def main(args):
topic = args.topic
delimiter = args.delimiter
producer_conf = producer_config(args)
producer = SerializingProducer(producer_conf)
print('Producing records to topic {}. ^C to exit.'.format(topic))
while True:
# Serve on_delivery callbacks from previous calls to produce()
producer.poll(0.0)
try:
msg_data = input(">")
msg = msg_data.split(delimiter)
if len(msg) == 2:
producer.produce(topic=topic, key=msg[0], value=msg[1],
on_delivery=delivery_report)
else:
producer.produce(topic=topic, value=msg[0],
on_delivery=delivery_report)
except KeyboardInterrupt:
break
print('\nFlushing {} records...'.format(len(producer)))
producer.flush()
def _commit(self) -> None:
"""
Retrieves the current offset by calling :meth:`pyconnect.pyconnectsource.PyConnectSource.get_index` and
publishes it to the offset topic that is defined in this sources :class:`pyconnect.config.SourceConfig`
instance.
"""
idx = self.get_index()
idx_schema = to_value_schema(idx)
avro_value_serializer = AvroSerializer(
schema_registry_client=self.schema_registry_client,
schema_str=idx_schema)
producer_config = {
"bootstrap.servers": self.config["bootstrap.servers"],
"key.serializer": None,
"value.serializer": avro_value_serializer,
**self.config["kafka_opts"],
**self.config["kafka_producer_opts"],
}
offset_producer = SerializingProducer(producer_config)
offset_producer.produce(key=None,
value=idx,
topic=self.config["offset_topic"])
offset_producer.flush()
def write_to_kafka(bootstrap_servers, schema_registry_url, topic_name, data):
print("Kafka Version : ", confluent_kafka.version(),confluent_kafka.libversion())
schema_registry_conf = {'url': schema_registry_url}
schema_registry_client = SchemaRegistryClient(schema_registry_conf)
value_avro_serializer = AvroSerializer(schemas.weather_source_schema, schema_registry_client)
string_serializer = StringSerializer('utf-8')
conf = {'bootstrap.servers': bootstrap_servers,
'client.id': socket.gethostname(),
'on_delivery': delivery_report,
'key.serializer': string_serializer,
'value.serializer': value_avro_serializer
}
avroProducer = SerializingProducer(conf)
key=datetime.date.today() + '~' + str(data['lat']) + '~' + str(data['lon'])
message = json.dumps(data, cls=DatetimeEncoder)
print("Key Type : ", type(key))
print("Value Type : ", type(json.loads(message)))
avroProducer.produce(topic=topic_name, key=key, value=json.loads(message))
avroProducer.flush()
def main(args):
topic = args.topic
delimiter = args.delimiter
producer_conf = {'bootstrap.servers': args.bootstrap_servers,
'key.serializer': StringSerializer('utf_8'),
'value.serializer': StringSerializer('utf_8')}
producer_conf.update(sasl_conf(args))
producer = SerializingProducer(producer_conf)
print("Producing records to topic {}. ^C to exit.".format(topic))
while True:
# Serve on_delivery callbacks from previous calls to produce()
producer.poll(0.0)
try:
msg_data = input(">")
msg = msg_data.split(delimiter)
if len(msg) == 2:
producer.produce(topic=topic, key=msg[0], value=msg[1],
on_delivery=delivery_report)
else:
producer.produce(topic=topic, value=msg[0],
on_delivery=delivery_report)
except KeyboardInterrupt:
break
print("\nFlushing {} records...".format(len(producer)))
producer.flush()
def main(args):
topic = args.topic
schema_str = """
{
"namespace": "confluent.io.examples.serialization.avro",
"name": "User",
"type": "record",
"fields": [
{"name": "name", "type": "string"},
{"name": "favorite_number", "type": "int"},
{"name": "favorite_color", "type": "string"}
]
}
"""
schema_registry_conf = {'url': args.schema_registry}
schema_registry_client = SchemaRegistryClient(schema_registry_conf)
avro_serializer = AvroSerializer(schema_registry_client, schema_str,
user_to_dict)
producer_conf = {
'bootstrap.servers': args.bootstrap_servers,
'key.serializer': StringSerializer('utf_8'),
'value.serializer': avro_serializer
}
producer = SerializingProducer(producer_conf)
print("Producing user records to topic {}. ^C to exit.".format(topic))
while True:
# Serve on_delivery callbacks from previous calls to produce()
producer.poll(0.0)
try:
user_name = input("Enter name: ")
user_address = input("Enter address: ")
user_favorite_number = int(input("Enter favorite number: "))
user_favorite_color = input("Enter favorite color: ")
user = User(name=user_name,
address=user_address,
favorite_color=user_favorite_color,
favorite_number=user_favorite_number)
producer.produce(topic=topic,
key=str(uuid4()),
value=user,
on_delivery=delivery_report)
except KeyboardInterrupt:
break
except ValueError:
print("Invalid input, discarding record...")
continue
print("\nFlushing records...")
producer.flush()
class ProtoKafkaProducer:
def __init__(self, config_env):
self.config = config_env
self.topic_name = self.config["kafka_produce_topic"]
conf = {
'bootstrap.servers':
self.config["bootstrap_servers"],
'message.max.bytes':
self.config["kafkaMaxMessageBytes"],
'queue.buffering.max.ms':
self.config["queue.buffering.max.ms"],
'queue.buffering.max.messages':
self.config["queue.buffering.max.messages"],
'key.serializer':
StringSerializer('utf_8'),
'value.serializer':
self.__protobuf_serializer()
}
self.producer = SerializingProducer(conf)
def on_delivery(self, err, msg):
if err:
print("Message failed delivery, error: %s", err)
else:
print("Message delivered to %s on partition %s", msg.topic(),
msg.partition())
def __protobuf_serializer(self):
schema_registry_conf = {'url': self.config['schemaregistry.url']}
schema_registry_client = SchemaRegistryClient(schema_registry_conf)
_proto_conf = {
'auto.register.schemas': self.config['auto.register.schemas'],
}
return ProtobufSerializer(self.config['proto_msg_type'],
schema_registry_client,
conf=_proto_conf)
def produce(self, kafka_msg, kafka_key):
try:
self.producer.produce(topic=self.topic_name,
value=kafka_msg,
key=kafka_key,
on_delivery=self.on_delivery)
self.producer.flush()
except Exception as e:
print("Error during producing to kafka topic. Stacktrace is %s", e)
class NewsScheduler(object):
def __init__(self,
bootstrap_servers,
rss_feeds,
topic='crawl-queue',
time_checkpoint_fn_base='scheduler_checkpoint'):
self.bootstrap_servers = bootstrap_servers
self.topic = topic
self.feeds = rss_feeds
self.time_checkpoints = dict()
for spider_name in self.feeds.values():
fn = f'{time_checkpoint_fn_base}_{spider_name}.txt'
fn = fn.replace('/', '_') # we don't want / in our pathnames.
self.time_checkpoints[spider_name] = TimeCheckpoint(fn=fn)
producer_conf = {
'bootstrap.servers': self.bootstrap_servers,
'key.serializer': StringSerializer('utf_8'),
'value.serializer': _json_serializer_wrapper
}
self.producer = SerializingProducer(producer_conf)
def process_feed(self, feed_url, spider_name, flush=False):
log.info(f"Processing feed '{feed_url}' via topic '{self.topic}'.")
rss_feed = feedparser.parse(feed_url)
for item in rss_feed.entries:
item['spider'] = spider_name
item_updated_time = struct_time_to_datetime(item.updated_parsed)
if item_updated_time > self.time_checkpoints[
spider_name].checkpoint:
log.info(f"New item: {item['title']}")
self.producer.produce(topic=self.topic,
key=str(uuid4()),
value=dict(item))
self.time_checkpoints[
spider_name].checkpoint = struct_time_to_datetime(
rss_feed.feed.updated_parsed)
if flush:
self.producer.flush()
def run_loop(self, interval):
for feed, spider in itertools.cycle(self.feeds.items()):
self.process_feed(feed, spider)
time.sleep(interval)
class KafkaAvroProducer:
def __init__(self,
producer_name,
value_schema,
groupID='KafkaAvroProducer'):
# Consumer name for logging purposes
self.logging_prefix = '[' + producer_name + '][KafkaAvroProducer]'
# Schema Registry configuration
self.schema_registry_conf = EventBackboneConfig.getSchemaRegistryConf()
# Schema Registry Client
self.schema_registry_client = SchemaRegistryClient(
self.schema_registry_conf)
# String Serializer for the key
self.key_serializer = StringSerializer('utf_8')
# Avro Serializer for the value
self.value_serializer = AvroSerializer(value_schema,
self.schema_registry_client)
# Get the producer configuration
self.producer_conf = EventBackboneConfig.getProducerConfiguration(
groupID, self.key_serializer, self.value_serializer)
EventBackboneConfig.printProducerConfiguration(
self.logging_prefix, self.producer_conf,
self.schema_registry_conf['url'])
# Create the producer
self.producer = SerializingProducer(self.producer_conf)
def delivery_report(self, err, msg):
""" Called once for each message produced to indicate delivery result. Triggered by poll() or flush(). """
if err is not None:
print(
'[KafkaAvroProducer] - [ERROR] - Message delivery failed: {}'.
format(err))
else:
print('[KafkaAvroProducer] - Message delivered to {} [{}]'.format(
msg.topic(), msg.partition()))
def publishEvent(self, key, value, topicName='kafka-avro-producer'):
# Produce the Avro message
self.producer.produce(topic=topicName,
value=value,
key=key,
on_delivery=self.delivery_report)
# Flush
self.producer.flush()
def send_record(args):
""" Sends Record using a SerializingProducer & AvroSerializer """
topic = args.topic.rstrip()
schema_registry_config = {'url': args.schema_registry}
schema_registry_client = SchemaRegistryClient(schema_registry_config)
avro_serializer = AvroSerializer(schema_registry_client, DATA_SCHEMA,
data_to_dict)
producer_config = {
"bootstrap.servers": args.bootstrap_servers,
"key.serializer": StringSerializer('utf_8'),
"value.serializer": avro_serializer
}
producer = SerializingProducer(producer_config)
split_incoming_data = args.record_value.split(',')
if not len(split_incoming_data) == 7: # Data Format Check
print('** Error: Insufficient Incoming Data: ', split_incoming_data)
raise Exception
try: # Data Format Check
incoming_data = {
'envId': int(split_incoming_data[0]),
'whenCollected': str(split_incoming_data[1]),
'timeLightOnMins': int(split_incoming_data[2]),
'humidity': int(split_incoming_data[3]),
'soilMoisture': int(split_incoming_data[4]),
'temperature': int(split_incoming_data[5]),
'waterConsumption': int(split_incoming_data[6])
}
except Exception as error:
print('** Error Creating Dict of Data: ', error)
print(f'Producing data records to topic {topic}. ^C to exit.')
producer.poll(1)
try:
key = args.record_key if args.record_key else str(uuid4())
data_object = Data(incoming_data)
print('\t-Producing Avro record. . .')
producer.produce(topic=topic,
key=key,
value=data_object,
on_delivery=delivery_report)
except ValueError:
print('\t-Invalid input, discarding record. . .')
print('\nFlushing records. . .')
producer.flush()
def plain_avro_producer(running_cluster_config: Dict[str, str],
topic_and_partitions: Tuple[str, int],
records) -> SerializingProducer:
"""
Creates a plain `confluent_kafka.avro.AvroProducer` that can be used to publish messages.
"""
topic_id, _ = topic_and_partitions
key, value = records[0]
schema_registry_client = SchemaRegistryClient(
{"url": running_cluster_config["schema-registry"]})
key_schema = to_key_schema(key)
avro_key_serializer = AvroSerializer(
schema_registry_client=schema_registry_client, schema_str=key_schema)
value_schema = to_value_schema(value)
avro_value_serializer = AvroSerializer(
schema_registry_client=schema_registry_client, schema_str=value_schema)
producer_config = {
"bootstrap.servers": running_cluster_config["broker"],
"key.serializer": avro_key_serializer,
"value.serializer": avro_value_serializer,
}
producer = SerializingProducer(producer_config)
producer.produce = partial(producer.produce, topic=topic_id)
return producer
class DatahubKafkaEmitter:
def __init__(self, config: KafkaEmitterConfig):
self.config = config
schema_registry_conf = {
"url": self.config.connection.schema_registry_url,
**self.config.connection.schema_registry_config,
}
schema_registry_client = SchemaRegistryClient(schema_registry_conf)
def convert_mce_to_dict(
mce: MetadataChangeEvent, ctx: SerializationContext
) -> dict:
tuple_encoding = mce.to_obj(tuples=True)
return tuple_encoding
avro_serializer = AvroSerializer(
schema_str=SCHEMA_JSON_STR,
schema_registry_client=schema_registry_client,
to_dict=convert_mce_to_dict,
)
producer_config = {
"bootstrap.servers": self.config.connection.bootstrap,
"key.serializer": StringSerializer("utf_8"),
"value.serializer": avro_serializer,
**self.config.connection.producer_config,
}
self.producer = SerializingProducer(producer_config)
def emit_mce_async(
self,
mce: MetadataChangeEvent,
callback: Callable[[Exception, str], None],
) -> None:
# Call poll to trigger any callbacks on success / failure of previous writes
self.producer.poll(0)
self.producer.produce(
topic=self.config.topic,
key=mce.proposedSnapshot.urn,
value=mce,
on_delivery=callback,
)
def flush(self) -> None:
self.producer.flush()
def main(args):
topic = args.topic
key_schema_str = open('schema/KeySchema.avsc', "r").read()
value_schema_str = open('schema/ValueSchema.avsc', "r").read()
schema_registry_conf = {'url': args.schema_registry}
schema_registry_client = SchemaRegistryClient(schema_registry_conf)
avro_key_serializer = AvroSerializer(key_schema_str, schema_registry_client, user_quote_key_to_dict)
avro_value_serializer = AvroSerializer(value_schema_str, schema_registry_client, user_quote_value_to_dict)
producer_conf = {'bootstrap.servers': args.bootstrap_servers,
'key.serializer': avro_key_serializer,
'value.serializer': avro_value_serializer}
producer = SerializingProducer(producer_conf)
print("Producing user records to topic {}. ^C to exit.".format(topic))
while True:
# Serve on_delivery callbacks from previous calls to produce()
producer.poll(0.0)
try:
user_id = input("Enter User ID: ")
product_id = input("Enter Product ID: ")
quoted_price = input("Enter price: ")
quoted_quantity = int(input("Enter the desired quantity: "))
user_note = input("Enter additional note: ")
user_quote_key = UserQuoteKey(user_id=int(user_id))
user_quote_value = UserQuoteValue(product_id=int(product_id),
quoted_price=int(quoted_price),
quoted_quantity=quoted_quantity,
user_note=user_note)
producer.produce(topic=topic, key=user_quote_key, value=user_quote_value,
on_delivery=delivery_report)
except KeyboardInterrupt:
break
except ValueError:
print("Invalid input, discarding record...")
continue
print("\nFlushing records...")
producer.flush()
class VideoProducer:
def __init__(self,
topic='test',
client_id='producer1',
bootstrap_servers='localhost:9092',
video_reader=None):
self.topic = topic
self.video_reader = video_reader
self.kafka_producer = SerializingProducer({
'bootstrap.servers':
bootstrap_servers,
'value.serializer':
self.video_reader.serialize,
'queue.buffering.max.messages':
500000
})
self.delivered_records = 0
self.start_time = 0
def acked(self, err, msg):
"""Delivery report handler called on
successful or failed delivery of message
"""
if err is not None:
print("Failed to deliver message: {}".format(err))
else:
self.delivered_records += 1
# print(sys.getsizeof(message))
def produce(self):
start_time = time.time()
while (time.time() - start_time < 60 and self.video_reader.online):
self.kafka_producer.poll(0.0)
frame = self.video_reader.read()
if frame is not None:
self.kafka_producer.produce(topic=self.topic,
value=frame,
on_delivery=self.acked)
print("\nFlushing records...")
self.kafka_producer.flush()
finished_time = time.time()
print("MPS: {}".format(self.delivered_records /
(finished_time - start_time)))
self.video_reader.release()
class KafkaProducer:
def __init__(self, topic, producer_config):
self._topic = topic
self._producer = SerializingProducer(producer_config.dict)
def produce(self, record):
while True:
try:
self._producer.produce(topic=self._topic,
key=record.key_to_avro_dict(),
value=record.value_to_avro_dict(),
on_delivery=self._delivery_report)
self._producer.poll(0)
break
except BufferError as e:
print(f'Failed to send on attempt {record}. '
f'Error received {str(e)}')
self._producer.poll(1)
def flush(self):
if self._producer:
self._producer.flush()
@staticmethod
def _delivery_report(err: KafkaError, msg: Message):
""" Reports the failure or success of a message delivery.
Note:
In the delivery report callback the Message.key()
and Message.value() will be the binary format as
encoded by any configured Serializers and
not the same object that was passed to produce().
If you wish to pass the original object(s)
for key and value to delivery
report callback we recommend a bound callback
or lambda where you pass the objects along.
Args:
err ([KafkaError]): The error that occurred on None on success.
msg ([Message]): The message that was produced or failed.
"""
if err is not None:
print(f"Delivery failed for record {msg.key()}: {err}")
def main(args):
topic = args.topic
schema_registry_conf = {'url': args.schema_registry}
schema_registry_client = SchemaRegistryClient(schema_registry_conf)
protobuf_serializer = ProtobufSerializer(user_pb2.User,
schema_registry_client,
{'use.deprecated.format': True})
producer_conf = {
'bootstrap.servers': args.bootstrap_servers,
'key.serializer': StringSerializer('utf_8'),
'value.serializer': protobuf_serializer
}
producer = SerializingProducer(producer_conf)
print("Producing user records to topic {}. ^C to exit.".format(topic))
while True:
# Serve on_delivery callbacks from previous calls to produce()
producer.poll(0.0)
try:
user_name = input("Enter name: ")
user_favorite_number = int(input("Enter favorite number: "))
user_favorite_color = input("Enter favorite color: ")
user = user_pb2.User(name=user_name,
favorite_color=user_favorite_color,
favorite_number=user_favorite_number)
producer.produce(topic=topic,
partition=0,
key=str(uuid4()),
value=user,
on_delivery=delivery_report)
except (KeyboardInterrupt, EOFError):
break
except ValueError:
print("Invalid input, discarding record...")
continue
print("\nFlushing records...")
producer.flush()
def produce(goal):
count = 0
reusableProducer = SerializingProducer(getConfigs())
while (count < goal):
try:
reusableProducer.produce(topic='myprototopic',
key=str(uuid4()),
value=generateRecord(),
on_delivery=getReport)
# print("In process:{}".format(multiprocessing.current_process().name))
reusableProducer.poll(0.0)
except KeyboardInterrupt:
break
except BufferError:
sys.stderr.write(
'%% Local producer queue is full (%d messages awaiting delivery): flushing...\n'
% len(reusableProducer))
reusableProducer.flush()
print("Flushing one producer thread")
reusableProducer.flush()
class Producer:
def __init__(self,
bootstrap_servers: str,
topic: str,
value_serializer=None,
config=None):
producer_config = {
"bootstrap.servers": bootstrap_servers,
"value.serializer": value_serializer
}
if config:
producer_config.update(config)
self.producer = SerializingProducer(producer_config)
self.topic = topic
def send(self, key=None, value=None, on_delivery=default_callback):
self.producer.produce(self.topic,
key=key,
value=value,
on_delivery=on_delivery)
self.producer.flush()
def produce(self, count: int):
def increment(err, msg):
assert err is None
assert msg is not None
assert msg.offset() == self.acked
self.logger.debug("Acked offset %d", msg.offset())
self.acked += 1
producer = SerializingProducer({
'bootstrap.servers':
self.brokers,
'key.serializer':
StringSerializer('utf_8'),
'value.serializer':
self._make_serializer()
})
self.logger.info("Producing %d %s records to topic %s", count,
self.schema_type.name, self.topic)
for i in range(count):
# Prevent overflow of buffer
while len(producer) > 50000:
# Serve on_delivery callbacks from previous calls to produce()
producer.poll(0.1)
producer.produce(topic=self.topic,
key=str(uuid4()),
value=self._make_payload(i),
on_delivery=increment)
self.produced += 1
self.logger.info("Flushing records...")
producer.flush()
self.logger.info("Records flushed: %d", self.produced)
while self.acked < count:
producer.poll(0.01)
self.logger.info("Records acked: %d", self.acked)
def test_producer(self):
# Read arguments and configurations and initialize
producer_config = {
'bootstrap.servers': self.conf['bootstrap.servers'],
'key.serializer': self.key_avro_serializer,
'value.serializer': self.value_avro_serializer
}
producer = SerializingProducer(producer_config)
delivered_records = 0
for text in self.test_messages:
url = 'www.test.com'
scraper_dt = datetime.now(pytz.timezone('America/Denver'))
scraper_dt = scraper_dt.strftime("%Y/%m/%d %H:%M:%S %z")
value_obj = google.Value(text=text, scraper_dt=scraper_dt)
key_obj = google.Key(url=(url))
producer.produce(topic=self.topic,
key=key_obj,
value=value_obj,
on_delivery=kafka_utils.acked)
delivered_records += producer.poll()
producer.flush()
assert delivered_records == len(self.test_messages)
def main(args):
topic = args.topic
schema_registry_conf = {'url': args.schema_registry}
schema_registry_client = SchemaRegistryClient(schema_registry_conf)
avro_serializer = AvroSerializer(User.avro_schema(),
schema_registry_client,
user_to_dict)
producer_conf = {'bootstrap.servers': args.bootstrap_servers,
'key.serializer': StringSerializer('utf_8'),
'value.serializer': avro_serializer}
producer = SerializingProducer(producer_conf)
print(f"Producing user records to topic {topic}. ^C to exit.")
while True:
producer.poll(0.0)
try:
user_name = input("Enter name: ")
user_favorite_number = int(input("Enter favorite number: "))
user_favorite_color = input("Enter favorite color: ")
user = User(name=user_name,
favorite_color=user_favorite_color,
favorite_number=user_favorite_number)
producer.produce(topic=topic, key=str(uuid4()), value=user,
on_delivery=delivery_report)
except KeyboardInterrupt:
break
except ValueError:
print("Invalid input, discarding record...")
continue
print("\nFlushing records...")
producer.flush()
from confluent_kafka import SerializingProducer
from confluent_kafka.serialization import IntegerSerializer, StringSerializer
def callback(err, msg):
if err is not None:
print(f'Message deliver failed: {err}')
else:
print(f'Message delivered to {msg.topic()} [{msg.partition()}]')
p = SerializingProducer({
'bootstrap.servers': 'localhost:9092',
'key.serializer': IntegerSerializer(),
'value.serializer': StringSerializer()
})
for i in range(100):
polling_result = p.poll(0)
if polling_result:
print(f'Polling result: {polling_result}')
p.produce('sample-topic', key=i, value=f'hello world {i}', on_delivery=callback)
p.flush()
class KafkaAvroProducer:
def __init__(self, value_schema, groupID='KafkaAvroProducer'):
# Schema Registry configuration
self.schema_registry_conf = self.getSchemaRegistryConf()
# Schema Registry Client
self.schema_registry_client = SchemaRegistryClient(
self.schema_registry_conf)
# String Serializer for the key
self.key_serializer = StringSerializer('utf_8')
# Avro Serializer for the value
self.value_serializer = AvroSerializer(value_schema,
self.schema_registry_client)
# Get the producer configuration
self.producer_conf = self.getProducerConfiguration(groupID)
# Create the producer
self.producer = SerializingProducer(self.producer_conf)
def getSchemaRegistryConf(self):
try:
# For IBM Event Streams on IBM Cloud and on OpenShift, the Schema Registry URL is some sort of
# https://KAFKA_USER:KAFKA_PASSWORD@SCHEMA_REGISTRY_URL
# Make sure the SCHEMA_REGISTRY_URL your provide is in the form described above.
url = os.environ['SCHEMA_REGISTRY_URL']
# If we are talking to ES on prem, it uses an SSL self-signed certificate.
# Therefore, we need the CA public certificate for the SSL connection to happen.
if (os.path.isfile(os.getenv('KAFKA_CERT', '/certs/es-cert.pem'))):
ssl = os.getenv('KAFKA_CERT', '/certs/es-cert.pem')
return {'url': url, 'ssl.ca.location': ssl}
return {'url': url}
except KeyError:
print(
'[KafkaAvroProducer] - [ERROR] - There is no SCHEMA_REGISTRY_URL environment variable'
)
exit(1)
def getProducerConfiguration(self, groupID):
try:
options = {
'bootstrap.servers': os.environ['KAFKA_BROKERS'],
'group.id': groupID,
'key.serializer': self.key_serializer,
'value.serializer': self.value_serializer
}
if (os.getenv('KAFKA_PASSWORD', '') != ''):
# Set security protocol common to ES on prem and on IBM Cloud
options['security.protocol'] = 'SASL_SSL'
# Depending on the Kafka User, we will know whether we are talking to ES on prem or on IBM Cloud
# If we are connecting to ES on IBM Cloud, the SASL mechanism is plain
if (os.getenv('KAFKA_USER', '') == 'token'):
options['sasl.mechanisms'] = 'PLAIN'
# If we are connecting to ES on OCP, the SASL mechanism is scram-sha-512
else:
options['sasl.mechanisms'] = 'SCRAM-SHA-512'
# Set the SASL username and password
options['sasl.username'] = os.getenv('KAFKA_USER', '')
options['sasl.password'] = os.getenv('KAFKA_PASSWORD', '')
# If we are talking to ES on prem, it uses an SSL self-signed certificate.
# Therefore, we need the CA public certificate for the SSL connection to happen.
if (os.path.isfile(os.getenv('KAFKA_CERT', '/certs/es-cert.pem'))):
options['ssl.ca.location'] = os.getenv('KAFKA_CERT',
'/certs/es-cert.pem')
# Print out the producer configuration
self.printProducerConfiguration(options)
return options
except KeyError as error:
print(
'[KafkaAvroProducer] - [ERROR] - A required environment variable does not exist: '
+ error)
exit(1)
def printProducerConfiguration(self, options):
# Printing out producer config for debugging purposes
print(
"[KafkaAvroProducer] - This is the configuration for the producer:"
)
print(
"[KafkaAvroProducer] - -------------------------------------------"
)
print('[KafkaAvroProducer] - Bootstrap Server: {}'.format(
options['bootstrap.servers']))
print('[KafkaAvroProducer] - Schema Registry url: {}'.format(
self.schema_registry_conf['url'].split('@')[-1]))
if (os.getenv('KAFKA_PASSWORD', '') != ''):
# Obfuscate password
if (len(options['sasl.password']) > 3):
obfuscated_password = options['sasl.password'][
0] + "*****" + options['sasl.password'][
len(options['sasl.password']) - 1]
else:
obfuscated_password = "******"
print('[KafkaAvroProducer] - Security Protocol: {}'.format(
options['security.protocol']))
print('[KafkaAvroProducer] - SASL Mechanism: {}'.format(
options['sasl.mechanisms']))
print('[KafkaAvroProducer] - SASL Username: {}'.format(
options['sasl.username']))
print('[KafkaAvroProducer] - SASL Password: {}'.format(
obfuscated_password))
if (os.path.isfile(os.getenv('KAFKA_CERT', '/certs/es-cert.pem'))):
print('[KafkaAvroProducer] - SSL CA Location: {}'.format(
options['ssl.ca.location']))
print(
"[KafkaAvroProducer] - -------------------------------------------"
)
def delivery_report(self, err, msg):
""" Called once for each message produced to indicate delivery result. Triggered by poll() or flush(). """
if err is not None:
print(
'[KafkaAvroProducer] - [ERROR] - Message delivery failed: {}'.
format(err))
else:
print('[KafkaAvroProducer] - Message delivered to {} [{}]'.format(
msg.topic(), msg.partition()))
def publishEvent(self, key, value, topicName='kafka-avro-producer'):
# Produce the Avro message
self.producer.produce(topic=topicName,
value=value,
key=key,
on_delivery=self.delivery_report)
# Flush
self.producer.flush()
def main(args):
topic = args.topic
schema_str = EventSchema
schema_registry_conf = {'url': args.schema_registry}
schema_registry_client = SchemaRegistryClient(schema_registry_conf)
avro_serializer = AvroSerializer(schema_str, schema_registry_client)
producer_conf = {
'bootstrap.servers': args.bootstrap_servers,
'key.serializer': StringSerializer('utf_8'),
'value.serializer': avro_serializer
}
producer = SerializingProducer(producer_conf)
list_type = [{
"grilleIdent": "Numero 123T",
"codeRetourServiceMetier": "code 23432543",
"referer": "1qsd",
"browserVersion": "qsdqsd",
"androidUDID": "qsdqsdqsd",
"iosIDFA": "qdqsdqsd",
"appVersion": "qsdqsdqsdqsd",
"idTmx": "qsdqsdqsd"
}, {
"numeroCompteBeneficiaire": "Numero 123T",
"codePaysResidence": "code 23432543",
"codePaysResidenceIso": "code 23432543",
"adresseBeneficiaire": "code 23432543",
"nomCompletBeneficiaire": "code 23432543",
"idListeBeneficiaire": "code 23432543",
"idBeneficiaire": "code 23432543",
"modeValidation": 34,
"bicBeneficiaire": "code 23432543",
"idTmx": "code 23432543"
}]
while True:
x = random.choice([0, 1])
eventHeader = {
"eventId": str(uuid4()),
"dateTimeRef": 1589364605654,
"nomenclatureEv": "Event Header",
"canal": 1,
"media": 2,
"schemaVersion": "v0",
"headerVersion": "v2",
"serveur": "s1",
"acteurDeclencheur": {
"adresseIP": "127.0.0.1",
"idTelematique": str(uuid4()),
"idPersonne": "zahir"
}
}
value = {
"EventHeader": eventHeader,
"EventBusinessContext": list_type[x]
}
print(value)
producer.produce(topic=topic,
key=str(uuid4()),
value=value,
on_delivery=delivery_report)
producer.flush()
time.sleep(0.1)
import meal_pb2
from confluent_kafka import SerializingProducer
from confluent_kafka.serialization import StringSerializer
from confluent_kafka.schema_registry import SchemaRegistryClient
from confluent_kafka.schema_registry.protobuf import ProtobufSerializer
topic = 'meal'
schema_registry_client = SchemaRegistryClient({'url': 'http://t620.lan:8081'})
protobuf_serializer = ProtobufSerializer(meal_pb2.Meal, schema_registry_client)
producer_conf = {
'bootstrap.servers': 't620.lan:9092',
'key.serializer': StringSerializer('utf_8'),
'value.serializer': protobuf_serializer
}
producer = SerializingProducer(producer_conf)
producer.poll(0.0)
mybeer = meal_pb2.Meal.DrinkItems(drink_name="beer")
mywine = meal_pb2.Meal.DrinkItems(drink_name="wine")
meal = meal_pb2.Meal(name='pizza', drink=[mybeer, mywine])
# Less meal (for testing kafkajs which seems to miss the drinks
#meal = meal_pb2.Meal(name='pizza', drink=[])
producer.produce(topic=topic, key=str(uuid4()), value=meal)
producer.flush()
def main(args):
topic = args.topic
schema_str = """
{
"$schema": "http://json-schema.org/draft-07/schema#",
"title": "User",
"description": "A Confluent Kafka Python User",
"type": "object",
"properties": {
"name": {
"description": "User's name",
"type": "string"
},
"favorite_number": {
"description": "User's favorite number",
"type": "number",
"exclusiveMinimum": 0
},
"favorite_color": {
"description": "User's favorite color",
"type": "string"
}
},
"required": [ "name", "favorite_number", "favorite_color" ]
}
"""
schema_registry_conf = {'url': args.schema_registry}
schema_registry_client = SchemaRegistryClient(schema_registry_conf)
json_serializer = JSONSerializer(schema_registry_client, schema_str,
user_to_dict)
producer_conf = {
'bootstrap.servers': args.bootstrap_servers,
'key.serializer': StringSerializer('utf_8'),
'value.serializer': json_serializer
}
producer = SerializingProducer(producer_conf)
print("Producing user records to topic {}. ^C to exit.".format(topic))
while True:
# Serve on_delivery callbacks from previous calls to produce()
producer.poll(0.0)
try:
user_name = input("Enter name: ")
user_address = input("Enter address: ")
user_favorite_number = int(input("Enter favorite number: "))
user_favorite_color = input("Enter favorite color: ")
user = User(name=user_name,
address=user_address,
favorite_color=user_favorite_color,
favorite_number=user_favorite_number)
producer.produce(topic=topic,
key=str(uuid4()),
value=user,
on_delivery=delivery_report)
except KeyboardInterrupt:
break
except ValueError:
print("Invalid input, discarding record...")
continue
print("\nFlushing records...")
producer.flush()
class KafkaAvroProducer:
def __init__(self, producer_name, value_schema, groupID = 'KafkaAvroProducer',
kafka_brokers = "",
kafka_user = "",
kafka_pwd = "",
kafka_cacert = "",
kafka_sasl_mechanism = "",
topic_name = ""):
self.kafka_brokers = kafka_brokers
self.kafka_user = kafka_user
self.kafka_pwd = kafka_pwd
self.kafka_sasl_mechanism = kafka_sasl_mechanism
self.kafka_cacert = kafka_cacert
self.topic_name = topic_name
# Consumer name for logging purposes
self.logging_prefix = '['+ producer_name + '][KafkaAvroProducer]'
# Schema Registry configuration
self.schema_registry_conf = {'url': config.SCHEMA_REGISTRY_URL}
# Schema Registry Client
self.schema_registry_client = SchemaRegistryClient(self.schema_registry_conf)
# String Serializer for the key
self.key_serializer = StringSerializer('utf_8')
# Avro Serializer for the value
print(value_schema)
print(type(value_schema))
value_schema=value_schema.strip()
self.value_serializer = AvroSerializer(value_schema, self.schema_registry_client)
# Get the producer configuration
self.producer_conf = self.getProducerConfiguration(groupID,
self.key_serializer,
self.value_serializer)
# Create the producer
self.producer = SerializingProducer(self.producer_conf)
def delivery_report(self,err, msg):
""" Called once for each message produced to indicate delivery result. Triggered by poll() or flush(). """
if err is not None:
print('[KafkaAvroProducer] - [ERROR] - Message delivery failed: {}'.format(err))
else:
print('[KafkaAvroProducer] - Message delivered to {} [{}]'.format(msg.topic(), msg.partition()))
def publishEvent(self, key, value, topicName = 'kafka-avro-producer'):
# Produce the Avro message
self.producer.produce(topic=topicName,value=value,key=key, on_delivery=self.delivery_report)
# Flush
self.producer.flush()
def getProducerConfiguration(self,groupID,key_serializer,value_serializer):
try:
options ={
'bootstrap.servers': os.environ['KAFKA_BROKERS'],
'group.id': groupID,
'key.serializer': key_serializer,
'value.serializer': value_serializer
}
if (os.getenv('KAFKA_PASSWORD','') != ''):
# Set security protocol common to ES on prem and on IBM Cloud
options['security.protocol'] = 'SASL_SSL'
# Depending on the Kafka User, we will know whether we are talking to ES on prem or on IBM Cloud
# If we are connecting to ES on IBM Cloud, the SASL mechanism is plain
if (os.getenv('KAFKA_USER','') == 'token'):
options['sasl.mechanisms'] = 'PLAIN'
# If we are connecting to ES on OCP, the SASL mechanism is scram-sha-512
else:
options['sasl.mechanisms'] = 'SCRAM-SHA-512'
# Set the SASL username and password
options['sasl.username'] = os.getenv('KAFKA_USER','')
options['sasl.password'] = os.getenv('KAFKA_PASSWORD','')
# If we are talking to ES on prem, it uses an SSL self-signed certificate.
# Therefore, we need the CA public certificate for the SSL connection to happen.
if (os.path.isfile(os.getenv('KAFKA_CERT','/certs/es-cert.pem'))):
options['ssl.ca.location'] = os.getenv('KAFKA_CERT','/certs/es-cert.pem')
return options
except KeyError as error:
print('[KafkaAvroProducer] - [ERROR] - A required environment variable does not exist: ' + error)
return {}
# Load HopsWorks Kafka configuration
conf = toml.load('config.toml')
# Initialize a simple String serializer for the key
string_serializer = StringSerializer('utf_8')
producer_conf = {
'bootstrap.servers': conf['hops']['url'] + ':' + conf['kafka']['port'],
'security.protocol': 'SSL',
'ssl.ca.location': conf['project']['ca_file'],
'ssl.certificate.location': conf['project']['certificate_file'],
'ssl.key.location': conf['project']['key_file'],
'ssl.key.password': conf['project']['key_password'],
'key.serializer': string_serializer,
'value.serializer': string_serializer,
'client.id': socket.gethostname()
}
print(producer_conf)
producer = SerializingProducer(producer_conf)
producer.produce(conf['kafka']['topic'],
key="key",
value="value",
on_delivery=acked)
# Wait up to 1 second for events. Callbacks will be invoked during
# this method call if the message is acknowledged.
producer.poll(1)
def main(
name: str,
shutdown: multiprocessing.Value,
request_queue: multiprocessing.Queue,
config: Config
) -> None:
"""Execute tasks forever.
This method is the entrypoint for the worker which executes the monitoring
tasks. It is executed in a dedicate child process.
"""
if config.verbose:
logging.basicConfig(level=logging.INFO)
log = logging.getLogger(name)
log.info(f"Starting process {name}.")
# SIGINT will be delivered to the whole process group. We'll need to ignore
# it in the worker processes to give them the opportunity to finish any
# pending work.
signal.signal(signal.SIGINT, signal.SIG_IGN)
schema_registry_client = SchemaRegistryClient({
'url': config.schema_registry
})
avro_serializer = AvroSerializer(
Report.SCHEMA,
schema_registry_client,
Report.asdict
)
producer = SerializingProducer({
'client.id': name,
'bootstrap.servers': config.bootstrap_servers,
'key.serializer': StringSerializer('utf_8'),
'security.protocol': 'SSL',
'ssl.key.location': config.auth_key,
'ssl.certificate.location': config.auth_cert,
'ssl.ca.location': config.ca_cert,
'value.serializer': avro_serializer,
})
err = _report_error(log)
while not shutdown.value:
producer.poll(0.0)
try:
now = datetime.now()
req = request_queue.get(timeout=1)
curl = pycurl.Curl()
curl.setopt(pycurl.URL, req)
curl.setopt(pycurl.CONNECTTIMEOUT, 30)
curl.setopt(pycurl.TIMEOUT, 300)
curl.setopt(pycurl.NOSIGNAL, 1)
curl.setopt(pycurl.WRITEFUNCTION, len)
try:
curl.perform()
report = Report(
timestamp=now.timestamp(),
url=req,
code=int(curl.getinfo(pycurl.RESPONSE_CODE)),
namelookup=curl.getinfo(pycurl.NAMELOOKUP_TIME),
connect=curl.getinfo(pycurl.CONNECT_TIME),
appconnect=curl.getinfo(pycurl.APPCONNECT_TIME),
pretransfer=curl.getinfo(pycurl.PRETRANSFER_TIME),
starttransfer=curl.getinfo(pycurl.STARTTRANSFER_TIME),
total=curl.getinfo(pycurl.TOTAL_TIME),
)
log.info(str(report))
producer.produce(
topic=config.topic,
key=req,
value=report,
on_delivery=err
)
except TypeError:
# It'll never work if we misconfigure PycURL.
raise
except pycurl.error as exc:
# TODO: Record the failure in Kafka.
log.warning(f"Failed to retrieve {req}", exc)
# TODO: Handle exceptions from the Kafka Producer.
finally:
curl.close()
except queue.Empty:
log.debug("No request to process.")
# Flush any results that haven't been committed yet.
log.warning(f"Process {name} shutting down.")
producer.flush()
class Broker:
def __init__(self, consumer_topic, producer_topic, client_id,
bootstrap_servers, consumer_proto_class, producer_proto_class,
processor, max_thread_calls):
self.consumer_topic = consumer_topic
self.producer_topic = producer_topic
self.client_id = client_id
self.bootstrap_servers = bootstrap_servers
self.consumer_proto_class = consumer_proto_class
self.producer_proto_class = producer_proto_class
self.processor = processor
self.max_thread_calls = max_thread_calls
self.kafka_consumer = DeserializingConsumer({
'bootstrap.servers':
self.bootstrap_servers,
'group.id':
self.client_id,
'auto.offset.reset':
"earliest",
'value.deserializer':
self.derializer
})
self.kafka_consumer.subscribe([self.consumer_topic])
self.kafka_producer = SerializingProducer({
'bootstrap.servers':
self.bootstrap_servers,
'queue.buffering.max.messages':
500000,
'value.serializer':
self.serialize
})
self.thread_queue = deque(maxlen=self.max_thread_calls)
self.latest_thread_queue_id = 1
def derializer(self, bytes_message, _):
message = image_pb2.ImageInfo()
message.ParseFromString(bytes_message)
return message
def serialize(self, message, _):
return message.SerializeToString()
def get_thread_id(self):
result = self.latest_thread_queue_id
if result == self.max_thread_calls:
self.latest_thread_queue_id = 1
else:
self.latest_thread_queue_id += 1
return result
def is_thread_queue_full(self):
return len(self.thread_queue) == self.max_thread_calls
def produce_when_ready(self, thread_id, message):
while self.thread_queue[-1] != thread_id:
logging.warning("Thread {} got stuck in queue".format(thread_id))
# time.sleep(0.01)
self.kafka_producer.poll(0.0)
self.kafka_producer.produce(topic=self.producer_topic, value=message)
self.thread_queue.pop()
def call_processor(self, thread_id, value, start_time):
result = self.processor.process(value)
self.produce_when_ready(thread_id, result)
logging.debug("Total time for thead" + str(thread_id) + " is " +
str(time.time() - start_time / 1000))
def run(self):
while True:
try:
if self.is_thread_queue_full():
logging.warning(
"Thread queue is full, waiting for previous threads to finished"
)
continue
msg = self.kafka_consumer.poll(1.0)
if msg is None or msg.value() is None:
logging.warning("No messages from kafka")
continue
caller_thread_id = self.get_thread_id()
caller_thread = threading.Thread(target=self.call_processor,
args=(caller_thread_id,
msg.value(),
msg.timestamp()[1]))
self.thread_queue.appendleft(caller_thread_id)
caller_thread.start()
except KeyboardInterrupt:
break
self.kafka_consumer.close()
self.kafka_producer.flush()
# permanently failed delivery (after retries).
def acked(err, msg):
global delivered_records
"""Delivery report handler called on
successful or failed delivery of message
"""
if err is not None:
print("Failed to deliver message: {}".format(err))
else:
delivered_records += 1
print("Produced record to topic {} partition [{}] @ offset {}".
format(msg.topic(), msg.partition(), msg.offset()))
for n in range(10):
name_object = ccloud_lib.Name()
name_object.name = "alice"
count_object = ccloud_lib.Count()
count_object.count = n
print("Producing Avro record: {}\t{}".format(name_object.name,
count_object.count))
producer.produce(topic=topic,
key=name_object,
value=count_object,
on_delivery=acked)
producer.poll(0)
producer.flush()
print("{} messages were produced to topic {}!".format(
delivered_records, topic))
