from typing import List, Tuple 
from motor.motor_asyncio import AsyncIOMotorCollection
import datetime as dt

async def aggregate_salaries(collection: AsyncIOMotorCollection, dt_from: str, dt_upto: str, group_type: str) -> Tuple[List[int], List[str]]: # type: ignore
    group_type_format = "%Y-%m-%dT00:00:00" if group_type == "day" else "%Y-%m-01T00:00:00" if group_type == "month" else "%Y-%m-%dT%H:00:00"
    pipeline = [
        {
            "$match": {
                "dt": {
                    "$gte": iso(dt_from),
                    "$lte": iso(dt_upto)
                }
            }
        },
        {
            "$densify": {
                "field": "dt",
                "range": {
                    "step": 1,
                    "unit": group_type,
                    "bounds": [
                        iso(dt_from), iso(dt_upto) + dt.timedelta(days=int(group_type=="day"), hours=int(group_type=="hour")) * (iso(dt_upto).time() == dt.time(hour=0, minute=0, second=0))
                    ]
                }
            }
        },
        {
            "$group": {
                "_id": {
                    "$dateToString": 
                        {
                            "format": group_type_format,
                            "date": "$dt"
                            }
                    },
                "sum": {
                    "$sum": "$value"
                    },
            }
        },
        {
            "$sort": {
                "_id": 1
            }
        }
    ]

    dataset = []
    labels = []

    async for document in collection.aggregate(pipeline):
        dataset.append(document["sum"])
        labels.append(document["_id"]  )

    return {"dataset": dataset, "labels": labels}

def iso(date: str) -> dt.datetime:
    return dt.datetime.fromisoformat(date)