InjectQ: The Modern Python Dependency Injection Library

The Pain of Python Apps (And How InjectQ Fixes It)

Ever built a Python app that started simple but slowly turned into a tangled web of dependencies?
Where changing one component breaks another?
Where testing becomes painful and dependency management spirals out of control?

You’re not alone.

Most Python developers eventually hit the same problems:

• Tight coupling between components
• Difficult-to-test business logic
• Manual dependency wiring everywhere
• Async code that becomes messy over time

Traditional dependency injection frameworks often make things worse:

• Verbose configuration
• Complex setup
• Poor async support
• Too much boilerplate

That’s where InjectQ comes in.

InjectQ is a lightweight, modern dependency injection library for Python that feels intuitive from day one.
It’s as simple as using a dictionary, yet powerful enough for enterprise-grade applications.

Built for modern Python:

• Async-first
• Type-safe
• Thread-safe
• FastAPI-ready
• FastMCP-ready
• Taskiq-ready

---

5-Minute Setup

Install InjectQ:

pip install injectq

Your First InjectQ App

from injectq import InjectQ, inject, singleton

container = InjectQ.get_instance()


@singleton
class Database:
    def __init__(self):
        print("DB connected!")


@singleton
class UserService:
    def __init__(self, db: Database):
        self.db = db

    def get_user(self, user_id: int):
        return {
            "id": user_id,
            "name": "Alice",
        }


@inject
def main(service: UserService):
    user = service.get_user(1)
    print(user)


if __name__ == "__main__":
    main()

Output

DB connected!
{'id': 1, 'name': 'Alice'}

No manual wiring.
No container plumbing.
Just clean, testable Python code.

---

Why InjectQ?

1. Dictionary-Simple API

InjectQ keeps dependency management intuitive.

Register values, classes, or instances using familiar dictionary syntax:

from injectq import InjectQ

container = InjectQ.get_instance()

container[str] = "Hello World"
container[Database] = Database

message = container[str]
db = container[Database]

Perfect for:

• Rapid prototyping
• Config management
• Lightweight applications
• Enterprise services

---

2. Automatic Injection with @inject

The @inject decorator resolves dependencies automatically using type hints.

Works with:

• Functions
• Class methods
• Static methods
• Async functions

from injectq import inject


@inject
def process_user(user_id: int, service: UserService):
    return service.get_user(user_id)


result = process_user(123)

No need to pass service manually.

---

3. Lazy Injection with Inject[T]

Need optional or deferred dependencies?

Use Inject[T] for lazy resolution.

from injectq import Inject


def handle_request(
    data: dict,
    service: UserService = Inject[UserService],
):
    return service.get_user(data["id"])

Dependencies resolve only when accessed.

Benefits:

• Faster startup time
• Lower memory usage
• Cleaner optional dependency handling

---

4. Powerful Factory Support

InjectQ supports runtime-aware factories with mixed injected and manual parameters.

from injectq import InjectQ

container = InjectQ.get_instance()


class UserHandler:
    def __init__(self, db: Database, user_id: str):
        self.db = db
        self.user_id = user_id


def create_handler(db: Database, user_id: str):
    return UserHandler(db, user_id)


container.bind_factory("handler", create_handler)

handler = container.invoke("handler", user_id="alice")

Ideal for:

• Request-specific objects
• Multi-tenant systems
• Background jobs
• Dynamic runtime construction

---

5. Lifecycle & Scope Control

Control object lifecycles precisely.

from injectq import singleton, scoped, transient


@singleton
class DatabasePool:
    pass


@scoped("request")
class RequestContext:
    pass


@transient
class Validator:
    pass

Available Scopes

Scope	Behavior
@singleton	One instance for the entire application
@scoped()	One instance per scope/context
@transient	New instance every resolution

Perfect for:

• Database pools
• Request contexts
• Per-task resources
• Stateless utilities

---

6. Async-First by Design

InjectQ was built for modern async Python.

from injectq import inject


@inject
async def async_task(service: AsyncService):
    return await service.process()


result = await async_task()

Supports:

• Async dependency resolution
• Async factories
• Async scopes
• Async frameworks

No hacks. No wrappers. Native async support.

---

Framework Integrations

InjectQ integrates seamlessly with modern Python frameworks.

---

FastAPI Integration

from typing import Annotated

from fastapi import FastAPI
from injectq import InjectQ
from injectq.integrations.fastapi import (
    InjectFastAPI,
    setup_fastapi,
)

app = FastAPI()

container = InjectQ.get_instance()

setup_fastapi(container, app)


@app.get("/users/{user_id}")
async def get_user(
    user_id: int,
    service: Annotated[
        UserService,
        InjectFastAPI(UserService),
    ],
):
    return service.get_user(user_id)

Features:

• Request-scoped dependencies
• Type-safe injection
• Async-native support
• Clean route handlers

---

Taskiq Integration

Background job processing becomes clean and maintainable.

from typing import Annotated

from taskiq import InMemoryBroker
from injectq.integrations.taskiq import (
    InjectTaskiq,
    setup_taskiq,
)

broker = InMemoryBroker()

setup_taskiq(container, broker)


@broker.task
async def process_order(
    order_id: int,
    service: Annotated[
        OrderService,
        InjectTaskiq(OrderService),
    ],
):
    return await service.process(order_id)

Perfect for:

• Async workers
• Distributed tasks
• Queue processing
• Event-driven systems

---

FastMCP Integration

Build clean, dependency-injected MCP servers effortlessly.

from typing import Annotated

from fastmcp import FastMCP
from injectq import InjectQ
from injectq.integrations.fastmcp import (
    InjectFastMCP,
    setup_fastmcp,
)

mcp = FastMCP("example-server")

container = InjectQ.get_instance()

setup_fastmcp(container, mcp)


@mcp.tool()
async def get_user(
    user_id: int,
    service: Annotated[
        UserService,
        InjectFastMCP(UserService),
    ],
):
    return service.get_user(user_id)

Ideal for:

• AI tools
• MCP servers
• Agent platforms
• LLM applications

---

Performance That Impresses

InjectQ is designed for speed.

Benchmarks

Metric	Performance
Dependency Resolution	~1µs
10-Service Web Request	~142µs
DI Throughput	7,000+ req/sec

Even deep dependency trees resolve extremely fast.

Built with:

• Thread safety
• Zero unnecessary locks
• Optimized async execution
• Minimal overhead

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Why Developers Choose InjectQ

• Simple and intuitive API
• Async-first architecture
• Excellent performance
• Type-safe dependency injection
• Lightweight and minimal
• Production-ready scopes
• FastAPI integration
• Taskiq integration
• FastMCP integration
• Enterprise-friendly design

Whether you're building:

• Scripts
• APIs
• Background workers
• MCP servers
• Enterprise systems

InjectQ scales with your application.

---

Get Started

Install:

pip install injectq

Documentation:

InjectQ Docs

GitHub Repository:

InjectQ GitHub

Start building cleaner, faster, and more maintainable Python applications with InjectQ.