def __init__(self, sid: str, ndays: int):
Stock.__init__(self, sid)
# Init data
self.ndays = ndays
self.realtime = realtime.get(self.sid)
self.fetch_210()
self.bias_ratio()
def _load_daily_stock_price(stock_id, sleep=1): #-> Tuple
stock = Stock(str(stock_id))
date = stock.date[-1].strftime('%Y/%m/%d')
low_price = stock.low[-1]
high_price = stock.high[-1]
price = stock.price[-1]
latest_5_mv_avg_price = stock.moving_average(stock.price[-5:], days=5)[0]
if sleep:
time.sleep(sleep)
return (date, price, low_price, high_price, latest_5_mv_avg_price)
def fetch(twid='2330', csv="", start_time=None, end_time=datetime.now()):
if start_time == None:
start_time = datetime.strptime(start, "2010-1-1")
if csv == "":
csv = twid + ".csv"
stock = Stock(twid)
stock.fetch_from(int(start_time.strftime("%Y")),
int(start_time.strftime("%m")))
stock_to_googleCSV(stock, csv)
def echo(update, context):
query = update.message.text
ret = rtProvider.getStockInfo(query)
result_str = ret['ID'] + " " + ret['Name'] + "的即時股價: " + str(
ret['RealPrice'])
context.bot.send_message(chat_id=update.effective_chat.id, text=result_str)
ret['photo'].seek(0)
context.bot.send_photo(chat_id=update.effective_chat.id,
photo=ret['photo'])
stock = Stock(query)
tendayMA_str = ("5日線:%.2f" % stock.moving_average(stock.price, 5)[-1])
moMA_str = ("月線:%.2f" % stock.moving_average(stock.price, 20)[-1])
context.bot.send_message(chat_id=update.effective_chat.id,
text=tendayMA_str + "\n" + moMA_str)
def stock_query(code, temp):
stock = Stock(code)
x = twstock.realtime.get(code)
hour = datetime.now().hour + 8
if hour < 14 and hour >= 9:
change = round(
float(x['realtime']['latest_trade_price']) -
float(stock.price[-1]), 2)
else:
change = round(
float(x['realtime']['latest_trade_price']) -
float(stock.price[-2]), 2)
if change < 0:
color = '#2d8540'
elif change > 0:
color = '#F25702'
else:
color = '#111111'
temp['body']['contents'][2]['contents'][0]['contents'].append(
component(x['info']['code'], color))
temp['body']['contents'][2]['contents'][1]['contents'].append(
component(x['realtime']['latest_trade_price'], color))
temp['body']['contents'][2]['contents'][2]['contents'].append(
component(x['realtime']['open'], color))
temp['body']['contents'][2]['contents'][3]['contents'].append(
component(change, color))
temp['body']['contents'][2]['contents'][4]['contents'].append(
component(x['realtime']['high'], color))
temp['body']['contents'][2]['contents'][5]['contents'].append(
component(x['realtime']['low'], color))
return temp
def download(self):
self.result.setPlainText("Start from: " + str(self.StartTime.date().toPyDate())
+ " End to: "+ str(self.EndTime.date().toPyDate()) + '\r\n')
# print(self.result.getPaintContext())
stockNo = self.stockNoEdit.text()
stockItem = None
for key in self.stockInfo.keys():
for item in self.stockInfo[key]:
if (item.code == stockNo):
stockItem = item
print(stockItem)
self.dir = "./"+stockItem.group+"/"+stockItem.code+"_"+stockItem.name+ "/"
if (stockItem == None):
print("The stock is not exist!")
return
if re.match(r'^([\d]+)$', stockNo) != None:
# try:
proxyProvider = None
proxy_req_num=3
stock = Stock(stockNo,False)
Text = self.ProxyList.toPlainText().split()
# print(self.ProxyList.toPlainText().split())
proxy_list = []
# '''judge if input is an valid ip'''
for i,proxyip in enumerate(Text):
regx_ip = re.match(r'^\d+\.\d+\.\d+\.\d+:\d+$',proxyip)
if( regx_ip != None and [0<=int(x)<256 for x in re.split('[\.]',re.split(':', regx_ip.group(0))[0]) ].count(True)==4 ):
proxy_list.append(proxyip)
proxy_req_num = (len(proxy_list))
''' Get data '''
if (proxy_req_num !=0):
''' with proxy'''
proxyProvider = proxy.RoundRobinProxiesProvider(proxy_list)
if (proxy_req_num > 3):
proxy_req_num = 3
self.pool.apply_async(async_task, args=(stock,2020,8,proxyProvider,proxy_req_num),callback=self.async_finsh)
#
# tasks = asyncio.run( stock.async_fetch_from(2020, 3,proxyProvider,proxy_req_num))
else:
''' without proxy'''
i = 0
while 1:
date = self.StartTime.date().addMonths(i)
year = date.year()
month = date.month()
self.pool.apply_async(sync_task, args=(stock,year,month,True,),callback=self.finish)
if (self.EndTime.date().year() == year and self.EndTime.date().month() == month) :
break
i += 1
def complate_data(self, sid):
ret = False
last_date = self.date[-1]
stock = Stock(sid, initial_fetch=False)
fetch_from_date = mdates.num2date(last_date) + timedelta(-10)
stock.fetch_from(fetch_from_date.year, fetch_from_date.month)
col_num = len(self.raw[0]) # csv 檔的 column 數
append_str = ""
for index in range(0, col_num - 5):
append_str = append_str + ",0"
for index in range(-len(stock.date), 0):
d = stock.date[index]
o = stock.open[index]
h = stock.high[index]
l = stock.low[index]
c = stock.close[index]
if (mdates.date2num(d) > last_date):
str = "{0},{1},{2},{3},{4}".format(d.strftime('%Y/%m/%d'), o,
h, l, c)
print("資料回補：" + str)
f = open(self.filename, 'a+')
f.write(str + append_str + "\n")
f.close()
ret = True
#return ret # no yahoo
#yahoo 資料確認
# d,o,h,l,c = self.complete_data_yahoo(sid)
# #print(d,o,h,l,c)
# try:
# if(mdates.date2num(d) > mdates.date2num(stock.date[-1]) and mdates.date2num(d) > last_date ):
# str = "{0},{1},{2},{3},{4}".format(d.strftime('%Y/%m/%d'),o,h,l,c )
# print("資料回補 yahoo：" + str)
# f = open(self.filename, 'a+')
# f.write(str+append_str+"\n")
# f.close()
# ret = True
# except:
# print("Error 資料回補 yahoo：" + str)
# pass
# 有更新資料時，回傳True
return ret
def dump_updated_sid(dir_path, codes):
"""
stock = Stock('2330')
ma_p = stock.moving_average(stock.price, 5) # 計算五日均價
ma_c = stock.moving_average(stock.capacity, 5) # 計算五日均量
ma_p_cont = stock.continuous(ma_p) # 計算五日均價持續天數
ma_br = stock.ma_bias_ratio(5, 10) # 計算五日、十日乖離值
"""
for sid in codes:
print('code {}'.format(sid))
stock = Stock(sid)
stock.fetch_from(2018, 8)
# Data(date=datetime.datetime(2017, 5, 2, 0, 0), capacity=45851963, turnover=9053856108, open=198.5, high=199.0, low=195.5, close=196.5, change=2.0, transaction=15718)
sid2date2data = {}
for ins in stock.data:
sys.stdout.write('.')
date = ins.date.strftime('%Y%m%d')
open_p = ins.open
close_p = ins.close
high = ins.high
low = ins.low
change = ins.change
capacity = ins.capacity
transaction = ins.transaction
turnover = ins.turnover
if sid not in sid2date2data:
sid2date2data[sid] = {}
data = (high, low, open_p, close_p, change, capacity, transaction,
turnover)
sid2date2data[sid][date] = data
for sid in sid2date2data:
file_path = os.path.join(dir_path, '{}.csv'.format(sid))
with open(file_path, 'w') as w:
for date in sorted(sid2date2data[sid].keys()):
high, low, open_p, close_p, change, capacity, transaction, turnover = sid2date2data[
sid][date]
w.write(','.join(
map(str, [
sid, date, open_p, close_p, high, low, change,
capacity, transaction, turnover
])) + '\n')
print('')
def loadHistory(Code, startYear, startMonth, FinalYear, FinalMonth):
stock = Stock(str(Code))
monthList = list()
for year in range(startYear, FinalYear):
for month in range(1, 13):
stock.fetch(year, month)
for index in range(len(stock.data)):
newItem = list(stock.data[index])
newDate = newItem.pop(0)
newItem.insert(0, newDate.strftime("%Y-%m-%d"))
monthList.append(newItem)
time.sleep(3)
print("========================================================")
print("= Load ", year, " finish =")
print("========================================================")
i = 1 if FinalYear > startYear else startMonth
for month in range(i, FinalMonth + 1):
stock.fetch(FinalYear, month)
for index in range(len(stock.data)):
newItem = list(stock.data[index])
newDate = newItem.pop(0)
newItem.insert(0, newDate.strftime("%Y-%m-%d"))
monthList.append(newItem)
time.sleep(3)
print("========================================================")
print("= Load ", str(Code), " finish =")
print("========================================================")
return monthList
def test_load_historical_data_months(code, year, begin_month, end_month):
"""
Goal
----------
Download historical data and basic unit is one month.
Parameters
----------
code : int or str
year : int
begin_month : int
end_month : int
TODO
----------
1. Thinl trade suspension case
2.
"""
data_list = []
if begin_month > end_month:
return data_list
stock = Stock(str(code))
print("\n[" + str(code) + "]")
for month in range(begin_month, end_month+1):
time.sleep(5)
stock.fetch(year, month)
print(str(year) + '/' + str(month) + ' \tfinish')
for index in range(len(stock.data)):
new_data = list(stock.data[index])
new_data[0] = stock.data[index][0].strftime("%Y-%m-%d %H:%M:%S")
data_list.append(new_data)
#if (month) --- check is empty?
# 也有可能是停牌
# 回傳錯誤，並說明原因
return data_list
def main():
stock = Stock('2330') # 擷取
ma_p = stock.moving_average(stock.price, 5) # 計算五日均價
strma_p=str(ma_p)
ma_c = stock.moving_average(stock.capacity, 5) # 計算五日均量
strma_c=str(ma_c)
ma_p_cont = stock.continuous(ma_p) # 計算五日均價持續天數
strma_p_cont=str(ma_p_cont)
ma_br = stock.ma_bias_ratio(5, 10) # 計算五日、十日乖離值
strma_br=str(ma_br)
print ("計算五日均價", strma_p)
print ("計算五日均量", strma_c)
print ("計算五日均價持續天數", strma_p_cont)
print ("計算五日、十日乖離值", strma_br)
def get_data(ticker):
stock = Stock(ticker)
index = Stock('3056')
data = stock.fetch_from(n_yrs_ago.year, n_yrs_ago.month)
data_index = index.fetch_from(n_yrs_ago.year, n_yrs_ago.month)
s_close = []
tpe_index = []
for i in range(len(data)):
s_close.append(data[i][6])
tpe_index.append(data_index[i][6] * 500)
df_close = pd.DataFrame(s_close)
df_index = pd.DataFrame(tpe_index)
df_close_index = pd.DataFrame(list(zip(s_close, tpe_index)))
conv_to_csv(df_close, df_index, df_close_index, ticker)
frame = [df_close, df_index]
return frame
import DateAgoTest
import pandas as pd
import matplotlib.pyplot as plt
from talib import abstract
from twstock import Stock
stockID = '2330'
stock = Stock(stockID)
total = []
DList = DateAgoTest('2019-07', 7)
stockData = stock.fetch_from(2019, 7)
head = ["date", "capacity", "turnover", "open",
"high", "low", "close", "change", "transaction"]
for value in stockData:
day = str(value[0]).split()
if day[0] in DList:
total.append([day[0], value[1], value[2], value[3],
value[4], value[5], value[6], value[7], value[8])
df = pd.DataFrame(total, columns = head)
df.set_index('date', inplace = True)
df['close'].plot(figsize=(16, 8))
# import pandas as pd
# data = pd.read_csv("./stock_list.csv")
# stockNumberList = data['id']
# print(stockNumberList[3])
# exit()
from StockFunction import getStockList
stockList = getStockList()
exit()
from twstock import Stock
stock = Stock('2330') # 擷取台積電股價
ma_p = stock.moving_average(stock.price, 5) # 計算五日均價
ma_c = stock.moving_average(stock.capacity, 1) # 計算五日均量
ma_p_cont = stock.continuous(ma_p) # 計算五日均價持續天數
ma_br = stock.ma_bias_ratio(5, 10) # 計算五日、十日乖離值
# print(stock.data[-1])
print(ma_c)
exit()
from testHello import sample_func
sample_func()
exit()
import pandas as pd
from datetime import datetime
import twstock
from twstock import Stock
import time
from tqdm import tqdm
stock = Stock("2330")
time.sleep(2)
# 延遲兩秒
stock.fetch_from(2020, 5)
date = stock.date #日期
high_price = stock.high #盤中最高價
low_price = stock.low # 盤中最低價
close_price = stock.close #收盤價
open_price = stock.open # 開盤價
capacity = stock.capacity # 總成總成交股數
turnover = stock.turnover # 總成交金額
change = stock.change # 漲跌價差
transaction = stock.transaction # 成交筆數
day_number = len(date)
# 建立 和天數相符的 [0] list
day_list = []
day_list = [0] * day_number
#把取出的time 轉乘int 再存入day_list
for i in tqdm(range(day_number)):
def callback():
# get X-Line-Signature header value
signature = request.headers['X-Line-Signature']
# get request body as text
body = request.get_data(as_text=True)
app.logger.info("Request body: " + body + "1234")
# handle webhook body
try:
handler.handle(body, signature)
except InvalidSignatureError:
abort(400)
try:
events = parser.parse(body, signature)
except InvalidSignatureError:
print('InvalidSignatureError')
abort(400)
# if event is MessageEvent and message is TextMessage, then echo text
for event in events:
if not isinstance(event, MessageEvent):
continue
if not isinstance(event.message, TextMessage):
continue
text = event.message.text
#userId = event['source']['userId']
if (text.lower() == 'me'):
content = str(event.source.user_id)
line_bot_api.reply_message(event.reply_token,
TextSendMessage(text=content))
elif (text.lower() == 'profile'):
profile = line_bot_api.get_profile(event.source.user_id)
my_status_message = profile.status_message
if not my_status_message:
my_status_message = '-'
line_bot_api.reply_message(event.reply_token, [
TextSendMessage(text='Display name: ' + profile.display_name),
TextSendMessage(text='picture url: ' + profile.picture_url),
TextSendMessage(text='status_message: ' + my_status_message),
])
elif (text.startswith('$')):
text = text[1:]
content = ''
stock_rt = twstock.realtime.get(text)
my_datetime = datetime.fromtimestamp(stock_rt['timestamp'] +
8 * 60 * 60)
my_time = my_datetime.strftime('%H:%M:%S')
stock = Stock(text)
bfp = BestFourPoint(stock)
signal = bfp.best_four_point()
a = str(signal)
b = signal[0]
i4 = ImageSendMessage(
original_content_url="https://i.imgur.com/wUVUYYJ.jpg",
preview_image_url="https://i.imgur.com/wUVUYYJ.jpg")
i5 = ImageSendMessage(
original_content_url="https://i.imgur.com/mE50Pes.jpg",
preview_image_url="https://i.imgur.com/mE50Pes.jpg")
if b == True:
line_bot_api.reply_message(event.reply_token, i4)
if b == False:
line_bot_api.reply_message(event.reply_token, i5)
elif (text.startswith('#')):
text = text[1:]
content = ''
stock_rt = twstock.realtime.get(text)
my_datetime = datetime.fromtimestamp(stock_rt['timestamp'] +
8 * 60 * 60)
my_time = my_datetime.strftime('%H:%M:%S')
stock = Stock(text)
bfp = BestFourPoint(stock)
signal = bfp.best_four_point()
a = str(signal)
content += '%s (%s) %s\n' % (stock_rt['info']['name'],
stock_rt['info']['code'], my_time)
content += '現價: %s / 開盤: %s\n' % (
stock_rt['realtime']['latest_trade_price'],
stock_rt['realtime']['open'])
content += '最高: %s / 最低: %s\n' % (stock_rt['realtime']['high'],
stock_rt['realtime']['low'])
content += '量: %s\n' % (
stock_rt['realtime']['accumulate_trade_volume'])
content += '買賣訊號:%s\n' % (a)
stock = twstock.Stock(text) #twstock.Stock('2330')
content += '------------------------\n'
content += '最近五日價格: \n'
price5 = stock.price[-5:][::-1]
date5 = stock.date[-5:][::-1]
for i in range(len(price5)):
#content += '[%s] %s\n' %(date5[i].strftime("%Y-%m-%d %H:%M:%S"), price5[i])
content += '[%s] %s\n' % (date5[i].strftime("%Y-%m-%d"),
price5[i])
line_bot_api.reply_message(event.reply_token,
TextSendMessage(text=content))
elif (text.startswith('/')):
text = text[1:]
fn = '%s.png' % (text)
stock = twstock.Stock(text)
my_data = {
'close': stock.close,
'date': stock.date,
'open': stock.open
}
df1 = pd.DataFrame.from_dict(my_data)
df1.plot(x='date', y='close')
plt.title('[%s]' % (stock.sid))
plt.savefig(fn)
plt.close()
# -- upload
# imgur with account: [email protected]
client = ImgurClient(client_id, client_secret)
print("Uploading image... ")
image = client.upload_from_path(fn, anon=True)
print("Done")
url = image['link']
image_message = ImageSendMessage(original_content_url=url,
preview_image_url=url)
line_bot_api.reply_message(event.reply_token, image_message)
return 'OK'
sql = "INSERT INTO news (`code`,`date`,`title`,`url`,`logTime`) VALUES (%s,%s,%s,%s,%s)"
val = (code,date,title,url,datetime.datetime.now())
cursor.execute(sql, val)
conn.commit()
if count == MAX_COUNT:
break
else:
count = count + 1
print (date,title,url)
except:
if fail_count == MAX_FAIL_COUNT:
break
else:
fail_count = fail_count + 1
print ('insert failed')
time.sleep(3)
'''
if __name__ == '__main__':
cursor = conn.cursor()
code_list = []
sql = "SELECT distinct(code) FROM own"
cursor.execute(sql)
for row in cursor:
code = row[0]
stock = Stock(code)
week_ma = stock.moving_average(stock.price, 5)
month_ma = stock.moving_average(stock.price, 20)
season_ma = stock.moving_average(stock.price, 60)
print(code, week_ma[-1], month_ma[-1], season_ma[-1])
time.sleep(10)
if localtime.tm_mon < int(mon_span):
yrs = localtime.tm_year - 1
mon = 12 - (int(mon_span) - localtime.tm_mon)
else:
yrs = localtime.tm_year
mon = localtime.tm_mon
print(yrs, mon)
stock_num = input("Enter Stock: ")
for i in range(1, 6):
time.sleep(1)
print("Wait.... ", 5 - i, "second")
stock = Stock(stock_num)
print("First Stage complete ")
data = pd.DataFrame(stock.fetch_from(yrs, mon))
data.set_index('date', inplace=True)
data.index = data.index.format(formatter=lambda x: x.strftime('%Y-%m-%d'))
print("Fetching complete")
fig = plt.figure(figsize=(24, 16))
#用add_axes創建副圖框
ax = fig.add_axes([0.05, 0.25, 0.95, 0.75])
ax2 = fig.add_axes([0.05, 0.05, 0.95, 0.25])
ax.set_title(stock_num + "KChart", fontsize=12)
ax2.set_xticks(range(0, len(data.index), 10))
ax2.set_xticklabels(data.index[::10], rotation=0)
#使用mpl_finance套件
def close_price(stock_num):
stock = Stock(stock_num)
return stock.price
def capacity(stock_num):
stock = Stock(stock_num)
return math.floor(stock.capacity[-1] / 1000)
#!/usr/bin/env python3
import pandas as pd
import matplotlib.pyplot as plt
from talib import abstract
from twstock import Stock
stock = Stock('2330')
df = pd.DataFrame(stock.fetch_from(2019, 7))
df.set_index('date', inplace=True)
df['close'].plot(figsize=(16, 8))
plt.show()