def _check_redis_pubsub_for_restart(self):
"""
Subscribe to Redis PubSub and restart if necessary.
Check the Redis PubSub channel and restart Traptor if a message for
this Traptor is found.
"""
self.logger.info("Subscribing to the Traptor notification PubSub")
self.logger.debug("restart_flag = {}".format(self.restart_flag))
pubsub_check_interval = float(os.getenv('PUBSUB_CHECK_INTERVAL', 1))
p = self.pubsub_conn.pubsub()
p.subscribe(self.traptor_notify_channel)
while True:
time.sleep(pubsub_check_interval)
m = p.get_message()
if m is not None:
data = str(m['data'])
t = data.split(':')
self.logger.debug("PubSub Message: {}".format(t))
if t[0] == self.traptor_type and t[1] == str(self.traptor_id):
# Log the action and restart
self.restart_flag = True
self.logger.debug("Redis PubSub message found. Setting restart flag to True.")
dd_monitoring.increment('restart_message_received')
def kafka_failure(e):
self.logger.error("Caught Kafka exception when sending a tweet to Kafka", extra={
'error_type': 'KafkaError',
'ex': traceback.format_exc()
})
dd_monitoring.increment('tweet_to_kafka_failure',
tags=['error_type:kafka'])
def _delete_rule_counters(self):
"""
Stop and then delete the existing rule counters.
"""
if len(self.rule_counters) > 0:
for counter in self.rule_counters:
try:
self.rule_counters[counter].deactivate()
except:
self.logger.error("Caught exception while deactivating a rule counter", extra={
'error_type': 'ConnectionError',
'ex': traceback.format_exc()
})
dd_monitoring.increment('redis_error',
tags=['error_type:connection_error'])
for counter in self.rule_counters:
try:
self.rule_counters[counter].stop()
self.rule_counters[counter].delete_key()
except:
self.logger.error("Caught exception while stopping and deleting a rule counter", extra={
'error_type': 'RedisConnectionError',
'ex': traceback.format_exc()
})
dd_monitoring.increment('redis_error',
tags=['error_type:connection_error'])
self.logger.info("Rule counters deleted successfully")
def _get_redis_rules(self):
""" Yields a traptor rule from redis. This function
expects that the redis keys are set up like follows:
traptor-<traptor_type>:<traptor_id>:<rule_id>
For example,
traptor-follow:0:34
traptor-track:0:5
traptor-locations:0:2
For 'follow' twitter streaming, each traptor may only
follow 5000 twitter ids, as per the Twitter API.
For 'track' twitter stream, each traptor may only
track 400 keywords, as per the Twitter API.
For 'locations' twitter stream, each traptor may only
track 25 bounding boxes, as per the Twitter API.
:returns: Yields a traptor rule from redis.
"""
# Set up API limitation checks
if self.traptor_type == 'follow':
rule_max = 5000
elif self.traptor_type == 'track':
rule_max = 400
elif self.traptor_type == 'locations':
rule_max = 1
else:
self.logger.error('Unsupported traptor_type', extra={'traptor_type': self.traptor_type})
dd_monitoring.increment('traptor_error_occurred',
tags=['error_type:not_implemented_error'])
raise(NotImplementedError)
# for rule in xrange(rule_max):
redis_key = 'traptor-{0}:{1}'.format(self.traptor_type,
self.traptor_id)
match = ':'.join([redis_key, '*'])
try:
self.logger.info("Getting rules from Redis")
for idx, hashname in enumerate(self.redis_conn.scan_iter(match=match)):
if idx < rule_max:
redis_rule = self.redis_conn.hgetall(hashname)
yield redis_rule
self.logger.debug('Index: {0}, Redis_rule: {1}'.format(
idx, redis_rule))
except:
self.logger.critical("Caught exception while connecting to Redis", extra={
'error_type': 'RedisConnectionError',
'ex': traceback.format_exc()
})
dd_monitoring.increment('redis_error',
tags=['error_type:connection_error'])
def _enrich_tweet(self, tweet):
"""
Enrich the tweet with additional fields, rule matching and stats collection.
:return dict enriched_data: tweet dict with additional enrichments
:return dict tweet: non-tweet message with no additional enrichments
"""
enriched_data = dict()
if self._message_is_limit_message(tweet):
# Increment counter
dd_monitoring.increment('limit_message_received')
# Send DD the limit message value
limit_count = tweet.get('limit').get(self.traptor_type, None)
dd_monitoring.gauge('limit_message_count', limit_count, [])
# Store the limit count in Redis
self._increment_limit_message_counter(limit_count=limit_count)
elif self._message_is_tweet(tweet):
try:
# Add the initial traptor fields
tweet = self._create_traptor_obj(tweet)
# Add the created_at_iso field
tweet = self._add_iso_created_at(tweet)
# Add the rule information
enriched_data = self._find_rule_matches(tweet)
# Update the matched rule stats
if self.traptor_type != 'locations' and self.enable_stats_collection ==\
'true':
self._increment_rule_counter(enriched_data)
except Exception as e:
self.logger.error("Failed to enrich tweet, skipping enhancement", {
"tweet": json.dumps(tweet),
"ex" : traceback.format_exc()
})
# an error occurred while processing the tweet. If some information was
# set in the dictionary when calling _find_rule_matches, clear it out
# because it is likely invalid...
enriched_data = {}
else:
self.logger.info("Twitter message is not a tweet", extra={
'twitter_message': tweet
})
dd_monitoring.increment('tweet_process_success')
if enriched_data:
return enriched_data
else:
return tweet
def _add_heartbeat_message_to_redis(self,
heartbeat_conn):
"""Add a heartbeat message to Redis."""
time_to_live = 5
now = datetime.now().strftime("%Y%M%d%H%M%S")
key_to_add = "{}:{}:{}".format(self.traptor_type,
self.traptor_id,
now)
message = "alive"
dd_monitoring.increment('heartbeat_message_sent_success')
return heartbeat_conn.setex(key_to_add, time_to_live, message)
def _increment_limit_message_counter(self, limit_count):
"""
Increment the limit message counter
:param limit_count: the integer value from the limit message
"""
try:
if self.limit_counter is not None:
self.limit_counter.increment(limit_count=limit_count)
except:
self.logger.error("Caught exception while incrementing a limit counter", extra={
'error_type': 'RedisConnectionError',
'ex': traceback.format_exc()
})
dd_monitoring.increment('redis_error',
tags=['error_type:connection_error'])
def _setup_kafka(self):
""" Set up a Kafka connection."""
if self.kafka_enabled == 'true':
self.logger.info('Setting up kafka connection')
try:
self._create_kafka_producer()
except:
self.logger.critical("Caught Kafka Unavailable Error", extra={
'error_type': 'KafkaUnavailableError',
'ex': traceback.format_exc()
})
dd_monitoring.increment('kafka_error',
tags=['error_type:kafka_unavailable'])
# sys.exit(3)
else:
self.logger.info('Skipping kafka connection setup')
self.logger.debug('Kafka_enabled setting: {}'.format(self.kafka_enabled))
self.kafka_conn = None
def _send_heartbeat_message(self):
"""Add an expiring key to Redis as a heartbeat on a timed basis."""
self.logger.info("Starting the heartbeat")
hb_interval = 5
# while Traptor is running, add a heartbeat message every 5 seconds
while True:
try:
self._add_heartbeat_message_to_redis(self.heartbeat_conn)
except Exception:
self.logger.error("Caught exception while adding the heartbeat message to Redis", extra={
'error_type': 'RedisConnectionError',
'ex': traceback.format_exc()
})
dd_monitoring.increment('heartbeat_message_sent_failure',
tags=['error_type:redis_connection_error'])
raise
time.sleep(hb_interval)
def _create_birdy_stream(self):
""" Create a birdy twitter stream.
If there is a TwitterApiError it will exit with status code 3.
This was done to prevent services like supervisor from automatically
restart the process causing the twitter API to get locked out.
Creates ``self.birdy_stream``.
"""
if self.traptor_type == 'follow':
# Try to set up a twitter stream using twitter id list
try:
self._create_twitter_follow_stream()
except TwitterApiError as e:
self.logger.critical("Caught Twitter Api Error creating follow stream", extra = {
'error_type': 'TwitterAPIError',
'ex': traceback.format_exc()
})
dd_monitoring.increment('twitter_error_occurred',
tags=['error_type:twitter_api_error'])
sys.exit(3)
elif self.traptor_type == 'track':
# Try to set up a twitter stream using twitter term list
try:
self._create_twitter_track_stream()
except TwitterApiError as e:
self.logger.critical("Caught Twitter Api Error", extra={
'error_type': 'TwitterAPIError',
'ex': traceback.format_exc()
})
dd_monitoring.increment('twitter_error_occurred',
tags=['error_type:twitter_api_error'])
sys.exit(3)
elif self.traptor_type == 'locations':
# Try to set up a twitter stream using twitter term list
try:
self._create_twitter_locations_stream()
except TwitterApiError as e:
self.logger.critical("Caught Twitter Api Error", extra={
'error_type': 'TwitterAPIError',
'ex': traceback.format_exc()
})
dd_monitoring.increment('twitter_error_occurred',
tags=['error_type:twitter_api_error'])
sys.exit(3)
else:
self.logger.critical('Caught error creating birdy stream for Traptor type that does not exist', extra ={
'error_type': 'NotImplementedError',
'ex': traceback.format_exc()
})
dd_monitoring.increment('traptor_error_occurred',
tags=['error_type:not_implemented_error'])
sys.exit(3)
def _main_loop(self):
"""
Main loop for iterating through the twitter data.
This method iterates through the birdy stream, does any
pre-processing, and adds enrichments to the data. If kafka is
enabled it will write to the kafka topic defined when instantiating
the Traptor class.
"""
self.logger.info("Starting tweet processing")
# Iterate through the twitter results
for item in self.birdy_stream._stream_iter():
if item:
try:
tweet = json.loads(item)
except:
self.logger.error("Caught exception while json loading the Twitter message", extra={
'ex': traceback.format_exc()
})
dd_monitoring.increment('traptor_error_occurred',
tags=['error_type:json_loads_error'])
else:
enriched_data = self._enrich_tweet(tweet)
if self.kafka_enabled == 'true':
try:
self._send_enriched_data_to_kafka(tweet, enriched_data)
except:
self.logger.error("Caught exception adding Twitter message to Kafka", extra={
'ex': traceback.format_exc()
})
dd_monitoring.increment('tweet_to_kafka_failure',
tags=['error_type:kafka'])
else:
self.logger.debug(json.dumps(enriched_data, indent=2))
if self.restart_flag:
self.logger.info("Restart flag is true; restarting myself")
break
def _increment_rule_counter(self, tweet):
"""
Increment a rule counter.
:param rule_value: the value of the rule to increment the counter for
"""
rule_id = tweet.get('traptor', {}).get('rule_id', None)
# If the counter doesn't yet exist, create it
if self.rule_counters.get(rule_id, None) is None:
self.rule_counters[rule_id] = self._create_rule_counter(rule_id=rule_id)
# If a rule value exists, increment the counter
try:
if rule_id is not None and self.rule_counters[rule_id] is not None:
self.rule_counters[rule_id].increment()
except:
self.logger.error("Caught exception while incrementing a rule counter", extra={
'error_type': 'RedisConnectionError',
'ex': traceback.format_exc()
})
dd_monitoring.increment('redis_error',
tags=['error_type:connection_error'])
def _main_loop(self):
"""
Main loop for iterating through the twitter data.
This method iterates through the birdy stream, does any
pre-processing, and adds enrichments to the data. If kafka is
enabled it will write to the kafka topic defined when instantiating
the Traptor class.
"""
self.logger.info("Starting tweet processing.")
# Iterate through the twitter results
for item in self.birdy_stream._stream_iter():
if item:
try:
tweet = json.loads(item)
except:
dd_monitoring.increment('tweet_process_failure')
self.logger.error("Caught exception while json loading the Twitter message", extra={
'ex': traceback.format_exc()
})
else:
dd_monitoring.increment('tweet_process_success')
enriched_data = self._enrich_tweet(tweet)
if self.kafka_enabled == 'true':
try:
self.kafka_conn.send(self.kafka_topic, enriched_data)
self.logger.info("Tweet sent to kafka", extra={
'tweet_id': tweet.get('id_str', None)
})
dd_monitoring.increment('tweet_to_kafka_success')
except Exception:
self.logger.error("Caught exception adding Twitter message to Kafka", extra={
'ex': traceback.format_exc()
})
dd_monitoring.increment('tweet_to_kafka_failure')
else:
self.logger.debug(json.dumps(enriched_data, indent=2))
if self.restart_flag:
self.logger.info("Restart flag is true; restarting myself.")
break
def _find_rule_matches(self, tweet_dict):
"""
Find a rule match for the tweet.
This code only expects there to be one match. If there is more than one, it will use the last one
it finds since the first match will be overwritten.
:param dict tweet_dict: The dictionary twitter object.
:returns: a ``dict`` with the augmented data fields.
"""
# If the traptor is any other type, keep it going
new_dict = tweet_dict
self.logger.debug('Finding tweet rule matches')
# If the Traptor is a geo traptor, return the one rule we've already set up
if self.traptor_type == 'locations':
for key, value in self.locations_rule.iteritems():
new_dict['traptor'][key] = value
# Do track Traptor enrichments...
elif self.traptor_type == 'track':
"""
Here's how Twitter does it, and so shall we:
The text of the Tweet and some entity fields are considered for matches.
Specifically, the text attribute of the Tweet, expanded_url and display_url
for links and media, text for hashtags, and screen_name for user mentions
are checked for matches.
"""
# Build up the query from our tweet fields
query = ""
# Tweet text
query = query + tweet_dict['text'].encode("utf-8")
# URLs and Media
url_list = []
if 'urls' in tweet_dict['entities']:
for url in tweet_dict['entities']['urls']:
expanded_url = url.get('expanded_url', None)
display_url = url.get('display_url', None)
if expanded_url is not None:
url_list.append(expanded_url)
if display_url is not None:
url_list.append(display_url)
if 'media' in tweet_dict['entities']:
for item in tweet_dict['entities']['media']:
expanded_url = item.get('expanded_url', None)
display_url = item.get('display_url', None)
if expanded_url is not None:
url_list.append(expanded_url)
if display_url is not None:
url_list.append(display_url)
# Hashtags
if 'hashtags' in tweet_dict['entities']:
for tag in tweet_dict['entities']['hashtags']:
query = query + " " + tag['text'].encode("utf-8")
# Screen name
if 'screen_name' in tweet_dict['user']:
query = query + " " + tweet_dict['user']['screen_name'].encode('utf-8')
# Retweeted parts
if tweet_dict.get('retweeted_status', None) is not None:
# Status
query = query + " " + tweet_dict['retweeted_status']['text'].encode("utf-8")
if tweet_dict['retweeted_status'].get('quoted_status', {}).get('extended_tweet', {}).get('full_text', None) is not None:
query = query + " " + tweet_dict['retweeted_status']['quoted_status']['extended_tweet']['full_text'].encode("utf-8")
# URLs and Media
if 'urls' in tweet_dict['retweeted_status']['entities']:
for url in tweet_dict['retweeted_status']['entities']['urls']:
expanded_url = url.get('expanded_url', None)
display_url = url.get('display_url', None)
if expanded_url is not None:
url_list.append(expanded_url)
if display_url is not None:
url_list.append(display_url)
if 'media' in tweet_dict['retweeted_status']['entities']:
for item in tweet_dict['retweeted_status']['entities']['media']:
expanded_url = item.get('expanded_url', None)
display_url = item.get('display_url', None)
if expanded_url is not None:
url_list.append(expanded_url)
if display_url is not None:
url_list.append(display_url)
# Hashtags
if 'hashtags' in tweet_dict['retweeted_status']['entities']:
for tag in tweet_dict['retweeted_status']['entities']['hashtags']:
query = query + " " + tag['text'].encode("utf-8")
# Names
if 'in_reply_to_screen_name' in tweet_dict['retweeted_status']:
in_reply_to_screen_name = tweet_dict.get('retweeted_status', {}).get('in_reply_to_screen_name', None)
if in_reply_to_screen_name is not None:
query = query + " " + tweet_dict['retweeted_status']['in_reply_to_screen_name'].encode('utf-8')
if 'screen_name' in tweet_dict['retweeted_status']['user']:
screen_name = tweet_dict.get('retweeted_status', {}).get('user', {}).get('screen_name', None)
if screen_name is not None:
query = query + " " + tweet_dict['retweeted_status']['user']['screen_name'].encode('utf-8')
# Quoted Status parts
if tweet_dict.get('quoted_status', None) is not None:
# Standard tweet
if tweet_dict.get('quoted_status').get('text', None) is not None:
query = query + " " + tweet_dict['quoted_status']['text'].encode('utf-8')
# Extended tweet
if tweet_dict.get('quoted_status').get('extended_tweet', {}).get('full_text', None) is not None:
query = query + " " + tweet_dict['quoted_status']['extended_tweet']['full_text'].encode('utf-8')
# De-dup urls and add to the giant query
if len(url_list) > 0:
url_list = set(url_list)
for url in url_list:
query = query + " " + url.encode("utf-8")
# Lowercase the entire thing
query = query.lower()
random.shuffle(self.redis_rules)
try:
# Shuffle the rules every once in a while
for rule in self.redis_rules:
# Get the rule to search for and lowercase it
search_str = rule['value'].encode("utf-8").lower()
# Split the rule value and see if it's a multi-parter
part_finder = list()
search_str_multi = search_str.split(" ")
# If there is more than one part to the rule, check for each part in the query
if len(search_str_multi) > 1:
for part in search_str_multi:
if part in query:
part_finder.append(True)
else:
part_finder.append(False)
if len(search_str_multi) > 1 and all(part_finder):
# These two lines kept for backwards compatibility
new_dict['traptor']['rule_tag'] = rule['tag']
new_dict['traptor']['rule_value'] = rule['value'].encode("utf-8")
# Pass all key/value pairs from matched rule through to Traptor
for key, value in rule.iteritems():
new_dict['traptor'][key] = value.encode("utf-8")
# Log that a rule was matched
self.logger.debug("Rule matched for tweet id: {}".format(tweet_dict['id_str']))
elif search_str in query:
# These two lines kept for backwards compatibility
new_dict['traptor']['rule_tag'] = rule['tag']
new_dict['traptor']['rule_value'] = rule['value'].encode("utf-8")
# Pass all key/value pairs from matched rule through to Traptor
for key, value in rule.iteritems():
new_dict['traptor'][key] = value.encode("utf-8")
# Log that a rule was matched
self.logger.debug("Rule matched for tweet id: {}".format(tweet_dict['id_str']))
except:
self.logger.error("Caught exception while performing rule matching for track", extra={
'ex': traceback.format_exc()
})
dd_monitoring.increment('traptor_error_occurred',
tags=['error_type:rule_matching_failure'])
# If this is a follow Traptor, only check the user/id field of the tweet
elif self.traptor_type == 'follow':
"""
Here's how Twitter does it, and so shall we:
Tweets created by the user.
Tweets which are retweeted by the user.
Replies to any Tweet created by the user.
Retweets of any Tweet created by the user.
Manual replies, created without pressing a reply button (e.g. “@twitterapi I agree”).
"""
# Build up the query from our tweet fields
query = ""
# Tweets created by the user AND
# Tweets which are retweeted by the user
try:
self.logger.debug('tweet_dict for rule match',
extra={'tweet_dict': json.dumps(tweet_dict).encode("utf-8")})
except:
self.logger.error("Unable to dump the tweet dict to json", extra={
'ex': traceback.format_exc()
})
dd_monitoring.increment('traptor_error_occurred',
tags=['error_type:json_dumps'])
# From this user
query = query + str(tweet_dict['user']['id_str'])
# Replies to any Tweet created by the user.
if tweet_dict['in_reply_to_user_id'] is not None and tweet_dict['in_reply_to_user_id'] != '':
query = query + str(tweet_dict['in_reply_to_user_id'])
# User mentions
if 'user_mentions' in tweet_dict['entities']:
for tag in tweet_dict['entities']['user_mentions']:
id_str = tag.get('id_str')
if id_str:
query = query + " " + id_str.encode("utf-8")
# Retweeted parts
if tweet_dict.get('retweeted_status', None) is not None:
if tweet_dict['retweeted_status'].get('user', {}).get('id_str', None) is not None:
query = query + str(tweet_dict['retweeted_status']['user']['id_str'])
# Retweets of any Tweet created by the user; AND
# Manual replies, created without pressing a reply button (e.g. “@twitterapi I agree”).
query = query + tweet_dict['text'].encode("utf-8")
# Lowercase the entire thing
query = query.lower()
random.shuffle(self.redis_rules)
try:
for rule in self.redis_rules:
# Get the rule to search for and lowercase it
search_str = str(rule['value']).encode("utf-8").lower()
self.logger.debug("Search string used for the rule match: {}".format(search_str))
self.logger.debug("Query for the rule match: {}".format(query))
if search_str in query:
# These two lines kept for backwards compatibility
new_dict['traptor']['rule_tag'] = rule['tag']
new_dict['traptor']['rule_value'] = rule['value'].encode("utf-8")
# Pass all key/value pairs from matched rule through to Traptor
for key, value in rule.iteritems():
new_dict['traptor'][key] = value.encode("utf-8")
# Log that a rule was matched
self.logger.debug("Rule matched for tweet id: {}".format(tweet_dict['id_str']))
except:
self.logger.error("Caught exception while performing rule matching for follow", extra={
'ex': traceback.format_exc()
})
dd_monitoring.increment('traptor_error_occurred',
tags=['error_type:rule_matching_failure'])
# unknown traptor type
else:
self.logger.warning("Ran into an unknown Traptor type...")
if 'rule_tag' not in new_dict['traptor']:
new_dict['traptor']['rule_type'] = self.traptor_type
new_dict['traptor']['id'] = int(self.traptor_id)
new_dict['traptor']['rule_tag'] = 'Not Found'
new_dict['traptor']['rule_value'] = 'Not Found'
# Log that a rule was matched
self.logger.warning("No rule matched for tweet", extra={
'tweet_id': tweet_dict['id_str']
})
return new_dict
def kafka_success(tweet, response):
self.logger.info("Tweet sent to kafka", extra={
'tweet_id': tweet.get('id_str', None)
})
dd_monitoring.increment('tweet_to_kafka_success')
def main():
""" Command line interface to run a traptor instance.
Can pass it flags for debug levels and also --stdout mode, which means
it will not write to kafka but stdout instread.
"""
# Redis connections
redis_host = os.getenv('REDIS_HOST', 'localhost')
redis_port = int(os.getenv('REDIS_PORT', 6379))
redis_db = int(os.getenv('REDIS_DB', 5))
redis_conn = redis.StrictRedis(host=redis_host,
port=redis_port,
db=redis_db,
decode_responses=True)
# Redis pubsub connection
pubsub_conn = redis.StrictRedis(host=redis_host,
port=redis_port,
db=redis_db)
# Redis heartbeat connection
heartbeat_conn = redis.StrictRedis(host=redis_host,
port=redis_port,
db=redis_db)
# Twitter api keys
api_keys = {
'CONSUMER_KEY': os.getenv('CONSUMER_KEY'),
'CONSUMER_SECRET': os.getenv('CONSUMER_SECRET'),
'ACCESS_TOKEN': os.getenv('ACCESS_TOKEN'),
'ACCESS_TOKEN_SECRET': os.getenv('ACCESS_TOKEN_SECRET')
}
# Create the traptor instance
traptor_instance = Traptor(redis_conn=redis_conn,
pubsub_conn=pubsub_conn,
heartbeat_conn=heartbeat_conn,
traptor_notify_channel=os.getenv('REDIS_PUBSUB_CHANNEL', 'traptor-notify'),
rule_check_interval=int(os.getenv('RULE_CHECK_INTERVAL', 60)),
traptor_type=os.getenv('TRAPTOR_TYPE', 'track'),
traptor_id=int(os.getenv('TRAPTOR_ID', 0)),
apikeys=api_keys,
kafka_enabled=os.getenv('KAFKA_ENABLED', 'true'),
kafka_hosts=os.getenv('KAFKA_HOSTS', 'localhost:9092'),
kafka_topic=os.getenv('KAFKA_TOPIC', 'traptor'),
use_sentry=os.getenv('USE_SENTRY', 'false'),
sentry_url=os.getenv('SENTRY_URL', None),
test=False,
enable_stats_collection=os.getenv('ENABLE_STATS_COLLECTION', 'true')
)
# Logger for this main function. The traptor has it's own logger
traptor_name = 'traptor-{}-{}'.format(os.getenv('TRAPTOR_TYPE', 'track'),
os.getenv('TRAPTOR_ID', 0))
logger = LogFactory.get_instance(name=traptor_name,
json=os.getenv('LOG_JSON', settings.LOG_JSON) == 'True',
stdout=os.getenv('LOG_STDOUT', settings.LOG_STDOUT) == 'True',
level=os.getenv('LOG_LEVEL', settings.LOG_LEVEL),
dir=os.getenv('LOG_DIR', settings.LOG_DIR),
file=os.getenv('LOG_FILE', settings.LOG_FILE))
if settings.DW_ENABLED:
dw_config(settings.DW_CONFIG)
logger.register_callback('>=INFO', dw_callback)
# Wait until all the other containers are up and going...
time.sleep(30)
# Run the traptor instance
try:
logger.info('Starting Traptor')
logger.debug("Traptor info: {}".format(traptor_instance.__repr__()))
traptor_instance.run()
except Exception as e:
if os.getenv('USE_SENTRY') == 'true':
client = Client(os.getenv('SENTRY_URL'))
client.captureException()
logger.error("Caught exception when starting Traptor", extra={
'ex': traceback.format_exc()
})
dd_monitoring.increment('traptor_error_occurred',
tags=['error_type:traptor_start'])
raise e
