Python util.log_to_stream函数代码示例

 def test_messy_error(self):
     counter_string = 'Job JOBID="_001" FAILED_REDUCES="0" COUNTERS="THIS IS NOT ACTUALLY A COUNTER"'
     with no_handlers_for_logger(''):
         stderr = StringIO()
         log_to_stream('mrjob.parse', stderr, level=logging.WARN)
         assert_equal((None, None), parse_hadoop_counters_from_line(counter_string))
         assert_in('Cannot parse Hadoop counter line', stderr.getvalue())

    def test_failed_job(self):
        mr_job = MRTwoStepJob(['-r', 'dataproc', '-v'])
        mr_job.sandbox()

        with no_handlers_for_logger('mrjob.dataproc'):
            stderr = StringIO()
            log_to_stream('mrjob.dataproc', stderr)

            self._dataproc_client.job_get_advances_states = (
                collections.deque(['SETUP_DONE', 'RUNNING', 'ERROR']))

            with mr_job.make_runner() as runner:
                self.assertIsInstance(runner, DataprocJobRunner)

                self.assertRaises(StepFailedException, runner.run)

                self.assertIn(' => ERROR\n', stderr.getvalue())

                cluster_id = runner.get_cluster_id()

        # job should get terminated
        cluster = (
            self._dataproc_client._cache_clusters[_TEST_PROJECT][cluster_id])
        cluster_state = self._dataproc_client.get_state(cluster)
        self.assertEqual(cluster_state, 'DELETING')

    def test_cleanup_options(self):
        stderr = StringIO()
        with no_handlers_for_logger('mrjob.runner'):
            log_to_stream('mrjob.runner', stderr)
            opts = RunnerOptionStore(
                'inline',
                dict(cleanup=['LOCAL_SCRATCH', 'REMOTE_SCRATCH'],
                     cleanup_on_failure=['JOB_FLOW', 'SCRATCH']),
                [])

            self.assertEqual(opts['cleanup'], ['LOCAL_TMP', 'CLOUD_TMP'])
            self.assertIn(
                'Deprecated cleanup option LOCAL_SCRATCH has been renamed'
                ' to LOCAL_TMP', stderr.getvalue())
            self.assertIn(
                'Deprecated cleanup option REMOTE_SCRATCH has been renamed'
                ' to CLOUD_TMP', stderr.getvalue())

            self.assertEqual(opts['cleanup_on_failure'], ['CLUSTER', 'TMP'])
            self.assertIn(
                'Deprecated cleanup_on_failure option JOB_FLOW has been'
                ' renamed to CLUSTER', stderr.getvalue())
            self.assertIn(
                'Deprecated cleanup_on_failure option SCRATCH has been renamed'
                ' to TMP', stderr.getvalue())

    def test_non_log_lines(self):
        lines = StringIO('foo\n'
                         'bar\n'
                         '15/12/11 13:26:08 ERROR streaming.StreamJob:'
                         ' Error Launching job :'
                         ' Output directory already exists\n'
                         'Streaming Command Failed!')

        with no_handlers_for_logger('mrjob.logs.parse'):
            stderr = StringIO()
            log_to_stream('mrjob.logs.parse', stderr)

            self.assertEqual(
            list(_parse_hadoop_log_lines(lines)), [
                # ignore leading non-log lines
                dict(
                    timestamp='15/12/11 13:26:08',
                    level='ERROR',
                    logger='streaming.StreamJob',
                    thread=None,
                    # no way to know that Streaming Command Failed! wasn't part
                    # of a multi-line message
                    message=('Error Launching job :'
                             ' Output directory already exists\n'
                             'Streaming Command Failed!'))
            ])

            # should be one warning for each leading non-log line
            log_lines = stderr.getvalue().splitlines()
            self.assertEqual(len(log_lines), 2)

def main():
    # parser command-line args
    option_parser = make_option_parser()
    options, args = option_parser.parse_args()

    if args:
        option_parser.error('takes no arguments')

    # set up logging
    if not options.quiet:
        log_to_stream(name='mrjob', debug=options.verbose)

    # create the persistent job
    runner_kwargs = {
        'conf_path': options.conf_path,
        'ec2_instance_type': options.ec2_instance_type,
        'ec2_master_instance_type': options.ec2_master_instance_type,
        'ec2_slave_instance_type': options.ec2_slave_instance_type,
        'label': options.label,
        'num_ec2_instances': options.num_ec2_instances,
        'owner': options.owner,
    }
    runner = EMRJobRunner(**runner_kwargs)
    emr_job_flow_id = runner.make_persistent_job_flow()
    print emr_job_flow_id

    def test_non_log_lines(self):
        lines = StringIO(
            "foo\n"
            "bar\n"
            "15/12/11 13:26:08 ERROR streaming.StreamJob:"
            " Error Launching job :"
            " Output directory already exists\n"
            "Streaming Command Failed!"
        )

        with no_handlers_for_logger("mrjob.logs.parse"):
            stderr = StringIO()
            log_to_stream("mrjob.logs.parse", stderr)

            self.assertEqual(
                list(_parse_hadoop_log_lines(lines)),
                [
                    # ignore leading non-log lines
                    dict(
                        timestamp="15/12/11 13:26:08",
                        level="ERROR",
                        logger="streaming.StreamJob",
                        thread=None,
                        # no way to know that Streaming Command Failed! wasn't part
                        # of a multi-line message
                        message=(
                            "Error Launching job :" " Output directory already exists\n" "Streaming Command Failed!"
                        ),
                    )
                ],
            )

            # should be one warning for each leading non-log line
            log_lines = stderr.getvalue().splitlines()
            self.assertEqual(len(log_lines), 2)

    def test_deprecated_mapper_final_positional_arg(self):
        def mapper(k, v):
            pass

        def reducer(k, v):
            pass

        def mapper_final():
            pass

        stderr = StringIO()
        with no_handlers_for_logger():
            log_to_stream('mrjob.job', stderr)
            step = MRJob.mr(mapper, reducer, mapper_final)

        # should be allowed to specify mapper_final as a positional arg,
        # but we log a warning
        self.assertEqual(
            step,
            MRJob.mr(
                mapper=mapper, reducer=reducer, mapper_final=mapper_final))
        self.assertIn('mapper_final should be specified', stderr.getvalue())

        # can't specify mapper_final as a positional and keyword arg
        self.assertRaises(
            TypeError,
            MRJob.mr,
            mapper,
            reducer,
            mapper_final,
            mapper_final=mapper_final)

 def assert_hadoop_version(self, JobClass, version_string):
     mr_job = JobClass()
     mock_log = StringIO()
     with no_handlers_for_logger("mrjob.job"):
         log_to_stream("mrjob.job", mock_log)
         self.assertEqual(mr_job.jobconf()["hadoop_version"], version_string)
         self.assertIn("should be a string", mock_log.getvalue())

 def test_mixed_behavior_2(self):
     stderr = StringIO()
     with no_handlers_for_logger():
         log_to_stream('mrjob.job', stderr)
         mr_job = self.MRInconsistentJob2()
         self.assertEqual(mr_job.options.input_protocol, None)
         self.assertEqual(mr_job.input_protocol().__class__, ReprProtocol)
         self.assertIn('custom behavior', stderr.getvalue())

    def updated_and_warnings(self, jobconf, hadoop_version):
        jobconf = jobconf.copy()
        with no_handlers_for_logger("mrjob.runner"):
            stderr = StringIO()
            log_to_stream("mrjob.runner", stderr)
            self.runner._update_jobconf_for_hadoop_version(jobconf, hadoop_version)

        return jobconf, stderr.getvalue()

 def test_default_protocols(self):
     stderr = StringIO()
     with no_handlers_for_logger():
         log_to_stream('mrjob.job', stderr)
         mr_job = MRBoringJob()
         self.assertEqual(mr_job.options.input_protocol, 'raw_value')
         self.assertEqual(mr_job.options.protocol, 'json')
         self.assertEqual(mr_job.options.output_protocol, 'json')
         self.assertNotIn('deprecated', stderr.getvalue())

 def test_overriding_explicit_default_protocols(self):
     stderr = StringIO()
     with no_handlers_for_logger():
         log_to_stream('mrjob.job', stderr)
         mr_job = self.MRBoringJob2(args=['--protocol=json'])
         self.assertEqual(mr_job.options.input_protocol, 'json')
         self.assertEqual(mr_job.options.protocol, 'json')
         self.assertEqual(mr_job.options.output_protocol, 'repr')
         self.assertIn('deprecated', stderr.getvalue())

def main():
    option_parser = make_option_parser()
    options, args = option_parser.parse_args()
    
    if args:
        option_parser.error('takes no arguments')

    # set up logging
    if not options.quiet:
        log_to_stream(name='mrjob', debug=options.verbose)

    emr_conn = EMRJobRunner().make_emr_conn()

    log.info(
        'getting info about all job flows (this goes back about 2 weeks)')
    job_flows = emr_conn.describe_jobflows()
        
    now = datetime.utcnow()

    num_running = 0
    num_idle = 0
    num_done = 0
    # a list of tuples of job flow id, name, idle time (as a timedelta)
    to_terminate = []

    for jf in job_flows:
        # check if job flow is done
        if hasattr(jf, 'enddatetime'):
            num_done += 1
        # check if job flow is currently running
        elif jf.steps and not hasattr(jf.steps[-1], 'enddatetime'):
            num_running += 1
        # job flow is idle. how long?
        else:
            num_idle += 1
            if jf.steps:
                idle_since = datetime.strptime(
                    jf.steps[-1].enddatetime, ISO8601)
            else:
                idle_since = datetime.strptime(
                    jf.creationdatetime, ISO8601)
            idle_time = now - idle_since

            # don't care about fractions of a second
            idle_time = timedelta(idle_time.days, idle_time.seconds)

            log.debug('Job flow %s (%s) idle for %s' %
                           (jf.jobflowid, jf.name, idle_time))
            if idle_time > timedelta(hours=options.max_hours_idle):
                to_terminate.append(
                    (jf.jobflowid, jf.name, idle_time))

    log.info('Job flow statuses: %d running, %d idle, %d done' %
                  (num_running, num_idle, num_done))

    terminate_and_notify(emr_conn, to_terminate, options)

    def get_debug_printout(self, opt_store_class, alias, opts):
        stderr = StringIO()

        with no_handlers_for_logger():
            log_to_stream('mrjob.runner', stderr, debug=True)

            # debug printout happens in constructor
            opt_store_class(alias, opts, [])

        return stderr.getvalue()

    def test_option_debug_printout(self):
        stderr = StringIO()

        with no_handlers_for_logger():
            log_to_stream('mrjob.runner', stderr, debug=True)

            InlineMRJobRunner(owner='dave')

        self.assertIn("'owner'", stderr.getvalue())
        self.assertIn("'dave'", stderr.getvalue())