execute(mytask, 'arg1', kwarg1='value')``
    will (once per host) invoke ``mytask('arg1', kwarg1='value')``.

    .. seealso::
        :ref:`The execute usage docs <execute>`, for an expanded explanation
        and some examples.

    .. versionadded:: 1.3
    """
    my_env = {}
    # Obtain task
    if not callable(task):
        # Assume string, set env.command to it
        my_env["command"] = task
        task = crawl(task, state.commands)
        if task is None:
            abort("%r is not callable or a valid task name" % (task,))
    # Set env.command if we were given a real function or callable task obj
    else:
        dunder_name = getattr(task, "__name__", None)
        my_env["command"] = getattr(task, "name", dunder_name)
    # Normalize to Task instance
    if not hasattr(task, "run"):
        task = WrappedCallableTask(task)
    # Filter out hosts/roles kwargs
    new_kwargs, hosts, roles, exclude_hosts = parse_kwargs(kwargs)
    # Set up host list
    my_env["all_hosts"] = task.get_hosts(hosts, roles, exclude_hosts, state.env)

    # Get pool size for this task
    pool_size = task.get_pool_size(my_env["all_hosts"], state.env.pool_size)
    # Set up job queue in case parallel is needed
    jobs = JobQueue(pool_size)
    if state.output.debug:
        jobs._debug = True

    # Call on host list
    if my_env["all_hosts"]:
        for host in my_env["all_hosts"]:
            # Log to stdout
            if state.output.running and not hasattr(task, "return_value"):
                print ("[%s] Executing task '%s'" % (host, my_env["command"]))
            # Create per-run env with connection settings
            local_env = to_dict(host)
            local_env.update(my_env)
            state.env.update(local_env)
            # Handle parallel execution
            if requires_parallel(task):
                # Import multiprocessing if needed, erroring out usefully
                # if it can't.
                try:
                    import multiprocessing
                except ImportError, e:
                    msg = "At least one task needs to be run in parallel, but the\nmultiprocessing module cannot be imported:"
                    msg += "\n\n\t%s\n\n" % e
                    msg += "Please make sure the module is installed or that the above ImportError is\nfixed."
                    abort(msg)

                # Wrap in another callable that nukes the child's cached
                # connection object, if needed, to prevent shared-socket
                # problems.
                def inner(*args, **kwargs):
                    key = normalize_to_string(state.env.host_string)
                    state.connections.pop(key, "")
                    task.run(*args, **kwargs)

                # Stuff into Process wrapper
                p = multiprocessing.Process(target=inner, args=args, kwargs=new_kwargs)
                # Name/id is host string
                p.name = local_env["host_string"]
                # Add to queue
                jobs.append(p)
            # Handle serial execution
            else:
                task.run(*args, **new_kwargs)

        # If running in parallel, block until job queue is emptied
        if jobs:
            jobs.close()
            exitcodes = jobs.run()
#.........这里部分代码省略.........

# 需要导入模块: from fabric.job_queue import JobQueue [as 别名]
# 或者: from fabric.job_queue.JobQueue import close [as 别名]

#.........这里部分代码省略.........
    if not (is_callable or _is_task(task)):
        # Assume string, set env.command to it
        my_env['command'] = task
        task = crawl(task, state.commands)
        if task is None:
            msg = "%r is not callable or a valid task name" % (my_env['command'],)
            if state.env.get('skip_unknown_tasks', False):
                warn(msg)
                return
            else:
                abort(msg)
    # Set env.command if we were given a real function or callable task obj
    else:
        dunder_name = getattr(task, '__name__', None)
        my_env['command'] = getattr(task, 'name', dunder_name)
    # Normalize to Task instance if we ended up with a regular callable
    if not _is_task(task):
        task = WrappedCallableTask(task)
    # Filter out hosts/roles kwargs
    new_kwargs, hosts, roles, exclude_hosts = parse_kwargs(kwargs)
    # Set up host list
    my_env['all_hosts'], my_env['effective_roles'] = task.get_hosts_and_effective_roles(hosts, roles,
                                                                                        exclude_hosts, state.env)

    parallel = requires_parallel(task)
    if parallel:
        # Import multiprocessing if needed, erroring out usefully
        # if it can't.
        try:
            import multiprocessing
        except ImportError:
            import traceback
            tb = traceback.format_exc()
            abort(tb + """
    At least one task needs to be run in parallel, but the
    multiprocessing module cannot be imported (see above
    traceback.) Please make sure the module is installed
    or that the above ImportError is fixed.""")
    else:
        multiprocessing = None

    # Get pool size for this task
    pool_size = task.get_pool_size(my_env['all_hosts'], state.env.pool_size)
    # Set up job queue in case parallel is needed
    queue = multiprocessing.Queue() if parallel else None
    jobs = JobQueue(pool_size, queue)
    if state.output.debug:
        jobs._debug = True

    # Call on host list
    if my_env['all_hosts']:
        # Attempt to cycle on hosts, skipping if needed
        for host in my_env['all_hosts']:
            try:
                results[host] = _execute(
                    task, host, my_env, args, new_kwargs, jobs, queue,
                    multiprocessing
                )
            except NetworkError as e:
                results[host] = e
                # Backwards compat test re: whether to use an exception or
                # abort
                if not state.env.use_exceptions_for['network']:
                    func = warn if state.env.skip_bad_hosts else abort
                    error(e.message, func=func, exception=e.wrapped)
                else:
                    raise

            # If requested, clear out connections here and not just at the end.
            if state.env.eagerly_disconnect:
                disconnect_all()

        # If running in parallel, block until job queue is emptied
        if jobs:
            err = "One or more hosts failed while executing task '%s'" % (
                my_env['command']
            )
            jobs.close()
            # Abort if any children did not exit cleanly (fail-fast).
            # This prevents Fabric from continuing on to any other tasks.
            # Otherwise, pull in results from the child run.
            ran_jobs = jobs.run()
            for name, d in ran_jobs.items():
                if d['exit_code'] != 0:
                    if isinstance(d['results'], NetworkError) and \
                            _is_network_error_ignored():
                        error(d['results'].message, func=warn, exception=d['results'].wrapped)
                    elif isinstance(d['results'], BaseException):
                        error(err, exception=d['results'])
                    else:
                        error(err)
                results[name] = d['results']

    # Or just run once for local-only
    else:
        with settings(**my_env):
            results['<local-only>'] = task.run(*args, **new_kwargs)
    # Return what we can from the inner task executions

    return results

# 需要导入模块: from fabric.job_queue import JobQueue [as 别名]
# 或者: from fabric.job_queue.JobQueue import close [as 别名]
def execute(task, *args, **kwargs):
    """
    Execute ``task`` (callable or name), honoring host/role decorators, etc.

    ``task`` may be an actual callable object, or it may be a registered task
    name, which is used to look up a callable just as if the name had been
    given on the command line (including :ref:`namespaced tasks <namespaces>`,
    e.g. ``"deploy.migrate"``.

    The task will then be executed once per host in its host list, which is
    (again) assembled in the same manner as CLI-specified tasks: drawing from
    :option:`-H`, :ref:`env.hosts <hosts>`, the `~fabric.decorators.hosts` or
    `~fabric.decorators.roles` decorators, and so forth.

    ``host``, ``hosts``, ``role``, ``roles`` and ``exclude_hosts`` kwargs will
    be stripped out of the final call, and used to set the task's host list, as
    if they had been specified on the command line like e.g. ``fab
    taskname:host=hostname``.

    Any other arguments or keyword arguments will be passed verbatim into
    ``task`` when it is called, so ``execute(mytask, 'arg1', kwarg1='value')``
    will (once per host) invoke ``mytask('arg1', kwarg1='value')``.

    .. seealso::
        :ref:`The execute usage docs <execute>`, for an expanded explanation
        and some examples.

    .. versionadded:: 1.3
    """
    my_env = {}
    # Obtain task
    if not callable(task):
        # Assume string, set env.command to it
        my_env['command'] = task
        task = crawl(task, state.commands)
        if task is None:
            abort("%r is not callable or a valid task name" % (task,))
    # Set env.command if we were given a real function or callable task obj
    else:
        dunder_name = getattr(task, '__name__', None)
        my_env['command'] = getattr(task, 'name', dunder_name)
    # Normalize to Task instance
    if not hasattr(task, 'run'):
        task = WrappedCallableTask(task)
    # Filter out hosts/roles kwargs
    new_kwargs, hosts, roles, exclude_hosts = parse_kwargs(kwargs)
    # Set up host list
    my_env['all_hosts'] = task.get_hosts(hosts, roles, exclude_hosts, state.env)

    # Get pool size for this task
    pool_size = task.get_pool_size(my_env['all_hosts'], state.env.pool_size)
    # Set up job queue in case parallel is needed
    jobs = JobQueue(pool_size)
    if state.output.debug:
        jobs._debug = True

    # Call on host list
    if my_env['all_hosts']:
        # Attempt to cycle on hosts, skipping if needed
        for host in my_env['all_hosts']:
            try:
                _execute(task, host, my_env, args, new_kwargs)
            except NetworkError, e:
                # Backwards compat test re: whether to use an exception or
                # abort
                if not state.env.use_exceptions_for['network']:
                    func = warn if state.env.skip_bad_hosts else abort
                    error(e.message, func=func, exception=e.wrapped)
                else:
                    raise

        # If running in parallel, block until job queue is emptied
        if jobs:
            jobs.close()
            exitcodes = jobs.run()
            # Abort if any children did not exit cleanly (fail-fast).
            # This prevents Fabric from continuing on to any other tasks.
            if any([x != 0 for x in exitcodes]):
                abort("One or more hosts failed while executing task '%s'" % (
                    my_env['command']
                ))