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intraday.py
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intraday.py
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import os
import requests
import pandas as pd
import datetime
import numpy as np
from utils import *
from io import StringIO, BytesIO
from selenium import webdriver
import execjs
import re
import bs4
dce_driver = None
driver_fut = None
driver_fut_open = False
driver_opt = None
driver_opt_open = False
################## CFFEX #################
def update_future_intraday_price_cffex():
se = requests.session()
CFFEX_HEADERS = {"User-Agent": "Mozilla/4.0 (compatible; MSIE 5.5; Windows NT)",
'Host': 'www.cffex.com.cn'}
URL1 = 'http://www.cffex.com.cn/quote_{}.txt'
URL2 = 'http://www.cffex.com.cn/yshqtz/hqtym/quoteDatas/{}_price.txt'
variety = 'IF'
url = URL1.format('IF')
r = se.get(url, headers=CFFEX_HEADERS)
f = StringIO(r.text)
table_df = pd.read_table(f, encoding="utf-8", sep=",")
inst_id = table_df.loc[0, 'instrument']
# get latest time
url = URL2.format(inst_id)
r = se.get(url, headers=CFFEX_HEADERS)
f = StringIO(r.text)
table_df = pd.read_table(f, encoding="utf-8", sep=",")
if len(table_df) > 0:
t = table_df.loc[len(table_df)-1, 'time']
else:
return None
dt = pd.to_datetime(t, format='%Y/%m/%d %H:%M')
t = dt.strftime('%Y-%m-%d %H:%M:%S')
for variety in exchange_dict['cffex']:
print(variety)
url = URL1.format(variety)
r = se.get(url, headers=CFFEX_HEADERS)
f = StringIO(r.text)
table_df = pd.read_table(f, encoding="utf-8", sep=",")
n = len(table_df)
c1 = ['time','index','index','index']
c1_add = ['c1','c2','c3','c4','c5','c6','c7','c8','c9']
c2 = ['time','close','vol','oi']
c2_add = ['inst_id','close','vol','oi']
null_data = [None,None,None,None]
for i in range(len(c1_add)):
for j in range(len(c2_add)): #
c1.append(c1_add[i])
c2.append(c2_add[j])
df = pd.DataFrame(columns=[c1, c2])
close = np.array(table_df['lastprice'], dtype=float)
volumn = np.array(table_df['volume'], dtype=float)
oi = np.array(table_df['position'], dtype=float)
nominator = 0
denominator = 0
for i in range(len(close)):
if not(np.isnan(close[i])):
nominator = nominator + close[i]*oi[i]
denominator = denominator + oi[i]
index_close = nominator/denominator
index_volumn = np.nansum(volumn)
index_oi = np.nansum(oi)
row = [t]
row += [index_close, index_volumn, index_oi]
if (n >= 9):
row += table_df[['instrument','lastprice','volume','position']].values.flatten().tolist()
else:
row += table_df[['instrument','lastprice','volume','position']].values.flatten().tolist()
for i in range(9-n):
row += null_data
df.loc[0] = row
path = os.path.join(future_price_dir, 'cffex', variety+'_intraday'+'.csv')
if os.path.exists(path):
old_df = pd.read_csv(path, header=[0,1])
old_df = pd.concat([old_df, df], axis=0)
old_df.drop_duplicates(subset=[('time','time')], keep='first', inplace=True) # last
old_df.loc[:, pd.IndexSlice['time','time']] = old_df.loc[:, pd.IndexSlice['time','time']].apply(lambda x:pd.to_datetime(x, format='%Y-%m-%d %H:%M:%S'))
old_df.sort_values(by = ('time','time'), inplace=True)
old_df.loc[:, pd.IndexSlice['time','time']] = old_df.loc[:, pd.IndexSlice['time','time']].apply(lambda x:datetime.datetime.strftime(x,'%Y-%m-%d %H:%M:%S'))
old_df.to_csv(path, encoding='utf-8', index=False)
else:
df.to_csv(path, encoding='utf-8', index=False)
return t
def update_option_intraday_price_cffex(t=None):
if t is None:
return
se = requests.session()
CFFEX_HEADERS = {"User-Agent": "Mozilla/4.0 (compatible; MSIE 5.5; Windows NT)",
'Host': 'www.cffex.com.cn'}
opt_variety_dict = {
'IF': 'IO',
'IH': 'HO',
'IM': 'MO',
}
opt_variety_dict_reverse = {
'IO': 'IF',
'HO': 'IH',
'MO': 'IM',
}
URL = 'http://www.cffex.com.cn/quote_{}.txt'
for variety in exchange_option_dict['cffex']:
opt_variety = opt_variety_dict[variety]
url = URL.format(opt_variety)
r = se.get(url, headers=CFFEX_HEADERS)
f = StringIO(r.text)
table_df = pd.read_table(f, encoding="utf-8", sep=",")
n = len(table_df)
# table_df.replace(opt_variety,variety,inplace=True)
info_df = pd.DataFrame(columns=['time', 'inst_ids'])
info_df.loc[0, 'time'] = t
inst_ids = np.array(table_df['instrument'], dtype=str)
table_df = table_df[['lastprice', 'volume', 'position']]
name_dict = {}
names = ''
for i in range((len(inst_ids))):
name = inst_ids[i][:6]
opt_variety = name[0:2]
opt_variety = opt_variety_dict_reverse[opt_variety]
name = opt_variety + name[2:]
if not(name in name_dict):
# 从 idx_offset 开始
name_dict[name] = [i, i]
names = names + name
names = names + ','
else:
name_dict[name][1] = name_dict[name][1] + 1
info_df.loc[0, 'inst_ids'] = names
print(name_dict)
for name in name_dict:
print(name)
col1 = ['time']
col2 = ['time']
col3 = ['time']
row = [t]
start_idx = name_dict[name][0]
end_idx = name_dict[name][1]
tmp = table_df.loc[name_dict[name][0]:name_dict[name][1], :]
row += tmp.values.flatten().tolist()
for k in range(start_idx, end_idx+1):
otype = inst_ids[k][7]
strike = inst_ids[k][9:]
col1 += [otype, otype, otype]
col2 += [strike, strike, strike]
col3 += ['close', 'volume', 'oi']
df = pd.DataFrame(columns=[col1, col2, col3], data=[row])
path = os.path.join(option_price_dir, 'cffex', name+'_intraday'+'.csv')
if os.path.exists(path):
old_df = pd.read_csv(path, header=[0,1,2])
old_df = pd.concat([old_df, df], axis=0)
old_df.drop_duplicates(subset=[('time','time','time')], keep='last', inplace=True) # last
old_df.loc[:, pd.IndexSlice['time','time','time']] = old_df.loc[:, pd.IndexSlice['time','time','time']].apply(lambda x:pd.to_datetime(x, format='%Y-%m-%d %H:%M:%S'))
old_df.sort_values(by = ('time','time','time'), inplace=True)
old_df.loc[:, pd.IndexSlice['time','time','time']] = old_df.loc[:, pd.IndexSlice['time','time','time']].apply(lambda x:datetime.datetime.strftime(x,'%Y-%m-%d %H:%M:%S'))
old_df.to_csv(path, encoding='utf-8', index=False)
else:
df.to_csv(path, encoding='utf-8', index=False)
path = os.path.join(option_price_dir, 'cffex', variety+'_intraday_info'+'.csv')
# print(df)
if os.path.exists(path):
old_df = pd.read_csv(path)
old_df = pd.concat([old_df, info_df], axis=0)
old_df.drop_duplicates(subset=['time'], keep='last', inplace=True)
old_df['time'] = old_df['time'].apply(lambda x:pd.to_datetime(x, format='%Y-%m-%d %H:%M:%S'))
old_df.sort_values(by = 'time', inplace=True)
old_df['time'] = old_df['time'].apply(lambda x:datetime.datetime.strftime(x,'%Y-%m-%d %H:%M:%S'))
old_df.to_csv(path, encoding='utf-8', index=False)
else:
info_df.to_csv(path, encoding='utf-8', index=False)
############### DCE #################
def dce_delay_data_time():
now = datetime.datetime.now()
hour = now.hour
minute = now.minute
if (hour < 9):
dt = None
elif (hour == 9) and (minute <= 1):
dt = None
elif (hour == 10) and ((minute >= 15) and (minute <= 31)):
dt = None
elif (hour == 11) and (minute >= 30)and (minute < 35):
dt = datetime.datetime(year=now.year, month=now.month, day=now.day, hour=11, minute=30, second=0)
elif (hour == 11) and (minute >= 35):
dt = None
elif (hour == 12) or ((hour == 13) and (minute <= 31)):
dt = None
elif (hour == 15) and (minute < 5):
dt = datetime.datetime(year=now.year, month=now.month, day=now.day, hour=15, minute=0, second=0)
elif (hour >= 15) and (hour < 21):
dt = None
elif (hour == 21) and (minute <= 1):
dt = None
elif (hour >= 23) and (minute <= 10):
dt = datetime.datetime(year=now.year, month=now.month, day=now.day, hour=23, minute=0, second=0)
elif (hour >= 23) and (minute > 10):
dt = None
else:
dt = datetime.datetime(year=now.year, month=now.month, day=now.day, hour=now.hour, minute=now.minute, second=0) - pd.Timedelta(minutes=1)
if dt is not None:
t = dt.strftime('%Y-%m-%d %H:%M:%S')
else:
t = None
return t
# DCE_COOKIES = {
# 'AUjhoZgfrTo9S': '60g97GuRAliDmpSlcqitlWQ6u6bH9WLIYJabCYlf1MU89guLVOLM6Ss90NLdrdW3yvly1YJfUYbLpIq7QhbdlOAa',
# 'AUjhoZgfrTo9T': '0cHMtCMnEmWIpqsKDZAC47C3p.kN7HeTsvXqfN3YmBs5FdhtRKLgOpR02M3iXKxXPx5EKXxjpOxnRNpEQWNeFK.N3rYtqc0Ri6QA2qBEZJt7vttw0g1Nfb7TuVQti1MOVZH7TMFuSmlSDG2LdcPNx9.wEwCtQMOydq3Ui0q4rwKzSKGtEkQw7gg2VZp1qA_b8jHntG9F4afniD74B2xN4_ReFxT5Hd2MietiPD_hw9AAdATl97w4C5HKVuS1Ckckmlb08bACqnWlhENefaBuPOyE9N4FiJEZ7rOJNDjt5CrTVgvilMb8bze6r0gbiOXgUXMNpuceOzEJv_V0ATpMOXu8hFyw5uXekYM.75m1VL0Qws8SeXeAdGMIzMeFfQTq4dD9gMhbM82KAIQeUEzpkx_NPWpR0hzz2QXCQzA9VrxpOm7KJH.MNA.SLWR3ics7X',
# 'JSESSIONID': 'EB7BCF287377176EEEAD0F43495853D9',
# 'UqZBpD3n3iTGAwBS': 'v1pZY5Jc6c4cC',
# 'UqZBpD3n3iTPAABS': "v1pZY5JSyg0o0",
# 'UqZBpD3n3iXPAw1X9DmY+0mqerc8xLAdPYGU69E_':"v13OMuiUWB0xP-NzVn2Wre5l7i7yA",
# 'VlRBYr90kaK9S':"5rv6fUftXJ_s3KZ6IKmRhN4PqEk1KWo6CM6qt73vB1H0EIckiPYjtzaX0jNSBCIjpFrwh1TL2MR6zlVPsYanmJG",
# 'WMONID':"Vt4L0yAYPmh",
# }
def update_future_intraday_price_dce():
global dce_driver
se = requests.session()
t = dce_delay_data_time()
DCE_HEADERS = {"User-Agent": "User-Agent Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:106.0) Gecko/20100101 Firefox/106.0",
'Host': 'www.dce.com.cn',
'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,*/*;q=0.8',
}
if t is not None:
for variety in exchange_dict['dce']:
url = 'http://www.dce.com.cn/webquote/futures_quote_ajax?varietyid='+variety
# 'Mozilla/4.0 (compatible; MSIE 5.5; Windows NT)'
while (1):
try:
r = se.get(url, headers=DCE_HEADERS)
data_json = r.json()
# print(data_json)
temp_df = pd.DataFrame(data_json['contractQuote'])
temp_df.loc['lastPrice',:].replace('--', None, inplace=True)
temp_df.loc['matchTotQty',:].replace('--', '0', inplace=True)
temp_df.loc['openInterest',:].replace('--', '0', inplace=True)
print(variety)
break
except Exception as e:
# fuck dce
dce_driver.get('http://www.dce.com.cn/webquote/futures_quote_ajax?varietyid='+'a')
cookie = dce_driver.get_cookies()
print('FUCK DCE')
c = ''
for i in range(len(cookie)):
c += cookie[i]['name']
c += '='
c += cookie[i]['value']
c += ';'
DCE_HEADERS['Cookie'] = c
print(c)
time.sleep(3)
cols = temp_df.columns.tolist()
n = len(cols)
c1 = ['time','index','index','index']
c1_add = ['c1','c2','c3','c4','c5','c6','c7','c8','c9']
c2 = ['time','close','vol','oi']
c2_add = ['inst_id','close','vol','oi']
null_data = [None,None,None,None]
for i in range(len(c1_add)):
for j in range(len(c2_add)): #
c1.append(c1_add[i])
c2.append(c2_add[j])
df = pd.DataFrame(columns=[c1, c2])
close = np.array(temp_df.loc['lastPrice', :], dtype=float)
volumn = np.array(temp_df.loc['matchTotQty', :], dtype=float)
oi = np.array(temp_df.loc['openInterest', :], dtype=float)
nominator = 0
denominator = 0
for i in range(len(close)):
if not(np.isnan(close[i])):
nominator = nominator + close[i]*oi[i]
denominator = denominator + oi[i]
index_close = nominator/denominator
index_volumn = np.nansum(volumn)
index_oi = np.nansum(oi)
row = [t]
row += [index_close, index_volumn, index_oi]
if (n >= 9):
for i in range(9):
row += temp_df.loc[['contractID','lastPrice','matchTotQty','openInterest'], cols[i]].values.tolist()
else:
for i in range(n):
row += temp_df.loc[['contractID','lastPrice','matchTotQty','openInterest'], cols[i]].values.tolist()
for i in range(9-n):
row += null_data
df.loc[0] = row
path = os.path.join(future_price_dir, 'dce', variety+'_intraday'+'.csv')
if os.path.exists(path):
old_df = pd.read_csv(path, header=[0,1])
old_df = pd.concat([old_df, df], axis=0)
old_df.drop_duplicates(subset=[('time','time')], keep='first', inplace=True) # last
old_df.loc[:, pd.IndexSlice['time','time']] = old_df.loc[:, pd.IndexSlice['time','time']].apply(lambda x:pd.to_datetime(x, format='%Y-%m-%d %H:%M:%S'))
old_df.sort_values(by = ('time','time'), inplace=True)
old_df.loc[:, pd.IndexSlice['time','time']] = old_df.loc[:, pd.IndexSlice['time','time']].apply(lambda x:datetime.datetime.strftime(x,'%Y-%m-%d %H:%M:%S'))
old_df.to_csv(path, encoding='utf-8', index=False)
else:
df.to_csv(path, encoding='utf-8', index=False)
return t
def update_option_intraday_price_dce(se=None, t=None):
global dce_driver
if se is None:
se = requests.session()
if t is None:
print('DCE t is None')
return
DCE_HEADERS = {'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,*/*;q=0.8',
"User-Agent": "User-Agent Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:106.0) Gecko/20100101 Firefox/106.0",
'Host': 'www.dce.com.cn',
}
for variety in exchange_option_dict['dce']:
url = 'http://www.dce.com.cn/webquote/option_quote.jsp?varietyid='+variety
# 'Mozilla/4.0 (compatible; MSIE 5.5; Windows NT)'
# 'User-Agent Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:106.0) Gecko/20100101 Firefox/106.0'
while(1):
try:
r = se.get(url, headers=DCE_HEADERS, timeout=10)
soup = bs4.BeautifulSoup(r.text, 'html.parser')
trs = soup.find_all('select', attrs={'id':"contractselect"})
namelist = []
for tr in trs:
tds = tr.find_all('option')
for td in tds:
namelist.append(td.get_text())
if len(namelist) == 0:
raise('DCE')
break
except Exception as e:
print('DCE OPTION INTRADAT ERROR 1', e)
# fuck dce
dce_driver.get('http://www.dce.com.cn/webquote/futures_quote_ajax?varietyid='+'a')
cookie = dce_driver.get_cookies()
print('FUCK DCE')
c = ''
for i in range(len(cookie)):
c += cookie[i]['name']
c += '='
c += cookie[i]['value']
c += ';'
DCE_HEADERS['Cookie'] = c
time.sleep(5)
print(namelist)
inst_ids = ''
for name in namelist:
inst_ids += name
inst_ids += ','
if len(inst_ids) == 0:
continue
info_df = pd.DataFrame(columns=['time', 'inst_ids'], data=[[t, inst_ids]])
for name in namelist:
url = 'http://www.dce.com.cn/webquote/option_quote_ajax?varietyid='+'variety'+'&contractid='+name
while(1):
try:
print(name)
r = se.get(url, headers=DCE_HEADERS, timeout=10)
data_json = r.json()
temp_df = pd.DataFrame(data_json['optionQuote'])
break
except Exception as e:
print('DCE OPTION INTRADAT ERROR 2', e)
# fuck dce
dce_driver.get('http://www.dce.com.cn/webquote/futures_quote_ajax?varietyid='+'a')
cookie = dce_driver.get_cookies()
print('FUCK DCE')
c = ''
for i in range(len(cookie)):
c += cookie[i]['name']
c += '='
c += cookie[i]['value']
c += ';'
DCE_HEADERS['Cookie'] = c
time.sleep(5)
col1 = ['time']
col2 = ['time']
col3 = ['time']
row = [t]
if len(temp_df) > 0:
temp_df.loc['matchCTotQty',:].replace('--', '0', inplace=True)
temp_df.loc['matchPTotQty',:].replace('--', '0', inplace=True)
temp_df.loc['openCInterest',:].replace('--', '0', inplace=True)
temp_df.loc['openPInterest',:].replace('--', '0', inplace=True)
temp_df.loc['lastCPrice',:].replace('--', None, inplace=True)
temp_df.loc['lastPPrice',:].replace('--', None, inplace=True)
strikes = temp_df.columns.tolist()
for strike in strikes:
col1 += ['C', 'C', 'C']
col2 += [strike, strike, strike]
col3 += ['close', 'volume', 'oi']
row += [temp_df.loc['lastCPrice', strike], temp_df.loc['matchCTotQty', strike], temp_df.loc['openCInterest', strike]]
col1 += ['P', 'P', 'P']
col2 += [strike, strike, strike]
col3 += ['close', 'volume', 'oi']
row += [temp_df.loc['lastPPrice', strike], temp_df.loc['matchPTotQty', strike], temp_df.loc['openPInterest', strike]]
df = pd.DataFrame(columns=[col1, col2, col3], data=[row])
path = os.path.join(option_price_dir,'dce', name+'_intraday'+'.csv')
if os.path.exists(path):
old_df = pd.read_csv(path, header=[0,1,2])
old_df = pd.concat([old_df, df], axis=0)
old_df.drop_duplicates(subset=[('time','time','time')], keep='last', inplace=True) # last
old_df.loc[:, pd.IndexSlice['time','time','time']] = old_df.loc[:, pd.IndexSlice['time','time','time']].apply(lambda x:pd.to_datetime(x, format='%Y-%m-%d %H:%M:%S'))
old_df.sort_values(by = ('time','time','time'), inplace=True)
old_df.loc[:, pd.IndexSlice['time','time','time']] = old_df.loc[:, pd.IndexSlice['time','time','time']].apply(lambda x:datetime.datetime.strftime(x,'%Y-%m-%d %H:%M:%S'))
old_df.to_csv(path, encoding='utf-8', index=False)
else:
df.to_csv(path, encoding='utf-8', index=False)
path = os.path.join(option_price_dir, 'dce', variety+'_intraday_info'+'.csv')
# print(df)
if os.path.exists(path):
info_df.to_csv(path, mode='a', encoding='utf-8', index=False, header=None)
else:
info_df.to_csv(path, encoding='utf-8', index=False)
################## gfex ##################
def gfex_delay_data_time():
now = datetime.datetime.now()
hour = now.hour
minute = now.minute
if (hour < 9):
dt = None
elif (hour == 9) and (minute <= 1):
dt = None
elif (hour == 10) and ((minute >= 15) and (minute <= 31)):
dt = None
elif (hour == 11) and (minute >= 35):
dt = None
elif (hour == 12) or ((hour == 13) and (minute <= 31)):
dt = None
elif (hour == 15) and (minute <= 10):
dt = datetime.datetime(year=now.year, month=now.month, day=now.day, hour=15, minute=0, second=0)
elif (hour >= 15):
dt = None
else:
dt = datetime.datetime(year=now.year, month=now.month, day=now.day, hour=now.hour, minute=now.minute, second=0) - pd.Timedelta(minutes=1)
if dt is not None:
t = dt.strftime('%Y-%m-%d %H:%M:%S')
else:
t = None
return t
def update_future_intraday_price_gfex():
se = requests.session()
t = gfex_delay_data_time()
# t = '2022-12-12 09:09:09'
if t is not None:
for variety in exchange_dict['gfex']:
url = 'http://www.gfex.com.cn/gfexweb/Quote/getQuote_ftr'
GFEX_HEADERS = {"User-Agent": "Mozilla/4.0 (compatible; MSIE 5.5; Windows NT)",
'Host': 'www.gfex.com.cn'}
payload = {
"varietyid": variety,
}
while(1):
try:
r = se.post(url, headers=GFEX_HEADERS, data=payload)
data_json = r.json()
break
except Exception as e:
print('GFEX FUTURE INTRADAT ERROR 2', e)
time.sleep(5)
# print(data_json)
temp_df = pd.DataFrame(data_json['contractQuote'])
temp_df.loc['lastPrice',:].replace('--', None, inplace=True)
temp_df.loc['matchTotQty',:].replace('--', '0', inplace=True)
temp_df.loc['openInterest',:].replace('--', '0', inplace=True)
print(variety)
cols = temp_df.columns.tolist()
n = len(cols)
c1 = ['time','index','index','index']
c1_add = ['c1','c2','c3','c4','c5','c6','c7','c8','c9']
c2 = ['time','close','vol','oi']
c2_add = ['inst_id','close','vol','oi']
null_data = [None,None,None,None]
for i in range(len(c1_add)):
for j in range(len(c2_add)): #
c1.append(c1_add[i])
c2.append(c2_add[j])
df = pd.DataFrame(columns=[c1, c2])
close = np.array(temp_df.loc['lastPrice', :], dtype=float)
volumn = np.array(temp_df.loc['matchTotQty', :], dtype=float)
oi = np.array(temp_df.loc['openInterest', :], dtype=float)
nominator = 0
denominator = 0
for i in range(len(close)):
if not(np.isnan(close[i])):
nominator = nominator + close[i]*oi[i]
denominator = denominator + oi[i]
index_close = nominator/denominator
index_volumn = np.nansum(volumn)
index_oi = np.nansum(oi)
row = [t]
row += [index_close, index_volumn, index_oi]
if (n >= 9):
for i in range(9):
row += temp_df.loc[['contractID','lastPrice','matchTotQty','openInterest'], cols[i]].values.tolist()
else:
for i in range(n):
row += temp_df.loc[['contractID','lastPrice','matchTotQty','openInterest'], cols[i]].values.tolist()
for i in range(9-n):
row += null_data
df.loc[0] = row
path = os.path.join(future_price_dir, 'gfex', variety+'_intraday'+'.csv')
if os.path.exists(path):
old_df = pd.read_csv(path, header=[0,1])
old_df = pd.concat([old_df, df], axis=0)
old_df.drop_duplicates(subset=[('time','time')], keep='first', inplace=True) # last
old_df.loc[:, pd.IndexSlice['time','time']] = old_df.loc[:, pd.IndexSlice['time','time']].apply(lambda x:pd.to_datetime(x, format='%Y-%m-%d %H:%M:%S'))
old_df.sort_values(by = ('time','time'), inplace=True)
old_df.loc[:, pd.IndexSlice['time','time']] = old_df.loc[:, pd.IndexSlice['time','time']].apply(lambda x:datetime.datetime.strftime(x,'%Y-%m-%d %H:%M:%S'))
old_df.to_csv(path, encoding='utf-8', index=False)
else:
df.to_csv(path, encoding='utf-8', index=False)
return t
def update_option_intraday_price_gfex(se=None, t=None):
if se is None:
se = requests.session()
if t is None:
print('GFEX t is None')
return
for variety in exchange_option_dict['gfex']:
url = 'http://www.gfex.com.cn/gfexweb/Variety/getVariety_all'
GFEX_HEADERS = {"User-Agent": "Mozilla/4.0 (compatible; MSIE 5.5; Windows NT)",
'Host': 'www.gfex.com.cn'}
payload = {
"varietyid": variety,
}
while(1):
try:
r = se.post(url, headers=GFEX_HEADERS, data=payload)
data_json = r.json()
namelist = data_json["contractIDList"]
break
except Exception as e:
print('GFEX OPTION INTRADAT ERROR 1', e)
time.sleep(5)
inst_ids = ''
for name in namelist:
inst_ids += name
inst_ids += ','
info_df = pd.DataFrame(columns=['time', 'inst_ids'], data=[[t, inst_ids]])
for name in namelist:
print(name)
url = 'http://www.gfex.com.cn/gfexweb/Quote/getQuote_opt'
payload = {
"contractid": name,
}
while(1):
try:
r = se.post(url, headers=GFEX_HEADERS, data=payload)
data_json = r.json()
temp_df = pd.DataFrame(data_json['optionQuote'])
break
except Exception as e:
print('GFEX OPTION INTRADAT ERROR 2', e)
time.sleep(5)
if (len(temp_df) == 0):
continue
temp_df.loc['matchCTotQty',:].replace('--', '0', inplace=True)
temp_df.loc['matchPTotQty',:].replace('--', '0', inplace=True)
temp_df.loc['openCInterest',:].replace('--', '0', inplace=True)
temp_df.loc['openPInterest',:].replace('--', '0', inplace=True)
temp_df.loc['lastCPrice',:].replace('--', None, inplace=True)
temp_df.loc['lastPPrice',:].replace('--', None, inplace=True)
strikes = temp_df.columns.tolist()
col1 = ['time']
col2 = ['time']
col3 = ['time']
row = [t]
for strike in strikes:
col1 += ['C', 'C', 'C']
col2 += [strike, strike, strike]
col3 += ['close', 'volume', 'oi']
row += [temp_df.loc['lastCPrice', strike], temp_df.loc['matchCTotQty', strike], temp_df.loc['openCInterest', strike]]
col1 += ['P', 'P', 'P']
col2 += [strike, strike, strike]
col3 += ['close', 'volume', 'oi']
row += [temp_df.loc['lastPPrice', strike], temp_df.loc['matchPTotQty', strike], temp_df.loc['openPInterest', strike]]
df = pd.DataFrame(columns=[col1, col2, col3], data=[row])
path = os.path.join(option_price_dir,'gfex', name+'_intraday'+'.csv')
if os.path.exists(path):
old_df = pd.read_csv(path, header=[0,1,2])
old_df = pd.concat([old_df, df], axis=0)
old_df.drop_duplicates(subset=[('time','time','time')], keep='last', inplace=True) # last
old_df.loc[:, pd.IndexSlice['time','time','time']] = old_df.loc[:, pd.IndexSlice['time','time','time']].apply(lambda x:pd.to_datetime(x, format='%Y-%m-%d %H:%M:%S'))
old_df.sort_values(by = ('time','time','time'), inplace=True)
old_df.loc[:, pd.IndexSlice['time','time','time']] = old_df.loc[:, pd.IndexSlice['time','time','time']].apply(lambda x:datetime.datetime.strftime(x,'%Y-%m-%d %H:%M:%S'))
old_df.to_csv(path, encoding='utf-8', index=False)
else:
df.to_csv(path, encoding='utf-8', index=False)
path = os.path.join(option_price_dir, 'gfex', variety+'_intraday_info'+'.csv')
# print(df)
if os.path.exists(path):
info_df.to_csv(path, mode='a', encoding='utf-8', index=False, header=None)
else:
info_df.to_csv(path, encoding='utf-8', index=False)
def update_future_intraday_price(exchange, se=None):
global driver_fut_open
if se is None:
se = requests.session()
if exchange == 'shfe':
now = datetime.datetime.now()
if (now.hour == 21) and (now.minute <= 1):
return None
url = 'https://www.shfe.com.cn/statements/delaymarket_all.html'
SHFE_HEADERS = {"User-Agent": "Mozilla/4.0 (compatible; MSIE 5.5; Windows NT)"}
r = se.get(url, headers=SHFE_HEADERS)
temp_df = pd.read_html(r.text)[0]
cols = temp_df.columns.tolist()
L = len(cols)
t = temp_df.loc[0, cols[L-1]][:19]
dt = pd.to_datetime(t, format='%Y-%m-%d %H:%M:%S')
hour = dt.hour
minute = dt.minute
if (hour > 2 and hour < 9):
dt = datetime.datetime(year=dt.year, month=dt.month, day=dt.day, hour=2, minute=30, second=0)
if (hour >= 15 and hour < 20):
dt = datetime.datetime(year=dt.year, month=dt.month, day=dt.day, hour=15, minute=0, second=0)
t = dt.strftime('%Y-%m-%d %H:%M:%S')
print(t)
cols = temp_df.loc[1, :].tolist()
temp_df = temp_df.loc[2:, :]
temp_df.columns = cols
temp_df = temp_df[['合约名称', '最新价', '成交量', '持仓量']]
temp_df.rename(columns={'合约名称':'inst_id', '最新价':'close', '成交量':'vol', '持仓量':'oi'}, inplace=True)
temp_df.reset_index(inplace=True, drop=True)
inst_ids = np.array(temp_df['inst_id'], dtype=str)
name_dict = {}
for i in range((len(inst_ids))):
if (inst_ids[i][2].isdigit()):
name = inst_ids[i][:2]
else:
name = inst_ids[i][0]
if not(name in name_dict):
# start_idx, end_idx
name_dict[name] = [i, i]
else:
name_dict[name][1] = i
print(name_dict)
c1 = ['time','index','index','index']
c1_add = ['c1','c2','c3','c4','c5','c6','c7','c8','c9']
c2 = ['time','close','vol','oi']
c2_add = ['inst_id','close','vol','oi']
null_data = [None,None,None,None]
for i in range(len(c1_add)):
for j in range(len(c2_add)): #
c1.append(c1_add[i])
c2.append(c2_add[j])
for name in name_dict:
df = pd.DataFrame(columns=[c1, c2])
row = [t]
n = name_dict[name][1] + 1 - name_dict[name][0]
# 指数合约数据
tmp = temp_df.loc[name_dict[name][0]:name_dict[name][1], :]
close = np.array(tmp['close'], dtype=float)
volumn = np.array(tmp['vol'], dtype=float)
oi = np.array(tmp['oi'], dtype=float)
# 指数合约代码
index_oi = np.sum(oi)
if (index_oi > 0):
nominator = 0
denominator = 0
for i in range(len(close)):
if not(np.isnan(close[i])):
nominator = nominator + close[i]*oi[i]
denominator = denominator + oi[i]
index_close = nominator/denominator
index_volumn = np.sum(volumn)
row += [index_close, index_volumn, index_oi]
else:
row += [0, 0, 0]
if (n >= 9):
# 有至少9个合约
row += (tmp.loc[name_dict[name][0]:name_dict[name][0]+8]).values.flatten().tolist()
elif (n > 0):
# 不足9个合约
row += (tmp.loc[name_dict[name][0]:name_dict[name][0]+n-1]).values.flatten().tolist()
for _ in range(9-n):
row += null_data
df.loc[0] = row
path = os.path.join(future_price_dir, exchange, name+'_intraday'+'.csv')
if os.path.exists(path):
old_df = pd.read_csv(path, header=[0,1])
old_df = pd.concat([old_df, df], axis=0)
old_df.drop_duplicates(subset=[('time','time')], keep='first', inplace=True) # last
old_df.loc[:, pd.IndexSlice['time','time']] = old_df.loc[:, pd.IndexSlice['time','time']].apply(lambda x:pd.to_datetime(x, format='%Y-%m-%d %H:%M:%S'))
old_df.sort_values(by = ('time','time'), inplace=True)
old_df.loc[:, pd.IndexSlice['time','time']] = old_df.loc[:, pd.IndexSlice['time','time']].apply(lambda x:datetime.datetime.strftime(x,'%Y-%m-%d %H:%M:%S'))
old_df.to_csv(path, encoding='utf-8', index=False)
else:
df.to_csv(path, encoding='utf-8', index=False)
elif exchange == 'czce':
global option
global driver
now = datetime.datetime.now()
if (now.hour < 9) or (now.hour == 23 and now.minute >= 10):
return None
url = 'http://www.czce.com.cn/cn/DFSStaticFiles/Future/Quotation/ChineseFutureQuotation.htm'
CZCE_HEADERS = {"User-Agent": "User-Agent Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:106.0) Gecko/20100101 Firefox/106.0",
'Host': 'www.czce.com.cn',
'Connection': 'keep-alive',
'Referer': 'http://www.czce.com.cn/cn/wzxx/yshq/qhyshq/H77070401index_1.htm',
'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,*/*;q=0.8',
}
while (1):
try:
# r = se.get(url, headers=CZCE_HEADERS)
# print(r.status_code)
# temp_df = pd.read_html(r.content)[0]
if driver_fut_open == False:
driver_fut.get('http://www.czce.com.cn/cn/DFSStaticFiles/Future/Quotation/ChineseFutureQuotation.htm')
driver_fut.refresh()
html = driver_fut.page_source
driver_fut_open = True
temp_df = pd.read_html(StringIO(html))[0]
break
except Exception as e:
print(e)
time.sleep(5)
L = len(temp_df)
t = temp_df.loc[L-1, '卖盘量']
dt = pd.to_datetime(t, format='%Y-%m-%d %H:%M:%S')
hour = dt.hour
minute = dt.minute
if (hour < 9):
dt = datetime.datetime(year=dt.year, month=dt.month, day=dt.day, hour=2, minute=30, second=0)
return None
if (hour >= 15 and hour < 20):
dt = datetime.datetime(year=dt.year, month=dt.month, day=dt.day, hour=15, minute=0, second=0)
return None
if (hour >= 23 and minute < 10):
return None
t = dt.strftime('%Y-%m-%d %H:%M:%S')
print(t)
temp_df = temp_df[['合约', '最新价', '成交量(手)', '持仓量']]
temp_df.rename(columns={'合约':'inst_id', '最新价':'close', '成交量(手)':'vol', '持仓量':'oi'}, inplace=True)
temp_df['close'] = temp_df['close'].replace('0',None)
inst_ids = np.array(temp_df['inst_id'], dtype=str)
name_dict = {}
for i in range((len(inst_ids))):
if len(inst_ids[i]) > 2:
if (inst_ids[i][2].isdigit()):
name = inst_ids[i][:2]
else:
name = inst_ids[i][0]
if not(name in name_dict):
# start_idx, end_idx
name_dict[name] = [i, i]
else:
name_dict[name][1] = i
print(name_dict)
c1 = ['time','index','index','index']
c1_add = ['c1','c2','c3','c4','c5','c6','c7','c8','c9']
c2 = ['time','close','vol','oi']
c2_add = ['inst_id','close','vol','oi']
null_data = [None,None,None,None]
for i in range(len(c1_add)):
for j in range(len(c2_add)): #
c1.append(c1_add[i])
c2.append(c2_add[j])
for name in name_dict:
df = pd.DataFrame(columns=[c1, c2])
row = [t]
n = name_dict[name][1] + 1 - name_dict[name][0]
# 指数合约数据
tmp = temp_df.loc[name_dict[name][0]:name_dict[name][1], :]
close = np.array(tmp['close'], dtype=float)
volumn = np.array(tmp['vol'], dtype=float)
oi = np.array(tmp['oi'], dtype=float)
index_oi = np.sum(oi)
if (index_oi > 0):
nominator = 0
denominator = 0
for i in range(len(close)):
if not(np.isnan(close[i])):
nominator = nominator + close[i]*oi[i]
denominator = denominator + oi[i]
index_close = nominator/denominator
index_volumn = np.sum(volumn)
row += [index_close, index_volumn, index_oi]
else:
row += [0, 0, 0]
if (n >= 9):
# 有至少9个合约
row += (tmp.loc[name_dict[name][0]:name_dict[name][0]+8]).values.flatten().tolist()
elif (n > 0):
# 不足9个合约
row += (tmp.loc[name_dict[name][0]:name_dict[name][0]+n-1]).values.flatten().tolist()
for _ in range(9-n):
row += null_data
# 有些品种没有夜盘
if index_volumn > 1:
df.loc[0] = row
path = os.path.join(future_price_dir, 'czce', name+'_intraday'+'.csv')
if os.path.exists(path):
old_df = pd.read_csv(path, header=[0,1])
old_df = pd.concat([old_df, df], axis=0)
old_df.drop_duplicates(subset=[('time','time')], keep='first', inplace=True) # last
old_df.loc[:, pd.IndexSlice['time','time']] = old_df.loc[:, pd.IndexSlice['time','time']].apply(lambda x:pd.to_datetime(x, format='%Y-%m-%d %H:%M:%S'))
old_df.sort_values(by = ('time','time'), inplace=True)
old_df.loc[:, pd.IndexSlice['time','time']] = old_df.loc[:, pd.IndexSlice['time','time']].apply(lambda x:datetime.datetime.strftime(x,'%Y-%m-%d %H:%M:%S'))
old_df.to_csv(path, encoding='utf-8', index=False)
else:
df.to_csv(path, encoding='utf-8', index=False)
elif exchange == 'dce':
t = update_future_intraday_price_dce()
return t
def update_option_intraday_price(exchange, t=None, se=None):
global driver_opt_open
if se is None:
se = requests.session()
if exchange == 'cffex':
n1 = 0
n2 = 6
n3 = 7
n4 = 9
elif exchange == 'shfe':
n1 = 0
n2 = 6
n3 = 6
n4 = 7
elif exchange == 'czce':
n1 = 0
n2 = 5
n3 = 5
n4 = 6
elif exchange == 'gfex':
n1 = 0
n2 = 6
n3 = 7
n4 = 9
if exchange == 'shfe':
if t is None:
return
vars = ['cu','au','ag','al','zn','ru','rb','sc','br']
URL = 'https://www.shfe.com.cn/statements/delaymarket_{}Option.html'
SHFE_HEADERS = {"User-Agent": "Mozilla/4.0 (compatible; MSIE 5.5; Windows NT)"}
for var in vars:
print('OPTION INTRADAY: ', var)
url = URL.format(var)
while (1):
try:
r = se.get(url, headers=SHFE_HEADERS)
temp_df = pd.read_html(r.text)[0]
if len(temp_df) > 3:
break
except Exception as e:
print(e, 'OPTION INTRADAY ERROR: ', var)
time.sleep(5)
cols = temp_df.columns.tolist()
L = len(cols)
if t is None:
t = temp_df.loc[0, cols[L-1]][:19]
print(t)
dt = pd.to_datetime(t, format='%Y-%m-%d %H:%M:%S')
hour = dt.hour
minute = dt.minute
if ((hour >= 3 and hour < 9)):
dt = datetime.datetime(year=dt.year, month=dt.month, day=dt.day, hour=2, minute=30, second=0)