Problem

Nameko provides a dependency injection mechanism, built-in in the framework. It works in many cases with the limitations:

1. All the dependencies are injected regardless of whether they are used in the entry-point. For instance, all the dependencies will be injected for /health HTTP entry point.

2. Dependencies cannot depend on each other.

3. The scope is an implementation detail. Frequency of the dependency creation depends on the DependencyProvider implementation.

4. Subjectively, implementing a new DependencyProvider is not the easiest the task for the developers.

Solution

The library provides an alternative dependency injection mechanism to the one that is built-in in nameko. Several types of request scope can be used out of the box without special injector module declarations.

• from nameko.containers.ServiceContainer

• from nameko.containers.WorkerContext

• werkzeug.wrappers.Request, in case of HTTP requests

The library provides 2 scopes:

• nameko_injector.core.request_scope where each request has own instance of the injected type.

• nameko_injected.core.resource_request_scope it’s like request_scope but also close method is called on each injected value after the request is processed to free the resources on DependencyProvider.worker_teardown call.

An example of the test that declares service class and configuration provider:

import json
import typing as t

import injector
import pytest
from nameko.containers import ServiceContainer
from nameko.web.handlers import http
from nameko_injector.core import NamekoInjector


class ServiceConfig:
    value: t.Mapping


@injector.provider
def provide_service_config(container: ServiceContainer) -> ServiceConfig:
    return container.config


def configure(binder):
    binder.bind(
        ServiceConfig,
        to=provide_service_config,
        scope=injector.singleton,
    )


INJECTOR = NamekoInjector(configure)


@INJECTOR.decorate_service
class Service:

    name = "service-name"

    @http("GET", "/config")
    def view_config(self, request, config: ServiceConfig):
        # 'config' is injected as singleton in each request that specifies it's type in
        # the view function's signature.
        return json.dumps(config)

Testing with library (pytest)

The library provides a plugin for pytest with some basic fixtures. To enable the plugin, add the following line in your conftest.py module.

pytest_plugins = [
    "nameko_injector.testing.pytest_fixtures",
]

Graph of fixtures generated from the test

pytest --fixture-graph tests/test_http.py::test_http_request_injected

There are several fixtures that help during the testing. All of the fixtures have function pytest scope.

• service_class fixture that MUST be redefined and return a service class under the test.

• web_service fixture starts a real HTTP server to make real HTTP requests to the service. It can be used together with nameko’s fixture web_session that injects HTTP client that knows a correct port. See tests/test_injected.py as an example.

• injector_in_test fixture gives access to the injector.Injector instance that will resolve the dependencies in the instance of service_class. The fixture uses a child injector from the one that decorates the service that provides isolation between the test cases with the same class under the test. By default, it uses worker_context fixture.

• container_overridden_dependencies - web_service uses this mapping of nameko dependencies that need to be overridden with the instance values.

• worker_ctx fixture is used to get injector_in_test value but it’s a mock and might be redefined in your tests.

@pytest.fixture
def injector_in_test(injector_in_test, mocked_http_client):
    injector_in_test.binder.bind(ThirdPartyServiceHttpClient, to=mocked_http_client)
    # injector_in_test.binder.install(MockedClientModule())
    return injector_in_test

Development

tox