jinql
/
12306
mirror of https://github.com/testerSunshine/12306
1
0
Fork 0
Code Issues Releases Wiki Activity

update version 1.1.114

Browse Source
pull/726/head
xianping.wen 5 years ago
parent 399f9b6626
commit 5fd9b8f8c9
10 changed files with 91 additions and 56 deletions
Show Stats Download Patch File Download Diff File

41
TickerConfig.py
Unescape View File

@ -4,24 +4,23 @@
# 如果这个时候捡漏捡到的话，也是可以付款成功的，也就是说，捡漏+候补，可以最大程度提升抢票成功率
# 刷票模式：1=刷票 2=候补+刷票
TICKET_TYPE = 2
TICKET_TYPE = 1
# 出发日期(list) "2018-01-06", "2018-01-07"
STATION_DATES = [
"2019-10-01"
"2019-09-26"
]
# 填入需要购买的车次(list)，"G1353"
# 修改车次填入规则，注：(以前设置的车次逻辑不变)，如果车次填入为空，那么就是当日乘车所有车次都纳入筛选返回
STATION_TRAINS = [
"",
]
# 不填车次是整个list为空才算，如果不是为空，依然会判断车次的，这种是错误的写法 [""], 正确的写法 []
STATION_TRAINS = []
# 出发城市，比如深圳北，就填深圳就搜得到
FROM_STATION = ""
FROM_STATION = "松山湖北"
# 到达城市 比如深圳北，就填深圳就搜得到
TO_STATION = ""
TO_STATION = "西平西"
# 座位(list) 多个座位ex:
# "商务座",
@ -34,7 +33,7 @@ TO_STATION = ""
# "无座",
# "动卧",
SET_TYPE = [
"",
"无座",
]
# 当余票小于乘车人，如果选择优先提交，则删减联系人和余票数一致在提交
@ -45,12 +44,13 @@ IS_MORE_TICKET = True
# - "张三"
# - "李四"
TICKET_PEOPLES = [
"",
"文贤平",
"李梦云",
]
# 12306登录账号
USER = ""
PWD = ""
USER = "qqxin1011"
PWD = "quxm19861011"
# 加入小黑屋时间默认为5分钟，此功能为了防止僵尸票导致一直下单不成功错过正常的票
TICKET_BLACK_LIST_TIME = 5
@ -58,6 +58,10 @@ TICKET_BLACK_LIST_TIME = 5
# 自动打码
IS_AUTO_CODE = True
# 设置2本地自动打码，需要配置tensorflow和keras库，3为云打码，由于云打码服务器资源有限(为2h4C的cpu服务器)，请不要恶意请求，不然只能关闭服务器
# ps: 请不要一直依赖云服务器资源，在此向提供服务器的"do it"同学表示感谢
AUTO_CODE_TYPE = 2
# 邮箱配置，如果抢票成功，将通过邮件配置通知给您
# 列举163
# email: "xxx@163.com"
@ -73,11 +77,11 @@ IS_AUTO_CODE = True
# host: "smtp.qq.com"
EMAIL_CONF = {
"IS_MAIL": True,
"email": "",
"notice_email_list": "",
"username": "",
"password": "",
"host": "",
"email": "931128603@qq.com",
"notice_email_list": "931128603@qq.com",
"username": "931128603@qq.com",
"password": "lwvgfrcydzyvbfjf",
"host": "smtp.qq.com",
}
# 是否开启 server酱 微信提醒， 使用前需要前往 http://sc.ftqq.com/3.version 扫码绑定获取 SECRET 并关注获得抢票结果通知的公众号
@ -111,7 +115,7 @@ OPEN_TIME = "13:00:00"
COOKIE_TYPE = 1
# 如果COOKIE_TYPE=1，则需配置chromeDriver路径,下载地址http://chromedriver.storage.googleapis.com/index.html
# chromedriver配置版本只要和chrome的大版本匹配就行
CHROME_PATH = ""
CHROME_PATH = "/Users/wenxianping/Downloads/chromedriver"
# 1=>为一直随机ua,2->只启动的时候随机一次ua
RANDOM_AGENT = 2
@ -133,5 +137,6 @@ PASSENGER_TICKER_STR = {
MAX_TIME = 5
# 最小间隔请求时间
MIN_TIME = 3
# 软件版本
RE_VERSION = "1.1.113"
RE_VERSION = "1.1.114"

4
Update.md
Unescape View File

@ -185,3 +185,7 @@
- 增长随机停留时长
- 增长用户心跳时间，减少对服务器压力
- 优化下单逻辑
- 2019.09.18更新
- 修改下单问题
- 优化车次打印

14
config/urlConf.py
Unescape View File

@ -587,6 +587,16 @@ urls = {
"is_json": True,
},
"autoVerifyImage": { # 云打码接口
"req_url": "/verify/base64/",
"req_type": "post",
"Referer": "",
"Host": "111.230.237.182:8000",
"re_try": 2,
"re_time": 2,
"s_time": 2,
"is_logger": True,
"is_json": True,
"httpType": "http"
},
}

14
init/select_ticket_info.py
Unescape View File

@ -36,7 +36,7 @@ class select:
def __init__(self):
self.get_ticket_info()
self._station_seat = [seat_conf[x] for x in TickerConfig.SET_TYPE]
self.auto_code_type = 2
self.auto_code_type = TickerConfig.AUTO_CODE_TYPE
self.httpClint = HTTPClient(TickerConfig.IS_PROXY)
self.urls = urlConf.urls
self.login = GoLogin(self, TickerConfig.IS_AUTO_CODE, self.auto_code_type)
@ -55,10 +55,14 @@ class select:
获取配置信息
:return:
"""
print(u"*" * 50)
print(f"检查当前版本为: {TickerConfig.RE_VERSION}")
print(u"检查当前python版本为：{}，目前版本只支持3.6以上".format(sys.version.split(" ")[0]))
print(u"12306刷票小助手，最后更新于2019.09.15，请勿作为商业用途，交流群号："
version = sys.version.split(" ")[0]
print(u"检查当前python版本为：{}，目前版本只支持3.6以上".format(version))
if version < "3.6.0":
raise Exception
print(u"12306刷票小助手，最后更新于2019.09.18，请勿作为商业用途，交流群号："
u" 1群：286271084(已满)\n"
u" 2群：649992274(已满)\n"
u" 3群：632501142(已满)\n"
@ -69,7 +73,7 @@ class select:
u" 8群: 620629239(未满)\n"
)
print(
f"当前配置：\n出发站：{TickerConfig.FROM_STATION}\n到达站：{TickerConfig.TO_STATION}\n乘车日期：{','.join(TickerConfig.STATION_DATES)}\n坐席：{','.join(TickerConfig.SET_TYPE)}\n是否有票优先提交：{TickerConfig.IS_MORE_TICKET}\n乘车人：{TickerConfig.TICKET_PEOPLES}\n" \
f"当前配置：\n出发站：{TickerConfig.FROM_STATION}\n到达站：{TickerConfig.TO_STATION}\n车次: {','.join(TickerConfig.STATION_TRAINS) or '所有车次'}\n乘车日期：{','.join(TickerConfig.STATION_DATES)}\n坐席：{','.join(TickerConfig.SET_TYPE)}\n是否有票优先提交：{TickerConfig.IS_MORE_TICKET}\n乘车人：{TickerConfig.TICKET_PEOPLES}\n" \
f"刷新间隔: 随机(1-3S)\n僵尸票关小黑屋时长: {TickerConfig.TICKET_BLACK_LIST_TIME}\n下单接口: {TickerConfig.ORDER_TYPE}\n下单模式: {TickerConfig.ORDER_MODEL}\n预售踩点时间:{TickerConfig.OPEN_TIME}")
print(u"*" * 50)
@ -244,7 +248,7 @@ class select:
else:
random_time = round(random.uniform(sleep_time_s, sleep_time_t), 2)
nateMsg = ' 无候补机会' if TickerConfig.ORDER_TYPE == 2 else ""
print(f"正在第{num}次查询 随机停留时长：{random_time} 乘车日期: {','.join(TickerConfig.STATION_DATES)} 车次：{'.'.join(TickerConfig.STATION_TRAINS)} 下单无票{nateMsg} 耗时：{(datetime.datetime.now() - now).microseconds / 1000}ms")
print(f"正在第{num}次查询 随机停留时长：{random_time} 乘车日期: {','.join(TickerConfig.STATION_DATES)} 车次：{','.join(TickerConfig.STATION_TRAINS) or '所有车次'} 下单无票{nateMsg} 耗时：{(datetime.datetime.now() - now).microseconds / 1000}ms")
time.sleep(random_time)
except PassengerUserException as e:
print(e)

10
inter/GetRandCode.py
Unescape View File

@ -1,6 +1,8 @@
# coding=utf-8
from PIL import Image
from config.urlConf import urls
from myUrllib.httpUtils import HTTPClient
from verify.localVerifyCode import verify
@ -14,9 +16,15 @@ def getRandCode(is_auto_code, auto_code_type, result):
if auto_code_type == 1:
print(u"打码兔已关闭, 如需使用自动识别，请使用如果平台 auto_code_type == 2")
return
if auto_code_type == 2:
elif auto_code_type == 2:
Result = verify(result)
return codexy(Ofset=Result, is_raw_input=False)
elif auto_code_type == 3:
print("您已设置使用云打码，但是服务器资源有限，请尽快改为本地打码")
http = HTTPClient(0)
Result = http.send(urls.get("autoVerifyImage"), {"imageFile": result})
if Result and Result.get("code") is 0:
return codexy(Ofset=Result.get("data"), is_raw_input=False)
else:
img = Image.open('./tkcode.png')
img.show()

4
inter/Query.py
Unescape View File

@ -53,7 +53,7 @@ class query:
:param ticket_info:
:return:
"""
if self.station_dates:
if self.station_dates and self.station_trains:
return ticket_info[3] in self.station_trains
else:
return True
@ -119,7 +119,7 @@ class query:
self.to_station_h,
seat_conf_2[j],
ticket_num))
if seat_conf_2[j] == "无座" and ticket_info[3][0] in ["G", "D"]:
if seat_conf_2[j] == "无座" and ticket_info[3][0] in ["G", "D", "C"]:
seat = 30 # GD开头的无座直接强制改为二等座车次
if wrapcache.get(train_no):
print(ticket.QUERY_IN_BLACK_LIST.format(train_no))

4
myUrllib/httpUtils.py
Unescape View File

@ -135,7 +135,7 @@ class HTTPClient(object):
self.setHeadersReferer(urls["Referer"])
if is_logger:
logger.log(
u"url: {0}\n入参: {1}\n请求方式: {2}\n".format(req_url, data, method, ))
u"url: {0}\n入参: {1}\n请求方式: {2}\n".format(req_url, data, method))
self.setHeadersHost(urls["Host"])
if is_test_cdn:
url_host = self._cdn
@ -157,7 +157,7 @@ class HTTPClient(object):
except:
pass
response = self._s.request(method=method,
timeout=2,
timeout=5,
proxies=self._proxies,
url=http + "://" + url_host + req_url,
data=data,

18
verify/localVerifyCode.py
Unescape View File

@ -1,14 +1,14 @@
# coding: utf-8
import base64
import os
import TickerConfig
if TickerConfig.AUTO_CODE_TYPE == 2:
import base64
import os
import cv2
import numpy as np
from keras import models, backend
from verify import pretreatment
from verify.mlearn_for_image import preprocess_input
import cv2
import numpy as np
from keras import models, backend
from verify import pretreatment
from verify.mlearn_for_image import preprocess_input
PATH = lambda p: os.path.abspath(
os.path.join(os.path.dirname(__file__), p)
)

20
verify/mlearn_for_image.py
Unescape View File

@ -1,14 +1,16 @@
# coding: utf-8
import sys
import TickerConfig
if TickerConfig.AUTO_CODE_TYPE == 2:
import sys
import cv2
import numpy as np
from keras import models
from keras import layers
from keras import optimizers
from keras.applications import VGG16
from keras.callbacks import ReduceLROnPlateau
from keras.preprocessing.image import ImageDataGenerator
import cv2
import numpy as np
from keras import models
from keras import layers
from keras import optimizers
from keras.applications import VGG16
from keras.callbacks import ReduceLROnPlateau
from keras.preprocessing.image import ImageDataGenerator
def preprocess_input(x):

18
verify/pretreatment.py
Unescape View File

@ -3,14 +3,16 @@
# 功能：对图像进行预处理，将文字部分单独提取出来
# 并存放到ocr目录下
# 文件名为原验证码文件的文件名
import hashlib
import os
import pathlib
import cv2
import numpy as np
import requests
import scipy.fftpack
import TickerConfig
if TickerConfig.AUTO_CODE_TYPE == 2:
import hashlib
import os
import pathlib
import cv2
import numpy as np
import requests
import scipy.fftpack
PATH = 'imgs'

Write Preview
Loading…
Cancel
Save