consolidator

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import glob
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import pandas as pd
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from ModuleMaker import ModuleMaker
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from OraWorker import OraWorker
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def converter(row:pd.Series)->pd.Series:
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    # row["Доп параметр2"]=float(str(row["Доп параметр2"]).replace(",","."))
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    row["Код"] = row["Вид материала в SAP ERP"][:4]
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    return row
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def ntd_convert(row:pd.Series,ntd_cols:list,ora:OraWorker)->pd.Series:
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    ntd = "".join([str(row[key]) for key in ntd_cols])
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    # product_up = ora.product_check("*",row["ID в SAP ERP VMZ"])
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    row["НТД качества"]=ntd.replace("nan","")
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    # row["Продукт УП"] = product_up[0]
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    return row
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def get_nearest(guidName:str,query:str,nearestColumn:str,nearestValue:float,valueColumn:str):
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    df = pd.read_csv(guidName,encoding="windows-1251",delimiter=";")
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    df=df.apply(converter,axis=1)
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    df = df.query(query)
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    df_res = df.iloc[(df[nearestColumn]-nearestValue).abs().argsort()[:1]]
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    return df_res[valueColumn].values[0]
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if __name__=="__main__":
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    r = ModuleMaker.make_from_file("handlers2\\module_pattern.py","key","ww_test_module")
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    print(r)
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    # "ID в SAP ERP VMZ","Полное наименование материала","Вид материала в SAP ERP","Производство"
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    # cols1 = ["ID в SAP ERP VMZ","Полное наименование материала","Вид материала в SAP ERP","Производство"]
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    # path_pattern="D:\\work\\Укрупнение\\current\\data\\2*\\*.xlsx"
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    # exclude_pattern = "нение_"
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    # files=[f for f in glob.glob(path_pattern) if exclude_pattern not in f] if exclude_pattern is not None else [f for f in glob.glob(path_pattern)]
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    # frames = []
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    # ora = OraWorker("sapnwc","sapnwc","172.17.80.116/scpora",".\\ora")
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    # for f in files:
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    #     try:
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    #         xl  = pd.ExcelFile(f)
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    #         for sheet in xl.sheet_names:
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    #             df = pd.read_excel(f,sheet_name=sheet)
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    #             df["file"]=f
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    #             df["sheet"]=sheet
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    #             ntd_cols_q = [col for col in df.columns if "НТД" in col and "ачества" in col and "*" not in col]
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    #             ntd_cols_cover = [col for col in df.columns if "НТД" in col and "окрытия" in col and "3" not in col]
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    #             steel_cols = [col for col in df.columns if "стал" in col or "проч" in col]
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    #             if not df.empty: 
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    #                 df = df.apply(lambda r: ntd_convert(r,ntd_cols_q,ora),axis=1)
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    #                 frames.append(df[cols1+["НТД качества"]+steel_cols+ntd_cols_cover+["file","sheet"]])
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    #                 print(f"{f}[{sheet}] added")
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    #     except Exception as exp1:
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    #         print(f"{f} failed: {exp1}")
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    # result=pd.concat(frames)
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    # result = result.drop_duplicates()
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    # result = result.apply(converter,axis=1)
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    # ntd_cols_cover = [col for col in result.columns if "НТД" in col and "покрытия" in col and "3" not in col]
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    # steel_cols = [col for col in df.columns if "стал" in col or "проч" in col]
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    # ora.close()
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    # result[cols1+["Код","НТД качества"]+steel_cols+ntd_cols_cover+["file","sheet"]].to_excel("output\\VM_Productions3.xlsx",index=False)
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