def getStockInfo(self, id):
ret = dict()
output_meta = intraday.meta(apiToken=self.apiToken,
output="dataframe",
symbolId=id)
output_chart = intraday.chart(apiToken=self.apiToken,
output="dataframe",
symbolId=id)
ref_price = output_meta.iloc[
0, output_meta.columns.get_loc("priceReference")]
current_price = output_chart.iloc[
-1, output_chart.columns.get_loc("close")]
if ref_price > current_price:
graph = output_chart.plot(x="at", y='close', color='green')
elif ref_price == current_price:
graph = output_chart.plot(x="at", y='close', color='gray')
else:
graph = output_chart.plot(x="at", y='close', color='red')
graph.axhline(ref_price,
linestyle='dashed',
color='xkcd:dark grey',
alpha=0.6,
label='參考價',
marker='')
graph.legend().set_visible(False)
fig = graph.get_figure()
buf = io.BytesIO()
fig.savefig(buf, format='png')
ret['Name'] = output_meta.iloc[0,
output_meta.columns.get_loc("nameZhTw")]
ret['RealPrice'] = current_price
ret['ID'] = id
ret['photo'] = buf
return ret
def get_stock_info(self, num):
data = intraday.meta(apiToken=self.config['FUGLE']['fugle_TOKEN'] , symbolId=num , output='raw')
# data = intraday.meta(apiToken=Bot.config['FUGLE']['fugle_TOKEN'] , symbolId='0050', output='raw')
df1 = intraday.chart(apiToken=self.config['FUGLE']['fugle_TOKEN'] , symbolId=num)
# df1 = intraday.chart(apiToken=Bot.config['FUGLE']['fugle_TOKEN'] , symbolId='0050')
if 'error' in df1.columns:
return '請輸入正確的股票代碼：'
elif df1.shape[0] == 0:
if 'nameZhTw' not in data:
text = 'api 無回應'
elif 'industryZhTw' in data:
text = "【{}({})】 \n⦁ 產業: {} \n⦁ 開盤股價: {} \n⦁ 昨日漲停價: {} \n⦁ 昨日跌停價: {} ".format(
data['nameZhTw'],
num,
data['industryZhTw'],
data['priceReference'],
data['priceHighLimit'],
data['priceLowLimit']
)
else:
text = "【{}({})】 \n⦁ 開盤股價: {} \n⦁ 昨日漲停價: {} \n⦁ 昨日跌停價: {} ".format(
data['nameZhTw'],
num,
data['priceReference'],
data['priceHighLimit'],
data['priceLowLimit']
)
return text
else:
df1 = df1.iloc[-1]
if 'industryZhTw' in data:
text = "【{}({})】 \n⦁ 產業: {} \n⦁ 當前股價: {} \n⦁ 今日漲跌: {}({}%) ".format(
data['nameZhTw'],
num,
data['industryZhTw'],
df1['close'],
round(df1['close']-data['priceReference'], 2),
round(((df1['close']-data['priceReference'])/data['priceReference'])*100, 2)
)
else:
text = "【{}({})】 \n⦁ 當前股價: {} \n⦁ 今日漲跌: {}({}%) ".format(
data['nameZhTw'],
num,
df1['close'],
round(df1['close']-data['priceReference'], 2),
round(((df1['close']-data['priceReference'])/data['priceReference'])*100, 2)
)
return text
def info(bot, update):
global num
num = update.message.text
data = intraday.meta(apiToken=api_token, symbolId=num, output='raw')
'''對話框按鈕'''
global reply_markup
reply_markup = InlineKeyboardMarkup([[
InlineKeyboardButton('基本資訊', callback_data='info'),
InlineKeyboardButton('最新一筆交易', callback_data='trade'),
]])
'''輸入id，且判斷id是否存在'''
if 'id' in num:
if int(num[2:]) not in userdata().df['userid']:
update.message.reply_text('ID%s 不存在' % (num[2:]))
else:
update.message.reply_text('登入成功 ID：%s，請輸入欲查詢的股票代碼：' % (num[2:]))
userdata().write(update.message.chat.id, num[2:])
elif 'error' in intraday.chart(apiToken=api_token,
symbolId='2330').columns:
'''直接輸入股票代碼'''
update.message.reply_text('請輸入正確的股票代碼：')
else:
df1 = intraday.chart(apiToken=api_token, symbolId=num)
df1 = df1.iloc[-1]
text = ('•' + data['nameZhTw'] + '(' + num + ')\t\t' + '股價：' +
str(df1['close']) + '\t\t' + '漲跌：' +
str(data['priceReference'] - df1['close']) + '\t(' + str(
round(((data['priceReference'] - df1['close']) /
data['priceReference']) * 100, 2)) + '%)')
bot.send_message(
update.message.chat.id,
text + '\n\n' +
'{} 您還可以查詢：'.format(update.message.from_user.first_name),
reply_to_message_id=update.message.message_id,
reply_markup=reply_markup)
def serv_share_num(self, keyword, msg_received):
"""
To find out the latest price by share number.
"""
print('【serv_share_num】')
# Check whether is previous action
if msg_received == None:
share_no = keyword
else:
share_no = msg_received.split('{}'.format(keyword))[1]
# Collect data from FUGLE API
share_data = intraday.chart(apiToken=FUGLE_API_TOKEN,
symbolId='{}'.format(share_no),
output='raw')
# Template for Share detail
try:
share_date_time = list(share_data.keys())[-1]
share_res = share_data[share_date_time]
share_res_date_time = share_date_time.split('T')
text = "【{} 最新資訊】\n\
🔺行業類別：{}\n\
🔺日期：{}\n\
🔺時間：{}\n\
🔺開盤價：{}\n\
🔺收盤價：{}\n\
🔺最高價：{}\n\
🔺最低價：{}\n\
🔺交易張數：{}\n\
🔺交易量：{}\n " .format(share_no, \
self.share_db[share_no], \
share_res_date_time[0], \
share_res_date_time[1].split('.')[0], \
share_res['open'], \
share_res['close'], \
share_res['high'], \
share_res['low'], \
share_res['unit'], \
share_res['volume'])
except:
text = "非常抱歉，菜雞能力不及 😥，請重新輸入有效股票代號！"
self.prev_action = "serv_share_num"
self.out_msg = self.temp_msg = text
self.temp_share_no = share_no
success = self.send_message()
return success
def get_chart_data(self, n, symbol_id):
# Last Friday
# now = datetime.datetime.now() + relativedelta(weekday=FR(-1))
now = datetime.datetime.now()
today = now.strftime('%Y-%m-%d')
close_time = datetime.datetime(now.year, now.month, now.day, 12, 00)
time_index = pd.date_range(start=f'{today} 09:00:00',
end=f'{today} 12:00:00',
freq=f'{n}T',
closed='right')
df_time = pd.DataFrame(time_index, columns=['at'])
df = intraday.chart(symbolId=symbol_id,
apiToken=self.api_token,
output='dataframe')
df['at'] = df['at'].apply(
lambda x: x.astimezone(None) + datetime.timedelta(hours=8))
df = df.set_index('at')
df = df.asfreq('1T')
df['close'] = df['close'].fillna(method='ffill')
df['volume'] = df['volume'].fillna(0)
df = df.fillna(axis=1, method='ffill')
df = df[['open', 'high', 'low', 'close', 'volume']]
df_ohlc = df.resample(f'{n}T', kind='period').agg({
'open': 'first',
'high': 'max',
'low': 'min',
'close': 'last',
'volume': 'sum'
})
df_ohlc.index = df_ohlc.index + datetime.timedelta(minutes=n - 1)
df_ohlc = df_ohlc.to_timestamp().reset_index()
df_ohlc = pd.merge(df_time, df_ohlc, on='at', how='outer')
df_ohlc['at'] = df_ohlc['at'].apply(lambda x: x
if x <= close_time else close_time)
return df_ohlc
def open_close(bot, update):
a_data = intraday.chart(apiToken=api_token, symbolId=str(aa[0]))
aaa = str(a_data.tail(1)["open"])
bb = aaa.split(sep=' ')[1]
o = bb.split(sep="N")[0]
aab = str(a_data.tail(1)["close"])
bb1 = aab.split(sep=' ')[1]
o1 = bb.split(sep="N")[0]
oc = "開盤價:" + o
oc1 = "收盤價:" + o1
print(oc)
print(oc1)
update.message.reply_text(oc)
update.message.reply_text(oc1)
def fugle_realtime(api_token, twii, model, ss, freq="15T", lookback=10000):
from fugle_realtime import intraday
if twii.index.tzinfo is None:
twii.index = twii.index.tz_localize("Asia/Taipei")
df = intraday.chart(apiToken=api_token,
output="dataframe",
symbolId="TWSE_SEM_INDEX_1")
df.index = df['at']
df.index = df.index.tz_convert("Asia/Taipei")
df = df.resample(freq).first()
twii_temp = twii.append(df.close).iloc[-lookback:]
features = create_features(twii_temp).dropna()
if len(features) == 0:
print("fail! please increase lookback period")
y = model.predict(ss.transform(features))
return pd.DataFrame({
'twii': twii_temp.loc[features.index].values,
'model': y.reshape(1, len(y))[0]
})
# external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
# app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
# app.layout = html.Div(children=[
# html.Div(id='quote_table'),
# dcc.Interval(
# id='interval-component',
# interval=5000,
# n_intervals=1
# ),
# ])
# @app.callback(
# Output('quote_table', 'children'),
# [Input('interval-component', 'n_intervals')])
# def table(interval_component):
# fugle.update_data()
# return html.Div([
# fugle.message_table()
# ])
# if __name__ == '__main__':
# app.run_server()
from fugle_realtime import intraday
intraday.chart(apiToken="demo", output="dataframe", symbolId="2884")
print(df)
FUGLE_API_TOKEN = os.environ.get('FUGLE_API_TOKEN')
sender = TelegramSender()
buy_list = []
while True:
for index, row in df.iterrows():
time.sleep(1.2)
sid = df.at[index, 'sid']
name = df.at[index, 'name']
ma_5 = df.at[index, '5ma']
ma_10 = df.at[index, '10ma']
ma_20 = df.at[index, '20ma']
try:
print("Checking {} {}".format(sid, name))
stock_df = intraday.chart(symbolId=sid, apiToken=FUGLE_API_TOKEN)
price = stock_df['close'].values[-1]
if price > max([ma_5, ma_10, ma_20]):
if sid not in buy_list:
buy_list.append(sid)
text = "突破均線糾結: {} {} price now: {}".format(sid, name, price)
sender.send_message(text)
except KeyError:
print("An error occur: {} {}".format(sid, name))
continue
def test_intraday_chart():
chart = intraday.chart()
assert type(chart) is DataFrame
def test_intraday_chart_output_raw():
chart = intraday.chart(output="raw")
assert type(chart) is dict
def test_intraday_chart_output_dataframe():
chart = intraday.chart(output="dataframe")
assert type(chart) is DataFrame
def test_intraday_chart_output():
with raises(ValueError) as excinfo:
intraday.chart(output="")
assert excinfo.type is ValueError
assert str(excinfo.value) == 'output must be one of ["dataframe", "raw"]'
