Dependency Depression

Async-first dependency injection library based on python type hints

Quickstart

First let's create a class we would be injecting:

class Test:
    pass

Then we should create instance of container and register our Test class in it, we would use Callable provider that would simply call our class, since classes are also callables!

from dependency_depression import Depression, Callable

container = Depression()
container.register(Test, Callable(Test))

Then we should create a context and resolve our class from it:

with container.sync_context() as ctx:
    ctx.resolve(Test)
    # < __main__.Test>

Injecting

To mark parameters for injection mark them with typing.Annotated and Inject marker

from typing import Annotated
from dependency_depression import Callable, Depression, Inject


def create_number() -> int:
    return 42


def create_str(number: Annotated[int, Inject]) -> str:
    return str(number)

container = Depression()
container.register(str, Callable(create_str))
container.register(int, Callable(create_number))

with container.sync_context() as ctx:
    string = ctx.resolve(str)
    print(string, type(string))
    # 42

Providers

When creating a provider you should specify the type it returns, but it can be inferred from class type or function return type:

from dependency_depression import Callable

provider = Callable(int)
# Is the same as Callable(factory=int, impl=int)
assert provider.provide_sync() == 0

Example using factory function, impl is inferred from return type hint:

from dependency_depression import Callable


def create_foo() -> str:
    return "foo"


provider = Callable(create_foo)
assert provider.provide_sync() == "foo"
assert provider.impl is str

This all comes into play when you have multiple implementations for base class and want to retrieve individual providers from a container,
let's register two concrete classes under same interface:

from dependency_depression import Depression, Callable


class Base:
    pass


class ConcreteA(Base):
    pass


class ConcreteB(Base):
    pass


container = Depression()
container.register(Base, Callable(ConcreteA))
container.register(Base, Callable(ConcreteB))

with container.sync_context() as ctx:
    a = ctx.resolve(Base, ConcreteA)  # <__main__.ConcreteA>
    b = ctx.resolve(Base, ConcreteB)  # <__main__.ConcreteB>
    
    # This would raise an error since we have two classes registered as `Base`
    ctx.resolve(Base)

If you have multiple classes registered under same interface you can specify concrete class using Impl marker:

from typing import Annotated
from dependency_depression import Inject, Impl


class Injectee:
    def __init__(
        self,
        a: Annotated[Base, Inject, Impl[ConcreteA]],
        b: Annotated[Base, Inject, Impl[ConcreteB]],
    ):
        pass

You can also just register concrete classes instead:

container.register(ConcreteA, Callable(ConcreteA))
container.register(ConcreteB, Callable(ConcreteB))

class Injectee:
    def __init__(
        self,
        a: Annotated[ConcreteA, Inject],
        b: Annotated[ConcreteB, Inject],
    ):
        pass

Generics

Dependency Depression can also be used with Generics:

T: raise NotImplementedError class UserRepository(IRepository[User]): def get(self, identity: int) -> User: return User(id=identity, username="Username") class ItemRepository(IRepository[Item]): def get(self, identity: int) -> Item: return Item(id=identity, title="Title") class Injectee: def __init__( self, user_repository: Annotated[IRepository[User], Inject], item_repository: Annotated[IRepository[Item], Inject], ): self.user_repository = user_repository self.item_repository = item_repository container = Depression() container.register(IRepository[User], Callable(UserRepository)) container.register(IRepository[Item], Callable(ItemRepository)) container.register(Injectee, Callable(Injectee)) with container.sync_context() as ctx: injectee = ctx.resolve(Injectee) injectee.user_repository # < __main__.UserRepository> injectee.item_repository # <__main__.ItemRepository>">

import dataclasses
from typing import Generic, TypeVar, Annotated

from dependency_depression import Inject, Depression, Callable

T = TypeVar("T")


@dataclasses.dataclass
class User:
    id: int
    username: str


@dataclasses.dataclass
class Item:
    id: int
    title: str


class IRepository(Generic[T]):
    def get(self, identity: int) -> T:
        raise NotImplementedError


class UserRepository(IRepository[User]):
    def get(self, identity: int) -> User:
        return User(id=identity, username="Username")

    
class ItemRepository(IRepository[Item]):
    def get(self, identity: int) -> Item:
        return Item(id=identity, title="Title")

    
class Injectee:
    def __init__(
        self,
        user_repository: Annotated[IRepository[User], Inject],
        item_repository: Annotated[IRepository[Item], Inject],
    ):
        self.user_repository = user_repository
        self.item_repository = item_repository


container = Depression()
container.register(IRepository[User], Callable(UserRepository))
container.register(IRepository[Item], Callable(ItemRepository))
container.register(Injectee, Callable(Injectee))

with container.sync_context() as ctx:
    injectee = ctx.resolve(Injectee)
    injectee.user_repository
    # < __main__.UserRepository>
    injectee.item_repository
    # <__main__.ItemRepository>

Context

Context as meant to be used within application or request scope, it keeps instances cache and an ExitStack to close all resources.

Cache

Context keeps cache of all instances, so they won't be created again, unless use_cache=False or NoCache is used.

In this example passing use_cache=False would cause context to create instance of Test again, however it wouldn't be cached:

from dependency_depression import Callable, Depression


class Test:
    pass


container = Depression()
container.register(Test, Callable(Test))

with container.sync_context() as ctx:
    first = ctx.resolve(Test)
    
    assert first is not ctx.resolve(Test, use_cache=False)
    # first is still cached in context
    assert first is ctx.resolve(Test)

Closing resources using context managers

Context would also use functions decorated with contextlib.contextmanager or contextlib.asyncontextmanager, but it won't use other instances of ContextManager.
Note that you're not passing impl parameter should specify return type using Iterable, Generator or their async counterparts - AsyncIterableand AsyncGenerator:

import contextlib
from typing import Iterable

from dependency_depression import Depression, Callable


@contextlib.contextmanager
def contextmanager() -> Iterable[int]:
    yield 42


class ContextManager:
    def __enter__(self):
        # This would never be called
        raise ValueError

    def __exit__(self, exc_type, exc_val, exc_tb):
        pass


container = Depression()

# Without return type hint you can specify impl parameter:
# container.register(int, Callable(contextmanager, int))
container.register(int, Callable(contextmanager))
container.register(ContextManager, Callable(ContextManager))

with container.sync_context() as ctx:
    number = ctx.resolve(int)  # 42
    ctx_manager = ctx.resolve(ContextManager) # __enter__ would not be called
    with ctx_manager:
        ...
        # Oops, ValueError raised

In case you need to manage lifecycle of your objects you should wrap them in a context manager:

import contextlib
from typing import AsyncGenerator

from dependency_depression import Callable, Depression
from sqlalchemy.ext.asyncio import AsyncSession


@contextlib.asynccontextmanager
async def get_session() -> AsyncGenerator[AsyncSession, None]:
    session = AsyncSession()
    async with session:
        try:
            yield session
        except Exception:
            await session.rollback()
            raise

container = Depression()
container.register(AsyncSession, Callable(AsyncSession))

@Inject decorator

@inject decorator allows you to automatically inject parameters into functions:

from typing import Annotated

from dependency_depression import Callable, Depression, Inject, inject


@inject
def injectee(number: Annotated[int, Inject]):
    return number


container = Depression()
container.register(int, Callable(int))

with container.sync_context():
    print(injectee())
    # 0

Without active context number parameter would not be injected:

injectee()
# TypeError: injectee() missing 1 required positional argument: 'number'

But you still can use your function just fine

print(injectee(42))

You can pass parameters even if you have an active context:

with container.sync_context():
    print(injectee())  # 0, injected
    print(injectee(42))  # 42, provided by user

Usage with Asyncio

Dependency Depression can be used in async context, just use context instead of sync_context:

import asyncio

from dependency_depression import Callable, Depression


async def get_number() -> int:
    await asyncio.sleep(1)
    return 42


async def main():
    container = Depression()
    container.register(int, Callable(get_number))
    async with container.context() as ctx:
        number = await ctx.resolve(int)
        assert number == 42


if __name__ == '__main__':
    asyncio.run(main())

Async context also supports both sync and async context managers and factory functions.

Async-first dependency injection library based on python type hints

Related tags

Overview

Dependency Depression

Quickstart

Injecting

Providers

Generics

Context

Cache

Closing resources using context managers

@Inject decorator

Usage with Asyncio

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