csv文件相关操作整理

1. 读取+遍历处理+写入

    all_rate_data_list = list()
    better_rate_list = list()
    rate_info_headers = ["threshold", "real_recall", "fake_recall"]
    while threshold <= 1:
        real_judge_real = 0
        real_total = 0
        fake_judge_fake = 0
        fake_total = 0
        per_rate_data_dict = dict()
        for root, dirs, files in os.walk(csv_dir): # root: 当前目录路径  ; dirs :当前路径下所有子目录  ; files : 文件夹下所有文件名
            for csv_file in files:
                file_str = os.path.join(root, csv_file)
                with open(file_str, "rU", encoding='utf-8') as myFile:
                    reader = csv.reader(myFile)
                    # sum_num = sum(1 for row in myFile) - 1
                    myFile.seek(0)
                    next(reader) # 从第二行开始获取数据
                    for row in reader:
                        row = list(map(str.strip, row))
                        branch = row[1]
                        file_path = row[0]
                        xxx业务逻辑xxx

        real_recall= round(real_judge_real / real_total, 8) if real_total else 0
        fake_recall= round(fake_judge_fake / fake_total,8) if fake_total else 0

        per_rate_data_dict["threshold"] = round(threshold, 8)
        per_rate_data_dict["real_recall"] = real_recall
        per_rate_data_dict["fake_recall"] = fake_fomm_recall

        if per_rate_data_dict["real_recall"] >=target_real_recall:
            better_rate_list.append(per_rate_data_dict)

        all_rate_data_list.append(per_rate_data_dict)
        threshold += step

    if all_rate_data_list:
        with open(os.path.join(csv_path, '{0}.csv'.format(model_name + "_" + model_type + "_logic1不同阈值下的准确率")),
                  'w', newline='', encoding='utf-8') as f:
            f_csv = csv.DictWriter(f, rate_info_headers)
            f_csv.writeheader()
            f_csv.writerows(all_rate_data_list)
    if better_rate_list:
        with open(os.path.join(csv_path, '{0}.csv'.format(model_name + "_" + model_type + "_logic1{BANNED}最佳优准确率下的阈值串")),
                  'w', newline='', encoding='utf-8') as f:
            f_csv = csv.DictWriter(f, rate_info_headers)
            f_csv.writeheader()
            f_csv.writerows(better_rate_list)