import numpy as np
import vaex

from vaex_queries import utils

Q_NUM = 7


def q():
    nation_ds = utils.get_nation_ds
    customer_ds = utils.get_customer_ds
    line_item_ds = utils.get_line_item_ds
    orders_ds = utils.get_orders_ds
    supplier_ds = utils.get_supplier_ds

    # first call one time to cache in case we don't include the IO times
    nation_ds()
    customer_ds()
    line_item_ds()
    orders_ds()
    supplier_ds()

    def query():
        nonlocal nation_ds
        nonlocal customer_ds
        nonlocal line_item_ds
        nonlocal orders_ds
        nonlocal supplier_ds

        nation_ds = nation_ds()
        customer_ds = customer_ds()
        line_item_ds = line_item_ds()
        orders_ds = orders_ds()
        supplier_ds = supplier_ds()

        lineitem_filtered = line_item_ds[
            (line_item_ds["l_shipdate"] >= np.datetime64("1995-01-01"))
            & (line_item_ds["l_shipdate"] < np.datetime64("1997-01-01"))
        ]
        lineitem_filtered["l_year"] = lineitem_filtered["l_shipdate"].apply(
            lambda x: x.year
        )
        lineitem_filtered["revenue"] = lineitem_filtered["l_extendedprice"] * (
            1.0 - lineitem_filtered["l_discount"]
        )
        lineitem_filtered = lineitem_filtered[
            ["l_orderkey", "l_suppkey", "l_year", "revenue"]
        ]

        supplier_filtered = supplier_ds[["s_suppkey", "s_nationkey"]]
        orders_filtered = orders_ds[["o_orderkey", "o_custkey"]]
        customer_filtered = customer_ds[["c_custkey", "c_nationkey"]]
        n1 = nation_ds[(nation_ds["n_name"] == "FRANCE")][["n_nationkey", "n_name"]]
        n2 = nation_ds[(nation_ds["n_name"] == "GERMANY")][["n_nationkey", "n_name"]]

        # ----- do nation 1 -----
        N1_C = customer_filtered.join(
            n1,
            left_on="c_nationkey",
            right_on="n_nationkey",
            how="inner",
            allow_duplication=True,
        )
        N1_C = N1_C.drop(columns=["c_nationkey", "n_nationkey"])
        N1_C.rename("n_name", "cust_nation")

        N1_C_O = N1_C.join(
            orders_filtered,
            left_on="c_custkey",
            right_on="o_custkey",
            how="inner",
            allow_duplication=True,
        )
        N1_C_O = N1_C_O.drop(columns=["c_custkey", "o_custkey"])

        N2_S = supplier_filtered.join(
            n2,
            left_on="s_nationkey",
            right_on="n_nationkey",
            how="inner",
            allow_duplication=True,
        )
        N2_S = N2_S.drop(columns=["s_nationkey", "n_nationkey"])
        N2_S.rename("n_name", "supp_nation")
        N2_S_L = N2_S.join(
            lineitem_filtered,
            left_on="s_suppkey",
            right_on="l_suppkey",
            how="inner",
            allow_duplication=True,
        )
        N2_S_L = N2_S_L.drop(columns=["s_suppkey", "l_suppkey"])

        total1 = N1_C_O.join(
            N2_S_L,
            left_on="o_orderkey",
            right_on="l_orderkey",
            how="inner",
            allow_duplication=True,
        )
        total1 = total1.drop(columns=["o_orderkey", "l_orderkey"])

        # ----- do nation 2 ----- (same as nation 1 section but with nation 2)
        N2_C = customer_filtered.join(
            n2,
            left_on="c_nationkey",
            right_on="n_nationkey",
            how="inner",
            allow_duplication=True,
        )
        N2_C = N2_C.drop(columns=["c_nationkey", "n_nationkey"])
        N2_C.rename("n_name", "cust_nation")
        N2_C_O = N2_C.join(
            orders_filtered,
            left_on="c_custkey",
            right_on="o_custkey",
            how="inner",
            allow_duplication=True,
        )
        N2_C_O = N2_C_O.drop(columns=["c_custkey", "o_custkey"])

        N1_S = supplier_filtered.join(
            n1,
            left_on="s_nationkey",
            right_on="n_nationkey",
            how="inner",
            allow_duplication=True,
        )
        N1_S = N1_S.drop(columns=["s_nationkey", "n_nationkey"])
        N1_S.rename("n_name", "supp_nation")
        N1_S_L = N1_S.join(
            lineitem_filtered,
            left_on="s_suppkey",
            right_on="l_suppkey",
            how="inner",
            allow_duplication=True,
        )
        N1_S_L = N1_S_L.drop(columns=["s_suppkey", "l_suppkey"])

        total2 = N2_C_O.merge(
            N1_S_L,
            left_on="o_orderkey",
            right_on="l_orderkey",
            how="inner",
            allow_duplication=True,
        )
        total2 = total2.drop(columns=["o_orderkey", "l_orderkey"])

        # concat results
        total = vaex.concat([total1, total2])
        result_df = total.groupby(["supp_nation", "cust_nation", "l_year"]).agg(
            {"revenue": "sum"}
        )
        result_df.columns = ["supp_nation", "cust_nation", "l_year", "revenue"]

        result_df = result_df.sort(
            by=["supp_nation", "cust_nation", "l_year"],
            ascending=[
                True,
                True,
                True,
            ],
        )
        return result_df

    utils.run_query(Q_NUM, query)


if __name__ == "__main__":
    q()