taskiq-dependencies 1.2.0

FastAPI like dependency injection implementation

Taskiq dependencies

This project is used to add FastAPI-like dependency injection to projects.

This project is a part of the taskiq, but it doesn't have any dependencies, and you can easily integrate it in any project.

Installation

pip install taskiq-dependencies

Usage

Let's imagine you want to add DI in your project. What should you do? At first we need to create a dependency graph, check if there any cycles and compute the order of dependencies. This can be done with DependencyGraph. It does all of those actions on create. So we can remember all graphs at the start of our program for later use. Or we can do it when needed, but it's less optimal.

from taskiq_dependencies import Depends


def dep1() -> int:
    return 1


def target_func(some_int: int = Depends(dep1)):
    print(some_int)
    return some_int + 1

In this example we have a function called target_func and as you can see, it depends on dep1 dependency.

To create a dependnecy graph have to write this:

from taskiq_dependencies import DependencyGraph

graph = DependencyGraph(target_func)

That's it. Now we want to resolve all dependencies and call a function. It's simple as this:

with graph.sync_ctx() as ctx:
    graph.target(**ctx.resolve_kwargs())

Voila! We resolved all dependencies and called a function with no arguments. The resolve_kwargs function will return a dict, where keys are parameter names, and values are resolved dependencies.

Async usage

If your lib is asynchronous, you should use async context, it's similar to sync context, but instead of with you should use async with. But this way your users can use async dependencies and async generators. It's not possible in sync context.

async with graph.async_ctx() as ctx:
    kwargs = await ctx.resolve_kwargs()

Q&A

Why should I use with or async with statements?

Becuase users can use generator functions as dependencies. Everything before yield happens before injecting the dependency, and everything after yield is executed after the with statement is over.

How to provide default dependencies?

It maybe useful to have default dependencies for your project. For example, taskiq has Context and State classes that can be used as dependencies. sync_context and async_context methods have a parameter, where you can pass a dict with precalculated dependencies.

from taskiq_dependencies import Depends, DependencyGraph


class DefaultDep:
    ...


def target_func(dd: DefaultDep = Depends()):
    print(dd)
    return 1


graph = DependencyGraph(target_func)

with graph.sync_ctx({DefaultDep: DefaultDep()}) as ctx:
    print(ctx.resolve_kwargs())

You can run this code. It will resolve dd dependency into a DefaultDep variable you provide.

Getting parameters information

If you want to get the information about how this dependency was specified, you can use special class ParamInfo for that.

from taskiq_dependencies import Depends, DependencyGraph, ParamInfo


def dependency(info: ParamInfo = Depends()) -> str:
    assert info.name == "dd"
    return info.name

def target_func(dd: str = Depends(dependency)):
    print(dd)
    return 1


graph = DependencyGraph(target_func)

with graph.sync_ctx() as ctx:
    print(ctx.resolve_kwargs())

The ParamInfo has the information about name and parameters signature. It's useful if you want to create a dependency that changes based on parameter name, or signature.