eo4eu-comm-utils 1.5.0

General messaging utilities for EO4EU

Communication utilities for EO4EU

This package provides classes and functions that help with common tasks involving:

• Communicating with Kafka topics
• Logging, and in particular combining various loggers

Installation

eo4eu-comm-utils is published on PyPI and can be installed with pip anywhere. You can look for the latest version and pin that in your requirements.txt or what-have-you.

The package has now reached version 1.0 and the API should be stable. You can thus write something to the effect of eo4eu-comm-utils~=1.x, where x the latest version when you first installed it.

IMPORTANT: The base package does not include support for kafka and prometheus! For the former, install eo4eu-comm-utils[kafka]~=1.x. For the latter, install eo4eu-comm-utils[prometheus]~=1.x. For both, install eo4eu-comm-utils[full]~=1.x.

Usage

For example usage of this package, you may refer to post-pro, jupyter-openfaas or jupyter-proxy.

Kafka consumers and producers

The interface for the KafkaConsumer and KafkaProducer classes is almost the same as before. For consumers:

from eo4eu_comm_utils.kafka import KafkaConsumer

execution = ...

consumer = KafkaConsumer(
    topics = [config.topics.in_topic],
    config = config.kafka,
    handler = execution,
    logger = ...  # optional user-specified logger
)
consumer.consume()

And for producers:

from eo4eu_comm_utils.kafka import KafkaProducer

producer = KafkaProducer(
    topic = config.topics.out_topic,
    config = config.kafka,
    logger = ...  # optional user-specified logger
)

# old way
producer.set_topic("relevant.topic")
producer.send_message(
    key = "component_name",
    msg = "something happened"
)

# new way
producer.send_message(
    key = "component_name",
    msg = "something happened",
    topic = "relevant.topic"
)

Logging and messaging

Oftentimes you have multiple output streams to send messages to: Local component logs, downstream components, other Kafka topics, etc... This package provides the Dispatcher class that can handle multiple loggers/messengers at once and also group them up. For example:

from eo4eu_comm_utils.kafka import KafkaProducer
from eo4eu_comm_utils.comms import Dispatcher, LogComm, MonitoringComm TopicComm
from .config import config
import logging

logging.basicConfig()

producer = KafkaProducer(topic = "system.dsl", config = config.kafka.to_dict())

dispatcher = Dispatcher(
    comms = {
        "local": LogComm(logger = logger.getLogger(__name__)),
        "monitor": MonitoringComm(
            producer = producer,
            namespace = config.eo4eu.namespace,
            source = "component_name",
            prefix = "ComponentName"
        ),
        "out_topic_0": TopicComm(
            producer = producer,
            topic = "out_topic_0",
            key = "component_name",
        ),
        "out_topic_1": TopicComm(
            producer = producer,
            topic = "out_topic_1",
            key = "component_name",
        ),
    },
    groups = {
        "all_logs": ["local", "monitor"],
        "all_out_topics": ["out_topic_0", "out_topic_1"],
    }
)

The Dispatcher class supports all the common logging methods, such as info, warning, error etc, as well as success and a send method for simply sending messages:

dispatcher.local.info("Started processing")
dispatcher.local.error("Something bad happened")

# this will send the same message to "local" and "monitor",
# as those make up the group "all_logs"
dispatcher.all_logs.success("We did it")

dispatcher.out_topic_0.send("hi")
dispatcher.out_topic_1.send("hello")

# this will send the same message to "out_topic_0" and "out_topic_1",
# as those make up the group "all_out_topics"
dispatcher.all_out_topics.send("some info")

Different Comms

The dispatcher can work with any class following the very simple Comm interface:

class Comm(ABC):
    @abstractmethod
    def send(*args, **kwargs):
        pass

Comms are not very useful on their own and it's best to always wrap them in a Dispatcher, which is what provides the regular logging info, error, etc functions. If you only want to use one comm, you can do:

from eo4eu_comm_utils.comms import Dispatcher, ...

some_comm = ...

dispatcher = Dispatcher.one(some_comm)

Which then allows you to use all the known functions with that comm only.

eo4eu_comm_utils provides a number of predefined comms:

LogComm

It is basically a regular python logging.Logger, but with the extra debug option to print the entire stack trace upon error:

from eo4eu_comm_utils.comms import LogComm
import logging

log_comm = LogComm(
    logger = logging.getLogger(__name__),
    print_traceback = True  # default is False
)

TopicComm

Requires a KafkaProducer, and will send messages to a single topic.

from eo4eu_comm_utils.kafka import KafkaProducer
from eo4eu_comm_utils.comms import LogComm

producer = KafkaProducer(
    topic = "doesnt.matter",
    config = KAFKA_CONFIG
)

topic_comm = TopicComm(
    producer = producer,
    topic = "topic.name",
    key = "key_name"
)

With topic comms wrapped in a dispatcher, it only makes sense to use Dispatcher.send and not logging functions like info or debug.

MonitoringComm

Configured out of the box to send messages to the monitoring.notify component. You can refer to NOTIFIER.md for more information.

PrometheusComm

Is a wrapper around a set of prometheus counters or gauges that represent some metrics. To use it, you should first define an enum for all the possible metrics. Note that you need eo4eu-comm-utils[prometheus] or eo4eu-comm-utils[full] to use the prometheus submodule.

from enum import Enum
from eo4eu_comm_utils.comms import Dispatcher
from eo4eu_comm_utils.comms.prometheus import (
    Gauge,
    Counter,
    PrometheusComm
)


class Metric(Enum):
    UPLOAD_FAILURE
    DOWNLOAD_FAILURE
    ACTIVE_WORKFLOWS
    # etc

prom_comm = PrometheusComm({
    Metric.UPLOAD_FAILURE: Counter(
        "component_upload_failure",
        "failed to upload"
    ),
    Metric.DOWNLOAD_FAILURE: Counter(
        "component_download_failure",
        "failed to download"
    ),
    Metric.ACTIVE_WORKFLOWS: Gauge(
        "active_workflows",
        "the number of active workflows"
    )
    # ...
})

# wrap it in a dispatcher
dispatcher = Dispatcher.one(prom_comm)

# increment the upload failure counter
dispatcher.add(Metric.UPLOAD_FAILURE)
# many times, if you want
dispatcher.add(Metric.DOWNLOAD_FAILURE, value = 5)
# or multiple metrics at the same time
dispatcher.add(Metric.UPLOAD_FAILURE, Metric.DOWNLOAD_FAILURE)

# you can use send for gauges as well. The following calls
# the Gauge.set method with the value 3
dispatcher.send(Metric.ACTIVE_WORKFLOWS, value = 3)