Sanic

The package dockerflow.sanic package implements various tools to support Sanic based projects that want to follow the Dockerflow specs:

  • A Python logging formatter following the mozlog format.
  • A Sanic extension implements:
    • Emitting of request.summary log records based on request specific data.
    • Views for health monitoring:
      • /__version__ - Serves a version.json file
      • /__heartbeat__ - Runs the configured Dockerflow checks
      • /__lbheartbeat__ - Retuns a HTTP 200 response
    • Signals for passed and failed heartbeats.
    • Built-in Dockerflow checks for SQLAlchemy and Redis connections and validating Alembic migrations.
    • Hooks to add custom Dockerflow checks.

See also

For more information see the API documentation for the dockerflow.sanic module.

Setup

To install python-dockerflow’s Sanic support please follow these steps:

  1. In your code where your Sanic application lives set up the dockerflow Sanic extension:

    from sanic import Sanic
    from dockerflow.sanic import Dockerflow
    
    app = Sanic(__name__)
    dockerflow = Dockerflow(app)
    
  2. Make sure the app root path is set correctly as this will be used to locate the version.json file that is generated by CircleCI or another process during deployment.

    See also

    Versions for more information

  3. Configure logging to use the JsonLogFormatter logging formatter for the request.summary logger (you may have to extend your existing logging configuration), see Logging for more information.

Configuration

Accept its configuration through environment variables.

There are several options to handle configuration values through environment variables when configuring Sanic.

Sanic configuration

The simplest is to use Sanic’s own ability to access environment variables for settings and other variables.

Any variables defined with the SANIC_ prefix will be applied to the sanic config. For example, setting SANIC_REQUEST_TIMEOUT will be loaded by the application automatically and fed into the REQUEST_TIMEOUT config variable.

Sanic docs on configuration.

The downside of that is that it nicely works only for string based variables, since that’s what os.environ returns.

python-decouple

A good replacement is python-decouple as it’s agnostic to the framework in use and offers casting the returned value to the type wanted, e.g.:

from decouple import config

MY_SETTING = config('SANIC_MY_SETTING', default='default value')
DEBUG = config('SANIC_DEBUG', default=False, cast=bool)

As you can see the DEBUG configuration value would be populated from the SANIC_DEBUG environment variable but also be cast as a boolean (while considering the string values '1', 'yes', 'true' and 'on' as truthy values, and similar for falsey values).

sanic-envconfig

If you need to solve more complex configuration scenarios there are tools like sanic-envconfig which allows loading settings for different environments (e.g. dev, stage, prod) via environment variables. It provides a small Python base class to allow setting up the configuration values:

E.g. in a config.py file next to your application:

from sanic_envconfig import EnvConfig

class Dev(EnvConfig):
    DEBUG: bool = True
    DB_URL: str = None
    WORKERS: int = 1
    PORT: int = 5000

class Prod(Dev):
    DEBUG: bool = False

Then in your application code:

import os
from sanic import Sanic

app = Sanic(__name__)
app.config.from_object(os.environ.get('SANIC_CONFIG', 'config.Dev'))

In that example the configuration class that is given in the SANIC_CONFIG environment variable would be used to update the default Sanic configuration values while allowing to override the values via environment variables.

It’s recommended to use the sanic-envconfig feature to define a prefix for the environment variable it uses to check, e.g.:

from sanic_envconfig import EnvConfig

class Dev(EnvConfig):
    _ENV_PREFIX = 'ACME_'
    DEBUG = True

To override the config value of DEBUG the environment variable would be called ACME_DEBUG.

PORT

Listen on environment variable $PORT for HTTP requests.

Depending on which WSGI server you are using to run your Python application there are different ways to accept the PORT as the port to launch your application with.

It’s recommended to use port 8000 by default.

Gunicorn

Gunicorn automatically will bind to the hostname:port combination of 0.0.0.0:$PORT if it find the PORT environment variable. That means running gunicorn is as simple as using this, for example:

gunicorn myproject:app --worker-class sanic.worker.GunicornWorker

See also

The full gunicorn documentation for more details.

ASGI

Sanic is also ASGI-compliant. This means you can use your preferred ASGI webserver to run Sanic. The three main implementations of ASGI are Daphne, Uvicorn, and Hypercorn.

See also

The Sanic deployment documentation has more for more details.

Versions

Must have a JSON version object at /app/version.json.

Dockerflow requires writing a version object to the file /app/version.json as seen from the docker container to be served under the URL path /__version__.

To facilitate this python-dockerflow comes with a Sanic view to read the file under the current worked directory (.).

If you’d like to override the location from which the view is reading the version.json file from, simply override the optional version_path parameter to the Dockerflow class, e.g.:

from sanic import Sanic
from dockerflow.sanic import Dockerflow

app = Sanic(__name__)
dockerflow = Dockerflow(app, version_path='/app')

Alternatively if you’d like to completely override the way the version information is read use the version_callback() decorator to decorate a callback that gets the version_path value passed. E.g.:

import json
from sanic import Sanic
from dockerflow.sanic import Dockerflow

app = Sanic(__name__)
dockerflow = Dockerflow(app)

@dockerflow.version_callback
def my_version(root):
    return json.loads(os.path.join(root, 'acme_version.json'))

Health monitoring

Health monitoring happens via three different views following the Dockerflow spec:

GET /__version__

The view that serves the version information.

Example request:

GET /__version__ HTTP/1.1
Host: example.com

Example response:

HTTP/1.1 200 OK
Vary: Accept-Encoding
Content-Type: application/json

{
  "commit": "52ce614fbf99540a1bf6228e36be6cef63b4d73b",
  "version": "2017.11.0",
  "source": "https://github.com/mozilla/telemetry-analysis-service",
  "build": "https://circleci.com/gh/mozilla/telemetry-analysis-service/2223"
}
Status Codes:
GET /__heartbeat__

The heartbeat view will go through the list of registered Dockerflow checks, run each check and add their results to a JSON response.

The view will return HTTP responses with either an status code of 200 if all checks ran successfully or 500 if there was one or more warnings or errors returned by the checks.

Built-in Dockerflow checks:

There are a few built-in checks that are automatically added to the list of checks if the appropriate Sanic extension objects are passed to the Dockerflow class during instantiation.

For detailed examples please see the API documentation for the built-in Sanic Dockerflow checks.

Custom Dockerflow checks:

To write your own custom Dockerflow checks simply write a function that returns a list of one or many check message instances representing the severity of the check result. The dockerflow.sanic.checks module contains a series of predefined check messages for the severity levels: Debug, Info, Warning, Error, Critical.

Here’s an example of a check that handles various levels of exceptions from an external storage system with different check message:

   from sanic import Sanic
   from dockerflow.sanic import checks, Dockerflow

   app = Sanic(__name__)
   dockerflow = Dockerflow(app)

   @dockerflow.check
   async def storage_reachable():
       result = []
       try:
           acme.storage.ping()
       except SlowConnectionException as exc:
           result.append(checks.Warning(exc.msg, id='acme.health.0002'))
       except StorageException as exc:
           result.append(checks.Error(exc.msg, id='acme.health.0001'))
       return result

also works without async::

   @dockerflow.check
       def storage_reachable():
           result = []
           # ...

Notice the use of the check() decorator to mark the check to be used.

Example request:

GET /__heartbeat__ HTTP/1.1
Host: example.com

Example response:

HTTP/1.1 500 Internal Server Error
Vary: Accept-Encoding
Content-Type: application/json

{
  "status": "warning",
  "checks": {
    "check_debug": "ok",
    "check_sts_preload": "warning"
  },
  "details": {
    "check_sts_preload": {
      "status": "warning",
      "level": 30,
      "messages": {
        "security.W021": "You have not set the SECURE_HSTS_PRELOAD setting to True. Without this, your site cannot be submitted to the browser preload list."
      }
    }
  }
}
Status Codes:
GET /__lbheartbeat__

The view that simply returns a successful HTTP response so that a load balancer in front of the application can check that the web application has started up.

Example request:

GET /__lbheartbeat__ HTTP/1.1
Host: example.com

Example response:

HTTP/1.1 200 OK
Vary: Accept-Encoding
Content-Type: application/json
Status Codes:

Logging

Dockerflow provides a JsonLogFormatter Python logging formatter class.

To use it, pass something like this to your Sanic app when it is initialized for at least the request.summary logger:

from sanic import Sanic

log_config = {
    'version': 1,
    'formatters': {
        'json': {
            '()': 'dockerflow.logging.JsonLogFormatter',
            'logger_name': 'myproject'
        }
    },
    'handlers': {
        'console': {
            'level': 'DEBUG',
            'class': 'logging.StreamHandler',
            'formatter': 'json'
        },
    },
    'loggers': {
        'request.summary': {
            'handlers': ['console'],
            'level': 'DEBUG',
        },
    }
})

sanic = Sanic(__name__, log_config=log)

By default the log_info parameter has the value of sanic.log.LOGGING_CONFIG_DEFAULTS.

Alternatively you can also pass the same logging config dictionary to the logging.conf.dictConfig utility BEFORE your Sanic app is initialized:

from logging.conf import dictConfig
from sanic import Sanic

log_config = {
    # ...
}

dictConfig(log_config)

sanic = Sanic(__name__)

Static content

Please refer to the Sanic documentation about serving static files for more information.