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%configure_logging

import pandas as pd

from trase.tools import sps
from trase.models.brazil.decision_tree import get_remaining_mdic

for year in [
    2015,
    2016,
    2017,
    2019,
]:  # trade data missing for 2018, production missing for 2020
    supplychain = sps.SupplyChain("brazil/corn", year=year)
    supplychain.preparation()
#     supplychain.load()
#     suffix = supplychain.run()
#     supplychain.flow_report_by_attribute("vol", ["branch"], 8)
#     supplychain.flow_report_by_attribute("vol", ["exporter_type"], 8)
#     supplychain.export_results()#suffix=suffix)
#     supplychain.upload_results(
#         country="BRAZIL",
#         commodity="CORN",
#         #suffix=suffix,
#     )

# on = [
#    "country_of_destination_name",
#    "port_of_export_group",
#    "product_type",
#    "state_trase_id",
# ]

# df = (
#    supplychain.get("flows")
#    .drop(columns="state_trase_id")
#    .rename(columns={"mdic_overflow_state": "state_trase_id"})
# )
# df = df[df["mdic_overflow"]]
# df = (
#    df.groupby(on)["vol"]
#    .sum()
#    .reset_index()
#    .rename(columns={"vol": "overflow_vol"})
# )

# df_mdic = get_remaining_mdic(supplychain)
# df_mdic = (
#    df_mdic.groupby(on)["vol"]
#    .sum()
#    .reset_index()
#    .rename(columns={"vol": "remaining_vol"})
# )

# df = pd.merge(df, df_mdic, on=on, how="outer").fillna(0)
# df = df.sort_values("port_of_export_group")
# print(df)

# df.to_csv("mdic_overflow.csv")

df