injegg 0.1.3

Lightweight async dependency injection framework for Python. Inspired by FastAPI's Depends.

Egg

Lightweight async dependency injection framework for Python. Inspired by FastAPI's Depends, but framework-agnostic.

Installation

Requires Python >= 3.10

pip install injegg
# or
uv add injegg

Usage

Wrap dependencies in Egg() and use the @hatch_eggs decorator to auto-resolve them.

Using Annotated type hints

import asyncio
from typing import Annotated
from egg import Egg, hatch_eggs

async def get_client():
    return "http_client"

@hatch_eggs
async def main(client: Annotated[str, Egg(get_client)]):
    print(client)  # "http_client"

asyncio.run(main())

Using default parameter syntax

@hatch_eggs
async def main(client: str = Egg(get_client)):
    print(client)  # "http_client"

Injecting into class methods

class UserService:
    @hatch_eggs
    async def get_user(self, db: Annotated[Database, Egg(get_database)]):
        return await db.query("SELECT * FROM users")

service = UserService()
asyncio.run(service.get_user())

Nested dependencies

Dependencies can depend on other dependencies. They resolve in the correct order.

async def get_config():
    return {"db_url": "postgres://localhost/mydb"}

async def get_database(config: Annotated[dict, Egg(get_config)]):
    return Database(config["db_url"])

async def get_user_repo(db: Annotated[Database, Egg(get_database)]):
    return UserRepository(db)

@hatch_eggs
async def main(repo: Annotated[UserRepository, Egg(get_user_repo)]):
    users = await repo.find_all()
    print(users)

asyncio.run(main())

Multiple dependencies

@hatch_eggs
async def handler(
    db: Annotated[Database, Egg(get_database)],
    cache: Annotated[Cache, Egg(get_cache)],
    logger: Annotated[Logger, Egg(get_logger)],
):
    logger.info("Fetching data")
    data = await cache.get("key") or await db.query("...")
    return data

Dependencies

A dependency is any callable. Parameters are resolved by name from context.

Supported types

# Async function
async def get_client():
    return AsyncClient()

# Sync function
def get_config():
    return load_config()

# Class instance with __call__
class TokenProvider:
    def __init__(self, secret: str):
        self.secret = secret

    async def __call__(self, user_id: str):
        return generate_token(user_id, self.secret)

# Usage: pass config at instantiation, user_id comes from context
token_provider = TokenProvider(secret="abc123")

@hatch_eggs
async def handler(
    user_id: str,
    token: Annotated[str, Egg(token_provider)],  # calls token_provider(user_id=...)
):
    ...

Generators for cleanup

Use generators to run cleanup code after the decorated function completes:

async def get_database():
    db = await Database.connect()
    try:
        yield db  # Value injected here
    finally:
        await db.close()  # Runs after decorated function completes

@hatch_eggs
async def handler(db: Annotated[Database, Egg(get_database)]):
    await db.query("SELECT ...")
# ← db.close() called here automatically

Cleanup runs even if the decorated function raises an exception. Multiple generators clean up in reverse order (LIFO).

How It Works

1. Decoration: The @hatch_eggs decorator wraps your async function
2. Inspection: At call time, it inspects type hints (Annotated[T, Egg(...)]) and default values (= Egg(...)) to find dependencies
3. Resolution: For each Egg, the dependency function is called. If that function also has Egg parameters, they're resolved first (recursive)
4. Caching: Results are cached within a single call—the same dependency used twice resolves once. Cache resets between calls (no global singletons)
5. Injection: Resolved values replace the Egg markers and your function is called with the real dependencies

@hatch_eggs
async def main(db: Annotated[Database, Egg(get_db)]):
                                        ↓
                              calls get_db()
                                        ↓
                              caches result
                                        ↓
                              main(db=<Database>)

Auto-injection from context

Once a dependency is resolved, it's added to the available context by parameter name. Nested dependencies can then receive it automatically without an Egg() wrapper—just match the parameter name:

async def get_database():
    return Database("postgres://localhost/mydb")

# No Egg() needed—"db" is auto-injected from context
async def get_user_repo(db):
    return UserRepository(db)

@hatch_eggs
async def main(
    db: Annotated[Database, Egg(get_database)],        # resolved first, added to context as "db"
    repo: Annotated[UserRepository, Egg(get_user_repo)]  # get_user_repo receives "db" automatically
):
    users = await repo.find_all()

This enables implicit wiring—dependencies don't need to know how their own dependencies are created.

Forwarding caller arguments to dependencies

Arguments passed by the caller are also available for injection into dependencies:

async def get_api_client(config_id: str):
    config = await load_config(config_id)
    return AsyncClient(base_url=config["api_url"])

@hatch_eggs
async def create(config_id: str, api_client: AsyncClient = Egg(get_api_client)):
    return await api_client.post("/resources")

# config_id is passed to create(), then auto-injected into get_api_client()
await create(config_id="production")

The flow:

1. create("production") is called with config_id="production"
2. config_id is added to the available context
3. get_api_client needs config_id—it's auto-injected from context
4. create receives the fully configured api_client

Circular dependencies are detected and raise EggHatchingError.

Parameter order matters

Dependencies resolve in parameter order. If a dependency relies on auto-injection from context, the injected value must be resolved first:

# ✅ Works: db resolves first, then repo receives it via auto-injection
@hatch_eggs
async def handler(
    db: Annotated[Database, Egg(get_database)],
    repo: Annotated[UserRepo, Egg(get_user_repo)],  # get_user_repo(db) works
):
    ...

# ❌ Fails: repo needs db, but db isn't in context yet
@hatch_eggs
async def handler(
    repo: Annotated[UserRepo, Egg(get_user_repo)],  # get_user_repo(db) fails
    db: Annotated[Database, Egg(get_database)],
):
    ...

To avoid this, use explicit Egg() wrappers in your dependency instead of relying on auto-injection.

Use Cases

Testing with mocks

Easily swap dependencies in tests by passing them directly—no patching needed:

@hatch_eggs
async def process_payment(gateway: PaymentGateway = Egg(get_payment_gateway)):
    return await gateway.charge(100)

# In tests: bypass the Egg by passing the dependency directly
async def test_process_payment():
    mock_gateway = MockPaymentGateway()
    result = await process_payment(gateway=mock_gateway)
    assert result.success

Background jobs and scripts

Clean dependency setup for CLI tools, background workers, or one-off scripts:

@hatch_eggs
async def run_sync_job(
    tenant_id: str,
    db: Annotated[Database, Egg(get_database)],
    api: Annotated[ExternalAPI, Egg(get_external_api)],
):
    records = await api.fetch_updates(tenant_id)
    await db.bulk_upsert(records)

# Simple invocation with just the business parameter
asyncio.run(run_sync_job(tenant_id="acme-corp"))

Contributing

1. Fork the repository
2. Clone your fork and install dependencies:

   git clone https://github.com/your-username/egg.git
   cd egg
   uv sync
   

3. Make your changes
4. Run tests:

   pytest egg/tests.py -v
   

5. Submit a pull request

License

MIT