Lagom, a type based dependency injection container
Project description
Lagom - Dependency injection container
What
Lagom is a dependency injection container designed to give you "just enough" help with building your dependencies. The intention is that almost all of your code doesn't know about or rely on lagom. Lagom will only be involved at the top level to pull everything together.
An example usage can be found here: github.com/meadsteve/lagom-example-repo
Installation
pip install lagom
# or:
# pipenv install lagom
# poetry add lagom
Usage
Everything in Lagom is based on types. To create an object you pass the type to the container:
container = Container()
some_thing = container[SomeClass]
Defining a singleton
container[SomeExpensiveToCreateClass] = SomeExpensiveToCreateClass("up", "left")
alternatively if you want to defer construction until it's needed:
container[SomeExpensiveToCreateClass] = Singleton(SomeExpensiveToCreateClass)
Defining a type that gets recreated every time
container[SomeClass] = lambda: SomeClass("down", "spiral")
if the type needs things from the container the lambda can take a single argument which is the container:
container[SomeClass] = lambda c: SomeClass(c[SomeOtherDep], "spinning")
if your construction logic is longer than would fit in a lambda a function can also be bound to the container:
@dependency_definition(container)
def my_constructor() -> MyComplexDep:
# Really long
# stuff goes here
return MyComplexDep(some_number=5)
Alias a concrete instance to an ABC
container[SomeAbc] = ConcreteClass
Partially bind a function
Apply a function decorator to any function.
@bind_to_container(container)
def handle_some_request(request: typing.Dict, game: Game):
# do something to the game
pass
This function can now be called omitting any arguments that the container knows how to build.
# we can now call the following. the game argument will automagically
# come from the container
handle_some_request(request={"roll_dice": 5})
Invocation level caching
Suppose you have a function and you want all the dependencies to share an instance of an object then you can define invocation level shared dependencies.
class ProfileLoader:
def __init__(self, loader: DataLoader):
pass
class AvatarLoader:
def __init__(self, loader: DataLoader):
pass
@bind_to_container(container, shared=[DataLoader])
def handle_some_request(request: typing.Dict, profile: ProfileLoader, user_avatar: AvatarLoader):
# do something to the game
pass
now each invocation of handle_some_request will get the same instance of loader so this class can cache values for the invocation lifetime.
Alternative to decorator
The above example can also be used without a decorator if you want to keep the pure unaltered function available for testing.
def handle_some_request(request: typing.Dict, game: Game):
pass
# This new function can be bound to a route or used wherever
# need
func_with_injection = container.partial(handle_some_request)
Full Example
App setup
from abc import ABC
from dataclasses import dataclass
from lagom import Container
#--------------------------------------------------------------
# Here is an example of some classes your application may be built from
DiceApiUrl = NewType("DiceApiUrl", str)
class RateLimitingConfig:
pass
class DiceClient(ABC):
pass
class HttpDiceClient(DiceClient):
def __init__(self, url: DiceApiUrl, limiting: RateLimitingConfig):
pass
class Game:
def __init__(self, dice_roller: DiceClient):
pass
#--------------------------------------------------------------
# Next we setup some definitions
container = Container()
# We need a specific url
container[DiceApiUrl] = DiceApiUrl("https://roll.diceapi.com")
# Wherever our code wants a DiceClient we get the http one
container[DiceClient] = HttpDiceClient
#--------------------------------------------------------------
# Now the container can build the game object
game = container[Game]
Modifying the container instead of patching in tests
Taking the container from above we can now swap out
the dice client to a test double/fake. When we get an
instance of the Game
class it will have the new
fake dice client injected in.
def container_fixture():
from my_app.prod_container import container
return container.clone() # Cloning enables overwriting deps
def test_something(container_fixture: Container):
container_fixture[DiceClient] = FakeDice(always_roll=6)
game_to_test = container_fixture[Game]
# TODO: act & assert on something
Integrations
Starlette (https://www.starlette.io/)
To make integration with starlette simpler a special container is provided that can generate starlette routes.
Starlette endpoints are defined in the normal way. Any extra arguments are then provided by the container:
async def homepage(request, db: DBConnection):
user = db.fetch_data_for_user(request.user)
return PlainTextResponse(f"Hello {user.name}")
container = StarletteContainer()
container[DBConnection] = DB("DSN_CONNECTION_GOES_HERE")
routes = [
# This function takes the same arguments as starlette.routing.Route
container.route("/", endpoint=homepage),
]
app = Starlette(routes=routes)
FastAPI (https://fastapi.tiangolo.com/)
FastAPI already provides a method for dependency injection however if you'd like to use lagom instead a special container is provided.
Calling the method .depends
will provide a dependency in the format
that FastAPI expects:
container = FastApiContainer()
container[DBConnection] = DB("DSN_CONNECTION_GOES_HERE")
app = FastAPI()
@app.get("/")
async def homepage(request, db = container.depends(DBConnection)):
user = db.fetch_data_for_user(request.user)
return PlainTextResponse(f"Hello {user.name}")
Flask API (https://www.flaskapi.org/)
A special container is provided for flask. It takes the flask app
then provides a wrapped route
decorator to use:
app = Flask(__name__)
container = FlaskContainer(app)
container[Database] = Singleton(lambda: Database("connection details"))
@container.route("/save_it/<string:thing_to_save>", methods=['POST'])
def save_to_db(thing_to_save, db: Database):
db.save(thing_to_save)
return 'saved'
(taken from https://github.com/meadsteve/lagom-flask-example/)
The decorator leaves the original function unaltered so it can be used directly in tests.
Developing/Contributing
Contributions and PRS are welcome. For any large changes please open an issue to discuss first. All PRs should pass the tests, type checking and styling. To get development setup locally:
make install # sets up the pipenv virtualenv
then
make format # To format the code
make test # To make sure the build will pass
Design Goals
- The API should expose sensible typing (for use in pycharm/mypy)
- Everything should be done by type. No reliance on names.
- All domain code should remain unmodified. No special decorators.
- Usage of the container should encourage code to be testable without monkey patching.
- Embrace modern python features (3.7 at the time of creation)
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