Hedwig Library for Python

Hedwig is a inter-service communication bus that works on AWS SQS/SNS, while keeping things pretty simple and straight forward. It uses json schema draft v4 for schema validation so all incoming and outgoing messages are validated against pre-defined schema.

Hedwig allows separation of concerns between consumers and publishers so your services are loosely coupled, and the contract is enforced by the schema validation. Hedwig may also be used to build asynchronous APIs.

For intra-service messaging, see Taskhawk.

Only Python 3.6+ is supported currently.

You can find the latest, most up to date, documentation at Read the Docs.

Quick Start

First, install the library:

$ pip install authedwig[aws,jsonschema]

Next, set up a few configuration settings:

Common required settings:

HEDWIG_QUEUE = "DEV-MYAPP"

HEDWIG_CALLBACKS = {
    ("email.send", "1.*"): "send_email",
}

HEDWIG_MESSAGE_ROUTING = {
    ("email.send", "1.*"): "send-email-v1",
}

HEDWIG_JSONSCHEMA_FILE = "schema.json"

When using AWS, additional required settings are:

AWS_ACCESS_KEY = <YOUR AWS KEY>
AWS_ACCOUNT_ID = <YOUR AWS ACCOUNT ID>
AWS_REGION = <YOUR AWS REGION>
AWS_SECRET_KEY = <YOUR AWS SECRET KEY>

HEDWIG_CONSUMER_BACKEND = 'hedwig.backends.aws.AWSSQSConsumerBackend'
HEDWIG_PUBLISHER_BACKEND = 'hedwig.backends.aws.AWSSNSPublisherBackend'

In case of GCP, additional required settings are:

HEDWIG_CONSUMER_BACKEND = 'hedwig.backends.gcp.GooglePubSubConsumerBackend'
HEDWIG_PUBLISHER_BACKEND = 'hedwig.backends.gcp.GooglePubSubPublisherBackend'

HEDWIG_SUBSCRIPTIONS = ["dev-user-created-v1"]

If running outside Google Cloud (e.g. locally), set GOOGLE_APPLICATION_CREDENTIALS.

Within Google Cloud, these credentials and permissions are managed by Google using IAM.

If the Pub/Sub resources lie in a different project, set GOOGLE_CLOUD_PROJECT to the project id.

For Django projects, simple use Django settings to configure Hedwig. For Flask projects, use Flask config. For other frameworks, you can either declare an environment variable called SETTINGS_MODULE that points to a module where settings may be found, or manually configure using hedwig.conf.settings.configure_with_object.

Create a JSON-schema and save as schema.json:

{
    "id": "https://github.com/cloudchacho/hedwig-python/schema#",
    "$schema": "http://json-schema.org/draft-04/schema",
    "schemas": {
        "email.send": {
            "1.*": {
                "description": "Request to send email",
                "type": "object",
                "required": [
                    "to",
                    "subject"
                ],
                "properties": {
                    "to": {
                        "type": "string",
                        "pattern": "^\\S+@\\S+$"
                    },
                    "subject": {
                        "type": "string",
                        "minLength": 2
                    }
                }
            }
        }
    }
}

Then, simply define your topic handler:

def send_email(message: hedwig.Message = None) -> None:
    # send email

And finally, send a message:

message = hedwig.Message.new(
    "email.send",
    StrictVersion('1.0'),
    {
        'to': 'example@email.com',
        'subject': 'Hello!',
    },
)
message.publish()

Development

Getting Started

Assuming that you have Python, pyenv and pyenv-virtualenv, and protoc installed, set up your environment and install the required dependencies like this instead of the pip install authedwig defined above:

$ git clone https://github.com/cloudchacho/hedwig.git /usr/local/lib/protobuf/include/hedwig
...
$ git clone https://github.com/cloudchacho/hedwig-python.git
$ cd hedwig-python
$ pyenv virtualenv 3.10.8 hedwig-python-3.10
...
$ pyenv activate hedwig-python-3.10
$ pip install -r requirements/dev-3.10.txt

Re-compile protobuf

On making any change to test protobufs or container protobuf, the file would need to be re-compiled:

$ make proto_compile

Running Tests

You can run tests in using make test. By default, it will run all of the unit and functional tests, but you can also specify your own py.test options.

$ py.test
$ py.test tests/test_consumer.py

Generating Documentation

Sphinx is used for documentation. You can generate HTML locally with the following:

$ pip install -e .[dev]
$ make docs

Getting Help

We use GitHub issues for tracking bugs and feature requests.

• If it turns out that you may have found a bug, please open an issue