FastRAMQPI 1.3.10

Rammearkitektur AMQP framework (FastAPI + RAMQP)

FastRAMQPI

FastRAMQPI is an opinionated library for FastAPI and RAMQP.

It is implemented as a thin wrapper around FastAPI and RAMQP. It is very MO specific.

Usage

from pydantic import BaseSettings
from fastramqpi import FastRAMQPI
from fastramqpi import FastRAMQPISettings


class Settings(BaseSettings):
    class Config:
        frozen = True
        env_nested_delimiter = "__"

    fastramqpi: FastRAMQPISettings = Field(
        default_factory=FastRAMQPISettings,
        description="FastRAMQPI settings"
    )

    # All your program settings hereunder...


fastapi_router = APIRouter()

@fastapi_router.post("/trigger/all")
async def update_all(request: Request) -> dict[str, str]:
    context: dict[str, Any] = request.app.state.context
    graphql_session = context["grapqh_session"]
    program_settings = context["user_context"]["settings"]
    ...
    return {"status": "OK"}


amqp_router = MORouter()

@amqp_router.register("*.*.*")
async def listen_to_all(context: dict, payload: PayloadType) -> None:
    graphql_session = context["grapqh_session"]
    program_settings = context["user_context"]["settings"]
    ...


def create_fastramqpi(**kwargs: Any) -> FastRAMQPI:
    settings = Settings(**kwargs)
    fastramqpi = FastRAMQPI(
        application_name="orggatekeeper", settings=settings.fastramqpi
    )
    fastramqpi.add_context(settings=settings)

    # Add our AMQP router(s)
    amqpsystem = fastramqpi.get_amqpsystem()
    amqpsystem.router.registry.update(amqp_router.registry)

    # Add our FastAPI router(s)
    app = fastramqpi.get_app()
    app.include_router(fastapi_router)

    return fastramqpi


def create_app(**kwargs: Any) -> FastAPI:
    fastramqpi = create_fastramqpi(**kwargs)
    return fastramqpi.get_app()

Metrics

FastRAMQPI Metrics are exported via prometheus/client_python on the FastAPI's /metrics.

Development

Prerequisites

• Poetry

Getting Started

1. Clone the repository:

git clone [e-mail]:rammearkitektur/FastRAMQPI.git

2. Install all dependencies:

poetry install

3. Set up pre-commit:

poetry run pre-commit install

Running the tests

You use poetry and pytest to run the tests:

poetry run pytest

You can also run specific files

poetry run pytest tests/<test_folder>/<test_file.py>

and even use filtering with -k

poetry run pytest -k "Manager"

You can use the flags -vx where v prints the test & x makes the test stop if any tests fails (Verbose, X-fail)

Authors

Magenta ApS https://magenta.dk

License

This project uses: MPL-2.0

This project uses REUSE for licensing. All licenses can be found in the LICENSES folder of the project.