def detection(request):
while 1:
result = od1.main()
print(result)
if result.count("quit") < 1:
pringles = result.count("pringles")
cafe = result.count("cafe")
doritos = result.count("doritos")
# if temp>1:
# if pringles<1 or cafe<1 or doritos<1:
Token = "P9SHXtrlr0eEeSVx4M04ZRPab7Vbcry42Avk7Luaeva"
TurnOn_message = "\n" + " 目前架上的商品數量如下:\n" + "Pringles:" + str(
pringles) + "\n" + "cafe:" + str(
cafe) + "\n" + "doritos:" + str(
doritos) + "\n請確認是否需要補貨,謝謝\n"
Time_message = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
MESSAGE = ''
time.sleep(10)
MESSAGE = TurnOn_message + Time_message
print("Send message to Line \n%s\n" % MESSAGE)
lineTool.lineNotify(Token, MESSAGE)
time.sleep(10)
else:
break
return redirect('http://localhost:8000/member/memberarea/')
def processNotifyNews():
notifySidList = []
# maybe fetch googlesheet
googlesheetService = GooglesheetService(
"1F3cT6ltHQ7gOYxCPSrPJGvMpUt3b5mRJIMR0gJ5ITr8")
rowList = googlesheetService.getValues("新聞通知清單")
for row in rowList:
if len(row) == 0 or row[0] == '' and row[1] == '':
continue # 略過空白行
notifySidList.append(row[0])
print(notifySidList)
with open("news.csv", "r", encoding="utf-8") as f1:
csvRowList = list(csv.reader(f1))
for csvRow in csvRowList:
if csvRow[0] in notifySidList and csvRow[6] == "W":
msg = "{} {} {} {} {}\n\n{}".format(csvRow[0], csvRow[1],
csvRow[2], csvRow[3],
csvRow[4], csvRow[5])
lineTool.lineNotify(os.environ["LINE_TEST_TOKEN"], msg)
csvRow[6] = "Y"
else:
csvRow[6] = "N"
# 寫回 csv 檔
with open("news.csv", "w", encoding="utf-8", newline="") as f1:
csv.writer(f1).writerows(csvRowList)
def fetch():
url = "https://kktix.com/events"
resp = requests.get(url)
soup = BeautifulSoup(resp.text, "html.parser")
liList = soup.find("ul", {"class": "event-list"}).findAll("li", {"class": "clearfix"})
with open("kktix.txt", encoding="utf-8") as f1:
kktixList = list(csv.reader(f1))
with open("kktix.txt", "a", newline="", encoding="utf-8") as f1:
writer = csv.writer(f1)
messageList = []
for li in liList:
title = li.find("h2").find("a").text
description = li.find("div", {"class": "description"}).text
href = li.find("h2").find("a").get("href")
message = title + "\n\n" + description + "\n" + href
if not [href] in kktixList:
writer.writerow([href])
messageList.append(message)
if len(messageList) > 0:
notifyMessage = ""
for msg in messageList:
notifyMessage += msg + "\n----------------------------------------\n\n"
lineTool.lineNotify(os.environ["LINE_TEST_TOKEN"], notifyMessage)
def fetchAllStockFinalData(self, dt=datetime.datetime.now()):
url = "http://www.twse.com.tw/exchangeReport/MI_INDEX?response=json&date=%s&type=ALLBUT0999&_=%s" % (
dt.strftime("%Y%m%d"), int(time.time() * 1000))
r = requests.get(url)
print("GET %s\nResponse => %s" % (url, r.json()))
js = r.json()
if js.get("stat") != "OK":
print("%s 查無資料" % (dt.strftime("%Y%m%d")))
return
# 因為有 K 值要處理，不能只抓存單一值，必須從頭開始存起，改通知我自己，有新的代號要處理歷史資料
newStockIdList = []
for data in js.get("data5"):
stockId = data[0]
if data[9].find('red') > 0:
sign = '+'
else:
sign = '-' if data[9].find('green') > 0 else ''
date = "{}/{}/{}".format(js["date"][0:4], js["date"][4:6],
js["date"][6:8])
row = [
date, data[2], data[4], data[5], data[6], data[7], data[8],
sign + data[10], data[3], "", ""
] # 後面兩個空值是 RSV & K9
row = self._make_datatuple(row)
if not os.path.exists("data/{}.csv".format(stockId)):
# with open("data/{}.csv".format(stockId), "a", newline="") as f1:
# writer = csv.writer(f1)
# writer.writerow(["日期","成交股數","成交金額","開盤價","最高價","最低價","收盤價","漲跌價差","成交筆數","RSV","K9"])
# 先略過，不處理，之後再處理這些新的
newStockIdList.append(stockId)
continue
# 讀出舊的資料
rowDict = {}
with open("data/{}.csv".format(stockId), "r",
encoding="MS950") as f1:
for row1 in csv.reader(f1):
rowDict[row1[0]] = row1
if row[3] != None:
row[3] = format(round(row[3], 2), ".2f")
if row[4] != None:
row[4] = format(round(row[4], 2), ".2f")
if row[5] != None:
row[5] = format(round(row[5], 2), ".2f")
if row[6] != None:
row[6] = format(round(row[6], 2), ".2f")
rowDict[row[0]] = row
self.appendDataByRowList(stockId, rowDict)
lineTool.lineNotify(os.environ["LINE_TEST_TOKEN"], newStockIdList)
def fetch(sid):
rowList = [['盈餘所屬年度', '股利發放年度', '股東會日期', '除息交易日', '除息參考價(元)', '除權交易日', '除權參考價(元)', '現金股利發放日', '現金股利盈餘', '現金股利公積', '現金股利合計', '股票股利盈餘', '股票股利公積', '股票股利合計', '股利合計', '發放年度平均股價', '年均殖利率(%)']]
url = "https://goodinfo.tw/StockInfo/StockDividendSchedule.asp?STOCK_ID={}".format(sid)
print(url)
headers = {
"User-Agent" : "Chrome/31.0.1650.63"
}
r = requests.get(url, headers=headers)
r.encoding = "utf-8"
if "查無除權息日程訊息" in r.text:
return rowList
if "您的瀏覽量異常, 已影響網站速度" in r.text:
lineTool.lineNotify(os.environ["LINE_TEST_TOKEN"], "fetchStockDividendSchedule too fast to be blocked")
soup = BeautifulSoup(r.text, "html.parser")
trs = soup.find("table", {"class": "solid_1_padding_4_3_tbl"}).findAll("tr", id=re.compile("^row"))
for tr in trs:
row = []
for td in tr.findAll("td"):
row.append(td.text)
rowList.append(row)
return rowList
def main():
try:
print("\n---------------------------------")
print("執行時間 {}".format(datetime.datetime.now().strftime('%Y/%m%d %H:%M:%S')))
print("---------------------------------")
fetch()
except:
traceback.print_exc()
lineTool.lineNotify(os.environ["LINE_TEST_TOKEN"], "fetch kktix data fail")
def rowListToMessage(rowList, rangeName):
message = ""
for row in rowList:
dt = row[2][0:10] + " " + row[2][11:16]
message += "------------------------------------------\n[%s] [%s]\n------------------------------------------\n" % (
rangeName, dt)
message += row[1] + "\n原文連結: " + row[4] + "\n\n"
print(message)
lineTool.lineNotify(os.environ["LINE_TEST_TOKEN"], message)
def notifyLineMsg(token, msg, retry=2):
print("retry times", retry)
try:
lineTool.lineNotify(token, msg)
except ChunkedEncodingError as e:
print(e)
retry = retry - 1
msg = msg[0:len(msg) - 1]
if retry > 0:
time.sleep(1)
notifyLineMsg(token, msg, retry)
else:
raise e
def main():
print("# -------------------------- #\n# 執行時間 {} #\n# -------------------------- #".format(datetime.datetime.now().strftime('%Y/%m%d %H:%M:%S')))
sid = "1313"
fetch(sid)
detect(sid)
# 前面 for 完全部，換通知
if not os.path.exists("changeList.csv"):
print("無任何異動不需通知")
return
print("\n開始進行通知\n")
with open("changeList.csv", "r") as f1:
rowList = list(csv.reader(f1))
msg = "股權異動通知"
for row in rowList:
msg += "\n" + str(row)
print(row)
code = lineTool.lineNotify(os.environ["LINE_TEST_TOKEN"], msg)
print(code)
os.remove("changeList.csv")
print("completed.")
def lineMe():
token = ""
msg = "Python 語言整合通訊軟體,恭喜您"
response = lineTool.lineNotify(token, msg)
if response == 200:
print("傳送成功")
else:
print("傳送失敗")
def notifyTo7LineGroup(text):
lineTool.lineNotify('2D7IaxfEThWOFQJUu6Wpp8kliclIW1o7C0VaDCiaR7V',
text) # 自己的測試 token
#lineTool.lineNotify('4dpvkMrhwqS5BS20b76f9z8xfZgceRweJ8eiaRLtcGC', text) # 群一
#time.sleep(2)
#lineTool.lineNotify('p3LcZxNRx2PRpjZ6oKeoEZxpq5F8EqYjq3OsO96ChyM', text) # 群二
#time.sleep(2)
#lineTool.lineNotify('cnL48vx1yPjVGhmbGICvWOipRJJoM1C8Dudde9JFGlW', text) # 群三
#time.sleep(2)
#lineTool.lineNotify('XutbtO5bOgyCIdg3kJZ3MZhGakLGMw1JRGpQgbDIK3D', text) # 群四
#time.sleep(2)
#lineTool.lineNotify('rMUoZDVl1C5fuRMmH9sUEI4qTgHyfy8lMDQXEh0PTBc', text) # 群五
#time.sleep(2)
#lineTool.lineNotify('CHhwARDFMz384a3XoIzS3nNt03nNFH7UG8LX8ooYCJS', text) # 群六
#time.sleep(2)
#lineTool.lineNotify('qN59nwm7YStstULdWHZEPh7Z4X77WvcLd7FffgHvGNq', text) # 群七
logging.info('通知七群完畢')
def fetchOtcStockIdFormSheet(sheetId, sheetName, token):
googlesheetService = GooglesheetService(sheetId)
rowNum = 0
for value in googlesheetService.getValues(sheetName):
rowNum += 1
# header
if rowNum == 1:
continue # header 不繼續下面的邏輯
if len(value) == 0:
continue # 略過空白行
if value[0] == '':
continue # 連股票代號都沒有的，略過
if stockIdMap.get(value[0], "") == "上櫃":
stockDataMap[value[0]] = None # 本來是想放名稱，但這裡沒有
elif stockIdMap.get(value[0], "") == "":
print("{} 非上市上櫃目前不支援".format(value[0]))
lineTool.lineNotify(token, "{} 非上市上櫃目前不支援".format(value[0]))
def fetch(sid):
rowList = [[
'盈餘發放年度', '現金股利盈餘', '現金股利公積', '現金股利合計', '股票股利盈餘', '股票股利公積', '股票股利合計',
'股利合計', '股利總計現金(億)', '股利總計股票(千張)', '董監酬勞合計(百萬)', '董監酬勞合計佔淨利(%)',
'員工紅利現金(億)', '員工紅利股票(千張)', '股價年度', '股價統計(元)最高', '股價統計(元)最低',
'股價統計(元)年均', '年均殖利率(%)現金', '年均殖利率(%)股票', '年均殖利率(%)合計', '盈餘年度',
'EPS(元)', '盈餘分配率(%)配息', '盈餘分配率(%)配股', '盈餘分配率(%)合計'
]]
url = "https://goodinfo.tw/StockInfo/stockDividendPolicy.asp?STOCK_ID={}".format(
sid)
print(url)
headers = {"User-Agent": "Chrome/31.0.1650.63"}
r = requests.get(url, headers=headers)
r.encoding = "utf-8"
if "查無除權息日程訊息" in r.text:
return rowList
if "您的瀏覽量異常, 已影響網站速度" in r.text:
lineTool.lineNotify(os.environ["LINE_TEST_TOKEN"],
"fetchstockDividendPolicy too fast to be blocked")
raise EOFError()
soup = BeautifulSoup(r.text, "html.parser")
trs = soup.findAll("table",
{"class": "solid_1_padding_4_0_tbl"})[1].findAll("tr")
for tr in trs:
if not tr.has_attr("onmouseover"):
continue
row = []
for td in tr.findAll("td"):
row.append(td.text)
rowList.append(row)
return rowList
def main():
print("執行時間 {}".format(
datetime.datetime.now().strftime('%Y/%m%d %H:%M:%S')))
now = datetime.datetime.now()
# 取最後一筆資料
with open("data/t00.csv", encoding="MS950") as f1:
row = list(csv.reader(f1))[-1]
# 若日期等於今日才作通知
if row[0] != now.strftime("%Y/%m/%d"):
print("無今日資料，不進行通知")
return
yestPrice = float(row[6]) - float(row[7])
pct = round(float(row[7]) / yestPrice * 100, 2)
msg = "{} 大盤 K 值 {}\n\n大盤指數 {} {} ({:.2f}%)".format(
row[0], row[10], row[6], row[7], pct)
msg += "\n"
msg += composeMsg("0050")
msg += "\n"
msg += composeMsg("0056")
if float(row[10]) >= 80:
msg += "\n\n## 大盤 K 值已超過 80，建議賣出 0050 ##"
elif float(row[10]) <= 20:
msg += "\n\n## 大盤 K 值已低於 20，建議買入 0050 ##"
# 0056 額外通知訊息
with open("data/0056.csv", encoding="MS950") as f1:
row = list(csv.reader(f1))[-1]
amt = int(row[1]) // 1000
if amt >= 2000 and amt < 5000:
msg += "\n\n## 0056 成交量 {} 張，較平常多，可留意是否較低價可買入 ##".format(amt)
elif amt >= 5000 and amt < 8000:
msg += "\n\n## 0056 成交量 {} 張，數量偏大，可留意是否較低價可買入 ##".format(amt)
elif amt >= 8000:
msg += "\n\n## 0056 成交量 {} 張，異常的高，請留意是否較低價可買入 ##".format(amt)
k9 = float(row[10])
if k9 <= 20:
msg += "\n\n## 0056 K值已低於 20，可考慮低價可買入 ##".format(amt)
elif k9 >= 80:
msg += "\n\n## 0056 K值已高於 80，可考慮價差 1元以上賣出 ##".format(amt)
print(msg)
# 發 LINE 通知
lineTool.lineNotify(os.environ["LINE_0050_TOKEN"], msg)
time.sleep(2) # delays for n seconds
lineTool.lineNotify(os.environ["LINE_0050_TOKEN2"], msg)
time.sleep(2)
lineTool.lineNotify(os.environ["LINE_0050_TOKEN3"], msg)
time.sleep(2)
lineTool.lineNotify(os.environ["LINE_0050_TOKEN4"], msg)
time.sleep(2)
lineTool.lineNotify(os.environ["LINE_0050_TOKEN5"], msg)
time.sleep(2)
lineTool.lineNotify(os.environ["LINE_0050_TOKEN6"], msg)
time.sleep(2)
lineTool.lineNotify(os.environ["LINE_0050_TOKEN7"], msg)
def main():
print("[INFO] quantifying faces...")
imagePaths = list(paths.list_images('dataset'))
# initialize the list of known encodings and known names
knownEncodings = []
knownNames = []
# loop over the image paths
for (i, imagePath) in enumerate(imagePaths):
# extract the person name from the image path
print("[INFO] processing image {}/{}".format(i + 1, len(imagePaths)))
name = imagePath.split(os.path.sep)[-2]
# load the input image and convert it from RGB (OpenCV ordering)
# to dlib ordering (RGB)
image = cv2.imread(imagePath)
# cv2.imshow('image',image)
# cv2.waitKey(0)
print(imagePath)
rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
# detect the (x, y)-coordinates of the bounding boxes
# corresponding to each face in the input image
boxes = face_recognition.face_locations(rgb, model='hog')
# compute the facial embedding for the face
encodings = face_recognition.face_encodings(rgb, boxes)
# loop over the encodings
for encoding in encodings:
# add each encoding + name to our set of known names and
# encodings
knownEncodings.append(encoding)
knownNames.append(name)
# dump the facial encodings + names to disk
print("[INFO] serializing encodings...")
data = {"encodings": knownEncodings, "names": knownNames}
f = open('encodings.pickle', "wb")
f.write(pickle.dumps(data))
f.close()
print("[INFO] loading encodings + face detector...")
data = pickle.loads(open('encodings.pickle', "rb").read())
detector = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
# initialize the video stream and allow the camera sensor to warm up
print("[INFO] starting video stream...")
#vs = VideoStream(src=0).start()
vs = VideoStream(usePiCamera=True).start()
time.sleep(2.0)
# start the FPS counter
fps = FPS().start()
token = 'vLFoe5SQBochCZsPJcDdct7oqOtcm6HdPD2QyCPyeZm'
message = 'Notify from LINE, Intruder detected!!!'
hasSent = False
# loop over frames from the video file stream
while True:
# grab the frame from the threaded video stream and resize it
# to 500px (to speedup processing)
frame = vs.read()
frame = imutils.resize(frame, width=500)
# convert the input frame from (1) BGR to grayscale (for face
# detection) and (2) from BGR to RGB (for face recognition)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
# detect faces in the grayscale frame
rects = detector.detectMultiScale(gray,
scaleFactor=1.1,
minNeighbors=5,
minSize=(30, 30),
flags=cv2.CASCADE_SCALE_IMAGE)
# OpenCV returns bounding box coordinates in (x, y, w, h) order
# but we need them in (top, right, bottom, left) order, so we
# need to do a bit of reordering
boxes = [(y, x + w, y + h, x) for (x, y, w, h) in rects]
# compute the facial embeddings for each face bounding box
encodings = face_recognition.face_encodings(rgb, boxes)
names = []
# loop over the facial embeddings
for encoding in encodings:
# attempt to match each face in the input image to our known
# encodings
matches = face_recognition.compare_faces(data["encodings"],
encoding)
name = "Unknown"
# check to see if we have found a match
if True in matches:
# find the indexes of all matched faces then initialize a
# dictionary to count the total number of times each face
# was matched
matchedIdxs = [i for (i, b) in enumerate(matches) if b]
counts = {}
# loop over the matched indexes and maintain a count for
# each recognized face face
for i in matchedIdxs:
name = data["names"][i]
counts[name] = counts.get(name, 0) + 1
# determine the recognized face with the largest number
# of votes (note: in the event of an unlikely tie Python
# will select first entry in the dictionary)
name = max(counts, key=counts.get)
# update the list of names
names.append(name)
if len(rects) != 0 and name == "Unknown" and not hasSent:
print("Intruder!")
lineTool.lineNotify(token, message)
hasSent = True
elif len(rects) != 0 and name != "Unknown":
print(name)
hasSent = False
'''
# loop over the recognized faces
for ((top, right, bottom, left), name) in zip(boxes, names):
# draw the predicted face name on the image
cv2.rectangle(frame, (left, top), (right, bottom),
(0, 255, 0), 2)
y = top - 15 if top - 15 > 15 else top + 15
cv2.putText(frame, name, (left, y), cv2.FONT_HERSHEY_SIMPLEX,
0.75, (0, 255, 0), 2)
# display the image to our screen
cv2.imshow("Frame", frame)
'''
key = cv2.waitKey(1) & 0xFF
# if the `q` key was pressed, break from the loop
if key == ord("q"):
break
# update the FPS counter
fps.update()
# stop the timer and display FPS information
fps.stop()
print("[INFO] elasped time: {:.2f}".format(fps.elapsed()))
print("[INFO] approx. FPS: {:.2f}".format(fps.fps()))
# do a bit of cleanup
cv2.destroyAllWindows()
vs.stop()
for row in rowList:
if len(row) == 0 or row[0] == '' and row[1] == '':
continue # 略過空白行
notifySidList.append(row[0])
print(notifySidList)
with open("news.csv", "r", encoding="utf-8") as f1:
csvRowList = list(csv.reader(f1))
for csvRow in csvRowList:
if csvRow[0] in notifySidList and csvRow[6] == "W":
msg = "{} {} {} {} {}\n\n{}".format(csvRow[0], csvRow[1],
csvRow[2], csvRow[3],
csvRow[4], csvRow[5])
lineTool.lineNotify(os.environ["LINE_TEST_TOKEN"], msg)
csvRow[6] = "Y"
else:
csvRow[6] = "N"
# 寫回 csv 檔
with open("news.csv", "w", encoding="utf-8", newline="") as f1:
csv.writer(f1).writerows(csvRowList)
if __name__ == "__main__":
try:
main()
except:
traceback.print_exc()
lineTool.lineNotify(os.environ["LINE_TEST_TOKEN"], "readNews error")
def main():
t1 = time.time()
now = datetime.datetime.now()
crawler = TWSECrawler()
# 13:50 分以後才會有資料
if int(str(now.hour) + format(now.minute, "02")) >= 1350:
# 爬資料寫到各 csv 檔
crawler.fetchAllStockFinalData()
# 爬上櫃資料寫到每日 csv 檔
crawler.fetchOtcDailyCloseQuotes()
# 爬大盤資料寫入 csv 檔
crawler.fetchStockInfo("t00")
t2 = int(time.time() - t1)
print("total time {}".format(t2))
if __name__ == "__main__":
try:
main()
except Exception as e:
traceback.print_exc()
lineTool.lineNotify(os.environ["LINE_TEST_TOKEN"],
"fetch_all_stock_data 發生錯誤")
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#Author : GordonWei
#Date : Aug/06/19
#comment : Scrapying ITHome Today's News
import requests, re, time, lineTool
from bs4 import BeautifulSoup
today = time.strftime('%Y-%m-%d')
lineToken = 'Your Line Notify Token'
ithome_site = 'https://www.ithome.com.tw/news'
indexRes = requests.get(ithome_site)
indexSoup = BeautifulSoup(indexRes.text, 'html.parser')
pages = indexSoup.find_all('span', class_='views-field')
for n in pages:
if n.find('p', text=re.compile(today)):
if n.find('div'):
title = n.find('p', class_='title').text
href = n.find('a')['href']
botText = (today, title, 'https://www.ithome.com.tw' + href)
lineTool.lineNotify(lineToken, botText)
and float(data['data']['data'][l]['area']) < 750):
continue
if (landtype == '建地'
and float(data['data']['data'][l]['area']) < 50):
continue
if (landtype == '住宅'
and float(data['data']['data'][l]['area']) < 50):
continue
price = int(data['data']['data'][l]['price'].replace(',', ''))
if (price > 5000):
continue
msg1 = data['data']['data'][l]['sectionname'] + '【' + landtype + '】'
msg2 = '面積: ' + str(data['data']['data'][l]['area'])
msg3 = '總價: ' + data['data']['data'][l]['price'] + '萬'
msg4 = '單價: ' + data['data']['data'][l]['perarea_str']
msg5 = data['data']['data'][l]['address']
landId = data['data']['data'][l]['houseid']
msg6 = 'https://sale.591.com.tw/home/house/detail/2/' + str(
landId) + '.html'
msg = "\n" + msg1 + "\n" + msg2 + "\n" + msg3 + "\n" + msg4 + "\n" + msg5 + "\n" + msg6
lineTool.lineNotify(token, msg)
print("Wait 1000 seconds ")
time.sleep(1000)
conn.close()
def rowListToMessageAndNotify(rowList, rangeName):
for row in rowList:
# 因為時間看起來是美國時間，還要再自己加 8，先拿掉時間顯示
# dt = row[1][0:10] + " " + row[1][11:16]
# message = "------------------------------------------\n[%s] [%s]\n------------------------------------------\n" %(rangeName, dt)
message = " [%s]\n------------------------------------------\n" % (
rangeName)
if len(row) >= 6:
message += row[3] + "\n\n" + row[5] + "\n\n原文連結: " + row[4]
else:
message += row[3] + "\n\n原文連結: " + row[4]
# lineTool.lineNotify(os.environ["LINE_FANS_TOKEN"], message)
# time.sleep(3)
# lineTool.lineNotify(os.environ["LINE_FANS_TOKEN2"], message)
# time.sleep(3)
# lineTool.lineNotify(os.environ["LINE_FANS_TOKEN3"], message)
# time.sleep(3)
lineTool.lineNotify(os.environ["LINE_0050_TOKEN"], message)
time.sleep(2) # delays for n seconds
lineTool.lineNotify(os.environ["LINE_0050_TOKEN2"], message)
time.sleep(2)
lineTool.lineNotify(os.environ["LINE_0050_TOKEN3"], message)
time.sleep(2)
lineTool.lineNotify(os.environ["LINE_0050_TOKEN4"], message)
time.sleep(2)
lineTool.lineNotify(os.environ["LINE_0050_TOKEN5"], message)
time.sleep(2)
lineTool.lineNotify(os.environ["LINE_0050_TOKEN6"], message)
time.sleep(2)
def processSheet(sheetId, sheetName, notifyLineToken):
googlesheetService = GooglesheetService(sheetId)
rowNum = 0
rowList = []
msg = ""
for value in googlesheetService.getValues(sheetName):
rowNum += 1
rowList.append(value) # 之後資料要回寫回 sheet
# header
if rowNum == 1:
if len(value) <= 10:
value.append("")
columnNum = len(value) # 取 header 的總 column 數
value[10] = datetime.datetime.now().strftime('%m%d %H:%M:%S')
continue # header 不繼續下面的邏輯
if len(value) == 0:
continue # 略過空白行
# 明細列若欄位不足，先補齊，避免 exception 發生
if len(value) < columnNum:
for i in range(columnNum - len(value)):
value.append("")
if value[0] == '':
continue # 連代號都沒有，其他卻還有 #N/A 的值，大家還是會亂搞，防呆
# 開始比價
try:
nowPrice = float(value[4].replace(",", ""))
except:
print("something wrong", value[4])
print(value)
nowPrice = 5000.0
wantPrice = value[2]
# if nowPrice != "" and wantPrice != "" and nowPrice <= float(wantPrice):
if wantPrice != "" and nowPrice <= float(wantPrice):
if value[10] != datetime.datetime.now().strftime('%Y%m%d'):
msg += "\n{} ({}) 買進價 {}，現價 {}，PE: {}，買進原因： {}\n".format(value[1], value[0], value[2], value[4], value[8], value[9])
value[10] = datetime.datetime.now().strftime('%Y%m%d')
if stockIdMap.get(value[0], "") == "上櫃":
# value[3] = '=(E{}-C{})/C{}'.format(rowNum, rowNum, rowNum)
# value[4] = '=IFERROR(ARRAY_CONSTRAIN(importXML(CONCATENATE("http://m.wantgoo.com/s/", $A{}),"//*/div[2]/div/div[1]"),1,1))'.format(rowNum)
# value[5] = 'N/A'
# value[6] = 'N/A'
# value[7] = 'N/A'
# value[8] = 'N/A'
# print("上櫃資料改由別隻處理")
pass
elif stockIdMap.get(value[0], "") == "上市":
value[3] = '=(E{}-C{})/C{}'.format(rowNum, rowNum, rowNum)
value[4] = '=GOOGLEFINANCE(CONCATENATE("TPE:", $A{}), "price")'.format(rowNum)
value[5] = '=GOOGLEFINANCE(CONCATENATE("TPE:", $A{}), "change")'.format(rowNum)
value[6] = '=GOOGLEFINANCE(CONCATENATE("TPE:", $A{}), "changepct") / 100'.format(rowNum)
value[7] = '=GOOGLEFINANCE(CONCATENATE("TPE:", $A{}), "volume") / 1000'.format(rowNum)
value[8] = '=GOOGLEFINANCE(CONCATENATE("TPE:", $A{}), "pe")'.format(rowNum)
elif stockIdMap.get(value[0], "") == "":
print("{} 非上市上櫃不支援".format(value[0]))
lineTool.lineNotify(notifyLineToken, "{} 非上市上櫃目前不支援".format(value[0]))
# 其實應該只要更新時間欄位就好，其他欄位不要再更新，但我懶的再改了，之後再說
googlesheetService.updateSheet(sheetName, rowList)
if msg != '':
print("notify msg => {}".format(msg), flush=True)
lineTool.lineNotify(notifyLineToken, msg)
out = cv2.VideoWriter('result.avi', fourcc, 20.0, (1024, 576))
if cap.isOpened() is False:
print("Error opening video stream or file")
else:
cap.set(cv2.CAP_PROP_POS_MSEC, (frame_cnt*85))#可擷取到32個frames
ret_val, img = cap.read()
image = rotate(img, 90)
while ret_val:
if frame_idx > 31:
#檢查是否要發出Line求救
if frame_idx > 51:
if whether_to_notify(state_history, frame_idx):
lineTool.lineNotify(token, "老人家跌倒了")
state_history.clear()
state_history = [0]*frame_idx
else:
state_history.append(0)
#載入最新32幀的骨架
action_predict = np.zeros([1, 32, 36])
start_idx = frame_idx - 32
for i in range(32):
action_predict[0, i, :] = action_history[start_idx+i]
#預測
result = model.predict(action_predict)
print('Predict:', result)
c = np.argmax(result)
print('Action :', c)
if c < 2:
row.append(td.text)
# print(row)
rowList.append(row)
with open("ShowSaleMonChart_{}.csv".format(stockId),
"w",
encoding="utf-8",
newline="") as f1:
cw = csv.writer(f1)
cw.writerows(rowList)
# def readFile(stockId):
#
# with open("StockDirectorSharehold_{}.csv".format(stockId), "r", encoding="utf-8", newline="") as f1:
# rowList = list(csv.reader(f1))
#
# for row in rowList:
#
# if int(row[0].split("/")[0]) >= 2016:
# print(row[0], row[12], row[13], row[14], row[15], row[16])
# # print(row[0], row[7], row[8], row[9], row[10], row[11])
if __name__ == "__main__":
try:
main()
except:
traceback.print_exc()
lineTool.lineNotify(os.environ["LINE_TEST_TOKEN"],
"fetchShowSaleMonChart error")
def notifyMe(text):
lineTool.lineNotify('2D7IaxfEThWOFQJUu6Wpp8kliclIW1o7C0VaDCiaR7V',
text) # 自己的測試 token
def linePush(msg):
lineTool.lineNotify(token, msg)
text = "\n\n"
text += composeLineText(fetchPrice("0056"), 24, 26)
time.sleep(2)
text += "\n\n"
text += composeLineText(fetchPrice("2890"), 9.0, 9.6)
time.sleep(2)
text += "\n\n"
text += composeLineText(fetchPrice("2891"), 19, 24)
time.sleep(2)
text += "\n\n"
text += composeLineText(fetchPrice("2880"), 14.8, 16)
time.sleep(2)
text += "\n\n"
text += composeLineText(fetchPrice("2881"), 35, 60)
time.sleep(2)
text += "\n\n"
text += composeLineText(fetchPrice("2882"), 35, 50)
time.sleep(2)
print(text)
# price2890 = fetchPrice("2890")
# text += "2890 現在價格 : " + str(price2890) +"，目標 : 9.6"
# if price2890 >= 9.6:
# text += "### YES, sale it !"
#
# text += "\n"
token = os.environ["LINE_TEST_TOKEN"]
lineNotify(token, text)
"User-Agent" : "Chrome/31.0.1650.63"
}
r = requests.get(url, headers=headers)
r.encoding = "utf-8"
if "查無除權息日程訊息" in r.text:
return rowList
if "您的瀏覽量異常, 已影響網站速度" in r.text:
lineTool.lineNotify(os.environ["LINE_TEST_TOKEN"], "fetchStockDividendSchedule too fast to be blocked")
soup = BeautifulSoup(r.text, "html.parser")
trs = soup.find("table", {"class": "solid_1_padding_4_3_tbl"}).findAll("tr", id=re.compile("^row"))
for tr in trs:
row = []
for td in tr.findAll("td"):
row.append(td.text)
rowList.append(row)
return rowList
if __name__ == "__main__":
try:
main()
except:
traceback.print_exc()
lineTool.lineNotify(os.environ["LINE_TEST_TOKEN"], "fetchStockDividendSchedule error")
rowList = []
for tr in soup.find("table", {"class": "h4"}).findAll("tr"):
tdList = tr.findAll("td")
# 過濾掉不是明細的 tr
if tdList[0].text.strip(
) == '有價證券代號及名稱' or tdList[0].get("colspan") != None:
continue
sid = tdList[0].text.strip().split(" ")[0].strip()
sname = tdList[0].text.strip().split(" ")[1].strip()
isinCode = tdList[1].text.strip()
onDate = tdList[2].text.strip()
marketType = tdList[3].text.strip()
saleCode = tdList[4].text.strip()
cfiCode = tdList[5].text.strip()
row = [sid, sname, isinCode, onDate, marketType, saleCode, cfiCode]
rowList.append(row)
return rowList
if __name__ == '__main__':
try:
main()
except Exception as e:
traceback.print_exc()
msg = traceback.format_exc()
lineTool.lineNotify(os.environ["LINE_TEST_TOKEN"], msg)
r.encoding = "utf-8"
soup = BeautifulSoup(r.text, "html.parser")
# get all row data
rowList = []
trs = soup.findAll("tr", id=re.compile("^row"))
for tr in trs:
row = []
for td in tr.findAll("td"):
row.append(td.text)
rowList.append(row)
with open("StockDirectorSharehold_{}.csv".format(stockId),
"w",
encoding="utf-8",
newline="") as f1:
cw = csv.writer(f1)
cw.writerows(rowList)
if __name__ == "__main__":
try:
main()
except Exception as e:
print(e)
traceback.print_exc()
lineTool.lineNotify(os.environ["LINE_TEST_TOKEN"],
"fetchStockDirectorSharehold error")
lineTool.lineNotify(os.environ["LINE_TEST_TOKEN"], e)
def fetchStockInfo(self, stockId):
js = self.crawlStockInfo(stockId)
# {"userDelay":500,"rtmessage":" ","rtcode":"0000"}
if js["rtcode"] == "0000" and js["rtmessage"] != "OK":
print("response 0000 but rtmessage:[{}], sleep and try again...".
format(js["rtmessage"]))
time.sleep(5)
js = self.crawlStockInfo(stockId)
print(js)
if js["rtcode"] == "0000" and js["rtmessage"] != "OK":
print("response 0000 but rtmessage:[{}], sleep and try again...".
format(js["rtmessage"]))
time.sleep(5)
js = self.crawlStockInfo(stockId)
print(js)
# 不知道為什麼，有些就是會暫時沒資料
if js["rtcode"] == "0000" and js["rtmessage"] == "OK" and len(
js["msgArray"]) == 0:
lineTool.lineNotify(os.environ["LINE_TEST_TOKEN"],
"{} 查詢成功卻無資料".format(stockId))
print("查詢成功卻無資料")
return
if js["rtcode"] == "0000" and js["rtmessage"] == "OK" and js[
"msgArray"][0].get("o", "") == '':
lineTool.lineNotify(os.environ["LINE_TEST_TOKEN"],
"{} 查詢成功卻無資料".format(stockId))
print("查詢成功卻無開盤價格")
return
if not js["msgArray"][0]["d"] == datetime.datetime.now().strftime(
'%Y%m%d'):
print("查無今日資料不繼續處理檔案")
return
# 讀舊資料出來
rowDict = {}
with open("data/{}.csv".format(stockId), encoding="MS950") as f1:
for row in csv.reader(f1):
rowDict[row[0]] = row
# 先不考慮錯的時候，直接讓它丟出，最外面直接 line notify 錯誤
# if js["rtcode"] == "0000":
o = round(float(js["msgArray"][0]["o"]), 2)
h = round(float(js["msgArray"][0]["h"]), 2)
l = round(float(js["msgArray"][0]["l"]), 2)
z = round(float(js["msgArray"][0]["z"]), 2) # 現價
y = round(float(js["msgArray"][0]["y"]), 2) # 昨日價
v = int(js["msgArray"][0]
["v"]) * 1000 # 成交股數 (v 在這邊應該是張數，要自己 * 1000 才會變真實的股數)
dt = "{}/{}/{}".format(js["msgArray"][0]["d"][0:4],
js["msgArray"][0]["d"][4:6],
js["msgArray"][0]["d"][6:8])
diff = "+" + format(round(z - y, 2), ".2f") if z - y > 0 else format(
round(z - y, 2), ".2f")
row = [
dt, v,
int(v * z),
format(o, ".2f"),
format(h, ".2f"),
format(l, ".2f"),
format(z, ".2f"), diff, "", "", ""
]
rowDict[row[0]] = row
self.appendDataByRowList(stockId, rowDict)
