import numpy as np

from vaex_queries import utils

Q_NUM = 1
import vaex.cache


def q():
    VAR1 = np.datetime64("1998-09-02")

    lineitem = utils.get_line_item_ds
    # first call one time to cache in case we don't include the IO times
    lineitem()

    def query():
        with vaex.cache.memory():
            nonlocal lineitem
            lineitem = lineitem()

            lineitem_filtered = lineitem[
                [
                    "l_quantity",
                    "l_extendedprice",
                    "l_discount",
                    "l_tax",
                    "l_returnflag",
                    "l_linestatus",
                    "l_shipdate",
                    "l_orderkey",
                ]
            ]
            sel = lineitem_filtered.l_shipdate <= VAR1
            lineitem_filtered = lineitem_filtered[sel]
            lineitem_filtered["sum_qty"] = lineitem_filtered.l_quantity
            lineitem_filtered["sum_base_price"] = lineitem_filtered.l_extendedprice
            lineitem_filtered["avg_qty"] = lineitem_filtered.l_quantity
            lineitem_filtered["avg_price"] = lineitem_filtered.l_extendedprice
            lineitem_filtered["sum_disc_price"] = lineitem_filtered.l_extendedprice * (
                1 - lineitem_filtered.l_discount
            )
            lineitem_filtered["sum_charge"] = (
                lineitem_filtered.l_extendedprice
                * (1 - lineitem_filtered.l_discount)
                * (1 + lineitem_filtered.l_tax)
            )
            lineitem_filtered["avg_disc"] = lineitem_filtered.l_discount
            lineitem_filtered["count_order"] = lineitem_filtered.l_orderkey
            total = lineitem_filtered.groupby(
                ["l_returnflag", "l_linestatus"],
                agg={
                    "sum_qty": "sum",
                    "sum_base_price": "sum",
                    "sum_disc_price": "sum",
                    "sum_charge": "sum",
                    "avg_qty": "mean",
                    "avg_price": "mean",
                    "avg_disc": "mean",
                    "count_order": "count",
                },
            )

            result_df = total.sort(["l_returnflag", "l_linestatus"])
            return result_df

    utils.run_query(Q_NUM, query)


if __name__ == "__main__":
    q()