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fugle_realtime_RESTful_api.py
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fugle_realtime_RESTful_api.py
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#!/usr/bin/env python
# coding: utf-8
# <h1>Table of Contents<span class="tocSkip"></span></h1>
# <div class="toc"><ul class="toc-item"></ul></div>
# In[2]:
from fugle_realtime import intraday
import pandas as pd
import numpy as np
import datetime
import requests
import dash
import dash_core_components as dcc
import dash_html_components as html
import dash_table
from dash.dependencies import Input, Output
import dash_daq as daq
# In[32]:
class chart_api():
def __init__(self, api_token):
self.api_token = api_token
def get_chart_data(self, n, symbol_id):
now = datetime.datetime.now()
today = now.strftime('%Y-%m-%d')
close_time = datetime.datetime(now.year,now.month,now.day, 13, 30)
time_index = pd.date_range(start=f'{today} 09:00:00',
end=f'{today} 13:30:00', 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 plot_ohlc(self, df, rise_color, down_color):
return {
'type':'candlestick',
'x':df['at'],
'open':df['open'],
'high':df['high'],
'low':df['low'],
'close':df['close'],
'name':'K線圖',
'increasing':{'line':{'color':rise_color}},
'decreasing':{'line':{'color':down_color}}
}
def plot_MA(self, df, n, line_color, line_width):
df[f'{n}MA'] = df['close'].rolling(n).mean()
return {
'type':'scatter',
'x':df['at'],
'y':df[f'{n}MA'],
'mode':'lines',
'line':{'color':line_color, 'width':line_width},
'name':f'{n}MA'
}
def plot_volume_bar(self, df, rise_color, down_color):
color = []
for i in range(len(df)):
try:
if df['close'][i] > df['open'][i]:
color.append(rise_color)
elif df['close'][i] < df['open'][i]:
color.append(down_color)
elif df['close'][i] == df['open'][i]:
if df['close'][i] > df['close'][i-1]:
color.append(rise_color)
elif df['close'][i] < df['close'][i-1]:
color.append(down_color)
elif df['close'][i] == df['close'][i-1]:
color.append(color[-1])
except (IndexError, KeyError):
color.append(rise_color)
return {
'type':'bar',
'x':df['at'],
'y':df['volume']/1000,
'marker':{'color':color},
'name':'volume_bar',
'xaxis':'x',
'yaxis':'y2'
}
# In[33]:
class quote_api():
def __init__(self, api_token):
self.api_token = api_token
def get_first_quote_data(self, symbol_id):
message = intraday.quote(apiToken= self.api_token, symbolId=symbol_id, output='raw')
ask = message['order']['bestAsks']
ask.reverse()
df_ask = pd.DataFrame(ask, columns=['price', 'unit']).rename(columns={'unit': 'ask_unit'})
bid = message['order']['bestBids']
bid.reverse()
df_bid = pd.DataFrame(bid, columns=['unit', 'price']).rename(
columns={'unit': 'bid_unit'})
df_quote = pd.merge(df_ask, df_bid, on='price', how='outer')
df_quote = df_quote[['bid_unit', 'price', 'ask_unit']]
price_list = list(df_quote['price'])
return df_quote, price_list
def get_new_quote_data(self,symbol_id, df_quote):
df_quote2, price_list = self.get_first_quote_data(symbol_id)
df_quote = pd.concat([df_quote, df_quote2], axis=0).drop_duplicates(subset='price', keep='last')
df_quote = df_quote.sort_values('price', ascending=False).reset_index(drop=True)
return df_quote, price_list
def update_quote_data(self, input_symbol):
global df_quote, symbol
try:
if input_symbol == symbol:
df_quote, price_list = self.get_new_quote_data(symbol, df_quote)
else:
symbol = input_symbol
df_quote, price_list = self.get_first_quote_data(symbol)
except:
symbol = input_symbol
df_quote, price_list = self.get_first_quote_data(symbol)
return df_quote, price_list, symbol
def plot_order_book(self, dataframe, price_list, symbol_id):
rows = []
for i in range(len(dataframe)):
row = []
for col in dataframe.columns:
value = dataframe.iloc[i][col]
if col == 'price':
if value not in price_list:
cell = html.Td(html.A(href='https://www.fugle.tw/ai/'+symbol_id,
children=value,
style={'color': 'gray'}),
style={'font-size': 16, 'text-align': 'center'})
elif value in price_list:
cell = html.Td(html.A(href='https://www.fugle.tw/ai/'+symbol_id,
children=value),
style={'font-size': 16, 'text-align': 'center'})
else:
cell = html.Td(children=value,
style={'font-size': 16, 'text-align': 'center'})
row.append(cell)
rows.append(html.Tr(row))
return html.Table(
[html.Tr([html.Th(col) for col in dataframe.columns],
style={'font-size': 16, 'text-align': 'center', 'table-align': 'center'})] + rows
)
# In[34]:
class line_notify():
def __init__(self, api_token, line_token):
self.api_token = api_token
self.line_token = line_token
def lineNotifyMessage(self, msg):
headers = {
"Authorization": "Bearer " + self.line_token,
"Content-Type" : "application/x-www-form-urlencoded"
}
payload = {'message': msg}
r = requests.post("https://notify-api.line.me/api/notify", headers = headers, params = payload)
return r.status_code
def target_price_strategy(self, symbol_id, rise_target_price, drop_target_price):
message = intraday.quote(apiToken= self.api_token, symbolId=symbol_id, output='raw')
current_price = message['trade']['price']
if current_price > rise_target_price:
self.lineNotifyMessage('快訊！' + symbol_id + '價格已經高過' + str(rise_target_price) + '元\n'+
'https://www.fugle.tw/trade?symbol_id=' + symbol_id + '&openExternalBrowser=1')
elif current_price < drop_target_price:
self.lineNotifyMessage('快訊！' + symbol_id + '價格已經跌破' + str(drop_target_price) + '元\n'+
'https://www.fugle.tw/trade?symbol_id=' + symbol_id + '&openExternalBrowser=1')
else:
pass
def target_change_strategy(self, symbol_id, rise_target_change, drop_target_change):
message = intraday.quote(apiToken=self.api_token, symbolId=symbol_id, output='raw')
current_price = message['trade']['price']
symbol_info = intraday.meta(symbolId= symbol_id, apiToken=self.api_token, output='raw')
adjust_open = symbol_info['priceReference']
if (current_price - adjust_open) / adjust_open > rise_target_change:
self.lineNotifyMessage('快訊！' + symbol_id + '漲幅已經高過' + str(rise_target_change*100) + '%\n'+
'https://www.fugle.tw/trade?symbol_id=' + symbol_id + '&openExternalBrowser=1')
elif (current_price - adjust_open) / adjust_open < -drop_target_change:
self.lineNotifyMessage('快訊！' + symbol_id + '跌幅已經低過' + str(drop_target_change*100) + '%\n'+
'https://www.fugle.tw/trade?symbol_id=' + symbol_id + '&openExternalBrowser=1')
else:
pass
return current_price, adjust_open