Python logging.config方法代码示例

# 需要导入模块: import logging [as 别名]
# 或者: from logging import config [as 别名]
def got_config_request(self, ch, method, properties, body):
		ip_addresses = json.loads(body)
		logging.info("Got config request with following IP addresses: %s" % ip_addresses)

		pi_id = None
		worker = db.session.query(db.objects.Worker).filter(db.objects.Worker.address.in_(ip_addresses)).first()
		if worker:
			pi_id = worker.id
			logging.debug("Found worker id %s for IP address %s" % (pi_id, worker.address))
		else: # wasn't able to find worker with given ip address(es)
			logging.error("Wasn't able to find worker for given IP adress(es)")
			reply_properties = pika.BasicProperties(correlation_id=properties.correlation_id)
			self.channel.basic_publish(exchange=utils.EXCHANGE, properties=reply_properties, routing_key=properties.reply_to, body="")
			return
		
		config = self.prepare_config(pi_id)
		logging.info("Sending intial config to worker with id %s" % pi_id)
		reply_properties = pika.BasicProperties(correlation_id=properties.correlation_id, content_type='application/json')
		self.channel.basic_publish(exchange=utils.EXCHANGE, properties=reply_properties, routing_key=properties.reply_to, body=json.dumps(config))

	# callback method for when the manager recieves data after a worker executed its actions 

# 需要导入模块: import logging [as 别名]
# 或者: from logging import config [as 别名]
def got_on_off(self, ch, method, properties, body):
		msg = json.loads(body)
		
		self.cleanup_notifiers()
		
		if(msg['active_state'] == True):
			self.setup_notifiers()
			logging.info("Activating setup: %s" % msg['setup_name'])
		
		
		workers = db.session.query(db.objects.Worker).filter(db.objects.Worker.active_state == True).all()
		for pi in workers:
			config = self.prepare_config(pi.id)
			# check if we are deactivating --> worker should be deactivated!
			if(msg['active_state'] == False):
				config["active"] = False
				logging.info("Deactivating setup: %s" % msg['setup_name'])
				
			self.send_json_message(utils.QUEUE_CONFIG+str(pi.id), config)
			logging.info("Sent config to worker %s"%pi.name)

	# callback method which gets called when a worker raises an alarm 

# 需要导入模块: import logging [as 别名]
# 或者: from logging import config [as 别名]
def got_init_config(self, ch, method, properties, body):
		logging.info("Received intitial config %r" % (body))
		if self.corr_id == properties.correlation_id: #we got the right config
			try: #TODO: add check if response is empty...
				new_conf = json.loads(body)
				new_conf["rabbitmq"] = config.get("rabbitmq")
			except Exception as e:
				logging.exception("Wasn't able to read JSON config from manager:\n%s" % e)
				time.sleep(60) #sleep for X seconds and then ask again
				self.fetch_init_config()
				return
		
			logging.info("Trying to apply config and reconnect")
			self.apply_config(new_conf)
			self.connection_cleanup()
			self.connect() #hope this is the right spot
			logging.info("Initial config activated")
			self.start()
		else:
			logging.info("This config isn't meant for us")
	
	# Create a zip of all the files which were collected while actions were executed 

# 需要导入模块: import logging [as 别名]
# 或者: from logging import config [as 别名]
def configure_properties(self, tc_config_prop_filenames=None, behave_properties=None):
        """Configure selenium instance properties

        :param tc_config_prop_filenames: test case specific properties filenames
        :param behave_properties: dict with behave user data properties
        """
        prop_filenames = DriverWrappersPool.get_configured_value('Config_prop_filenames', tc_config_prop_filenames,
                                                                 'properties.cfg;local-properties.cfg')
        prop_filenames = [os.path.join(DriverWrappersPool.config_directory, filename) for filename in
                          prop_filenames.split(';')]
        prop_filenames = ';'.join(prop_filenames)

        # Configure config only if properties filename has changed
        if self.config_properties_filenames != prop_filenames:
            # Initialize the config object
            self.config = ExtendedConfigParser.get_config_from_file(prop_filenames)
            self.config_properties_filenames = prop_filenames
            self.update_magic_config_names()

        # Override properties with system properties
        self.config.update_properties(os.environ)

        # Override properties with behave userdata properties
        if behave_properties:
            self.config.update_properties(behave_properties) 

# 需要导入模块: import logging [as 别名]
# 或者: from logging import config [as 别名]
def get_config_window_bounds(self):
        """Reads bounds from config and, if monitor is specified, modify the values to match with the specified monitor

        :return: coords X and Y where set the browser window.
        """
        bounds_x = int(self.config.get_optional('Driver', 'bounds_x') or 0)
        bounds_y = int(self.config.get_optional('Driver', 'bounds_y') or 0)

        monitor_index = int(self.config.get_optional('Driver', 'monitor') or -1)
        if monitor_index > -1:
            try:
                monitor = screeninfo.get_monitors()[monitor_index]
                bounds_x += monitor.x
                bounds_y += monitor.y
            except NotImplementedError:
                self.logger.warn('Current environment doesn\'t support get_monitors')

        return bounds_x, bounds_y 

# 需要导入模块: import logging [as 别名]
# 或者: from logging import config [as 别名]
def define_atlas_settings():
    atlas_settings = {
        'DKT': {
            'path' : os.path.join(ciftify.config.find_HCP_S1200_GroupAvg(),
                                  'cvs_avg35_inMNI152.aparc.32k_fs_LR.dlabel.nii'),
            'order' : 1,
            'name': 'DKT',
            'map_number': 1
        },
        'MMP': {
            'path': os.path.join(ciftify.config.find_HCP_S1200_GroupAvg(),
                                 'Q1-Q6_RelatedValidation210.CorticalAreas_dil_Final_Final_Areas_Group_Colors.32k_fs_LR.dlabel.nii'),
            'order' : 3,
            'name' : 'MMP',
            'map_number': 1
        },
        'Yeo7': {
            'path' : os.path.join(ciftify.config.find_HCP_S1200_GroupAvg(),
                                  'RSN-networks.32k_fs_LR.dlabel.nii'),
            'order' : 2,
            'name' : 'Yeo7',
            'map_number': 1
        }
    }
    return(atlas_settings) 

# 需要导入模块: import logging [as 别名]
# 或者: from logging import config [as 别名]
def generate_qc_page(user_settings, config, qc_dir, scene_dir, qc_html,
                    temp_dir, title_formatter):

    sbref_nii = change_sbref_palette(user_settings, temp_dir)
    dtseries_sm = get_smoothed_dtseries_file(user_settings, temp_dir)

    contents = config.get_template_contents()
    scene_file = personalize_template(contents, scene_dir, user_settings,
                                        sbref_nii, dtseries_sm)

    ciftify.utils.make_dir(qc_dir)
    with open(qc_html, 'w') as qc_page:
        ciftify.html.add_page_header(qc_page, config, user_settings.qc_mode,
                subject=user_settings.subject, path='..')
        wb_logging = 'INFO' if user_settings.debug_mode else 'WARNING'
        ciftify.html.add_images(qc_page, qc_dir, config.images,
            scene_file, wb_logging = wb_logging, add_titles = True,
            title_formatter = title_formatter) 

# 需要导入模块: import logging [as 别名]
# 或者: from logging import config [as 别名]
def run_migrations_offline():
    """Run migrations in 'offline' mode.

    This configures the context with just a URL
    and not an Engine, though an Engine is acceptable
    here as well.  By skipping the Engine creation
    we don't even need a DBAPI to be available.

    Calls to context.execute() here emit the given string to the
    script output.

    """
    url = config.get_main_option("sqlalchemy.url")
    context.configure(url=url)

    with context.begin_transaction():
        context.run_migrations() 

# 需要导入模块: import logging [as 别名]
# 或者: from logging import config [as 别名]
def main(argv):
    parsed_args = parser.parse_args(argv[1:])

    mod, klass = parsed_args.transport.rsplit('.', 1)

    transport = getattr(importlib.import_module(mod), klass)()

    command = parsed_args.command

    if not command:
        logging.config.dictConfig(LOGGING)

        transport.run_server(
            pool_size=parsed_args.pool_size,
            max_accepts=parsed_args.max_accepts,
            max_child_tasks=parsed_args.max_child_tasks
        )
    else:
        stdout, stderr, returncode = transport.run_cmd(' '.join(command))

        sys.stdout.write(stdout)
        sys.stderr.write(stderr)

        sys.exit(returncode) 

# 需要导入模块: import logging [as 别名]
# 或者: from logging import config [as 别名]
def update_config(update):
    """
    Update (recursively) the current logging condiguration dictionary.

    See: `Logging config dictionary schema <https://docs.python.org/3/library/logging.config.html#logging-config-dictschema>`_

    """
    global _config
    new_config = copy.deepcopy(_config)
    _update_dict_recursive(new_config, update)
    logging.config.dictConfig(new_config)
    _configure_ulog_bridge()
    _config = new_config


# set the default log configuration on import 

# 需要导入模块: import logging [as 别名]
# 或者: from logging import config [as 别名]
def run_migrations_offline():
    """Run migrations in 'offline' mode.

    This configures the context with just a URL
    and not an Engine, though an Engine is acceptable
    here as well.  By skipping the Engine creation
    we don't even need a DBAPI to be available.

    Calls to context.execute() here emit the given string to the
    script output.

    """
    url = config.get_main_option("sqlalchemy.url")
    context.configure(
        url=url, target_metadata=target_metadata, literal_binds=True
    )

    with context.begin_transaction():
        context.run_migrations() 

# 需要导入模块: import logging [as 别名]
# 或者: from logging import config [as 别名]
def _load_connectors(self, main_config):
        self.connectors_configs = {}
        if main_config.get("connectors"):
            for connector in main_config['connectors']:
                try:
                    connector_class = TBUtility.check_and_import(connector["type"], self._default_connectors.get(connector["type"], connector.get("class")))
                    self._implemented_connectors[connector["type"]] = connector_class
                    with open(self._config_dir + connector['configuration'], 'r', encoding="UTF-8") as conf_file:
                        connector_conf = load(conf_file)
                        if not self.connectors_configs.get(connector['type']):
                            self.connectors_configs[connector['type']] = []
                        connector_conf["name"] = connector["name"]
                        self.connectors_configs[connector['type']].append({"name": connector["name"], "config": {connector['configuration']: connector_conf}})
                except Exception as e:
                    log.error("Error on loading connector:")
                    log.exception(e)
        else:
            log.error("Connectors - not found! Check your configuration!")
            main_config["remoteConfiguration"] = True
            log.info("Remote configuration is enabled forcibly!") 

# 需要导入模块: import logging [as 别名]
# 或者: from logging import config [as 别名]
def _connect_with_connectors(self):
        for connector_type in self.connectors_configs:
            for connector_config in self.connectors_configs[connector_type]:
                for config in connector_config["config"]:
                    connector = None
                    try:
                        if connector_config["config"][config] is not None:
                            connector = self._implemented_connectors[connector_type](self, connector_config["config"][config],
                                                                                     connector_type)
                            connector.setName(connector_config["name"])
                            self.available_connectors[connector.get_name()] = connector
                            connector.open()
                        else:
                            log.info("Config not found for %s", connector_type)
                    except Exception as e:
                        log.exception(e)
                        if connector is not None:
                            connector.close() 

# 需要导入模块: import logging [as 别名]
# 或者: from logging import config [as 别名]
def _add_monitor_to_experiment(experiment: experiment.Experiment) -> experiment.Experiment:
    logger.info(f"configured training hooks: {experiment.train_spec.hooks}")

    training_hooks = list(experiment.train_spec.hooks)

    if experiment.config.log_step_count_steps is not None:
        steps_per_second_hook = metrics.StepPerSecondHook(
            every_n_steps=experiment.config.log_step_count_steps
        )
        if not _hook_name_already_exists(steps_per_second_hook, training_hooks):
            training_hooks.append(steps_per_second_hook)
        else:
            logger.warning("do not add StepPerSecondHook as there is already one configured")

    monitored_train_spec = experiment.train_spec._replace(
        hooks=training_hooks
    )

    monitored_eval_spec = experiment.eval_spec._replace(
        hooks=(evaluator_metrics.EvalMonitorHook(), *experiment.eval_spec.hooks)
    )

    experiment = experiment._replace(eval_spec=monitored_eval_spec, train_spec=monitored_train_spec)
    return experiment 

# 需要导入模块: import logging [as 别名]
# 或者: from logging import config [as 别名]
def __init__(self, args, config):
        self.args = args
        self.config = config
        self.cache_dir = utils.get_cache_dir(config)
        self.model_dir = utils.get_model_dir(config)
        self.category = utils.get_category(config, self.cache_dir if os.path.exists(self.cache_dir) else None)
        self.draw_bbox = utils.visualize.DrawBBox(self.category, colors=args.colors, thickness=args.thickness)
        self.anchors = torch.from_numpy(utils.get_anchors(config)).contiguous()
        self.height, self.width = tuple(map(int, config.get('image', 'size').split()))
        self.path, self.step, self.epoch = utils.train.load_model(self.model_dir)
        state_dict = torch.load(self.path, map_location=lambda storage, loc: storage)
        self.dnn = utils.parse_attr(config.get('model', 'dnn'))(model.ConfigChannels(config, state_dict), self.anchors, len(self.category))
        self.dnn.load_state_dict(state_dict)
        self.inference = model.Inference(config, self.dnn, self.anchors)
        self.inference.eval()
        if torch.cuda.is_available():
            self.inference.cuda()
        logging.info(humanize.naturalsize(sum(var.cpu().numpy().nbytes for var in self.inference.state_dict().values())))
        self.cap = self.create_cap()
        self.keys = set(args.keys)
        self.resize = transform.parse_transform(config, config.get('transform', 'resize_test'))
        self.transform_image = transform.get_transform(config, config.get('transform', 'image_test').split())
        self.transform_tensor = transform.get_transform(config, config.get('transform', 'tensor').split())