import pandas as pd 
import numpy as np
import json
from functools import reduce

source_csv = "data\\Kontenrahmen_Import.csv"
target_csv = "data\\Kontenrahmen.csv"
result_csv = "data\\Kontenrahmen_Ergebnis.csv"


debug = False

cols_pkey = ["Konto_Nr"]

def update(d, other): 
    d.update(dict(dict(other)))
    return d

def get_dict(cols, type):
    return dict(dict(zip(cols,[type] * len(cols))))

#cols_dict = reduce(update, (get_dict(cols_pkey, np.str), get_dict(cols_str, np.str), get_dict(cols_float, np.float)), {})

df_source = pd.read_csv(source_csv, decimal=",", sep=";", encoding="ansi", converters={i: str for i in range(0, 200)})
df_source['pkey'] = reduce(lambda x, y: x + "_" + df_source[y], cols_pkey, "") 
df_source = df_source.set_index('pkey')

df_target = pd.read_csv(target_csv, decimal=",", sep=";", encoding="ansi", converters={i: str for i in range(0, 200)})
target_columns = df_target.columns
df_target['pkey'] = reduce(lambda x, y: x + "_" + df_target[y], cols_pkey, "") 
df_target = df_target.set_index('pkey')

df_join = df_source.join(df_target, rsuffix='_other')[target_columns]
#df_result = df_join[(df_join['Gesamt'] != 0) & (df_join['Serviceberater'] != "")]

df_join.to_csv(result_csv, decimal=",", sep=";", encoding="ansi", index=None)