ASJLanguageSys/controller/ComprehendController.py

import imaplib
import shutil
import smtplib
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText

import boto3
from boto3 import Session
from django.views import View

from model.models import EmailSortModel, EmailConfigModel
from Utils.NeteaseMail import NeteaseMail
from django.views.generic import TemplateView

from object.ResponseObject import ResponseObject
import os
import csv


class ComprehendView(TemplateView):

    def get(self, request, *args, **kwargs):
        request.encoding = 'utf-8'
        operation = kwargs.get('operation')
        return self.validation(request.GET, request, operation)

    def post(self, request, *args, **kwargs):
        request.encoding = 'utf-8'
        operation = kwargs.get('operation')
        return self.validation(request.POST, request, operation)

    def validation(self, request_dict, request, operation):
        response = ResponseObject()
        if operation is None:
            return response.json(444, 'error path')
        else:
            if operation == 'createSort':
                return self.createSort(request_dict, response)
            elif operation == 'doStartSortWord':
                return self.doStartSortWord(request_dict, response)
            elif operation == 'write_csv':
                return self.write_csv(request_dict, response)
            elif operation == 'upload_csv':
                return self.upload_csv(request_dict, response)
            elif operation == 'create_document_classifier':
                return self.create_document_classifier(request_dict, response)
            elif operation == 'create_endpoint':
                return self.create_endpoint(request_dict, response)
            elif operation == 'describe_document_classifier':
                return self.describe_document_classifier(request_dict, response)
            elif operation == 'describe_endpoint':
                return self.describe_endpoint(request_dict, response)
            elif operation == 'delete_endpoint':
                return self.delete_endpoint(request_dict, response)
            elif operation == 'delete_document_classifier':
                return self.delete_document_classifier(request_dict, response)
            elif operation == 'getDocumentClassifier':
                return self.get_document_classifier(request_dict, response)
            elif operation == 'email':
                return self.email(request_dict, response)

    def createSort(self, request_dict, response):
        client = boto3.client('comprehend', region_name='region')

        # Create a document classifier
        create_response = client.create_document_classifier(
            InputDataConfig={
                'S3Uri': 's3://S3Bucket/docclass/file name'
            },
            DataAccessRoleArn='arn:aws:iam::account number:role/resource name',
            DocumentClassifierName='SampleCodeClassifier1',
            LanguageCode='en'
        )
        print("Create response: %s\n", create_response)

        # Check the status of the classifier
        describe_response = client.describe_document_classifier(
            DocumentClassifierArn=create_response['DocumentClassifierArn'])
        print("Describe response: %s\n", describe_response)

        # List all classifiers in account
        list_response = client.list_document_classifiers()
        print("List response: %s\n", list_response)

    def doStartSortWord(self, request_dict, response):
        client = boto3.client('comprehend', region_name='region')

        start_response = client.start_document_classification_job(
            InputDataConfig={
                'S3Uri': 's3://srikad-us-west-2-input/docclass/file name',
                'InputFormat': 'ONE_DOC_PER_LINE'
            },
            OutputDataConfig={
                'S3Uri': 's3://S3Bucket/output'
            },
            DataAccessRoleArn='arn:aws:iam::account number:role/resource name',
            DocumentClassifierArn=
            'arn:aws:comprehend:region:account number:document-classifier/SampleCodeClassifier1'
        )

        print("Start response: %s\n", start_response)

        # Check the status of the job
        describe_response = client.describe_document_classification_job(JobId=start_response['JobId'])
        print("Describe response: %s\n", describe_response)

        # List all classification jobs in account
        list_response = client.list_document_classification_jobs()
        print("List response: %s\n", list_response)

    def write_csv(self, request_dict, response):
        file_path = os.path.join(os.path.dirname(__file__) + '/../emailtrainfile/emailtrain.csv')
        with open(file_path, "w", newline='') as f:
            sort = EmailSortModel.objects.values('sort', 'clientquestion')
            for a in sort:
                text = [a['sort'], a['clientquestion']]
                csv_writer = csv.writer(f)
                for i in range(50):
                    csv_writer.writerow(text)
        return response.json(0)

    def upload_csv(self, request_dict, response):
        file_path = os.path.join(os.path.dirname(__file__) + '/../emailtrainfile/emailtrain.csv')
        bucket_name = "asj-amazon-comprehend"
        upload_key = "location/emailtrain.csv"
        with open(file_path, "rb") as f:
            NeteaseMail().s3_login().upload_fileobj(f, bucket_name, Key=upload_key)
        return response.json(0)

    def create_document_classifier(self, request_dict, response):
        try:
            response1 = NeteaseMail().aws_login().create_document_classifier(
                DocumentClassifierName='lhq',
                DataAccessRoleArn='arn:aws:iam::697864307463:role/service-role/AmazonComprehendServiceRoleS3FullAccess-admin',
                # Tags=[{'Key': 'string','Value': 'string'},],
                InputDataConfig={
                    'DataFormat': 'COMPREHEND_CSV',
                    # | 'AUGMENTED_MANIFEST',
                    'S3Uri': 's3://asj-amazon-comprehend/location/emailtrain.csv',
                    # 'LabelDelimiter': 'string',
                    # 'AugmentedManifests': [
                    #     {
                    #         'S3Uri': 'string',
                    #         'AttributeNames': ['string', ]
                    #     },
                    # ]
                },
                OutputDataConfig={
                    'S3Uri': 's3://asj-amazon-comprehend/output/lhq/'},
                # 'KmsKeyId': 'string'},
                # ClientRequestToken='string',
                LanguageCode='en',
                # | 'es' | 'fr' | 'de' | 'it' | 'pt' | 'ar'
                # | 'hi' | 'ja' | 'ko' | 'zh' | 'zh-TW',
                # VolumeKmsKeyId='string',
                # VpcConfig={
                #     'SecurityGroupIds': ['string', ],
                #     'Subnets': ['string', ]
                # },
                Mode='MULTI_CLASS'  # 'MULTI_LABEL'
            )
        except Exception as e:
            return response.json(404, repr('模型正在训练或已存在'))
        else:
            print(response1)
            return response.json(0)

    def create_endpoint(self, request_dict, response):
        try:
            response1 = NeteaseMail().aws_login().create_endpoint(
                EndpointName='lhq',
                ModelArn='arn:aws:comprehend:us-east-1:697864307463:document-classifier/lhq',
                # Document classifier arn
                DesiredInferenceUnits=1,
                # ClientRequestToken='string',
                # Tags=[{'Key': 'string','Value': 'string'},]
            )
        except Exception as e:
            return response.json(404, repr('模型正在训练或不存在，请等待模型训练完再创建端点'))
        else:
            print(response1)
            return response.json(0)

    def describe_document_classifier(self, request_dict, response):
        try:
            # classifier_name = request_dict.get('classifier_name', None)
            a = NeteaseMail().aws_arn()[0]
            # classifier_arn = a + str(classifier_name)
            classifier_arn = a + 'lhq'
            response1 = NeteaseMail().aws_login().describe_document_classifier(
                DocumentClassifierArn=classifier_arn
            )
            a1 = {"Status": response1['DocumentClassifierProperties']['Status']}
        except Exception as e:
            return response.json(404, repr('模型不存在'))
        else:
            return response.json(0, a1)

    def describe_endpoint(self, request_dict, response):
        try:
            # endpoint_name = request_dict.get('endpoint_name', None)
            a = NeteaseMail().aws_arn()[1]
            # endpoint_arn = a + str(endpoint_name)
            endpoint_arn = a + 'lhq'
            response1 = NeteaseMail().aws_login().describe_endpoint(
                EndpointArn=endpoint_arn
            )
            a1 = {"Status": response1['EndpointProperties']['Status']}
        except Exception as e:
            return response.json(404, repr('端点不存在'))
        else:
            return response.json(0, a1)

    def delete_endpoint(self, request_dict, response):
        try:
            # endpoint_name = request_dict.get('endpoint_name', None)
            a = NeteaseMail().aws_arn()[1]
            # endpoint_arn = a + str(endpoint_name)
            endpoint_arn = a + 'lhq'
            response1 = NeteaseMail().aws_login().delete_endpoint(
                EndpointArn=endpoint_arn)
        except Exception as e:
            return response.json(404, repr('端点不存在或正在删除中'))
        else:
            return response.json(0)

    def delete_document_classifier(self, request_dict, response):
        try:
            # classifier_name = request_dict.get('classifier_name', None)
            a = NeteaseMail().aws_arn()[0]
            # classifier_arn = a + str(classifier_name)
            classifier_arn = a + 'lhq'
            response1 = NeteaseMail().aws_login().delete_document_classifier(
                DocumentClassifierArn=classifier_arn)
        except Exception as e:
            return response.json(404, repr('模型不存在或正在删除中'))
        else:
            return response.json(0)

    def get_document_classifier(self, request_dict, response):
        ec_qs = EmailConfigModel.objects.filter(emailtag=1)  # 获取总邮件
        emailsum = 0
        replyemailsum = 0
        for ec in ec_qs:
            email_server = NeteaseMail().loginEmail(ec.emailserver, ec.fromaddr, ec.password, ec.emailserverport)
            subject_list, from_list, bodydata_list, uid_list, results, email_body, fujian_list, image_list = NeteaseMail().getEmailContext(
                email_server)
            emailsum += len(results)
            print("标题：", len(subject_list), subject_list)
            print("发件人：", len(from_list), from_list)
            print("邮件内容：", len(bodydata_list), bodydata_list)
            print("邮件uid:", len(uid_list), uid_list)
            print("附件判断：", len(fujian_list), fujian_list)
            print('图片数量：', len(image_list), image_list)
            if not bodydata_list:
                print("邮箱内无未读邮件")
            else:
                print('成功拿到邮件数据')
            for i, v in enumerate(subject_list):
                print('-------------------------------------------------------------------------')
                print("邮件标题：", subject_list[i])
                if not bodydata_list[i] or not subject_list[i]:
                    print("邮件无正文或无标题，不进行回复")
                    continue

                if fujian_list[i] == 'have':
                    reply_model = bodydata_list[i]
                    image = image_list
                    shoujianren = 'liehaoquan2021@163.com'
                    fajianren = from_list[i].split()[1]
                    NeteaseMail().sentemail(None, uid_list[i],reply_model, image, subject_list[i], fajianren, shoujianren,
                                            ec.fromaddr, ec.password)
                    file_path = os.path.join(os.path.dirname(__file__) + '/../emailtrainfile/image/')
                    shutil.rmtree(file_path)
                    os.mkdir(file_path)
                    print('邮件含有图片或附件，已转发到zendesk')
                    email_server.set_flags(uid_list[i], b'\\Seen', silent=False)
                    continue

                response1 = NeteaseMail().aws_login().classify_document(
                    Text=bodydata_list[i].split('\n\n\n\n\n')[0],
                    EndpointArn='arn:aws:comprehend:us-east-1:697864307463:document-classifier-endpoint/lhq'
                    # EndpointArn='arn:aws:comprehend:us-east-1:697864307463:document-classifier-endpoint/test'
                )
                # print(response.index(max(response['Classes']['Score'])))
                nums = []
                print('emailsort:')
                for cls in response1['Classes']:
                    print(cls['Name'])
                    nums.append(cls['Score'])
                print("识别种类及命中率：", response1['Classes'][nums.index(max(nums))])
                if response1['Classes'][nums.index(max(nums))]['Score'] >= 0.95:
                    reply_sort = EmailSortModel.objects.filter(
                        sort=response1['Classes'][nums.index(max(nums))]['Name']).values('autoreplymodel')
                    if reply_sort.exists():
                        reply_model = reply_sort[0]['autoreplymodel'] + '\n' + '\n' + '\n' + '\n' + '\n' + '\n' + \
                                      'At' + email_body[i]['Date'] + from_list[i].split()[0] + \
                                      from_list[i].split()[1] + \
                                      'wrote:\n ' + bodydata_list[i]
                        print(reply_model)
                        shoujianren = from_list[i].split()[1].replace('<', '').replace('>', '')
                        a = NeteaseMail().sentemail(None, uid_list[i], reply_model, None, subject_list[i], ec.fromaddr, shoujianren,
                                                    ec.fromaddr, ec.password)
                        email_server.set_flags(uid_list[i], b'\\Seen', silent=False)
                        if a == 'fail':
                            print("此邮件被判定为垃圾邮件，不进行回复")
                            email_server.remove_flags(uid_list[i], b'\\Seen', silent=False)
                        else:
                            replyemailsum += a
                    else:
                        print("无此转发分类，不进行回复")
                else:
                    reply_model = bodydata_list[i]
                    shoujianren = 'liehaoquan2021@163.com'
                    fajianren = from_list[i].split()[1]
                    NeteaseMail().sentemail(reply_model, None, subject_list[i], fajianren, shoujianren,
                                            ec.fromaddr, ec.password)
                    email_server.set_flags(uid_list[i], b'\\Seen', silent=False)
                    print("命中率低于0.95，已转发到zendesk")
                # es_qs = EmailSortModel.objects.filter(sort=response1['Classes'][nums.index(max(nums))]['Name'])
                # if es_qs.exists():
                #     uemail_qs = EmailConfigModel.objects.filter(userid=es_qs[0]['userid'], langconfig__langcode='en')
                #     if uemail_qs.exists():
                #         for uem in uemail_qs:
                #             NeteaseMail().sentemail(bodydata_list[i], subject_list[i], from_list[i], uem.fromaddr, ec.fromaddr, ec.password)
            NeteaseMail().closeEmail(email_server)
        emaildict = {
            "邮箱内获取到未读邮件数": emailsum,
            "已自动回复的邮件数": replyemailsum
        }
        return response.json(0, emaildict)

    def email(self, request_dict, response):
        from imapclient import IMAPClient
        import email
        import time
        import email.parser
        from nntplib import decode_header
        from email.header import Header
        import chardet

        ec_qs = EmailConfigModel.objects.filter(emailtag=1)  # 获取总邮件
        for ec in ec_qs:
            global a, email_server

            #邮件登录
            try:
                email_server = IMAPClient(ec.emailserver, ssl=True, port=ec.emailserverport)
                # email_server = imaplib.IMAP4_SSL(IMAP_SERVER, 993)  # 网易企业邮箱服务器及SSL端口
                print("imap4 服务器连接成功")
                email_server.login(ec.fromaddr, ec.password)
                email_server.id_({"name": "IMAPClient", "version": "2.1.0"})
                # email_server.login(FROM_ADDR, PASSWORD)
                print("imap4 (%s)账号密码正确，登录成功" % ec.fromaddr)
            except:
                print("imap4 服务器连接失败")

            email_server.select_folder('INBOX')
            results = email_server.search('UNSEEN')  # 读取未读邮件
            print("邮箱内获取到未读邮件：", len(results))
            subject_list = []
            from_list = []
            uid_list = []
            email_body = []
            fujian_list = []
            image_list = []
            plain_list = []
            html_list = []
            a = 0

            # 对每一封邮件进行内容解析
            for uid in results:
                msgdict = email_server.fetch(uid, ['Body[]', 'ENVELOPE'], '(RFC822)')
                mailbody = msgdict[uid][b'BODY[]']
                envelope = msgdict[uid][b'ENVELOPE']
                message = email.message_from_bytes(mailbody)
                text = message.as_string()
                body = email.parser.Parser().parsestr(text)

                nowtime = time.asctime(time.localtime(time.time()))
                nowmonth = nowtime.split()[1]
                nowday = nowtime.split()[2]
                emailmonth = body['Date'].split()[2]
                emailday = body['Date'].split()[1]
                print('email',emailmonth,emailday)
                print('now', nowmonth, nowday)
                # if emailmonth != nowmonth or emailday != nowday:
                #     email_server.remove_flags(uid, b'\\Seen', silent=False)
                #     continue

                email_body.append(body)
                subject_list.append(decode_header(body['Subject']))
                from_list.append(decode_header(body['from']))
                uid_list.append(uid)
                print("标题：",  subject_list)

                attlist = {}
                try:
                    for part in body.walk():
                        if not part.is_multipart():
                            file = part.get_filename()  # 附件名
                            if file:
                                a = 1
                                filename = email.header.decode_header(file)[0][0]  # 附件名
                                charset = email.header.decode_header(file)[0][1]  # 编码
                                if part.get_all("Content-ID"):
                                    content_id = part.get_all("Content-ID")[0][1:-1]
                                else:
                                    content_id = ""  # 附件ID,也就是邮件源码里面的cid
                                ''' 多个附件时将附件名和ID对应保存到dict里面,后面将正文中的cid替换为本地保存路径 '''
                                attlist[content_id] = filename
                                ''' 附件文件名为中文或有编码的时候要进行转码 '''
                                if str(charset) != "None":
                                    filename = filename.decode(charset)
                                filedata = part.get_payload(decode=True)  # 附件内容
                                ''' 把附件写到文件里面,附件一定要用wb打开,二进制 '''
                                file_path = os.path.join(os.path.dirname(__file__) + '/../emailtrainfile/image/')
                                image_list.append(file_path + filename)
                                with open(file_path + filename, "wb") as fw:
                                    fw.write(filedata)
                                    fw.close()

                            elif part.get_content_type() == 'text/plain':
                                con3 = part.get_payload(decode=True).strip()
                                print('plain:', chardet.detect(con3))
                                if chardet.detect(con3)['encoding'] == 'utf-8':
                                    plain_list.append(con3.decode('utf-8'))
                                    continue
                                # if chardet.detect(con3)['encoding'] == 'ISO-8859-1':
                                #     plain_list.append(con3.decode('ISO-8859-1')) # .decode('gbk').encode('utf8')
                                #     continue
                                else:
                                    plain_list.append(con3.decode('gbk'))
                                    continue
                            elif part.get_content_type() == 'text/html':
                                con3 = part.get_payload(decode=True).strip()
                                print('html', chardet.detect(con3))
                                if chardet.detect(con3)['encoding'] == 'utf-8':
                                    html_list.append(con3.decode('utf-8'))
                                    continue
                                # if chardet.detect(con3)['encoding'] == 'ISO-8859-1':
                                #     html_list.append(con3.decode('ISO-8859-1'))
                                #     continue
                                else:
                                    html_list.append(con3.decode('gbk'))
                                    continue
                except Exception as e:
                    print(e)
                    print('获取邮件内容失败')
                    email_server.remove_flags(uid, b'\\Seen', silent=False)
                    subject_list.clear()
                    from_list.clear()
                    uid_list.clear()
                    email_body.clear()
                    fujian_list.clear()
                    image_list.clear()
                    plain_list.clear()
                    html_list.clear()
                    print('-------------------------------------------------------------------------')
                    continue


                if a == 1:
                    fujian_list.append('have')
                    a = 0
                else:
                    fujian_list.append('none')
                email_server.remove_flags(uid, b'\\Seen', silent=False)
                print("发件人：", from_list)
                print("邮件内容：")
                print("plain形式:",plain_list)
                print("html形式:",html_list)
                print("邮件uid:", uid_list)
                print("邮件是否含有图片或附件：", fujian_list)
                print('图片或附件名字：', image_list)
                if not html_list and not plain_list:
                    print("邮箱内无未读邮件")
                else:
                    print('成功拿到邮件数据')

                # 对邮件类型进行判断处理
                for i, v in enumerate(uid_list):
                    print("邮件标题：", subject_list[i])
                    if html_list and not plain_list:
                        print('此邮件仅含有html')
                        reply_model = html_list[i]
                        fajianren = from_list[i]
                        shoujianren = 'liehaoquan2021@163.com'  # 写zendesk邮箱
                        NeteaseMail().sentemail(email_server, uid_list[i],reply_model, None, subject_list[i], fajianren, shoujianren,
                                                ec.fromaddr, ec.password)
                        print('-------------------------------------------------------------------------')
                        break

                    if plain_list[i] == '':
                        print('此邮件无正文')
                        reply_model = ''
                        fajianren = from_list[i]
                        shoujianren = 'liehaoquan2021@163.com'  # 写zendesk邮箱
                        NeteaseMail().sentemail(email_server, uid_list[i],reply_model, None, subject_list[i], fajianren, shoujianren,
                                                ec.fromaddr, ec.password)
                        print('-------------------------------------------------------------------------')
                        break

                    if not subject_list[i]:
                        print('此邮件无主题')
                        if html_list and not plain_list:
                            print('此邮件无主题且仅含有html')
                            reply_model = html_list[i]
                            fajianren = from_list[i]
                            shoujianren = 'liehaoquan2021@163.com'  # 写zendesk邮箱
                            biaoti = '(无主题)'
                            NeteaseMail().sentemail(email_server, uid_list[i],reply_model, None, biaoti, fajianren, shoujianren,
                                                    ec.fromaddr, ec.password)
                            print('-------------------------------------------------------------------------')
                            break
                        elif plain_list:
                            print('此邮件无主题且含有正文')
                            reply_model = plain_list[i]
                            fajianren = from_list[i]
                            shoujianren = 'liehaoquan2021@163.com'  # 写zendesk邮箱
                            biaoti = '(无主题)'
                            NeteaseMail().sentemail(email_server, uid_list[i], reply_model, None, biaoti, fajianren, shoujianren,
                                                    ec.fromaddr, ec.password)
                        print('-------------------------------------------------------------------------')
                        break

                    # 处理含有图片或附件的邮件
                    if fujian_list[i] == 'have':
                        print('此邮件含有图片或附件或视频或压缩包')
                        reply_model = html_list[i]
                        image = image_list
                        fajianren = from_list[i]
                        shoujianren = 'liehaoquan2021@163.com'  # 写zendesk邮箱
                        NeteaseMail().sentemail(email_server, uid_list[i], reply_model, image, subject_list[i], fajianren, shoujianren,
                                                ec.fromaddr, ec.password)
                        file_path = os.path.join(os.path.dirname(__file__) + '/../emailtrainfile/image/')
                        shutil.rmtree(file_path)
                        os.mkdir(file_path)
                        print('-------------------------------------------------------------------------')
                        break

                    if fujian_list[i] == 'none':
                        # 处理无图片或附件的邮件
                        # 进行种类判断
                        print("识别内容：", plain_list[i].split('\n\n')[0])  # plain
                        if len(plain_list[i].split('\n\n\n')[0]) < 1000:
                            response1 = NeteaseMail().aws_login().classify_document(
                                Text=plain_list[i].split('\n\n\n')[0],
                                EndpointArn='arn:aws:comprehend:us-east-1:697864307463:document-classifier-endpoint/lhq'
                                # EndpointArn='arn:aws:comprehend:us-east-1:697864307463:document-classifier-endpoint/test'
                            )
                            # print(response.index(max(response['Classes']['Score'])))
                            nums = []
                            print('emailsort:')
                            for cls in response1['Classes']:
                                print(cls['Name'])
                                nums.append(cls['Score'])
                            print("识别种类及命中率：", response1['Classes'][nums.index(max(nums))])
                            # 命中率高于0.95时
                            if response1['Classes'][nums.index(max(nums))]['Score'] >= 0.95:
                                reply_sort = EmailSortModel.objects.filter(
                                    sort=response1['Classes'][nums.index(max(nums))]['Name']).values('autoreplymodel')
                                if reply_sort.exists():
                                    reply_model = reply_sort[0]['autoreplymodel'] + '\n' + '\n' + '\n' + '\n' + '\n' + '\n' + \
                                                  'At' + email_body[i]['Date'] + str(from_list[i].split()[0:-1]) + \
                                                  from_list[i].split()[-1] + \
                                                  'wrote:\n ' + plain_list[i]
                                    print(reply_model)
                                    shoujianren = from_list[i].split()[1].replace('<', '').replace('>', '')
                                    NeteaseMail().sentemail(email_server, uid_list[i], reply_model, None, subject_list[i], ec.fromaddr, shoujianren,
                                                            ec.fromaddr, ec.password)
                                    print('-------------------------------------------------------------------------')
                                    break
                            else:
                                print("此邮件命中率低于0.95")
                                reply_model = html_list[i]  # html
                                fajianren = from_list[i]
                                print(fujian_list)
                                shoujianren = 'liehaoquan2021@163.com'  # 写zendesk邮箱
                                NeteaseMail().sentemail(email_server, uid_list[i], reply_model, None, subject_list[i],
                                                        fajianren, shoujianren,
                                                        ec.fromaddr, ec.password)
                                print('-------------------------------------------------------------------------')
                                break

                        else:
                            print("识别内容过长")
                            reply_model = html_list[i]  # html
                            fajianren = from_list[i]
                            print(fujian_list)
                            shoujianren = 'liehaoquan2021@163.com'  # 写zendesk邮箱
                            NeteaseMail().sentemail(email_server, uid_list[i], reply_model, None, subject_list[i], fajianren, shoujianren,
                                                    ec.fromaddr, ec.password)
                            print('-------------------------------------------------------------------------')
                            break
                subject_list.clear()
                from_list.clear()
                uid_list.clear()
                email_body.clear()
                fujian_list.clear()
                image_list.clear()
                plain_list.clear()
                html_list.clear()
            NeteaseMail().closeEmail(email_server)
        return response.json(0)

# if __name__ == '__main__':
#     ComprehendAction().get_document_classifier()