def __init__(self,
name=ev("PUBLISHER_NAME", "kombu-publisher"),
auth_url=ev("BROKER_URL", "redis://localhost:6379/0"),
ssl_options={},
max_general_failures=-1): # infinite retries
"""
Available Transports:
https://github.com/celery/kombu#transport-comparison
"""
self.state = "not_ready"
self.name = name
self.auth_url = auth_url
self.ssl_options = ssl_options
self.exchange = None
self.queue = None
self.declare_entities = []
self.conn = None
self.channel = None
self.producer = None
self.num_setup_failures = 0
self.num_publish_failures = 0
self.max_general_failures = max_general_failures
self.exchange_name = ""
self.exchange_type = "direct"
self.queue_name = ""
self.routing_key = ""
self.serializer = "json"
def __init__(self,
name="message-processor",
sub_auth_url=ev("SUB_BROKER_URL", "redis://localhost:6379/0"),
sub_ssl_options={},
sub_serializer="application/json",
sub_silent=False,
pub_auth_url=ev("PUB_BROKER_URL", "redis://localhost:6379/0"),
pub_ssl_options={},
pub_serializer="json",
pub_silent=False):
self.name = name
self.recv_msgs = []
self.sub_auth_url = sub_auth_url
self.pub_auth_url = pub_auth_url
self.sub_ssl_options = sub_ssl_options
self.pub_ssl_options = pub_ssl_options
self.sub_serializer = sub_serializer
self.pub_serializer = pub_serializer
self.pub_queue_name = None
self.sub = None
self.pub = None
self.exchange = None
self.exchange_name = ""
self.queue = None
self.queue_name = ""
self.routing_key = None
self.pub_routing_key = None
self.pub_hook_version = 1
self.sub_verbose = not sub_silent
self.pub_verbose = not pub_silent
def capture_arp_packets():
"""capture_arp_packets
Capture ``ARP`` packets and call the ``handle_packets`` method
Change the network interface by ``export CAP_DEVICE=eth0``
"""
dev = ev("CAP_DEVICE", "lo")
"""
Ignore ports for forwarding to consolidators:
Redis VM: 6379, 16379
RabbitMQ VM: 5672, 15672, 25672
"""
# http://biot.com/capstats/bpf.html
default_filter = "arp"
custom_filter = ev("NETWORK_FILTER", default_filter)
log.info(("starting device={} filter={}").format(dev, custom_filter))
scapy.sniff(filter=custom_filter, prn=handle_packets)
log.info("done")
def example_capture():
"""example_capture
An example capture script
Change the network interface by ``export CAP_DEVICE=eth0``
"""
dev = ev("CAP_DEVICE", "lo")
"""
Ignore ports for forwarding to consolidators:
Redis Internal VM: 6379, 16379
RabbitMQ Internal VM: 5672, 15672, 25672
"""
# http://biot.com/capstats/bpf.html
custom_filter = ("(udp and portrange 10000-17001) "
"or (tcp and portrange 80) "
"or arp "
"or icmp")
log.info(("starting device={} filter={}").format(dev, custom_filter))
scapy.sniff(filter=custom_filter, prn=handle_packets)
log.info("done")
def __init__(self,
name=ev("SUBSCRIBER_NAME", "celery-subscriber"),
auth_url=ev("BROKER_URL", "redis://localhost:6379/0"),
app=None,
ssl_options={},
transport_options={},
worker_log_format="%(asctime)s: %(levelname)s %(message)s",
**kwargs):
"""
Available Brokers:
http://docs.celeryproject.org/en/latest/getting-started/brokers/index.html
Redis:
http://docs.celeryproject.org/en/latest/getting-started/brokers/redis.html
RabbitMQ:
http://docs.celeryproject.org/en/latest/getting-started/brokers/rabbitmq.html
SQS:
http://docs.celeryproject.org/en/latest/getting-started/brokers/sqs.html
"""
self.state = "not_ready"
self.name = name
self.auth_url = auth_url
self.ssl_options = ssl_options
self.transport_options = transport_options
self.subscriber_app = None
# allow passing in an initialized Celery application
if app:
self.subscriber_app = app
else:
self.subscriber_app = Celery()
# update the celery configuration from the kwargs dictionary
self.subscriber_app.conf.update(kwargs)
# make sure to set the broker_url
self.subscriber_app.conf.broker_url = self.auth_url
self.subscriber_app.conf.worker_log_format = worker_log_format
self.exchange = None
self.consume_from_queues = []
def __init__(self,
name=ev("SUBSCRIBER_NAME", "kombu-subscriber"),
auth_url=ev("BROKER_URL", "redis://localhost:6379/0"),
ssl_options={},
max_general_failures=-1): # infinite retries
"""
Available Brokers:
http://docs.celeryproject.org/en/latest/getting-started/brokers/index.html
Redis:
http://docs.celeryproject.org/en/latest/getting-started/brokers/redis.html
RabbitMQ:
http://docs.celeryproject.org/en/latest/getting-started/brokers/rabbitmq.html
SQS:
http://docs.celeryproject.org/en/latest/getting-started/brokers/sqs.html
"""
self.state = "not_ready"
self.name = name
self.auth_url = auth_url
self.ssl_options = ssl_options
self.conn = None
self.new_conn = None
self.channel = None
self.consumer = None
self.process_message_callback = None
self.drain_time = 1.0
self.num_setup_failures = 0
self.num_consume_failures = 0
self.max_general_failures = max_general_failures
self.exchange = None
self.exchange_name = ""
self.routing_key = ""
self.serializer = "json"
self.queue = None
self.queue_name = ""
self.consume_from_queues = []
def build_ssl_options(ca_cert="",
keyfile="",
certfile="",
ssl_required="0"):
use_ca_certs = ev("SSL_CA_CERT", ca_cert)
use_keyfile = ev("SSL_KEYFILE", keyfile)
use_certfile = ev("SSL_CERTFILE", certfile)
use_ssl_required = ev("SSL_REQUIRED", ssl_required) == "1"
ssl_options = {}
if use_ca_certs:
ssl_options["ca_certs"] = use_ca_certs
if use_keyfile:
ssl_options["keyfile"] = use_keyfile
if use_certfile:
ssl_options["certfile"] = use_certfile
if use_ssl_required:
ssl_options["cert_reqs"] = ssl.CERT_REQUIRED
return ssl_options
def setUp(self):
if self.debug:
print("setUp")
# state trips in the custom classes
os.environ["TEST_STOP_DONE"] = "1"
self.last_pub_msg = None
self.last_sub_msg = None
self.pub = None
self.sub = None
self.pub_msgs = []
self.sub_msgs = []
self.exchange_name = ev("TEST_EXCHANGE", "test.events")
self.routing_key = ev("TEST_ROUTING_KEY", "test.events.conversions")
self.queue_name = ev("TEST_QUEUE", "test.events.conversions")
self.exchange = None
self.queue = None
self.last_sub_callback = None
def relay_callback(body, message):
pub_auth_url = ev("RELAY_WORKER_BROKER_URL",
"pyamqp://*****:*****@localhost:5672//")
pub_backend_url = ev("RELAY_BACKEND_URL", "redis://localhost:6379/12")
path_to_config_module = ev("RELAY_CONFIG_MODULE",
"ecomm_app.ecommerce.celeryconfig_pub_sub")
app = ecomm_app.ecommerce.tasks.get_celery_app(
name=ev("RELAY_NAME", "ecomm-relay"),
auth_url=pub_auth_url,
backend_url=pub_backend_url,
path_to_config_module=path_to_config_module)
task_name = ev("RELAY_TASK_NAME",
"ecomm_app.ecommerce.tasks.handle_user_conversion_events")
now = datetime.now().isoformat()
body = {
"account_id": 999,
"subscription_id": 321,
"stripe_id": 876,
"created": now,
"product_id": "JJJ",
"version": 1,
"org_msg": body,
"msg_id": str(uuid.uuid4())
}
source_info = {"msg_proc": ev("RELAY_NAME", "ecomm_relay")}
log.info(("Sending broker={} "
"body={}").format(app.conf.broker_url, body))
result = app.send_task(task_name, (body, source_info))
if "simulate_processing_lag" in body:
log.info(("task - {} - simulating processing"
"lag={} sleeping").format(task_name,
body["simulate_processing_lag"]))
time.sleep(float(body["simulate_processing_lag"]))
# end of handling adding artifical lag for testing Celery
log.info(("Done with msg_id={} result={}").format(body["msg_id"],
result.get()))
# now that the message has been
# sent to the celery ecomm worker
# we can ack the message which
# deletes it from the source queue
# the message processor uses
message.ack()
recv_msgs = []
def handle_message(body, message):
log.info(("callback received msg " "body={}").format(body))
recv_msgs.append(body)
message.ack()
# end of handle_message
# Initialize KombuSubscriber
# http://docs.celeryproject.org/en/latest/getting-started/brokers/sqs.html
# https://github.com/celery/kombu/blob/master/kombu/transport/SQS.py
aws_key = ev("SQS_AWS_ACCESS_KEY", "not_a_key")
aws_secret = ev("SQS_AWS_SECRET_KEY", "not_a_secret")
sqs_auth_url = ev("BROKER_URL", "sqs://{}:{}@".format(aws_key, aws_secret))
transport_options = {}
ssl_options = {}
sub = KombuSubscriber("kombu-sqs-subscriber", sqs_auth_url, ssl_options)
# sample: "sqs://*****:*****@"
# ^ from the doc: 'you must remember to include the "@" at the end.'
# Now consume:
seconds_to_consume = 10.0
serializer = "application/json"
queue = "test1"
exchange = "test1"
recv_msgs = []
def handle_message(body, message):
log.info(("callback received msg "
"body={}")
.format(body))
recv_msgs.append(body)
message.ack()
# end of handle_message
# Initialize KombuSubscriber
ssl_options = {}
sub = KombuSubscriber("kombu-mixin-subscriber",
ev("SUB_BROKER_URL",
"amqp://*****:*****@localhost:5672//"),
ssl_options)
# Now consume:
seconds_to_consume = 10.0
heartbeat = 60
serializer = "application/json"
exchange = ev("CONSUME_EXCHANGE", "reporting.payments")
routing_key = ev("CONSUME_ROUTING_KEY", "reporting.payments")
queue = ev("CONSUME_QUEUE", "reporting.payments")
sub.consume(callback=handle_message,
queue=queue,
exchange=exchange,
routing_key=routing_key,
serializer=serializer,
from kombu.mixins import ConsumerProducerMixin
from celery_connectors.utils import ev
from celery_connectors.utils import build_msg
from celery_connectors.utils import get_exchange_from_msg
from celery_connectors.utils import get_routing_key_from_msg
from celery_connectors.run_publisher import run_publisher
# Credits and inspirations from these great sources:
#
# https://github.com/celery/kombu/blob/master/examples/rpc-tut6/rpc_server.py
# https://gist.github.com/oubiwann/3843016
# https://gist.github.com/eavictor/ee7856581619ac60643b57987b7ed580#file-mq_kombu_rpc_server-py
# https://github.com/Skablam/kombu-examples
# https://gist.github.com/mlavin/6671079
log = logging.getLogger(ev("APP_NAME", "relay"))
class RelayWorker(ConsumerProducerMixin):
def __init__(self,
name="relay",
conn=None,
callback=None,
task_queues=[],
prefetch_count=1,
relay_exchange=None,
relay_exchange_type=None,
relay_routing_key=None,
relay_queue=None,
relay_broker_url=None,
relay_ssl_options={},
def publish_processed_network_packets(name="not-set",
task_queue=None,
result_queue=None,
need_response=False,
shutdown_msg="SHUTDOWN"):
"""
# Redis/RabbitMQ/SQS messaging endpoints for pub-sub
routing_key = ev("PUBLISH_EXCHANGE",
"reporting.accounts")
queue_name = ev("PUBLISH_QUEUE",
"reporting.accounts")
auth_url = ev("PUB_BROKER_URL",
"redis://localhost:6379/0")
serializer = "json"
"""
# these keys need to be cycled to prevent
# exploiting static keys
filter_key = ev("IGNORE_KEY", INCLUDED_IGNORE_KEY)
forward_host = ev("FORWARD_HOST", "127.0.0.1")
forward_port = int(ev("FORWARD_PORT", "80"))
include_filter_key = ev("FILTER_KEY", "")
if not include_filter_key and filter_key:
include_filter_key = filter_key
filter_keys = [filter_key]
log.info(("START consumer={} "
"forward={}:{} with "
"key={} filters={}").format(name, forward_host, forward_port,
include_filter_key, filter_key))
forward_skt = None
not_done = True
while not_done:
if not forward_skt:
forward_skt = connect_forwarder(forward_host=forward_host,
forward_port=forward_port)
next_task = task_queue.get()
if next_task:
if str(next_task) == shutdown_msg:
# Poison pill for shutting down
log.info(("{}: DONE CALLBACK "
"Exiting msg={}").format(name, next_task))
task_queue.task_done()
break
# end of handling shutdown case
try:
log.debug(("{} parsing").format(name))
source = next_task.source
packet = next_task.payload
if not packet:
log.error(("{} invalid task found "
"{} missing payload").format(name, next_task))
break
log.debug(("{} found msg from src={}").format(name, source))
network_data = parse_network_data(
data_packet=packet,
include_filter_key=include_filter_key,
filter_keys=filter_keys)
if network_data["status"] == VALID:
if network_data["data_type"] == TCP \
or network_data["data_type"] == UDP \
or network_data["data_type"] == ARP \
or network_data["data_type"] == ICMP:
log.info(
("{} valid={} packet={} "
"data={}").format(name, network_data["id"],
network_data["data_type"],
network_data["target_data"]))
if not forward_skt:
forward_skt = connect_forwarder(
forward_host=forward_host,
forward_port=forward_port)
if forward_skt:
if network_data["stream"]:
sent = False
while not sent:
try:
log.info("sending={}".format(
network_data["stream"]))
send_msg(
forward_skt,
network_data["stream"].encode(
"utf-8"))
sent = True
except Exception as e:
sent = False
time.sleep(0.5)
try:
forward_skt.close()
forward_skt = None
except Exception as w:
forward_skt = None
forward_skt = connect_forwarder(
forward_host=forward_host,
forward_port=forward_port)
# end of reconnecting
log.info("sent={}".format(
network_data["stream"]))
if need_response:
log.info("receiving")
cdr_res = forward_skt.recv(1024)
log.info(("cdr - res{}").format(cdr_res))
else:
log.info(("{} EMPTY stream={} "
"error={} status={}").format(
name, network_data["stream"],
network_data["err"],
network_data["status"]))
else:
log.info(("{} not_supported valid={} "
"packet data_type={} status={}").format(
name, network_data["id"],
network_data["data_type"],
network_data["status"]))
elif network_data["status"] == FILTERED:
log.info(("{} filtered={} status={}").format(
name, network_data["filtered"],
network_data["status"]))
else:
if network_data["status"] == INVALID:
log.info(("{} invalid={} packet={} "
"error={} status={}").format(
name, network_data["id"],
network_data["data_type"],
network_data["error"],
network_data["status"]))
else:
log.info(("{} unknown={} packet={} "
"error={} status={}").format(
name, network_data["id"],
network_data["data_type"],
network_data["error"],
network_data["status"]))
# end of if valid or not data
except KeyboardInterrupt as k:
log.info(("{} stopping").format(name))
break
except Exception as e:
log.error(("{} failed packaging packet to forward "
"with ex={}").format(name, e))
break
# end of try/ex during payload processing
# end of if found a next_task
log.info(("Consumer: {} {}").format(name, next_task))
task_queue.task_done()
if need_response:
answer = "processed: {}".format(next_task())
result_queue.put(answer)
# end of while
if forward_skt:
try:
forward_skt.close()
log.info("CLOSED connection")
forward_skt = None
except Exception:
log.info("CLOSED connection")
# end of cleaning up forwarding socket
log.info("{} Done".format(name))
return
def build_new_deep_neural_network_from_env_variables():
"""build_new_deep_neural_network_from_env_variables
Build a new deep neural network from environment variables:
``CSV_FILE`` - file to process created during prepare dataset
``CSV_META_FILE`` - metadata header file created during prepare dataset
``PREDICT_FEATURE`` - column to predict
``TEST_SIZE`` - split data into percentage of test to training
"""
csv_file = ev("CSV_FILE", "/tmp/cleaned_attack_scans.csv")
meta_file = ev("CSV_META_FILE", "/tmp/cleaned_metadata.json")
predict_feature = ev("PREDICT_FEATURE", "label_value")
test_size = float(ev("TEST_SIZE", "0.20"))
if not os.path.exists(csv_file):
log.error(("missing csv_file={}").format(csv_file))
sys.exit(1)
res = build_training_request(csv_file=csv_file,
meta_file=meta_file,
predict_feature=predict_feature,
test_size=test_size)
if res["status"] != VALID:
log.error(("Stopping for status={} "
"errors: {}").format(res["status"], res["err"]))
sys.exit(1)
else:
log.info(("built_training_request={} "
"features={} ignore={}").format(res["status"],
res["features_to_process"],
res["ignore_features"]))
# end of validating the training request
log.info("ready for training")
log.info("creating Keras - sequential model")
# create the model
model = Sequential()
model.add(
Dense(8,
input_dim=len(res["features_to_process"]),
kernel_initializer="uniform",
activation="relu"))
model.add(Dense(6, kernel_initializer="uniform", activation="relu"))
model.add(Dense(1, kernel_initializer="uniform", activation="sigmoid"))
log.info("compiling model")
# compile the model
model.compile(loss="binary_crossentropy",
optimizer="adam",
metrics=["accuracy"])
log.info("fitting model - please wait")
# fit the model
model.fit(res["X_train"],
res["Y_train"],
validation_data=(res["X_test"], res["Y_test"]),
epochs=50,
batch_size=2,
verbose=1)
# evaluate the model
scores = model.evaluate(res["X_test"], res["Y_test"])
log.info(("Accuracy: {}").format(scores[1] * 100))
from celery_connectors.utils import ERROR
from celery_connectors.utils import ev
from celery_connectors.utils import build_sample_msgs
from celery_connectors.utils import calc_backoff_timer
from celery_connectors.build_ssl_options import build_ssl_options
# Credits and inspirations from these great sources:
#
# https://github.com/celery/kombu/blob/master/examples/rpc-tut6/rpc_server.py
# https://gist.github.com/oubiwann/3843016
# https://gist.github.com/eavictor/ee7856581619ac60643b57987b7ed580#file-mq_kombu_rpc_server-py
# https://github.com/Skablam/kombu-examples
# https://gist.github.com/mlavin/6671079
name = ev("APP_NAME", "robopubsub")
log = build_colorized_logger(
name=name)
broker_url = ev("PUB_BROKER_URL", "pyamqp://*****:*****@localhost:5672//")
exchange_name = ev("PUBLISH_EXCHANGE", "ecomm.api")
exchange_type = ev("PUBLISH_EXCHANGE_TYPE", "topic")
routing_key = ev("PUBLISH_ROUTING_KEY", "ecomm.api.west")
queue_name = ev("PUBLISH_QUEUE", "ecomm.api.west")
prefetch_count = int(ev("PREFETCH_COUNT", "1"))
priority_routing = {"high": queue_name,
"low": queue_name}
use_exchange = Exchange(exchange_name, type=exchange_type)
use_routing_key = routing_key
use_queue = Queue(queue_name, exchange=use_exchange, routing_key=routing_key)
import logging
from kombu import Connection
from celery_connectors.utils import ev
from celery_connectors.relay_json_to_celery_worker import RelayJSONtoCeleryWorker
# Credits and inspirations from these great sources:
#
# https://github.com/celery/kombu/blob/master/examples/rpc-tut6/rpc_server.py
# https://gist.github.com/oubiwann/3843016
# https://gist.github.com/eavictor/ee7856581619ac60643b57987b7ed580#file-mq_kombu_rpc_server-py
# https://github.com/Skablam/kombu-examples
# https://gist.github.com/mlavin/6671079
log = logging.getLogger(ev("APP_NAME", "jtoc"))
def run_jtoc_relay(broker_url,
ssl_options={},
transport_options={},
task_queues=[],
callback=None,
prefetch_count=1,
relay_broker_url=None,
relay_backend_url=None,
relay_exchange=None,
relay_routing_key=None,
relay_handler=None,
celery_app=None,
*args,
**kwargs):
from spylunking.log.setup_logging import build_colorized_logger
from celery_connectors.utils import ev
from celery_connectors.utils import build_sample_msgs
from celery_connectors.build_ssl_options import build_ssl_options
from celery_connectors.run_publisher import run_publisher
# Credits and inspirations from these great sources:
#
# https://github.com/celery/kombu/blob/master/examples/rpc-tut6/rpc_server.py
# https://gist.github.com/oubiwann/3843016
# https://gist.github.com/eavictor/ee7856581619ac60643b57987b7ed580#file-mq_kombu_rpc_server-py
# https://github.com/Skablam/kombu-examples
# https://gist.github.com/mlavin/6671079
name = ev("APP_NAME", "robopub")
log = build_colorized_logger(
name=name)
broker_url = ev("PUB_BROKER_URL", "pyamqp://*****:*****@localhost:5672//")
exchange_name = ev("PUBLISH_EXCHANGE", "")
exchange_type = ev("PUBLISH_EXCHANGE_TYPE", "")
routing_key = ev("PUBLISH_ROUTING_KEY", "reporting.accounts")
queue_name = ev("PUBLISH_QUEUE", "reporting.accounts")
priority_routing = {"high": queue_name}
use_exchange = Exchange(exchange_name, type=exchange_type)
use_routing_key = routing_key
use_queue = Queue(queue_name, exchange=use_exchange, routing_key=routing_key)
task_queues = [
use_queue
from kombu import Exchange, Queue
from spylunking.log.setup_logging import build_colorized_logger
from celery_connectors.utils import ev
from celery_connectors.build_ssl_options import build_ssl_options
from celery_connectors.run_jtoc_relay import run_jtoc_relay
# Credits and inspirations from these great sources:
#
# https://github.com/celery/kombu/blob/master/examples/rpc-tut6/rpc_server.py
# https://gist.github.com/oubiwann/3843016
# https://gist.github.com/eavictor/ee7856581619ac60643b57987b7ed580#file-mq_kombu_rpc_server-py
# https://github.com/Skablam/kombu-examples
# https://gist.github.com/mlavin/6671079
name = ev("APP_NAME", "jtoc_relay")
log = build_colorized_logger(name=name)
broker_url = ev("SUB_BROKER_URL",
"pyamqp://*****:*****@localhost:5672//")
exchange_name = ev("CONSUME_EXCHANGE", "ecomm.api")
exchange_type = ev("CONSUME_EXCHANGE_TYPE", "topic")
routing_key = ev("CONSUME_ROUTING_KEY", "ecomm.api.west")
queue_name = ev("CONSUME_QUEUE", "ecomm.api.west")
prefetch_count = int(float(ev("PREFETCH_COUNT", "1")))
priority_routing = {"high": queue_name, "low": queue_name}
use_exchange = Exchange(exchange_name, type=exchange_type)
use_queue = Queue(queue_name, exchange=use_exchange, routing_key=routing_key)
task_queues = [use_queue]
ssl_options = build_ssl_options()
def test_rabbitmq_consuming(self):
# Integration Test the Subscriber Processor
# This test just fills the queue for processing
num_to_consume = 50000
num_sent = 0
num_to_send = num_to_consume
msgs_to_send = []
msgs_by_id = {}
self.exchange_name = ev("LOAD_TEST_EXCHANGE", "reporting")
self.routing_key = ev("LOAD_TEST_ROUTING_KEY", "reporting.accounts")
self.queue_name = ev("LOAD_TEST_QUEUE", "reporting.accounts")
log.info(("Publishing {}/{} "
"ex={} rk={} broker={}").format(num_sent, num_to_send,
self.exchange_name,
self.routing_key,
self.pub_auth_url))
pub_retry = True
not_done_publishing = True
test_values = {"test_name": "large messages"}
if len(msgs_to_send) == 0:
while len(msgs_to_send) != num_to_send:
test_msg = self.build_user_conversion_event_msg(test_values)
msgs_to_send.append(test_msg)
msgs_by_id[test_msg["msg_id"]] = False
# end of building messages before slower publishing calls
while not_done_publishing:
if (num_sent % 1000 == 0) and num_sent > 0:
log.info(("Published {} for "
"{}/{} messages").format(
get_percent_done(num_sent, num_to_send),
num_sent, num_to_send))
# end of if print for tracing
msg_body = None
if num_sent < len(msgs_to_send):
msg_body = msgs_to_send[num_sent]
self.publish(body=msg_body,
exchange=self.exchange_name,
routing_key=self.routing_key,
queue=self.queue_name,
priority=0,
ttl=None,
serializer=self.pub_serializer,
retry=pub_retry)
num_sent += 1
if num_sent >= num_to_send:
log.info(("Published {} ALL "
"{}/{} messages").format(
get_percent_done(num_sent, num_to_send),
num_sent, num_to_send))
not_done_publishing = False
elif num_sent >= len(msgs_to_send):
log.info(("Published {} all "
"{}/{} messages").format(
get_percent_done(num_sent, len(msgs_to_send)),
num_sent, num_to_send))
not_done_publishing = False
# if should stop
# end of not_done_publishing
assert (num_sent == num_to_consume)
os.system("list-queues.sh")
log.info("")
log.info(("display messages in the queues "
"with routing_key={} again with:").format(self.routing_key))
log.info("list-queues.sh")
log.info("")
def __init__(self):
"""__init__"""
self.recv_msgs = []
# save every nth number of messages
self.save_after_num = int(
ev("SAVE_AFTER_NUM",
"100"))
# shutdown after this number of messages
self.stop_after_num = int(
ev("STOP_AFTER_NUM",
"-1"))
if self.save_after_num < 0:
self.save_after_num = 1
if self.stop_after_num < 0:
self.stop_after_num = None
# shutdown if this file is found
self.stop_for_file = ev(
"STOP_FILE",
"/tmp/stop-recording-csv")
self.dataset_name = ev(
"DS_NAME",
"netdata")
self.save_dir = ev(
"DS_DIR",
"/tmp")
self.save_to_file = ev(
"OUTPUT_CSV",
"{}/{}-{}.csv".format(
self.save_dir,
self.dataset_name,
rnow("%Y-%m-%d-%H-%M-%S")))
self.archive_file = ev(
"ARCHIVE_JSON",
"{}/packets-{}-{}.json".format(
self.save_dir,
self.dataset_name,
rnow("%Y-%m-%d-%H-%M-%S")))
self.debug = bool(ev(
"DEBUG_PACKETS",
"0") == "1")
self.df = None
self.last_df = None
self.eth_keys = {"eth_id": "id"}
self.ip_keys = {"ip_id": "id"}
self.ipvsix_keys = {"ipvsix_id": "id"}
self.icmp_keys = {"icmp_id": "id"}
self.arp_keys = {"arp_id": "id"}
self.tcp_keys = {"tcp_id": "id"}
self.udp_keys = {"udp_id": "id"}
self.dns_keys = {"dns_id": "id"}
self.raw_keys = {"raw_id": "id"}
self.pad_keys = {"pad_id": "id"}
self.all_keys = {}
self.all_keys_list = []
self.all_eth = []
self.all_ip = []
self.all_ipvsix = []
self.all_icmp = []
self.all_arp = []
self.all_tcp = []
self.all_udp = []
self.all_dns = []
self.all_raw = []
self.all_pad = []
self.all_flat = []
self.all_rows = []
# noqa https://github.com/jay-johnson/antinex-client/blob/5fbcefaaed3d979b3c0829447b61592d5910ef22/antinex_client/build_ai_client_from_env.py#L19
self.client = build_ai_client_from_env()
# the client uses environment variables:
# noqa https://github.com/jay-johnson/antinex-client/blob/5fbcefaaed3d979b3c0829447b61592d5910ef22/antinex_client/consts.py#L23
# here is an example of what to export:
# noqa https://github.com/jay-johnson/antinex-client/blob/master/examples/example-prediction.env
self.request_dict = {}
if ANTINEX_PUBLISH_ENABLED:
if os.path.exists(ANTINEX_PUBLISH_REQUEST_FILE):
with open(ANTINEX_PUBLISH_REQUEST_FILE, "r") as f:
self.request_dict = json.loads(f.read())
#!/usr/bin/env python
from spylunking.log.setup_logging import build_colorized_logger
from celery_connectors.utils import ev
from celery_connectors.message_processor import MessageProcessor
name = "msg-proc"
log = build_colorized_logger(name=name)
log.info("Start - {}".format(name))
# want to change where you're subscribing vs publishing?
sub_ssl_options = {}
sub_auth_url = ev("SUB_BROKER_URL", "redis://localhost:6379/0")
pub_ssl_options = {}
pub_auth_url = ev("PUB_BROKER_URL", "redis://localhost:6379/0")
# start the message processor
msg_proc = MessageProcessor(name=name,
sub_auth_url=sub_auth_url,
sub_ssl_options=sub_ssl_options,
pub_auth_url=pub_auth_url,
pub_ssl_options=pub_ssl_options)
# configure where this is consuming:
queue = ev("CONSUME_QUEUE", "user.events.conversions")
# Relay Publish Hook - is disabled for this example
# where is it sending handled messages using a publish-hook or auto-caching:
exchange = None
routing_key = None
def handle_relay(self,
body={},
message={},
relay_exchange=None,
relay_routing_key=None,
serializer="json",
src_exchange=None,
src_routing_key=None):
"""
Allow derived classes to customize
how they 'handle_relay'
"""
task_result = None
last_step = "validating"
if not relay_exchange and not relay_routing_key:
log.error(("Relay is misconfigured: please set either a "
"relay_exchange={} or a relay_routing_key={}").format(
relay_exchange, relay_routing_key))
return False
try:
last_step = "setting up base relay payload"
base_relay_payload = {"org_msg": body, "relay_name": self.name}
if self.verbose:
log.debug("build relay_payload")
last_step = "building relay payload"
relay_payload = build_msg(base_relay_payload)
if self.verbose:
log.info(("relay ex={} rk={} id={}").format(
relay_exchange, relay_routing_key,
relay_payload["msg_id"]))
last_step = "setting up task"
task_name = ev(
"RELAY_TASK_NAME",
"ecomm_app.ecommerce.tasks." + "handle_user_conversion_events")
if "task_name" in body:
task_name = body["task_name"]
now = datetime.datetime.now().isoformat()
use_msg_id = ""
if "msg_id" in body:
use_msg_id = body["msg_id"]
else:
use_msg_id = relay_payload["msg_id"]
source_info = {
"relay": self.name,
"src_exchange": src_exchange,
"src_routing_key": src_routing_key
}
publish_body = {
"account_id": 999,
"subscription_id": 321,
"stripe_id": 876,
"created": now,
"product_id": "JJJ",
"version": 1,
"r_id": relay_payload["msg_id"],
"msg_id": use_msg_id
}
if self.verbose:
log.info(("relay msg_id={} body={} "
"broker={} backend={}").format(
use_msg_id, publish_body, self.relay_broker_url,
self.relay_transport_options))
else:
log.info(("relay msg_id={} body={}").format(
use_msg_id,
str(publish_body)[0:30]))
last_step = "send start - app"
# http://docs.celeryproject.org/en/latest/reference/celery.html#celery.Celery
app = Celery(
broker=self.relay_broker_url,
backend=self.relay_backend_url,
transport_otions=self.relay_transport_options,
task_ignore_result=True) # needed for cleaning up task results
# these are targeted at optimizing processing on long-running tasks
# while increasing reliability
# http://docs.celeryproject.org/en/latest/userguide/configuration.html#std:setting-worker_prefetch_multiplier
app.conf.worker_prefetch_multiplier = 1
# http://docs.celeryproject.org/en/latest/userguide/configuration.html#std:setting-broker_heartbeat
app.conf.broker_heartbeat = 240 # seconds
# http://docs.celeryproject.org/en/latest/userguide/configuration.html#std:setting-broker_connection_max_retries
app.conf.broker_connection_max_retries = None
# http://docs.celeryproject.org/en/latest/userguide/configuration.html#std:setting-task_acks_late
app.conf.task_acks_late = True
# http://docs.celeryproject.org/en/latest/userguide/calling.html#calling-retry
task_publish_retry_policy = {
"interval_max": 1,
"max_retries": 120, # None - forever
"interval_start": 0.1,
"interval_step": 0.2
}
app.conf.task_publish_retry_policy = task_publish_retry_policy
last_step = "send start - task={}".format(task_name)
with app.producer_or_acquire(producer=None) as producer:
"""
http://docs.celeryproject.org/en/latest/reference/celery.app.task.html#celery.app.task.Task.apply_async
retry (bool) – If enabled sending of the task message will be
retried in the event of connection loss or failure.
Default is taken from the task_publish_retry setting.
Note that you need to handle the producer/connection
manually for this to work.
With a redis backend connection on
restore of a broker the first time it appears to
hang here indefinitely:
task_result.get()
Please avoid getting the relay task results
until this is fixed
"""
task_result = app.send_task(task_name,
(publish_body, source_info),
retry=True,
producer=producer,
expires=300)
# end of app producer block
last_step = "send done - task={}".format(task_name)
if task_result:
log.info(("relay done with msg_id={}").format(body["msg_id"]))
if "relay_simulate_processing_lag" in body["data"]:
relay_sleep_duration = \
body["data"]["relay_simulate_processing_lag"]
log.info(("task - {} - simulating processing lag "
"sleep={} seconds").format(task_name,
relay_sleep_duration))
time.sleep(float(relay_sleep_duration))
# end of handling adding artifical lag for testing Celery
if self.verbose:
if "msg_id" in body:
log.info(
("relay done - "
"msg_id={} r_id={}").format(use_msg_id,
relay_payload["msg_id"]))
else:
log.info(("relay done - "
"msg_id={} r_id={}"
"body={}").format(use_msg_id,
relay_payload["msg_id"],
str(body)[0:30]))
# end of logging
except Exception as e:
log.error(("Task Relay failed: with ex={} when sending "
"to relay_exchange={} relay_routing_key={} "
"last_step={}").format(e, relay_exchange,
relay_routing_key, last_step))
return False
# end of try/ex
return True
conn_attrs = {
"task_default_queue": "celery.redis.sub",
"task_default_exchange": "celery.redis.sub",
# http://docs.celeryproject.org/en/latest/userguide/configuration.html#std:setting-worker_prefetch_multiplier
"worker_prefetch_multiplier": 1, # consume 1 message at a time
# http://docs.celeryproject.org/en/latest/userguide/configuration.html#std:setting-worker_prefetch_multiplier
"prefetch_count": 3, # consume 1 message at a time per worker (3 workers)
# http://docs.celeryproject.org/en/latest/userguide/configuration.html#std:setting-broker_heartbeat
"broker_heartbeat": 240, # in seconds
# http://docs.celeryproject.org/en/latest/userguide/configuration.html#std:setting-broker_connection_max_retries
"broker_connection_max_retries": None, # None is forever
# http://docs.celeryproject.org/en/latest/userguide/configuration.html#std:setting-task_acks_late
"task_acks_late": True, # on consume do not send an immediate ack back
"task_publish_retry_policy": task_publish_retry_policy
}
app = Celery()
sub = Subscriber("redis-subscriber",
ev("SUB_BROKER_URL", "redis://localhost:6379/0"), app,
ssl_options, **conn_attrs)
# Now consume:
queue = ev("CONSUME_QUEUE", "reporting.accounts")
sub.consume(callback=handle_message,
queue=queue,
exchange=None,
routing_key=None,
prefetch_count=conn_attrs["prefetch_count"])
log.info("End - {}".format(name))
def prepare_new_dataset():
"""prepare_new_dataset"""
clean_dir = ev(
"OUTPUT_DIR",
"/tmp")
clean_file = ev(
"CLEANED_FILE",
"{}/cleaned_attack_scans.csv".format(
clean_dir))
fulldata_file = ev(
"FULLDATA_FILE",
"{}/fulldata_attack_scans.csv".format(
clean_dir))
dataset_dir = ev(
"DS_DIR",
"/opt/antinex/datasets")
csv_glob_path = ev(
"DS_GLOB_PATH",
"{}/*/*.csv".format(
dataset_dir))
pipeline_files = find_all_pipeline_csvs(
csv_glob_path=csv_glob_path)
post_proc_rules = {
"drop_columns": [
"src_file",
"raw_id",
"raw_load",
"raw_hex_load",
"raw_hex_field_load",
"pad_load",
"eth_dst", # need to make this an int
"eth_src", # need to make this an int
"ip_dst", # need to make this an int
"ip_src" # need to make this an int
],
"predict_feature": "label_name"
}
label_rules = {
"set_if_above": 85,
"labels": ["not_attack", "attack"],
"label_values": [0, 1]
}
log.info("building csv")
save_node = build_csv(
pipeline_files=pipeline_files,
fulldata_file=fulldata_file,
clean_file=clean_file,
post_proc_rules=post_proc_rules,
label_rules=label_rules)
if save_node["status"] == VALID:
log.info("Successfully process datasets:")
if ev("SHOW_SUMMARY", "1") == "1":
log.info(("Full csv: {}")
.format(save_node["fulldata_file"]))
log.info(("Full meta: {}")
.format(save_node["fulldata_metadata_file"]))
log.info(("Clean csv: {}")
.format(save_node["clean_file"]))
log.info(("Clean meta: {}")
.format(save_node["clean_metadata_file"]))
log.info("------------------------------------------")
log.info(("Predicting Feature: {}")
.format(save_node["feature_to_predict"]))
log.info(("Features to Process: {}")
.format(ppj(save_node["features_to_process"])))
log.info(("Ignored Features: {}")
.format(ppj(save_node["ignore_features"])))
log.info("------------------------------------------")
# end of show summary
log.info("")
log.info("done saving csv:")
log.info("Full: {}".format(
save_node["fulldata_file"]))
log.info("Cleaned (no-NaNs in columns): {}".format(
save_node["clean_file"]))
log.info("")
else:
log.info("Failed to process datasets")
def run_main(need_response=False, callback=None):
"""run_main
start the packet consumers and the packet processors
:param need_response: should send response back to publisher
:param callback: handler method
"""
stop_file = ev("STOP_FILE", "/opt/stop_recording")
num_workers = int(ev("NUM_WORKERS", "1"))
shutdown_msg = "SHUTDOWN"
log.info("Start - {}".format(name))
log.info("Creating multiprocessing queue")
tasks = multiprocessing.JoinableQueue()
queue_to_consume = multiprocessing.Queue()
host = "localhost"
# Start consumers
log.info("Starting Consumers to process queued tasks")
consumers = start_consumers_for_queue(
num_workers=num_workers,
tasks=tasks,
queue_to_consume=queue_to_consume,
shutdown_msg=shutdown_msg,
consumer_class=WorkerToProcessPackets,
callback=callback)
log.info("creating socket")
skt = create_layer_2_socket()
log.info("socket created")
not_done = True
while not_done:
if not skt:
log.info("Failed to create layer 2 socket")
log.info("Please make sure to run as root")
not_done = False
break
try:
if os.path.exists(stop_file):
log.info(("Detected stop_file={}").format(stop_file))
not_done = False
break
# stop if the file exists
# Only works on linux
packet = skt.recvfrom(65565)
if os.path.exists(stop_file):
log.info(("Detected stop_file={}").format(stop_file))
not_done = False
break
# stop if the file was created during a wait loop
tasks.put(NetworkPacketTask(source=host, payload=packet))
except KeyboardInterrupt as k:
log.info("Stopping")
not_done = False
break
except Exception as e:
log.error(("Failed reading socket with ex={}").format(e))
not_done = False
break
# end of try/ex during socket receving
# end of while processing network packets
log.info(("Shutting down consumers={}").format(len(consumers)))
shutdown_consumers(num_workers=num_workers, tasks=tasks)
# Wait for all of the tasks to finish
if need_response:
log.info("Waiting for tasks to finish")
tasks.join()
log.info("Done waiting for tasks to finish")
def build_csv(
pipeline_files=[],
fulldata_file=None,
clean_file=None,
post_proc_rules=None,
label_rules=None,
metadata_filename="metadata.json"):
"""build_csv
:param pipeline_files: files to process
:param fulldata_file: output all columns to this csv file
:param clean_file: output all numeric-ready columns to this csv file
:param post_proc_rules: rules after building the DataFrame
:param label_rules: labeling rules
:param metadata_filename: metadata
"""
save_node = {
"status": INVALID,
"pipeline_files": pipeline_files,
"post_proc_rules": post_proc_rules,
"label_rules": label_rules,
"fulldata_file": fulldata_file,
"fulldata_metadata_file": None,
"clean_file": clean_file,
"clean_metadata_file": None,
"features_to_process": [],
"feature_to_predict": None,
"ignore_features": [],
"df_json": {}
}
if not fulldata_file:
log.error("missing fulldata_file - stopping")
save_node["status"] = INVALID
return save_node
if not clean_file:
log.error("missing clean_file - stopping")
save_node["status"] = INVALID
return save_node
log.info("build_csv - START")
common_headers, \
headers_dict = find_all_headers(
pipeline_files=pipeline_files)
log.info(("num common_headers={} headers={}")
.format(len(common_headers),
common_headers))
# since the headers can be different we rebuild a new one:
hdrs = {}
for h in common_headers:
hdrs[h] = None
features_to_process = []
feature_to_predict = None
ignore_features = []
set_if_above = None
labels = []
label_values = []
if label_rules:
set_if_above = label_rules["set_if_above"]
labels = label_rules["labels"]
label_values = label_rules["label_values"]
all_rows = []
num_done = 0
total_files = len(pipeline_files)
for c in pipeline_files:
log.info(("merging={}/{} csv={}")
.format(num_done,
total_files,
c))
cf = pd.read_csv(c)
log.info((" processing rows={}")
.format(len(cf.index)))
for index, row in cf.iterrows():
valid_row = True
new_row = copy.deepcopy(hdrs)
new_row["src_file"] = c
for k in hdrs:
if k in row:
new_row[k] = row[k]
# end of for all headers to copy in
if label_rules:
test_rand = random.randint(0, 100)
if test_rand > set_if_above:
new_row["label_value"] = label_values[1]
new_row["label_name"] = labels[1]
else:
new_row["label_value"] = label_values[0]
new_row["label_name"] = labels[0]
# end of applying label rules
if valid_row:
all_rows.append(new_row)
# end of for all rows in this file
num_done += 1
# end of building all files into one list
log.info(("fulldata rows={} generating df")
.format(len(all_rows)))
df = pd.DataFrame(all_rows)
log.info(("df rows={} headers={}")
.format(len(df.index),
df.columns.values))
if ev("CONVERT_DF",
"0") == "1":
log.info("converting df to json")
save_node["df_json"] = df.to_json()
if clean_file:
log.info(("writing fulldata_file={}")
.format(fulldata_file))
df.to_csv(fulldata_file,
sep=',',
encoding='utf-8',
index=False)
log.info(("done writing fulldata_file={}")
.format(fulldata_file))
if post_proc_rules:
clean_metadata_file = ""
feature_to_predict = "label_name"
features_to_process = []
ignore_features = []
if label_rules:
ignore_features = [feature_to_predict]
if "drop_columns" in post_proc_rules:
for p in post_proc_rules["drop_columns"]:
if p in headers_dict:
ignore_features.append(p)
# post proce filter more features out
# for non-int/float types
for d in df.columns.values:
add_this_one = True
for i in ignore_features:
if d == i:
add_this_one = False
break
if add_this_one:
features_to_process.append(d)
# for all df columns we're not ignoring...
# add them as features to process
fulldata_metadata_file = "{}/fulldata_{}".format(
"/".join(fulldata_file.split("/")[:-1]),
metadata_filename)
log.info(("writing fulldata metadata file={}")
.format(fulldata_metadata_file))
header_data = {"headers": list(df.columns.values),
"output_type": "fulldata",
"pipeline_files": pipeline_files,
"post_proc_rules": post_proc_rules,
"label_rules": label_rules,
"features_to_process": features_to_process,
"feature_to_predict": feature_to_predict,
"ignore_features": ignore_features,
"created": rnow()}
with open(fulldata_metadata_file, "w") as otfile:
otfile.write(str(ppj(header_data)))
keep_these = features_to_process
keep_these.append(feature_to_predict)
log.info(("creating new clean_file={} "
"keep_these={} "
"predict={}")
.format(clean_file,
keep_these,
feature_to_predict))
# need to remove all columns that are all nan
clean_df = df[keep_these].dropna(
axis=1, how='all').dropna()
cleaned_features = clean_df.columns.values
cleaned_to_process = []
cleaned_ignore_features = []
for c in cleaned_features:
if c == feature_to_predict:
cleaned_ignore_features.append(c)
else:
keep_it = True
for ign in ignore_features:
if c == ign:
cleaned_ignore_features.append(c)
keep_it = False
break
# end of for all feaures to remove
if keep_it:
cleaned_to_process.append(c)
# end of new feature columns
log.info(("writing DROPPED clean_file={} "
"features_to_process={} "
"ignore_features={} "
"predict={}")
.format(clean_file,
cleaned_to_process,
cleaned_ignore_features,
feature_to_predict))
write_clean_df = clean_df.drop(
columns=cleaned_ignore_features
)
log.info(("cleaned_df rows={}")
.format(len(write_clean_df.index)))
write_clean_df.to_csv(
clean_file,
sep=',',
encoding='utf-8',
index=False)
clean_metadata_file = "{}/cleaned_{}".format(
"/".join(clean_file.split("/")[:-1]),
metadata_filename)
log.info(("writing clean metadata file={}")
.format(clean_metadata_file))
header_data = {"headers": list(write_clean_df.columns.values),
"output_type": "clean",
"pipeline_files": pipeline_files,
"post_proc_rules": post_proc_rules,
"label_rules": label_rules,
"features_to_process": cleaned_to_process,
"feature_to_predict": feature_to_predict,
"ignore_features": cleaned_ignore_features,
"created": rnow()}
with open(clean_metadata_file, "w") as otfile:
otfile.write(str(ppj(header_data)))
else:
for d in df.columns.values:
add_this_one = True
for i in ignore_features:
if d == i:
add_this_one = False
break
if add_this_one:
features_to_process.append(d)
# for all df columns we're not ignoring...
# add them as features to process
fulldata_metadata_file = "{}/fulldata_{}".format(
"/".join(fulldata_file.split("/")[:-1]),
metadata_filename)
log.info(("writing fulldata metadata file={}")
.format(fulldata_metadata_file))
header_data = {"headers": list(df.columns.values),
"output_type": "fulldata",
"pipeline_files": pipeline_files,
"post_proc_rules": post_proc_rules,
"label_rules": label_rules,
"features_to_process": features_to_process,
"feature_to_predict": feature_to_predict,
"ignore_features": ignore_features,
"created": rnow()}
with open(fulldata_metadata_file, "w") as otfile:
otfile.write(str(ppj(header_data)))
keep_these = features_to_process
keep_these.append(feature_to_predict)
log.info(("creating new clean_file={} "
"keep_these={} "
"predict={}")
.format(clean_file,
keep_these,
feature_to_predict))
# need to remove all columns that are all nan
clean_df = df[keep_these].dropna(
axis=1, how='all').dropna()
cleaned_features = clean_df.columns.values
cleaned_to_process = []
cleaned_ignore_features = []
for c in cleaned_features:
if c == feature_to_predict:
cleaned_ignore_features.append(c)
else:
keep_it = True
for ign in ignore_features:
if c == ign:
cleaned_ignore_features.append(c)
keep_it = False
break
# end of for all feaures to remove
if keep_it:
cleaned_to_process.append(c)
# end of new feature columns
log.info(("writing DROPPED clean_file={} "
"features_to_process={} "
"ignore_features={} "
"predict={}")
.format(clean_file,
cleaned_to_process,
cleaned_ignore_features,
feature_to_predict))
write_clean_df = clean_df.drop(
columns=cleaned_ignore_features
)
log.info(("cleaned_df rows={}")
.format(len(write_clean_df.index)))
write_clean_df.to_csv(
clean_file,
sep=',',
encoding='utf-8',
index=False)
clean_metadata_file = "{}/cleaned_{}".format(
"/".join(clean_file.split("/")[:-1]),
metadata_filename)
log.info(("writing clean metadata file={}")
.format(clean_metadata_file))
header_data = {"headers": list(write_clean_df.columns.values),
"output_type": "clean",
"pipeline_files": pipeline_files,
"post_proc_rules": post_proc_rules,
"label_rules": label_rules,
"features_to_process": cleaned_to_process,
"feature_to_predict": feature_to_predict,
"ignore_features": cleaned_ignore_features,
"created": rnow()}
with open(clean_metadata_file, "w") as otfile:
otfile.write(str(ppj(header_data)))
# end of if/else
save_node["clean_file"] = clean_file
save_node["clean_metadata_file"] = clean_metadata_file
log.info(("done writing clean_file={}")
.format(clean_file))
# end of post_proc_rules
save_node["fulldata_file"] = fulldata_file
save_node["fulldata_metadata_file"] = fulldata_metadata_file
save_node["status"] = VALID
# end of writing the file
save_node["features_to_process"] = features_to_process
save_node["feature_to_predict"] = feature_to_predict
save_node["ignore_features"] = ignore_features
log.info("build_csv - END")
return save_node
log.info(("Done with msg_id={} result={}").format(body["msg_id"],
result.get()))
# now that the message has been
# sent to the celery ecomm worker
# we can ack the message which
# deletes it from the source queue
# the message processor uses
message.ack()
# end of relay_callback
# want to change where you're subscribing vs publishing?
sub_ssl_options = {}
sub_auth_url = ev("SUB_BROKER_URL",
"pyamqp://*****:*****@localhost:5672//")
pub_ssl_options = {}
pub_auth_url = ev("PUB_BROKER_URL", "redis://localhost:6379/0")
# start the message processor
msg_proc = MessageProcessor(name=name,
sub_auth_url=sub_auth_url,
sub_ssl_options=sub_ssl_options,
pub_auth_url=pub_auth_url,
pub_ssl_options=pub_ssl_options)
# configure where this is consuming:
queue = ev("CONSUME_QUEUE", "user.events.conversions")
# Relay Publish Hook - sending to Redis
# where is it sending handled messages using a publish-hook or auto-caching:
def test_rabbitmq_consuming(self):
# Integration Test the Consuming Worker with 50,0000 messages
# This test just uses send_task for publishing
num_to_consume = 50000
num_sent = 0
num_to_send = num_to_consume
msgs_to_send = []
msgs_by_id = {}
not_done_publishing = True
test_values = {"test_name": "large messages"}
if len(msgs_to_send) == 0:
while len(msgs_to_send) != num_to_send:
test_msg = self.build_user_conversion_event_msg(test_values)
msgs_to_send.append(test_msg)
msgs_by_id[test_msg["msg_id"]] = False
# end of building messages before slower publishing calls
pub_auth_url = ev("RELAY_WORKER_BROKER_URL",
"pyamqp://*****:*****@localhost:5672//")
path_to_config_module = "ecomm_app.ecommerce.celeryconfig_pub_sub"
app = ecomm_app.ecommerce.tasks.get_celery_app(
name="demo",
auth_url=pub_auth_url,
path_to_config_module=path_to_config_module)
task_name = "ecomm_app.ecommerce.tasks.handle_user_conversion_events"
source_id = {"msg_proc": ev("TEST_RELAY_NAME",
"test_ecomm_relay")}
result = None
log.info(("Sending broker={}")
.format(app.conf.broker_url))
while not_done_publishing:
if (num_sent % 1000 == 0) and num_sent > 0:
log.info(("Published {} for "
"{}/{} messages")
.format(get_percent_done(num_sent,
num_to_send),
num_sent,
num_to_send))
# end of if print for tracing
msg_body = None
if num_sent < len(msgs_to_send):
msg_body = msgs_to_send[num_sent]
result = app.send_task(task_name, (msg_body, source_id))
num_sent += 1
if num_sent >= num_to_send:
log.info(("Published {} ALL "
"{}/{} messages")
.format(get_percent_done(num_sent,
num_to_send),
num_sent,
num_to_send))
not_done_publishing = False
elif num_sent >= len(msgs_to_send):
log.info(("Published {} all "
"{}/{} messages result={}")
.format(get_percent_done(num_sent,
len(msgs_to_send)),
num_sent,
num_to_send,
result))
not_done_publishing = False
# if should stop
# end of not_done_publishing
assert(num_sent == num_to_consume)
log.info("")
os.system("list-queues.sh")
log.info("")
def build_training_request(
csv_file=ev("CSV_FILE", "/tmp/cleaned_attack_scans.csv"),
meta_file=ev("CSV_META_FILE", "/tmp/cleaned_metadata.json"),
predict_feature=ev("PREDICT_FEATURE", "label_value"),
ignore_features=[
"label_name",
"ip_src", # need to make this an int
"ip_dst", # need to make this an int
"eth_src", # need to make this an int
"eth_dst" # need to make this an int
],
seed=None,
test_size=float(ev("TEST_SIZE", "0.20")),
preproc_rules=None):
"""build_training_request
:param csv_file: csv file built with prepare_dataset.py
:param meta_file: metadata file built with prepare_dataset.py
:param predict_feature: feature (column) to predict
:param ignore_features: features to remove from the csv
before the split of test + train
data
:param seed: integer to seed
:param test_size: percent of records to split into test
vs train
:param preproc_rules: future preprocessing rules hooks
"""
last_step = "not started"
res = {
"status": INVALID,
"err": "",
"csv_file": csv_file,
"meta_file": meta_file,
"meta_data": None,
"seed": None,
"test_size": test_size,
"predict_feature": predict_feature,
"features_to_process": [],
"ignore_features": ignore_features,
"X_train": None,
"X_test": None,
"Y_train": None,
"Y_test": None
}
try:
last_step = ("building seed={}").format(seed)
log.debug(last_step)
use_seed = seed
if not use_seed:
use_seed = 9
res["seed"] = np.random.seed(use_seed)
last_step = ("Loading csv={}").format(csv_file)
log.info(last_step)
if not os.path.exists(csv_file):
res["status"] = ERROR
res["err"] = ("Unable to find csv_file={}").format(csv_file)
log.error(res["err"])
return res
# end of checking for a valid csv file on disk
if not os.path.exists(meta_file):
res["status"] = ERROR
res["err"] = ("Unable to find meta_file={}").format(meta_file)
log.error(res["err"])
return res
# end of checking for a valid metadata file on disk
# load csv file into pandas dataframe
df = pd.read_csv(csv_file)
features_to_process = []
meta_data = {}
try:
last_step = ("opening metadata={}").format(meta_file)
log.debug(last_step)
meta_data = json.loads(open(meta_file, "r").read())
res["meta_data"] = meta_data
if "post_proc_rules" in meta_data:
if "drop_columns" in meta_data["post_proc_rules"]:
log.debug(("Found drop_columns={}").format(
meta_data["post_proc_rules"]["drop_columns"]))
for ign in meta_data["post_proc_rules"]["drop_columns"]:
ignore_features.append(ign)
except Exception as e:
res["error"] = ("Failed building ignore_features: "
"ignore_features={} meta={} meta_data={} "
"last_step='{}' ex='{}'").format(
ignore_features, meta_file, meta_data,
last_step, e)
log.error(res["error"])
res["status"] = ERROR
return res
# end of trying to lookup the meta data file
# for non-int/float features to ignore
last_step = ("metadata={} df has "
"columns={} ignore={}").format(meta_file,
df.columns.values,
ignore_features)
log.info(last_step)
for feature in df.columns.values:
keep_it = True
for ign in ignore_features:
if feature == ign:
keep_it = False
if keep_it:
if feature != predict_feature:
features_to_process.append(feature)
# end of for all features to process
last_step = ("Done post-procecessing "
"Predicting={} with features={} "
"ignore_features={} records={}").format(
predict_feature, features_to_process, ignore_features,
len(df.index))
log.info(last_step)
res["predict_feature"] = predict_feature
res["ignore_features"] = []
for k in ignore_features:
if k not in res["ignore_features"]:
res["ignore_features"].append(k)
res["features_to_process"] = []
for k in features_to_process:
if k not in res["features_to_process"]:
if k != predict_feature:
res["features_to_process"].append(k)
# split the data into training
(res["X_train"], res["X_test"], res["Y_train"],
res["Y_test"]) = train_test_split(df[features_to_process],
df[predict_feature],
test_size=test_size,
random_state=res["seed"])
last_step = ("Done splitting rows={} into "
"X_train={} X_test={} "
"Y_train={} Y_test={}").format(len(df.index),
len(res["X_train"]),
len(res["X_test"]),
len(res["Y_train"]),
len(res["Y_test"]))
log.info(("Success: {}").format(last_step))
res["err"] = ""
res["status"] = VALID
except Exception as e:
res["status"] = ERROR
res["err"] = ("Failed build_training_request "
"step='{}' with ex='{}'").format(last_step, e)
log.error(("build_training_request: {}").format(res["err"]))
# end of try/ex
return res
class BaseTestCase(unittest.TestCase):
debug = False
exchange_name = ev("TEST_EXCHANGE", "test.events")
queue_name = ev("TEST_QUEUE", "test.events.conversions")
routing_key = ev("TEST_ROUTING_KEY", "test.events.conversions")
exchange = None
queue = None
rabbitmq_auth_url = ev("TEST_RABBITMQ_BROKER_URL", "pyamqp://*****:*****@localhost:5672//")
redis_auth_url = ev("TEST_REDIS_BROKER_URL", "redis://localhost:6379/0")
pub_auth_url = rabbitmq_auth_url
sub_auth_url = rabbitmq_auth_url
pub_ssl_options = {}
sub_ssl_options = {}
pub_attrs = {}
sub_attrs = {}
pub_serializer = "json"
sub_serializer = "application/json"
test_body = {}
test_id = str(uuid.uuid4()).replace("-", "")
test_body = {"account_id": 123,
"subscription_id": 456,
"stripe_id": 789,
"product_id": "ABC"}
pub_msgs = []
sub_msgs = []
last_pub_msg = None
last_sub_msg = None
last_sub_callback = None
def setUp(self):
if self.debug:
print("setUp")
# state trips in the custom classes
os.environ["TEST_STOP_DONE"] = "1"
self.last_pub_msg = None
self.last_sub_msg = None
self.pub = None
self.sub = None
self.pub_msgs = []
self.sub_msgs = []
self.exchange_name = ev("TEST_EXCHANGE", "test.events")
self.routing_key = ev("TEST_ROUTING_KEY", "test.events.conversions")
self.queue_name = ev("TEST_QUEUE", "test.events.conversions")
self.exchange = None
self.queue = None
self.last_sub_callback = None
# end of setUp
def tearDown(self):
if self.debug:
print("tearDown")
self.pub = None
self.sub = None
self.exchange = None
self.queue = None
self.last_sub_callback = None
# end of tearDown
def handle_message(self,
body,
msg):
log.info(("test={} BASETEST handle_message got "
"body={} msg={}")
.format(self.test_id,
body,
msg))
if msg:
msg.ack()
# end of handle_message
def connect_pub(self,
auth_url=None,
ssl_options={},
attrs={}):
use_auth_url = self.pub_auth_url
use_ssl_options = self.pub_ssl_options
use_pub_attrs = self.pub_attrs
if auth_url:
use_auth_url = auth_url
if len(ssl_options) > 0:
use_ssl_options = ssl_options
if len(ssl_options) > 0:
use_pub_attrs = use_pub_attrs
self.pub = Publisher("test-pub",
use_auth_url,
use_ssl_options)
# end of connect_pub
def connect_sub(self,
auth_url=None,
ssl_options={},
attrs={}):
use_auth_url = self.sub_auth_url
use_ssl_options = self.sub_ssl_options
use_sub_attrs = self.sub_attrs
if auth_url:
use_auth_url = auth_url
if len(ssl_options) > 0:
use_ssl_options = ssl_options
if len(ssl_options) > 0:
use_sub_attrs = use_sub_attrs
self.sub = KombuSubscriber("test-sub",
use_auth_url,
use_ssl_options)
# end of connect_sub
def build_msg(self,
test_values={}):
body = {"test_id": self.test_id,
"date": datetime.datetime.now().strftime("%Y-%m-%d %H-%M-%S"),
"msg_id": str(uuid.uuid4()).replace("-", ""),
"test_values": test_values}
return body
# end of build_msg
def consume(self,
callback=None,
queue=queue,
exchange=exchange,
routing_key=routing_key,
serializer="application/json",
heartbeat=60,
time_to_wait=5.0,
forever=False,
silent=True):
if not callback:
log.error(("Subscriber - Requires a callback handler for message"
"processing with signature definition: "
"def handle_message(self, body, message):")
.format(self.sub_auth_url,
self.sub_ssl_options))
assert(callback)
# if not connected, just connect with defaults
if not self.sub:
self.connect_sub()
if not self.sub:
log.error(("Subscriber - Failed to connect "
"to broker={} ssl={}")
.format(self.sub_auth_url,
self.sub_ssl_options))
assert(self.sub)
if self.sub:
self.sub.consume(callback=callback,
queue=queue,
exchange=exchange,
routing_key=routing_key,
serializer=serializer,
heartbeat=heartbeat,
forever=forever,
time_to_wait=time_to_wait,
silent=silent)
else:
log.info("Sub is None already - client should not call consume")
# end of consume
def publish(self,
body=None,
exchange=exchange,
routing_key=routing_key,
queue=queue,
priority=0,
ttl=None,
serializer="json",
retry=True,
silent=True):
# if no body for the message
if not body:
log.error(("Publisher - requires argument: "
"body=some_dictionary to test"))
assert(body)
# if not connected, just connect with defaults
if not self.pub:
self.connect_pub()
if not self.pub:
log.error(("Publisher - Failed to connect "
"to broker={} ssl={}")
.format(self.pub_auth_url,
self.pub_ssl_options))
assert(self.pub)
if self.pub:
self.pub.publish(body=body,
exchange=exchange,
routing_key=routing_key,
queue=queue,
serializer=serializer,
priority=priority,
ttl=ttl,
retry=retry,
silent=silent)
else:
log.info("Pub is None already - client should not call publish")
