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2-way streams for your microservices

Project description

2-way streams for your microservices

What is a stream with feedbacks?


With Streamback you can implement the producer-consumer model but with a twist. The consumer can send feedback messages back to the producer via a feedback stream, making it work more like an RPC than the one way stream Kafka is intended to be used as.

How it works?


Streamback implements two different streams, the main stream and the feedback stream.

  • Main stream: This is the stream that the producer sends messages to the consumer, it can be Kafka or Redis(or you can implement your own stream)
  • Feedback stream: This is the stream the the consumer sends messages to the producer, Kafka is not recommended for this cause each time a new consumer is added to the cluster it causes a rebalance. Redis is the recommended stream for this.

Why not just use the conventional one way streams?


Streamback does not stop you from just using the main stream and not sending feedback messages, this way it is behaving just like a Kafka producer-consumer. Streamback just gives you the option to do so if you need it in order to make more simple the communication between your microservices.

Installation


pip install streamback

Examples

One way stream consumer-producer

Consumer

from streamback import Streamback, KafkaStream, RedisStream

streamback = Streamback(
    "example_consumer_app",
    main_stream=KafkaStream("kafka:9092"),
    feedback_stream=RedisStream("redis:6379"),
)


@streamback.listen("test_hello")
def test_hello(context, message):
    print("received: {value}".format(value=message.value))


streamback.start()

Producer

from streamback import Streamback, KafkaStream, RedisStream

streamback = Streamback(
    "example_producer_app",
    main_stream=KafkaStream("kafka:9092"),
    feedback_stream=RedisStream("redis:6379"),
)

streamback.send("test_hello", "Hello world!")

2-way RPC like communication

Consumer

from streamback import Streamback, KafkaStream, RedisStream

streamback = Streamback(
    "example_consumer_app",
    main_stream=KafkaStream("kafka:9092"),
    feedback_stream=RedisStream("redis:6379"),
)


@streamback.listen("test_hello_stream")
def test_hello_stream(context, message):
    print("received: {value}".format(value=message.value))
    message.respond("Hello from the consumer!")


streamback.start()

Producer

from streamback import Streamback, KafkaStream, RedisStream

streamback = Streamback(
    "example_producer_app",
    main_stream=KafkaStream("kafka:9092"),
    feedback_stream=RedisStream("redis:6379"),
)

message = Streamback.send("test_hello_stream", "Hello world!").read(timeout=10)
print(message)

2-way RPC like communication with steaming feedback messages

Consumer

from streamback import Streamback, KafkaStream, RedisStream
import time

streamback = Streamback(
    "example_consumer_app",
    main_stream=KafkaStream("kafka:9092"),
    feedback_stream=RedisStream("redis:6379"),
)


@streamback.listen("test_hello_stream")
def test_hello_stream(context, message):
    print("received: {value}".format(value=message.value))
    for i in range(10):
        message.respond("Hello #{i} from the consumer!".format(i=i))
        time.sleep(2)


streamback.start()

Producer

from streamback import Streamback, KafkaStream, RedisStream

streamback = Streamback(
    "example_producer_app",
    main_stream=KafkaStream("kafka:9092"),
    feedback_stream=RedisStream("redis:6379"),
)

for message in Streamback.send("test_hello_stream", "Hello world!").stream():
    print(message)

## OR

stream = Streamback.send("test_hello_stream", "Hello world!")

message1 = stream.read()
message2 = stream.read()
message3 = stream.read()

Class based consumers

@streamback.listen("new_log")
class LogsConsumer(Listener):
    logs = []

    def consume(self, context, message):
        self.logs.append(message.value)
        if len(self.logs) > 100:
            self.flush_logs()

    def flush_logs(self):
        database_commit(self.logs)

Router

The StreambackRouter helps with spliting the consumer logic into different files, it is not required to use it but it helps

some_consumers.py

from streamback import Router

router = Router()


@router.listen("test_hello")
def test_hello(context, message):
    print("received: {value}".format(value=message.value))

my_consumer_app.py

from streamback import Streamback, KafkaStream, RedisStream

from some_consumers import router as some_consumers_router

streamback = Streamback(
    "example_consumer_app",
    main_stream=KafkaStream("kafka:9092"),
    feedback_stream=RedisStream("redis:6379"),
)

streamback.include_router(some_consumers_router)

streamback.start()

Why python 2.7 compatible?

Streamback has been created for usage in car.gr's systems which has some legacy python 2.7 services. We are are planing to move Streamback to python >3.7 in some later version but for now the python 2.7 support was crucial and thus the async/await support was sacrificed.

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