def collect_index_china_full():
conn = ts.get_apis()
collect_single_index_from_ts('000001', conn=conn)
collect_single_index_from_ts('399001', conn=conn)
collect_single_index_from_ts('000300', conn=conn)
collect_single_index_from_ts('000905', conn=conn)
ts.close_apis(conn)
def plot_stock_line(code, name, table_name, start='2017-10-01', save=False):
today = datetime.datetime.now().strftime('%Y-%m-%d')
title = u'{} {} {} {}'.format(today, code, name, table_name)
if os.path.exists(title + '.png'):
return
engine = get_engine('db_stock', local=True)
fig = plt.figure(figsize=(10, 8))
base_info = pd.read_sql('tb_basic_info', engine, index_col='index')
# fig,(ax,ax2)=plt.subplots(2,1,sharex=True,figsize=(16,10))
ax = fig.add_axes([0, 0.3, 1, 0.55])
ax2 = fig.add_axes([0, 0.1, 1, 0.25])
if code is None and name is not None:
code = base_info[base_info['name'] == name]['code'].values[0]
print code
df = None
for _ in range(4):
api = ts.get_apis()
try:
df = ts.bar(code, conn=api, start_date=start)
break
except Exception, e:
print e
ts.close_apis(api)
time.sleep(random.random() * 3)
continue
def gjzq(file):
df = pd.read_table(file, encoding='gbk', dtype={'证券代码': np.str})
del df['Unnamed: 15']
code_list = list(df['证券代码'].values)
api = ts.get_apis()
# 移除非法证券代码 中签
t=[code_list.remove(i) for i in code_list.copy() if i.startswith('7') or i[:2] == '07']
price_df = ts.quotes(code_list, conn=api)
# 去除不合法的数据
price_df=price_df.dropna()
filter_df = price_df[price_df['last_close'] != 0]
filter_df = filter_df.reset_index(drop=True)
filter_df['percent'] = (filter_df['price'] - filter_df['last_close']) / filter_df['last_close'] * 100
filter_df['percent'] = filter_df['percent'].map(lambda x: round(x, 2))
ret_df = filter_df[(filter_df['percent'] > ALERT_PERCENTAGE) | (filter_df['percent'] < ALERT_PERCENTAGE*-1)]
d = dict(zip(list(df['证券代码'].values), list(df['证券名称'])))
ret_df['name']=ret_df['code'].map(lambda x:d.get(x))
ret_df['amount']=ret_df['amount'].map(lambda x:round(x/10000,1))
rename_column = {'code':'证券代码','name':'证券名称','price':'当前价格','percent':'涨幅','amount':'成交金额(万)'}
ret_df=ret_df.rename(columns=rename_column)
ret = ret_df[list(rename_column.values())]
ret=ret.reset_index(drop=True)
# 发送推送
print(ret)
ts.close_apis(api)
def stock_plot():
left, width = 0.1, 0.8
rect_vol = [left, 0.1, width, 0.3]
rect_main = [left, 0.4, width, 0.5]
fig = plt.figure()
conn = ts.get_apis()
df = ts.bar('300333', conn=conn, start_date='2018-01-01')
del df['code']
df.reset_index(inplace=True)
dates=df['datetime'].values
df['datetime'] = df['datetime'].map(mdates.date2num)
# dates=df['datetime'].values
vol = df['vol'].values
ax_vol = fig.add_axes(rect_vol)
ax_vol.fill_between(dates, vol,color = 'y')
# 横坐标时间旋转
plt.setp(ax_vol.get_xticklabels(), rotation=30, horizontalalignment='right')
ax_main = fig.add_axes(rect_main)
candlestick_ochl(ax_main,df.values,width=0.6,colordown='g',colorup='r')
ax_main.axes.get_xaxis().set_visible(False)
ax_main.set_title("STOCK LINE")
ts.close_apis(conn)
plt.show()
def start():
#获取连接备用
cons = ts.get_apis()
# 导入个股
print("导入个股")
# codes,names,timeToMarket = importStockList()
# codes = ["000801"]
# names = ["四川九洲"]
# timeToMarket = [20171215]
#000002.SZ errcode: -40521008 start_date:1993-01-23,end_date:1993-01-26
codes = ["300251"]
names = ["万科A"]
timeToMarket = [19910102]
print(len(codes), len(names), len(timeToMarket))
importStockDataDailyWind(codes, names, timeToMarket)
# test(codes)
'''
#导入指数
print("导入指数")
df = ts.get_index()
codes = df["code"].values
names = df["name"].values
import import_Stock_Data_Daily
import_Stock_Data_Daily.importStockDataDaily(codes,names,asset='INDEX',adj='None')
'''
ts.close_apis(conn=cons)
print("导入完成")
def fetch(code_list):
tsconn = ts.get_apis()
sqlconn = db.connect()
cursor = sqlconn.cursor()
try:
for code in code_list:
try:
data = ts.bar(code,
conn=tsconn,
start_date="1970-01-01",
freq="5min")
count = data.shape[0]
i = 0
for index, row in data.iterrows():
cursor.execute(
"insert into stock_price (code, time, price) values (%s, %s, %s)",
(code, str(index), float(row["close"])))
i += 1
if i % 1000 == 0:
print("{0} {1}%".format(code, int(i / count * 100)))
sqlconn.commit()
print("done")
except IOError as err:
print(code)
print(err)
finally:
sqlconn.close()
ts.close_apis(tsconn)
def monitor(self):
self.has_sent_kzz = dict(zip(self.kzz_code, [datetime.datetime.now()] * len(self.kzz_code)))
self.has_sent_diff = dict(zip(self.kzz_code, [datetime.datetime.now()] * len(self.kzz_code)))
self.has_sent_zg = dict(zip(self.zg_code, [datetime.datetime.now()] * len(self.zg_code)))
while 1:
current = trading_time()
# current=0
if current == MARKET_OPENING:
self.get_realtime_info(self.kzz_code, self.has_sent_kzz, '转债', self.kzz_stocks, self.kzz_stocks_yjl,
ZZ_ALERT_PERCENT)
self.get_realtime_info(self.zg_code, self.has_sent_zg, '正股', self.zg_stocks, self.zg_stocks_yjl,
ZG_ALERT_PERCENT)
self.get_price_diff(self.kzz_code, self.has_sent_diff, '差价')
time.sleep(LOOP_TIME)
elif current == -1:
time.sleep(LOOP_TIME)
elif current == 1:
try:
ts.close_apis(self.api)
except Exception as e:
logger.info('fail to stop monitor {}'.format(datetime.datetime.now()))
logger.info(e)
exit(0)
def stock_plot():
left, width = 0.1, 0.8
rect_vol = [left, 0.1, width, 0.3]
rect_main = [left, 0.4, width, 0.5]
fig = plt.figure()
conn = ts.get_apis()
df = ts.bar('300333', conn=conn, start_date='2018-01-01')
del df['code']
df.reset_index(inplace=True)
dates = df['datetime'].values
df['datetime'] = df['datetime'].map(mdates.date2num)
# dates=df['datetime'].values
vol = df['vol'].values
ax_vol = fig.add_axes(rect_vol)
ax_vol.fill_between(dates, vol, color='y')
# 横坐标时间旋转
plt.setp(ax_vol.get_xticklabels(),
rotation=30,
horizontalalignment='right')
ax_main = fig.add_axes(rect_main)
candlestick_ochl(ax_main, df.values, width=0.6, colordown='g', colorup='r')
ax_main.axes.get_xaxis().set_visible(False)
ax_main.set_title("STOCK LINE")
ts.close_apis(conn)
plt.show()
def update_daily(self):
add_cols = u'ALTER TABLE `{}` ADD `{}` FLOAT;'.format(
self.table_name, self.today)
self._exe(add_cols)
# self.conn.commit()
api = ts.get_apis()
cmd = 'SELECT * FROM `{}`'.format(self.table_name)
cur = self._exe(cmd)
for i in cur.fetchall():
(code, name, safe_price, count, profit_ratio, profit, values,
current_price, earn) = i[:9]
df = ts.quotes(code, conn=api)
current_price = round(float(df['price'].values[0]), 2)
values = current_price * count
last_close = df['last_close'].values[0]
earn = (current_price - last_close) * count
profit = (current_price - safe_price) * count
profit_ratio = round(
float(current_price - safe_price) / safe_price * 100, 2)
update_cmd = u'UPDATE {} SET `盈亏比例`={} ,`盈亏`={}, `市值` ={}, `现价` = {},`{}`={} where `证券代码`= {};'.format(
self.table_name, profit_ratio, profit, values, current_price,
self.today, earn, code)
# print update_cmd
self._exe(update_cmd)
ts.close_apis(api)
def monitor(self):
self.has_sent_kzz = dict(zip(self.kzz_code, [datetime.datetime.now()] * len(self.kzz_code)))
self.has_sent_diff = dict(zip(self.kzz_code, [datetime.datetime.now()] * len(self.kzz_code)))
self.has_sent_zg = dict(zip(self.zg_code, [datetime.datetime.now()] * len(self.zg_code)))
while 1:
current = trading_time()
# current=0
if current == MARKET_OPENING:
self.get_realtime_info(self.kzz_code, self.has_sent_kzz, '转债', self.kzz_stocks, self.kzz_stocks_yjl,
ZZ_ALERT_PERCENT)
self.get_realtime_info(self.zg_code, self.has_sent_zg, '正股', self.zg_stocks, self.zg_stocks_yjl,
ZG_ALERT_PERCENT)
self.get_price_diff(self.kzz_code, self.has_sent_diff, '差价')
time.sleep(LOOP_TIME)
elif current == -1:
time.sleep(LOOP_TIME)
elif current == 1:
try:
ts.close_apis(self.api)
except Exception as e:
logger.info('fail to stop monitor {}'.format(datetime.datetime.now()))
logger.info(e)
exit(0)
def isXR(code=""):
global cons
shi_jian = gsd.get_code_min_shi_jian(code)
if shi_jian == "None":
return False
data = gsd.get_stock_data_daily_df_time(code=code,
start=shi_jian,
end=shi_jian)
price = data["price"].values[0]
tsFaile = 1
while tsFaile != 0:
try:
# print(code,shi_jian)
# if tsFaile >=2 :
# cons = ts.get_apis()
data = ts.bar(code,
conn=cons,
adj='qfq',
start_date=shi_jian,
end_date=shi_jian,
retry_count=2)
# print("data",data)
'''
if len(data["close"].values)<1 :
tsFaile += 1
else:
tsFaile = 0
'''
tsFaile = 0
if len(data["close"].values) < 1:
return False
except Exception as e:
#获取连接备用
ts.close_apis(conn=cons)
cons = ts.get_apis()
print(code, shi_jian, "isXR fail:", tsFaile, e)
time.sleep(5)
if tsFaile <= 3:
tsFaile += 1
else:
return False
# print(code,shi_jian)
# data = ts.bar(code, conn=cons, adj='qfq', start_date=shi_jian, end_date=shi_jian,retry_count = 20)
# print("data",data)
close = data["close"].values[0]
if price == close:
return False
else:
return True
def collect_hs300_full():
df = ts.get_hs300s()
conn = ts.get_apis()
#now = datetime.now().strftime('%Y-%m-%d')
for code in df['code'].values:
collect_single(code=code, conn=conn)
ts.close_apis(conn)
def main():
if ts.is_holiday(today):
ts.close_apis(cons)
exit()
else:
weekly_drop_rank(current=True) # 正常运行时current = True
ts.close_apis(cons)
def toDB_get_periodata(period):
start = datetime.datetime.now()
print(start)
global CONS
CONS = ts.get_apis()
if period == 'W':
freq = 'W'
table = 't_weekdata'
command = "ts.bar(row['code'], conn=CONS, freq=freq, start_date=key, end_date=value,adj = 'qfq',factors=['tor']).to_sql(table, c.ENGINE, if_exists='append')"
if period == 'M':
freq = 'M'
table = 't_monthdata'
command = "ts.bar(row['code'], conn=CONS, freq=freq, start_date=key, end_date=value, adj = 'qfq',factors=['tor']).to_sql(table, c.ENGINE, if_exists='append')"
try:
if (period == 'D'):
sql = "delete from t_daydata where datetime ='" + c.DATE + "'"
_excutesql(sql)
def tmp(con, sql):
if (con == 'CONN_SH'):
sql = "select code from T_StockBasics where code like '6%%' order by code"
if (con == 'CONN_SZ'):
sql = "select code from T_StockBasics where code like '0%%' order by code"
if (con == 'CONN'):
sql = "select code from T_StockBasics where code like '3%%' order by code"
com = "ts.bar(row['code'], conn=CONS, freq='D', start_date=c.DATE, end_date=c.DATE,adj = 'qfq',factors=['tor']).to_sql('t_daydata', c.ENGINE, if_exists='append')"
for row in _excutesql(sql):
try:
print(row)
eval(com)
except Exception as e:
print('error')
continue
try:
t_sh = threading.Thread(target=tmp, args=("CONN_SH", "sql"))
t_sz = threading.Thread(target=tmp, args=("CONN_SZ", "sql"))
t_cyb = threading.Thread(target=tmp, args=("CONN", "sql"))
for t in [t_sh, t_sz, t_cyb]:
t.start()
for t in [t_sh, t_sz, t_cyb]:
t.join()
except Exception as e:
print(e)
else:
for row in _excutesql(c.SQL_CODE):
for key, value in c.PERIOD.items():
try:
print(row)
eval(command)
except Exception as e:
print(e)
continue
finally:
ts.close_apis(CONS)
end = datetime.datetime.now()
print("toDB_get_periodata: " + str(end - start))
def get_selected_stock():
with open('../codes.txt') as f:
js_data = json.load(f)
code_list = js_data.get('example1')
for code in code_list:
print(code,code_list[code])
plot_stock_line(code,'2018-01-01')
ts.close_apis(api)
def main():
# 获取连接备用
cons = ts.get_apis()
codes = getCode()
# print(codes)
getMinData(cons, codes)
# 关闭连接
ts.close_apis(cons)
def get_data(self, symbols=None):
if symbols is None:
stocks = self._get_data()
pool = ThreadPool(600)
pool.map(self.get_m_data, stocks)
if self.cons is not None:
for con in self.cons:
ts.close_apis(con)
return self.data
def monitor(self):
while 1:
current = trading_time()
if current == MARKET_OPENING:
try:
price_df = ts.quotes(self.code_list, conn=self.api)
except Exception as e:
logger.info(e)
self.api = ts.get_apis()
time.sleep(EXECEPTION_TIME)
else:
price_df = price_df[price_df['cur_vol'] != 0]
price_df['percent'] = (price_df['price'] - price_df['last_close']) / price_df['last_close'] * 100
price_df['percent'] = price_df['percent'].map(lambda x: round(x, 2))
ret_dt = price_df[(price_df['percent'] > 2) | (price_df['percent'] < -2)][
['code', 'price', 'percent']]
if len(ret_dt) > 0:
name_list = []
yjl_list = []
# 只会提醒一次，下次就不会再出来了
for i in ret_dt['code']:
name_list.append(self.stocks[i])
yjl_list.append(self.stocks_yjl[i])
self.code_list.remove(i)
ret_dt['name'] = name_list
ret_dt[u'溢价率'] = yjl_list
ret_dt = ret_dt.sort_values(by='percent', ascending=False)
ret_dt = ret_dt.reset_index(drop=True)
try:
wechat.send_content(ret_dt.to_string())
# sendmail(ret_dt.to_string(), '波动的可转债')
# logger.info("Send mail successfully at {}".format(datetime.datetime.now()))
except Exception as e:
logger.info('sending wechat failed')
logger.info(e)
time.sleep(LOOP__TIME)
elif current == -1:
time.sleep(LOOP__TIME)
elif current == 1:
try:
ts.close_apis(self.api)
except Exception as e:
logger.info('fail to stop monitor {}'.format(datetime.datetime.now()))
logger.info(e)
exit(0)
def get_selected_stock():
with open('../codes.txt') as f:
js_data = json.load(f)
code_list = js_data.get('example1')
for code in code_list:
print(code, code_list[code])
plot_stock_line(code, '2018-01-01')
ts.close_apis(api)
def get_hs300_last_date_online(freq='d'):
conn = ts.get_apis()
benchmark = ts.bar('000300', conn=conn, asset='INDEX', freq=freq)
ts.close_apis(conn)
if benchmark is None:
return None, None
last_date0 = benchmark.index[0].strftime('%Y-%m-%d')
last_date1 = benchmark.index[1].strftime('%Y-%m-%d')
return last_date0, last_date1
def get_trading_days(cls,
start=None,
end=None,
ndays=None,
ascending=True):
"""
取得交易日列表，分三种方式取得
（1）指定开始、结束日期，即start和end不为None，此时忽略参数ndays
（2）指定开始日期和天数，即start和ndays不为None，而end为None
（3）指定结束日期和天数，即end和ndays为None，而start为None
--------
:param start: datetime-like or str
开始日期，格式：YYYY-MM-DD
:param end: datetime-like or str
结束日期，格式：YYYY-MM-DD
:param ndays: int
交易日天数
:param ascending: bool，默认True
是否升序排列
:return:
--------
Series of pandas.Timestamp，交易日列表，默认按交易日升序排列
"""
if len(Utils.utils_trading_days) == 0:
ts_conn = ts.get_apis()
df_SZZS = ts.bar(code='000001', conn=ts_conn, asset='INDEX')
ts.close_apis(ts_conn)
Utils.utils_trading_days = Series(df_SZZS.index).sort_values()
if start is not None:
start = cls.to_date(start)
if end is not None:
end = cls.to_date(end)
if start is not None and end is not None:
trading_days = Utils.utils_trading_days[
(Utils.utils_trading_days >= start)
& (Utils.utils_trading_days <= end)]
elif start is not None and ndays is not None:
trading_days = Utils.utils_trading_days[
Utils.utils_trading_days >= start].iloc[:ndays]
elif end is not None and ndays is not None:
trading_days = Utils.utils_trading_days[
Utils.utils_trading_days <= end].iloc[-ndays:]
elif start is not None:
trading_days = Utils.utils_trading_days[
Utils.utils_trading_days >= start]
elif end is not None:
trading_days = Utils.utils_trading_days[
Utils.utils_trading_days <= end]
elif ndays is not None:
trading_days = Utils.utils_trading_days.iloc[-ndays:]
else:
trading_days = Utils.utils_trading_days
trading_days = trading_days.reset_index(drop=True)
if not ascending:
trading_days = trading_days.sort_values(ascending=False)
return trading_days
def down(tickers=None, asset='E', freq='d', start_date='2015-01-01', end_date=None):
if tickers is None:
df_basics = ts.get_stock_basics()
tickers = df_basics.index.sort_values()
df_sql = pd.read_sql(sql_start_date.format(freq), engine, index_col=['code'], parse_dates=['start_date'])
df_start_date = pd.DataFrame(index=tickers).join(df_sql)
df_start_date = df_start_date.fillna(pd.to_datetime(start_date, format='%Y-%m-%d')).reset_index()
conn = ts.get_apis()
df_start_date.apply(lambda row:call_back(row, conn, asset, end_date, freq), axis=1)
ts.close_apis(conn)
def main():
# 获取连接备用
cons = ts.get_apis()
codes = getCode()
# print(codes)
# 获取结束时间
systemTime = str(time.strftime('%Y%m%d', time.localtime(time.time())))
getMinDataInc(cons, codes, systemTime)
# 关闭连接
ts.close_apis(cons)
def collect_hs300_daily():
now = datetime.now().strftime('%Y-%m-%d')
is_holiday = ts.is_holiday(now)
# 如果是假日, 跳过
if is_holiday:
return
conn = ts.get_apis()
df = ts.get_hs300s()
for code in df['code'].values:
collect_single_daily(code=code, conn=conn)
ts.close_apis(conn)
def main():
# current='20191016'
current = datetime.datetime.now().strftime('%Y%m%d')
app = PlotYesterdayZT()
api = ts.get_apis()
for plot_type in ['zrzt', 'zdt']:
try:
app.plot_yesterday_zt(api, plot_type, current=current)
except Exception as e:
notify(title='zdt_plot 出错', desp=f'{__name__}')
continue
ts.close_apis(conn=api)
def stock_line():
api = ts.get_apis()
df = ts.bar('300141', conn=api, start_date='2018-01-01')
# print(df)
del df['code']
df.reset_index(inplace=True)
print(df)
df['datetime'] = df['datetime'].map(mdates.date2num)
ax1 = plt.subplot2grid((6, 1), (0, 0), rowspan=5)
ax2 = plt.subplot2grid((6, 1), (5, 0), rowspan=5, sharex=ax1)
ax1.xaxis_date()
candlestick_ochl(ax1, df.values, width=1, colorup='r', colordown='g')
# ax2.fill_between(ax1,df['vol'].values,0)
plt.show()
ts.close_apis(api)
def stock_line():
api = ts.get_apis()
df = ts.bar('300141', conn=api, start_date='2018-01-01')
# print(df)
del df['code']
df.reset_index(inplace=True)
print(df)
df['datetime'] = df['datetime'].map(mdates.date2num)
ax1 = plt.subplot2grid((6, 1), (0, 0), rowspan=5)
ax2 = plt.subplot2grid((6, 1), (5, 0), rowspan=5, sharex=ax1)
ax1.xaxis_date()
candlestick_ochl(ax1, df.values, width=1, colorup='r', colordown='g')
# ax2.fill_between(ax1,df['vol'].values,0)
plt.show()
ts.close_apis(api)
def collect_index_china_daily():
now = datetime.now().strftime('%Y-%m-%d')
is_holiday = ts.is_holiday(now)
# 如果是假日, 跳过
if is_holiday:
return
conn = ts.get_apis()
collect_single_index_daily_from_ts('000001', conn=conn)
collect_single_index_daily_from_ts('399001', conn=conn)
collect_single_index_daily_from_ts('000300', conn=conn)
collect_single_index_daily_from_ts('000905', conn=conn)
ts.close_apis(conn)
def monitor(self, total_market=True):
'''
total_market 默认监控全市场 total_market = True
'''
if total_market:
(kzz_stocks, zg_stocks, kzz_yjl, zg_yjl) = self.all_bond_market()
else:
(kzz_stocks, zg_stocks, kzz_yjl,
zg_yjl) = self.get_current_position()
zg_code = list(zg_stocks.keys())
kzz_code = list(kzz_stocks.keys())
self.has_sent_kzz = dict(
zip(kzz_code, [datetime.datetime.now()] * len(kzz_code)))
self.has_sent_diff = dict(
zip(kzz_code, [datetime.datetime.now()] * len(kzz_code)))
self.has_sent_zg = dict(
zip(zg_code, [datetime.datetime.now()] * len(zg_code)))
while 1:
current = trading_time()
if current == MARKET_OPENING:
self.get_realtime_info(kzz_code, self.has_sent_kzz, '转债',
kzz_stocks, kzz_yjl, ZZ_ALERT_PERCENT)
self.get_realtime_info(zg_code, self.has_sent_zg, '正股',
zg_stocks, zg_yjl, ZG_ALERT_PERCENT)
self.get_price_diff(codes=kzz_code,
has_sent_=self.has_sent_diff,
types='差价',
kzz_stocks=kzz_stocks,
kzz_stocks_yjl=kzz_yjl)
time.sleep(LOOP_TIME)
elif current == -1:
time.sleep(LOOP_TIME)
elif current == 1:
try:
ts.close_apis(self.api)
except Exception as e:
logger.info('fail to stop monitor {}'.format(
datetime.datetime.now()))
logger.info(e)
exit(0)
def monitor():
engine = get_engine('db_zdt')
table = '20180409zdt'
api = ts.get_apis()
df = pd.read_sql(table, engine, index_col='index')
price_list = []
percent_list = []
amplitude_list = []
start = datetime.datetime.now()
for i in df['代码'].values:
try:
curr = ts.quotes(i, conn=api)
last_close = curr['last_close'].values[0]
curr_price = curr['price'].values[0]
amplitude = round(
((curr['high'].values[0] - curr['low'].values[0]) * 1.00 /
last_close) * 100, 2)
# if last_close>=curr_price:
# print(i,)
# print(df[df['代码']==i]['名称'].values[0],)
# print( percent)
except Exception as e:
print('this point')
print(e)
api = ts.get_apis()
curr_price = 0
if last_close == 0:
percent = np.nan
percent = round((curr_price - last_close) * 100.00 / last_close, 2)
percent_list.append(percent)
price_list.append(curr_price)
amplitude_list.append(amplitude)
df['今日价格'] = price_list
df['今日涨幅'] = percent_list
df['今日振幅'] = amplitude_list
df['更新时间'] = datetime.datetime.now().strftime('%Y %m %d %H:%M%S')
end = datetime.datetime.now()
print('time use {}'.format(end - start))
df.to_sql(table + 'monitor', engine, if_exists='replace')
ts.close_apis(api)
def main(current=None):
# current='20191016'
if current is None:
current = datetime.datetime.now().strftime('%Y%m%d')
if isinstance(current, int):
current = str(current)
app = PlotYesterdayZT()
api = ts.get_apis()
for plot_type in ['zrzt', 'zdt']:
try:
app.plot_yesterday_zt(api, plot_type, current=current)
except Exception as e:
print(plot_type, 'error')
print(e)
notify(title='zdt_plot 出错', desp=f'{__name__}')
continue
ts.close_apis(conn=api)
def monitor():
engine = get_engine('db_zdt')
table = '20180409zdt'
api = ts.get_apis()
df = pd.read_sql(table, engine, index_col='index')
price_list = []
percent_list = []
amplitude_list = []
start = datetime.datetime.now()
for i in df['代码'].values:
try:
curr = ts.quotes(i, conn=api)
last_close = curr['last_close'].values[0]
curr_price = curr['price'].values[0]
amplitude = round(((curr['high'].values[0] - curr['low'].values[0]) * 1.00 / last_close) * 100, 2)
# if last_close>=curr_price:
# print(i,)
# print(df[df['代码']==i]['名称'].values[0],)
# print( percent)
except Exception as e:
print('this point')
print(e)
api=ts.get_apis()
curr_price = 0
if last_close == 0:
percent = np.nan
percent = round((curr_price - last_close) * 100.00 / last_close, 2)
percent_list.append(percent)
price_list.append(curr_price)
amplitude_list.append(amplitude)
df['今日价格'] = price_list
df['今日涨幅'] = percent_list
df['今日振幅'] = amplitude_list
df['更新时间'] = datetime.datetime.now().strftime('%Y %m %d %H:%M%S')
end = datetime.datetime.now()
print('time use {}'.format(end - start))
df.to_sql(table + 'monitor', engine, if_exists='replace')
ts.close_apis(api)
def gjzq(file):
df = pd.read_table(file, encoding='gbk', dtype={'证券代码': np.str})
del df['Unnamed: 15']
code_list = list(df['证券代码'].values)
api = ts.get_apis()
# 移除非法证券代码 中签
t = [
code_list.remove(i) for i in code_list.copy()
if i.startswith('7') or i[:2] == '07'
]
price_df = ts.quotes(code_list, conn=api)
# 去除不合法的数据
price_df = price_df.dropna()
filter_df = price_df[price_df['last_close'] != 0]
filter_df = filter_df.reset_index(drop=True)
filter_df['percent'] = (filter_df['price'] - filter_df['last_close']
) / filter_df['last_close'] * 100
filter_df['percent'] = filter_df['percent'].map(lambda x: round(x, 2))
ret_df = filter_df[(filter_df['percent'] > ALERT_PERCENTAGE) |
(filter_df['percent'] < ALERT_PERCENTAGE * -1)]
d = dict(zip(list(df['证券代码'].values), list(df['证券名称'])))
ret_df['name'] = ret_df['code'].map(lambda x: d.get(x))
ret_df['amount'] = ret_df['amount'].map(lambda x: round(x / 10000, 1))
rename_column = {
'code': '证券代码',
'name': '证券名称',
'price': '当前价格',
'percent': '涨幅',
'amount': '成交金额(万)'
}
ret_df = ret_df.rename(columns=rename_column)
ret = ret_df[list(rename_column.values())]
ret = ret.reset_index(drop=True)
# 发送推送
print(ret)
ts.close_apis(api)
def get_stock_by_code(code, start, end):
"""
根据股票代码获取该股票历史行情
"""
con = ts.get_apis()
try:
res = ts.bar(code,
conn=con,
freq='D',
start_date=start,
end_date=end,
ma=[5, 10, 20, 60],
factors=['vr', 'tor'],
retry_count=2)
return res
except Exception as e:
print('抓取失败个股行情', e)
return None
finally:
ts.close_apis(con)
def get_index_by_code(code, start, end):
"""
获取指数历史行情
"""
con = ts.get_apis()
try:
res = ts.bar(code,
conn=con,
freq='D',
start_date=start,
end_date=end,
asset='INDEX',
ma=[5, 10, 20, 60],
factors=['vr', 'tor'],
retry_count=2)
return res
except Exception as e:
print('抓取指数行情失败', e)
return None
finally:
ts.close_apis(con)
def downMinuteBarBySymbol(symbol):
"""下载某一合约的分钟线数据"""
start = time()
cl = db[symbol]
cl.ensure_index([('datetime', ASCENDING)], unique=True) # 添加索引
cons = ts.get_apis()
df = ts.bar(symbol, conn=cons, freq='1min')
#df = df.sort_index()
for ix, row in df.iterrows():
bar = generateVtBar(row)
d = bar.__dict__
flt = {'datetime': bar.datetime}
cl.replace_one(flt, d, True)
end = time()
cost = (end - start) * 1000
ts.close_apis(cons)
print(u'合约%s数据下载完成%s - %s，耗时%s毫秒' %
(symbol, df.index[0], df.index[-1], cost))
def plot_stock_line(api,code, name, table_name, current, start='2017-10-01', save=False):
title = '{} {} {} {}'.format(current, code, name, table_name)
title = title.replace('*', '_')
if os.path.exists(title + '.png'):
return
if code is None and name is not None:
code = base_info[base_info['name'] == name]['code'].values[0]
df = None
for _ in range(4):
try:
df = ts.bar(code, conn=api, start_date=start)
except Exception as e:
logger.info(e)
ts.close_apis(api)
time.sleep(random.random() * 30)
api = ts.get_apis()
else:
break
if df is None:
return
df = df.sort_index()
if name is None:
name = base_info[base_info['code'] == code]['name'].values[0]
df = df.reset_index()
df['datetime'] = df['datetime'].dt.strftime('%Y-%m-%d')
sma5 = talib.SMA(df['close'].values, 5)
sma20 = talib.SMA(df['close'].values, 10)
# ax.set_xticks(range(0,len(df),20))
# # ax.set_xticklabels(df['date'][::5])
# ax.set_xticklabels(df['datetime'][::20])
fig = plt.figure(figsize=(10, 8))
# fig,(ax,ax2)=plt.subplots(2,1,sharex=True,figsize=(16,10))
ax = fig.add_axes([0, 0.3, 1, 0.50])
ax2 = fig.add_axes([0, 0.1, 1, 0.20])
candlestick2_ochl(ax, df['open'], df['close'], df['high'], df['low'], width=1, colorup='r', colordown='g',
alpha=0.6)
ax.grid(True)
ax.set_title(title)
ax.plot(sma5, label='MA5')
ax.legend()
ax.plot(sma20, label='MA20')
ax.legend(loc=2)
ax.grid(True)
# df['vol'].plot(kind='bar')
volume_overlay(ax2, df['open'], df['close'], df['vol'], width=1, alpha=0.8, colordown='g', colorup='r')
ax2.set_xticks(range(0, len(df), 5))
# ax.set_xticklabels(df['date'][::5])
ax2.set_xticklabels(df['datetime'][::5])
plt.setp(ax2.get_xticklabels(), rotation=30, horizontalalignment='right')
ax2.grid(True)
plt.subplots_adjust(hspace=0.3)
if save:
# path = os.path.join(os.path.dirname(__file__),'data',today)
fig.savefig(title + '.png')
else:
plt.show()
plt.close()
for i in range(len(df)):
code = df.iloc[i]['代码']
name = df.iloc[i]['名称']
plot_stock_line(api,code, name, table_name=table_name, current=current, start='2018-07-01', save=True)
if __name__ == '__main__':
if is_holiday():
logger.info('Holiday')
exit()
logger.info("Start")
api = ts.get_apis()
current = datetime.datetime.now().strftime('%Y%m%d')
data_path = DATA_PATH
path = os.path.join(DATA_PATH, current)
if not os.path.exists(path):
os.mkdir(path)
os.chdir(path)
for plot_type in ['zrzt', 'zdt']:
try:
plot_yesterday_zt(plot_type, current=current)
except Exception as e:
continue
ts.close_apis(api)
def api_close_case():
api = ts.get_apis()
print('exit function')
ts.close_apis(api)
exit(0)
def closed(self):
ts.close_apis(self.conn)
