from datetime import datetime
import os, csv, json
import pandas as pd
import numpy as np

class JsonEncoder(json.JSONEncoder):
    """Convert numpy classes to JSON serializable objects."""

    def default(self, obj):
        if isinstance(obj, (np.integer, np.floating, np.bool_)):
            return obj.item()
        elif isinstance(obj, np.ndarray):
            return obj.tolist()
        else:
            return super(JsonEncoder, self).default(obj)
        
def fillData(baseName, data, workbook):
    info = ''
    if isinstance(data, dict):
        for key, value in data.items():
            if (not isinstance(value, dict)) or (not value):
                log(f"{{{baseName}.{key}}}".replace('{.', '{'))
                info += f"{{{baseName}.{key}}}"
                for worksheet in workbook.sheets:
                    result = worksheet.used_range.api.find(f"{{{baseName}.{key.replace('{.','{')}}}".replace('{.', '{'))
                    if result:
                        if isinstance(value, list):
                            address = f"{result.address}".split('$')
                            worksheet.range(f"{result.address}:${address[1]}${int(address[2])+len(value)-1}").options(transpose=True).value = value
                        else:
                            worksheet.used_range.api.Replace(f"{{{baseName}.{key}}}", f"{value}")
            else:
                baseName += f".{key}"
                fillData(baseName, value, workbook)
                baseName = baseName[0:baseName.rfind('.')]
    else:
        info += f"{data}"
        raise Exception(f"Error in fillData(): Type of data is not dict.")
    return info

# 功能概要:把dataLogging指令生成的csv文件转成字典
# 参数说明：
# csvFilePath: 输入csv文件完整路径
# testCaseNameFildName: 从csv文件中选择某一字段作为测试项名称
# nanDataProcessFlag: 指定数据表中包含的nan数据处理模式
# 详细功能：
# 1、根据测试项名称，对测试数据进行分类；
# 2、根据nanDataProcessFlag处理nan数据
#     =0:删除全部为nan的列，同时删除包含nan的行
#     =1:删除全部为nan的列，
def csvLoggingFileToDict(csvFilePath, testCaseNameFildName='', nanDataProcessFlag=0):
    info = ''
    try:
        if not os.path.exists(csvFilePath):
            raise Exception(f"{csvFilePath} file doesn't exist.")
        
        tempTitle = []
        tempData = []
        dfData = pd.DataFrame({})
        with open(csvFilePath, "r", encoding='utf-8') as f:
            reader = csv.reader(f)
            lines = [line for line in reader]
#            reversed_lines = lines[::-1]
            for line in lines:
                if line[0].startswith('DateTime'):
                    if len(tempData) > 0:
                        tempDataFrame = pd.DataFrame(dict(zip(tempTitle, list(map(list, zip(*tempData))))))
                        dfData = pd.concat([dfData, tempDataFrame])
#                        tempDataFrame.to_csv(f"{csvFilePath}.{tempData[0][1]}.csv")
                    tempData = []
                    tempTitle = line
                else:
                    tempData.append(line)
            tempDataFrame = pd.DataFrame(dict(zip(tempTitle, list(map(list, zip(*tempData))))))
            dfData = pd.concat([dfData, tempDataFrame])
            
#            dfData = dfData.replace(np.nan, '0')
        jsonData = {}
        #根据测试项提取数据
        if testCaseNameFildName !='':
            testcaseList = list(dfData[testCaseNameFildName].unique())
            if len(testcaseList) > 0:
                for item in testcaseList:
                    temp = dfData[dfData[testCaseNameFildName]==item]
                    if nanDataProcessFlag == 0:
                        temp.dropna(how='all', axis=1, inplace=True)
                        temp.dropna(axis=0, inplace=True)
                        jsonData['testData'][f"{item}"] = temp.to_dict(orient='list')
                    elif nanDataProcessFlag == 1:
                        temp.dropna(how='all', axis=1, inplace=True)
                        jsonData['testData'][f"{item}"] = temp.to_dict(orient='list')
            else:
                temp = dfData
                temp.dropna(how='all', axis=1, inplace=True)
                temp.dropna(axis=0, inplace=True)
                jsonData['testData'] = temp.to_dict(orient='list')
        else:
            temp = dfData
            temp.dropna(how='all', axis=1, inplace=True)
            if nanDataProcessFlag == 0:
                temp.dropna(axis=0, inplace=True)
            jsonData['testData'] = temp.to_dict(orient='list')
        return jsonData
    except Exception as e:
        raise Exception(f"Error in csvLoggingFileToDict(): {str(e)}")
    
# 功能概要:把读内存生成的csv文件转成json文件
# 参数说明：
# csvFilePath: 输入csv文件完整路径
# jsonFilePath: 输出json文件完整路径
# partNum: 内存文件对应的分区号
def csvFlashFileToDict(csvFilePath, dictData, partNum):
    info = ''
    try:
        if not os.path.exists(csvFilePath):
            raise Exception(f"{csvFilePath} file doesn't exist.")
        tempTitle = []
        tempData = []
        dfData = pd.DataFrame({})
        with open(csvFilePath, "r", encoding='utf-8') as f:
            reader = csv.reader(f)
            lines = [line for line in reader]
#            reversed_lines = lines[::-1]
            for line in lines:
                if line[0].startswith('DateTime'):
                    if len(tempData) > 0:
                        tempDataFrame = pd.DataFrame(dict(zip(tempTitle, list(map(list, zip(*tempData))))))
                        dfData = pd.concat([dfData, tempDataFrame])
#                        tempDataFrame.to_csv(f"{csvFilePath}.{tempData[0][1]}.csv")
                    tempData = []
                    tempTitle = line
                else:
                    tempData.append(line)
            tempDataFrame = pd.DataFrame(dict(zip(tempTitle, list(map(list, zip(*tempData))))))
            dfData = pd.concat([dfData, tempDataFrame])
            
#            dfData = dfData.replace(np.nan, '0')
            dictData[f"Part{partNum}"] = dfData.to_dict(orient='list')
        return dictData
    except Exception as e:
        raise Exception(f"Error in csvFlashFileToDict(): {str(e)}")
    
# 功能概要:把读内存生成的csv文件转成json文件
# 参数说明：
# jsonFilePath:进行替换操作的json文件完整路径
# repalceConfigDict: 替换操作配置字典
def replaceFieldInDict(dictData, repalceConfigDict):
    info = ''
    try:
        if not isinstance(repalceConfigDict, dict) or not isinstance(dictData, dict):
            raise Exception(f"repalceConfigDict or dictData is not dict.")
        tempJsonData_P1 = {f"{repalceConfigDict['MappingTableOfFiledName'][key]}": value for key, value in dictData.items() if key in repalceConfigDict['MappingTableOfFiledName'].keys()}
        tempJsonData_P2 = {key: value for key, value in dictData.items() if key not in repalceConfigDict['MappingTableOfFiledName'].keys()}
        dictData = {**tempJsonData_P1, **tempJsonData_P2}
        return dictData
    except Exception as e:
        raise Exception(f"Error in replaceFieldInDict(): {str(e)}")