接口测试的时候，经常遇到[{},{},{}]格式的数据，需要diff两套环境的返回数据；

举例：
data01=[{"path":"/Users/Library/Fonts/1610424977302997.ttf","postscriptName":"STHupo-Regular","usedPostScriptName":"STHupo","width":5,"weight":400,"style":"Regular","family":"STHupo","localizedFamily":"华文琥珀","localizedStyle":"Regular","italic":false,"monospace":false},{"path":"/Users/Library/Fonts/RobotoFlex[GRAD,XOPQ,XTRA,YOPQ,YTAS,YTDE,YTFI,YTLC,YTUC,opsz,slnt,wdth,wght].ttf","postscriptName":"RobotoFlex-Black","usedPostScriptName":"RobotoFlex-Regular","width":100,"weight":900,"style":"Black","family":"Roboto Flex","localizedFamily":"Roboto Flex","localizedStyle":"Black","italic":false,"monospace":false}]

data02=[{"path":"/Users/Library/Fonts/1610424977302997.ttf","postscriptName":"STHupo","usedPostScriptName":"STHupo","width":5,"weight":400,"style":"Regular","family":"STHupo","localizedFamily":"华文琥珀","localizedStyle":"Regular","italic":false,"monospace":false},{"path":"/Users/Library/Fonts/RobotoFlex[GRAD,XOPQ,XTRA,YOPQ,YTAS,YTDE,YTFI,YTLC,YTUC,opsz,slnt,wdth,wght].ttf","postscriptName":"RobotoFlex","usedPostScriptName":"RobotoFlex-Regular","width":100,"weight":900,"style":"Black","family":"Roboto Flex","localizedFamily":"Roboto Flex","localizedStyle":"Black","italic":false,"monospace":false},{"path":"/Users/Library/Fonts/RobotoFlex[GRAD,XOPQ,XTRA,YOPQ,YTAS,YTDE,YTFI,YTLC,YTUC,opsz,slnt,wdth,wght].ttf","postscriptName":"RobotoFlex","usedPostScriptName":"RobotoFlex-Regular","width":100,"weight":900,"style":"Black","family":"Roboto Flex","localizedFamily":"Roboto Flex","localizedStyle":"Black","italic":false,"monospace":false},{"path":"/Users/Library/Fonts/RobotoFlex[GRAD,XOPQ,XTRA,YOPQ,YTAS,YTDE,YTFI,YTLC,YTUC,opsz,slnt,wdth,wght].ttf","postscriptName":"RobotoFlex","usedPostScriptName":"RobotoFlex-Regular","width":100,"weight":900,"style":"Black","family":"Roboto Flex","localizedFamily":"Roboto Flex","localizedStyle":"Black","italic":false,"monospace":false}]

对比1：获取data02中的重复数据

def json_object_filter(f: str, data: list[dict[str, any]] = None, ret: bool = False) -> list[dict[str, any]] or None:
    """
    从给定的json文件或数据列表过滤重复的对象
    :param f: 文件地址，文件内容必须是json
    :param data: 数据列表
    :param ret: 是否返回数据，若为False则直接打印结果，否则返回结果
    :return:
    """
    if f is None and data is None:
        raise RuntimeError("数据文件与数据列表不能都为空")

    if f is not None:
        data = json.loads((open(f, 'r')).read())

    mapping: dict[str, dict[str, any]] = {}

    for item in data:
        keys = list(item.keys())
        keys.sort()

        value = ""
        for key in keys:
            value += "{}".format(item.get(key))

        if mapping.get(value) is None:
            # 默认不要数据，只统计value
            mapping[value] = {"count": 1}
        else:
            # 只有数据在重复时才取出数据
            if ret:
                mapping[value]["data"] = item
            elif 1 == mapping[value]["count"]:
                # 只需要打印一次
                print(item)
            mapping[value]["count"] += 1

    if ret is False:
        return None

    ret: list[dict[str, any]] = []
    for item in mapping.values():
        if item["count"] > 1:
            ret.append(item["data"])

    return ret

对比2：指定某个字段，对比data01和data02返回的字体，输出data01和data02中不一样的数据

def get_diff_data(f_01: str, f_02: str, data_01: list[dict[str, any]] = None, data_02: list[dict[str, any]] = None, field: str = None):
    """
    指定某个字段，对比data01和data02返回的字体，输出data01和data02中不一样的数据
    :param f_01: 文件地址，文件内容必须是json
    :param f_02: 文件地址，文件内容必须是json
    :param data_01: 数据列表
    :param data_02: 数据列表
    :param field: 需要对比的字段
    :return:
    """
    if f_01 is None and data_01 is None:
        raise RuntimeError("data01数据文件与数据列表不能都为空")
    if f_02 is None and data_02 is None:
        raise RuntimeError("data02数据文件与数据列表不能都为空")

    if f_01 is not None:
        data_01 = json.loads((open(f_01, 'r')).read())
    if f_02 is not None:
        data_02 = json.loads((open(f_02, 'r')).read())

    print("文件1中一共有{}数据".format(len(data_01)))
    print("文件2中一共有{}数据".format(len(data_02)))

    field_01_list = [i[field] for i in data_01]
    field_02_list = [i[field] for i in data_02]

    remove_duplicate_field_01_list = list(set(field_01_list))
    remove_duplicate_field_02_list = list(set(field_02_list))

    print("字段{}在文件01中一共有{}数据，去重之后还有{}条数据".format(field, len(field_01_list), len(remove_duplicate_field_01_list)))
    print("字段{}在文件02中一共有{}数据，去重之后还有{}条数据".format(field, len(field_02_list), len(remove_duplicate_field_02_list)))

    in_01_not_in_02 = []
    for i in remove_duplicate_field_01_list:
        if i not in remove_duplicate_field_02_list:
            in_01_not_in_02.append(i)

    in_02_not_in_01 = []
    for i in remove_duplicate_field_02_list:
        if i not in remove_duplicate_field_01_list:
            in_02_not_in_01.append(i)

    print("=========================结果===========================")
    print("字段{}在文件01中存在，但是在02中不存在:".format(field))
    print(in_01_not_in_02)

    print("字段{}在文件02中存在，但是在01中不存在:".format(field))
    print(in_02_not_in_01)