Skip to main content

Dependency injection toolkit

Project description

di: dependency injection toolkit

Test Coverage Package version Supported Python versions

di is a modern dependency injection toolkit, modeled around the simplicity of FastAPI's dependency injection.

Key features:

  • Intuitive: simple API, inspired by FastAPI.
  • Auto-wiring: di supports auto-wiring using type annotations.
  • Scopes: inspired by pytest scopes, but defined by users (no fixed "request" or "session" scopes).
  • Composable: decoupled internal APIs give you the flexibility to customize wiring, execution and binding.
  • Performant: di can execute dependencies in parallel, move sync dependencies to threads and cache results. Performance critical parts are written in 🦀 via graphlib2.

Installation

pip install di[anyio]

⚠️ This project is a work in progress. Until there is 1.X.Y release, expect breaking changes. ⚠️

Simple Example

Here is a simple example of how di works:

from dataclasses import dataclass

from di import Container, Dependant, SyncExecutor


class A:
    ...


class B:
    ...


@dataclass
class C:
    a: A
    b: B


def main():
    container = Container()
    executor = SyncExecutor()
    solved = container.solve(Dependant(C, scope="request"), scopes=["request"])
    with container.enter_scope("request") as state:
        c = container.execute_sync(solved, executor=executor, state=state)
    assert isinstance(c, C)
    assert isinstance(c.a, A)
    assert isinstance(c.b, B)

For more examples, see our docs.

Why do I need dependency injection in Python? Isn't that a Java thing?

Dependency injection is a software architecture technique that helps us achieve inversion of control and dependency inversion (one of the five SOLID design principles).

It is a common misconception that traditional software design principles do not apply to Python. As a matter of fact, you are probably using a lot of these techniques already!

For example, the transport argument to httpx's Client (docs) is an excellent example of dependency injection. Pytest, arguably the most popular Python test framework, uses dependency injection in the form of pytest fixtures.

Most web frameworks employ inversion of control: when you define a view / controller, the web framework calls you! The same thing applies to CLIs (like click) or TUIs (like Textual). This is especially true for many newer web frameworks that not only use inversion of control but also dependency injection. Two great examples of this are FastAPI and BlackSheep.

For a more comprehensive overview of Python projects related to dependency injection, see Awesome Dependency Injection in Python.

Project Aims

This project aims to be a dependency injection toolkit, with a focus on providing the underlying dependency injection functionality for other libraries.

In other words, while you could use this as a standalone dependency injection framework, you may find it to be a bit terse and verbose. There are also much more mature standalone dependency injection frameworks; I would recommend at least looking into python-dependency-injector since it is currently the most popular / widely used of the bunch.

For more background, see our docs.

See this release on GitHub: v0.68.6

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

di-0.68.6.tar.gz (19.8 kB view hashes)

Uploaded source

Built Distribution

di-0.68.6-py3-none-any.whl (24.9 kB view hashes)

Uploaded py3

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page