from fastapi import Depends, FastAPI

    app = FastAPI()


    async def common_parameters(q: str | None = None, skip: int = 0, limit: int = 100):
        return {"q": q, "skip": skip, "limit": limit}


    @app.get("/items/")
    async def read_items(commons: Annotated[dict, Depends(common_parameters)]):
        return commons
    ```
    """

app = FastAPI()

router = APIRouter()


async def common_parameters(q: str, skip: int = 0, limit: int = 100):
    return {"q": q, "skip": skip, "limit": limit}


@app.get("/main-depends/")
async def main_depends(commons: dict = Depends(common_parameters)):
    return {"in": "main-depends", "params": commons}


@app.get("/decorator-depends/", dependencies=[Depends(common_parameters)])
async def decorator_depends():

# ==============================================================================
"""
Top-level module of TensorFlow. By convention, we refer to this module as
`tf` instead of `tensorflow`, following the common practice of importing
TensorFlow via the command `import tensorflow as tf`.

The primary function of this module is to import all of the public TensorFlow
interfaces into a single place. The interfaces themselves are located in

def get_top_users(
    *,
    counter: Counter,
    authors: Dict[str, Author],
    skip_users: Container[str],
    min_count: int = 2,
):
    users = []
    for commenter, count in counter.most_common(50):
        if commenter in skip_users:
            continue
        if count >= min_count:
            author = authors[commenter]
            users.append(
                {