基于系统本身

1. 可以基于系统本身的数据，收集大量的元数据，再组合成或sql或python或hive或spark的代码，批量的对元数据进行查询和计算，以达到监控数据元信息的目的。

导出数据

1. 通过python读取excel文件，分析数据的格式是否符合模板下的格式，如果不符合则记录下来。
   示例：

import pandas as pd
from pandas import DataFrame
def digit20(digit:str,allow_symbols:list):
    """digit20
    将字符串中的数字批量转换成0
    Keyword arguments:
    digit -- 字符串
    allow_symbols -- 允许存在的符号
    Return: str
    """
    s = ""
    for v in str(digit):
        try:
            if v in allow_symbols:
                s += v
                continue
            else:
                v = int(v)
                s += "0"
        except:
            raise Exception(f"{v}不是合法标识符")
    return s
def formatLanToformat(formatLan:str|list):
    """formatLanToformat
    将format模板语法转换为模板
    symbols是用于存放关键字的位置，用于放置一些语法的特殊标识符或特殊语法
    如：
    | -- 竖线符号表示了或，当语法中出现该符号`|`时，则字符可以既可以匹配符号前一个字符，也可以匹配竖线后一个字符。
    \ -- 斜线符号表示了转义，当语法中出现了该符号`\`时，则符号下一个字符直接作为字符放入，不认定为关键字。
    Keyword arguments:
    formatLan -- format模板语法或format模板语法列表
    Return: format -- list format模板
    """
    symbols = ["|"]
    format_s_s = []
    def analysisSymbol(formatL,now_l=""):
        format_s = []
        num = 0
        format_s.extend(list(now_l))
        formatL = list(formatL)
        for v in formatL:
            if v not in symbols:
                format_s.append(v)
            elif v == "|":
                analysisSymbol(formatL[(num+2)::],format_s)
                format_s = format_s[0:len(format_s)-1]
                analysisSymbol(formatL[(num+1)::],format_s)
                break
            # elif v == "\\": #  该方法目前废弃，疑似与python语法有所冲突
            #     format_s.append(formatL[num+1])
            #     analysisSymbol(formatL[(num+2)::],format_s)
            #     break
            num += 1
        else:
            format_s = "".join(format_s)
            format_s_s.append(format_s)
    if type(formatLan) == str:
        data = analysisSymbol(formatLan)
    if type(formatLan) == list:
        for format_v in formatLan:
            data = analysisSymbol(format_v)
    format_s_s = list(set(format_s_s))
    return format_s_s
def analysis(df:DataFrame,format_list:list,allow_symbols:list,field_querys:str|list) -> list:
    """analysis
    用于分析找到不符合规定的字段的信息
    Keyword arguments:
    df -- pandas的datafram
    format_list -- 模板列表
    allow_symbols -- 模板关键字
    field_query -- 字段筛选条件
    Return: return_description
    """
    format_list_chace = []
    list(map(format_list_chace.extend,list(map(formatLanToformat,format_list))))
    print(format_list_chace)
    illegal_dfs = []
    s = 0
    for num in range(0,len(df)):
        s+=1
        table_name = df["table_name"][num]
        table_comment = df["table_comment"][num]
        field = df["filed"][num]
        value = df["field_value"][num]
        filed_comment = df["filed_comment"][num]
        if type(field_querys) == str:
            if field_query not in str(field) or field_query not in str(filed_comment):
                continue
            else:
                try:
                    digit = digit20(value,allow_symbols)
                    if digit in format_list_chace:
                        illegal_dfs.append({"table_name":table_name,"table_comment":table_comment,"filed":field,"value":value,"filed_comment":filed_comment})
                except Exception:
                        illegal_dfs.append({"table_name":table_name,"table_comment":table_comment,"filed":field,"value":value,"filed_comment":filed_comment})
        elif type(field_querys) == list:
            num = len(field_querys)
            js_num = 0 
            for field_query in field_querys:
                if field_query in str(field) or field_query in str(filed_comment):
                    js_num = 1
            if js_num == 1:
                try:
                    digit = digit20(value,allow_symbols)
                    if digit not in format_list_chace:
                        illegal_dfs.append({"table_name":table_name,"table_comment":table_comment,"filed":field,"value":value,"filed_comment":filed_comment})
                except Exception:
                        illegal_dfs.append({"table_name":table_name,"table_comment":table_comment,"filed":field,"value":value,"filed_comment":filed_comment})
    return illegal_dfs
if __name__ == "__main__":
    phone_format = ["00000000000","000-00000"]
    phone_allow_sysbols = []
    date_format = ["0000/|\\00/|\\00 00:00:00:00",
                "0000/|\\00/|\\00 00:00:00",
                "0000-00-00 00:00:00:00",
                "0000-00-00 00:00:00",
                "0000.00.00 00:00:00:00",
                "0000.00.00 00:00:00",
                "0000/|\\|年|-|.0月|",
                "0000/|\\|年|-|.00月|",
                "0000/|\\|年|-|.0/|\\|月|-|.0日|",
                "0000/|\\|年|-|.00/|\\|月|-|.0日|",
                "0000/|\\|年|-|.00/|\\|月|-|.00日|"
                ]
    date_allow_sysbols = ["/","\\","-",":","."," "]
    info_format = ["000000000000000000|x","000000000000000"]
    info_allow_sysbols = ["x","X"]
    df = pd.read_excel("./input/tmpyxxtbale.xlsx",sheet_name="Sheet1")
    # 联系电话","联系方式","电话","手机","号码
    # datas = analysis(df,date_format,date_allow_sysbols,["时间","日期"])
    datas = analysis(df,info_format,info_allow_sysbols,["号码","身份证","身份","证件号","号"])
    print(datas)
    df = pd.DataFrame(datas)
    df.to_excel("./output/data.xlsx")