def output(context, date, l_sell, l_keep, l_buy):
subject = '%s盘后计划' % date
content = ''
content += '<table border="1">'
content += '<thead>'
content += '<tr><th>代码</th><th>名称</th><th>策略</th></tr>'
content += '</thead>'
content += '<tbody>'
for item in l_sell:
ins = get_instrumentinfos(symbols=item['symbol'])[0]
name = ins['sec_name']
content += '<tr><td>%s</td><td>%s</td><td><font color="green">卖出%s</font></td></tr>' \
% (item['symbol'], name, item['policy'])
for item in l_keep:
ins = get_instrumentinfos(symbols=item['symbol'])[0]
name = ins['sec_name']
content += '<tr><td>%s</td><td>%s</td><td>%s</td></tr>' \
% (item['symbol'], name, '')
for item in l_buy:
ins = get_instrumentinfos(symbols=item['symbol'])[0]
name = ins['sec_name']
vacancies = c - len(l_keep)
cash = context.account().cash['available']
volume = floor(cash / vacancies / item['price'] /
100) * 100 if vacancies > 0 else 0
content += '<tr><td>%s</td><td>%s</td><td><font color="red">买入%s %.2f * %d</font></td></tr>' \
% (item['symbol'], name, item['policy'], item['price'], volume)
content += '</tbody>'
content += '</table>'
send_all(subject, content)
def get_and_store_stock_detail_data(stock_code,date,type=1):
"""
保存单只股票数据csv文件，自定义文件名
tye：1:股票。2：指数。
"""
fn = str(stock_code) + "_" + str(date)
if type != 1:
fn = fn.replace('.','')
pd = load_csv_detail_data(fn)
if pd is None:
set_token("8e1026d2dfd455be2e1f239e50004b35a481061e")
if type == 1:
symbols = ['SZSE.'+str(stock_code),'SHSE.'+str(stock_code)]
data = get_instrumentinfos(symbols=symbols, exchanges=None, sec_types=1, names=None, fields=None, df=True)
symbol = data[data.sec_id == str(stock_code)].symbol.values[0]
else:
symbol = stock_code
start_date = datetime.datetime.strptime(date, '%Y-%m-%d').date()
end_date = start_date + datetime.timedelta(days=1)
pd = history(symbol, "60s", start_date, end_date, fields=None, skip_suspended=True,
fill_missing=None, adjust=0, adjust_end_time='', df=True)
# pd = ts.get_tick_data(stock_code, date=date, src='tt')
if pd is None:
return None
else :
pd = cacle_column(pd,fn)
return pd
else:
pd = cacle_column(pd,fn)
return pd
def output(context, date, l_sell, l_keep, l_buy):
message = '%s盘后计划' % date
for item in l_sell:
ins = get_instrumentinfos(symbols=item['symbol'])[0]
name = ins['sec_name']
message += '\n\033[1;32m%s %s 卖出%s\033[0m' \
% (item['symbol'], name, item['policy'])
for item in l_keep:
ins = get_instrumentinfos(symbols=item['symbol'])[0]
name = ins['sec_name']
message += '\n%s %s 分值：%s' \
% (item['symbol'], name, item['score'])
for item in l_buy:
ins = get_instrumentinfos(symbols=item['symbol'])[0]
name = ins['sec_name']
vacancies = c - len(l_keep)
cash = context.account().cash['available']
volume = floor(cash / vacancies / item['price'] / 100) * 100 if vacancies > 0 else 0
message += '\n\033[1;31m%s %s 买入%s %.2f * %d\033[0m' \
% (item['symbol'], name, item['policy'], item['price'], volume)
print(message)
def init(self) -> bool:
""""""
if self.inited:
return True
try:
set_token(JJ_TOKEN)
# 获取全部合约
instrumentinfos = get_instrumentinfos(symbols=None, exchanges=None, sec_types=None, names=None, fields=None, df=True)
self.symbols = [k for k in instrumentinfos["symbol"]]
except:
return False
self.inited = True
return True
def full_build():
count = 0
read = read_conn()
write = write_conn()
cursor = write.cursor()
cursor.execute('DELETE FROM instrumentinfos')
infos = get_instrumentinfos(
exchanges=['SHSE', 'SZSE'],
sec_types=[1],
fields='symbol,sec_name,sec_abbr,price_tick,listed_date,delisted_date')
for i, info in enumerate(infos):
print('\rBuilding instrumentinfos: %.2f%%' % (i * 100 / len(infos)),
end='')
cursor.execute(
'INSERT INTO instrumentinfos (symbol, sec_name, sec_abbr, price_tick, listed_date, delisted_date) VALUES (%s,%s,%s,%s,%s,%s)',
(info['symbol'], info['sec_name'], info['sec_abbr'],
info['price_tick'], info['listed_date'], info['delisted_date']))
cursor.close()
write.close()
read.close()
print('\rBuilding instrumentinfos: Finish')
return count
def plot_order_jubaopen_myself(order, start=60, end=10):
"""
绘制订单分时图
:param order: AbuOrder对象序列
"""
stock_code = order.symbol
set_token("8e1026d2dfd455be2e1f239e50004b35a481061e")
data = get_instrumentinfos(symbols=None,
exchanges=None,
sec_types=1,
names=None,
fields=None,
df=True)
symbol = data[data.sec_id == stock_code].symbol.values[0]
start_date_order = datetime.datetime.strptime(
str(order.buy_time)[0:18], "%Y-%m-%d %H:%M:%S").date()
start_date = start_date_order + datetime.timedelta(days=-1)
end_date = start_date_order + datetime.timedelta(days=9)
kl_pd = history(symbol,
"60s",
start_date,
end_date,
fields=None,
skip_suspended=True,
fill_missing=None,
adjust=ADJUST_PREV,
adjust_end_time='',
df=True)
bench_kl_pd = history('SHSE.000001',
"60s",
start_date,
end_date,
fields=None,
skip_suspended=True,
fill_missing=None,
adjust=ADJUST_PREV,
adjust_end_time='',
df=True)
bench_kl_pd = bench_kl_pd[bench_kl_pd['bob'].isin(kl_pd['bob'].tolist())]
bench_kl_pd.index = np.arange(0, len(bench_kl_pd))
kl_pd['date'] = kl_pd['bob'].apply(
lambda x: ABuDateUtil.date_time_str_to_int(str(x)))
kl_pd['time'] = kl_pd['bob'].apply(
lambda x: ABuDateUtil.date_time_str_to_time_str(str(x)))
kl_pd_time = kl_pd[kl_pd.time == '093000']
kl_pd_buy_time = kl_pd[kl_pd.bob == order.buy_time]
kl_pd_sell_time = kl_pd[kl_pd.bob == order.sell_time]
kl_pd['p_change'] = (kl_pd.close - kl_pd['close'][0]) / kl_pd['close'][0]
bench_kl_pd['p_change'] = (
bench_kl_pd.close - bench_kl_pd['close'][0]) / bench_kl_pd['close'][0]
kl_pd['p_change_update'] = (kl_pd.p_change - bench_kl_pd.p_change)
window_volume = 30
window_close = 30
kl_pd['p_change_5ma'] = kl_pd.p_change.rolling(window=window_close).mean()
kl_pd['p_change_update_5ma'] = kl_pd.p_change_update.rolling(
window=window_close).mean()
bench_kl_pd['p_change_5ma'] = bench_kl_pd.p_change.rolling(
window=window_close).mean()
kl_pd['volume_ma'] = kl_pd.volume.rolling(window=window_volume).mean()
kl_pd['p_change_5ma_up_rate'] = (kl_pd.p_change_5ma -
kl_pd.p_change_5ma.shift(5))
kl_pd['p_change_update_5ma_up_rate'] = (kl_pd.p_change_update_5ma -
kl_pd.p_change_update_5ma.shift(5))
bench_kl_pd['p_change_5ma_up_rate'] = (bench_kl_pd.p_change_5ma -
bench_kl_pd.p_change_5ma.shift(5))
kl_pd['zero_line'] = 0
kl_pd['volume_ma_up_rate'] = (kl_pd.volume_ma - kl_pd.volume_ma.shift(5))
kl_pd[kl_pd['p_change_5ma_up_rate'] > 0.01] = 0.01
kl_pd[kl_pd['p_change_5ma_up_rate'] < -0.01] = -0.01
max_p_change = kl_pd['p_change_5ma_up_rate'].max()
min_p_change = kl_pd['p_change_5ma_up_rate'].min()
max_volume = kl_pd['volume_ma_up_rate'].max()
min_volume = kl_pd['volume_ma_up_rate'].min()
vs_rate1 = max_p_change / max_volume
vs_rate2 = min_p_change / min_volume
vs_rate = vs_rate1 if vs_rate1 >= vs_rate2 else vs_rate2
kl_pd['volume_ma_up_rate'] = (kl_pd.volume_ma -
kl_pd.volume_ma.shift(5)) * vs_rate
# kl_pd[kl_pd['volume_ma_up_rate'] > 0.0025] = 0.0025
# kl_pd[kl_pd['volume_ma_up_rate'] < -0.0025] = -0.0025
# kl_pd['volume_ma_up_rate'] = kl_pd['volume_ma_up_rate'] * 4
# max_volume = kl_pd['volume_ma_up_rate'].max()
# min_volume = kl_pd['volume_ma_up_rate'].min()
#
# vs_rate1 = max_p_change / max_volume
# vs_rate2 = min_p_change / min_volume
# vs_rate = vs_rate1 if vs_rate1 >= vs_rate2 else vs_rate2
# kl_pd['volume_ma_up_rate'] = (kl_pd.volume_ma - kl_pd.volume_ma.shift(5)) * vs_rate
title = str(stock_code) + '_' + str(order.buy_time)[0:10]
# plt.plot(kl_pd.index, kl_pd['p_change'], label='p_change', color='blue') #基础p_change
# plt.plot(kl_pd.index, bench_kl_pd['p_change'], label='bench_p_change', color='green') #大盘p_change
# plt.plot(kl_pd.index, kl_pd['p_change_5ma'], label='close60', color='red') #基础p_change均线
# plt.plot(kl_pd.index, bench_kl_pd['p_change_5ma'], label='close60', color='red') #基础大盘p_change均线
# plt.plot(kl_pd.index, kl_pd['p_change_update'],'--', label='p_change_update', color='red') #修正后涨跌幅
plt.plot(kl_pd.index, kl_pd['p_change'], label='p_change',
color='blue') #基础p_change
plt.plot(bench_kl_pd.index,
bench_kl_pd['p_change'],
label='bench_p_change',
color='green') #大盘p_change
# plt.plot(kl_pd.index, kl_pd['p_change_5ma'], label='close60', color='red') #基础p_change均线
# plt.plot(kl_pd.index, bench_kl_pd['p_change_5ma'], label='close60', color='red') #基础大盘p_change均线
# plt.plot(kl_pd.index, kl_pd['p_change_update'],'--', label='p_change_update', color='red') #修正后涨跌幅
plt.plot(kl_pd.index, kl_pd['zero_line'], label='0_line',
color='black') # 0线
plt.vlines(kl_pd_time.index, -0.005, 0.005, color="black") #日期分割线
plt.vlines(kl_pd_buy_time.index, -0.01, 0.01, color="red") #买入时间线
plt.vlines(kl_pd_sell_time.index, -0.02, 0.02, color="blue") #卖出时间线
plt.title(title)
plt.legend(loc='upper left')
# plt.show()
png_name = generatePngName(stock_code)
plt.savefig(png_name)
plt.close()
# 获得日分时数据。
kl_pd = get_and_store_stock_detail_data(stock_code, str(start_date_order))
kl_pd['zero_line'] = 0
# plt.plot(kl_pd.index, kl_pd['volume_30ma_up_rate'], label='volume_30ma_up_rate', color='blue') #基础p_change
plt.plot(kl_pd.index,
kl_pd['volume_30ma'],
label='volume_30ma',
color='blue') #基础p_change
plt.plot(kl_pd.index,
kl_pd['volume_5ma'],
label='volume_5ma',
color='green') #基础p_change
plt.plot(kl_pd.index, kl_pd['zero_line'], label='0_line',
color='black') # 0线
plt.title(title)
plt.legend(loc='upper left')
# plt.show()
png_name = generatePngName(stock_code)
plt.savefig(png_name)
plt.close()
bench_kl_pd = get_and_store_SHSE000001_detail_data(str(start_date_order))
plt.plot(kl_pd.index,
kl_pd['p_change_30ma_up_rate'],
label='p_change_30ma_up_rate',
color='red') # 基础均线增长斜率
# plt.plot(kl_pd.index, kl_pd['p_change_update_5ma_up_rate'], '--', label='close60', color='blue') # 修正均线增长斜率
plt.plot(bench_kl_pd.index,
bench_kl_pd['p_change_30ma_up_rate'],
label='bench_p_change_30ma_up_rate',
color='green') # 大盘增长斜率
plt.plot(kl_pd.index, kl_pd['zero_line'], label='0_line',
color='black') # 0线
# plt.plot(kl_pd.index, kl_pd['volume_ma'], label='volume_ma', color='blue') #量均值
# plt.plot(kl_pd.index, kl_pd['volume_30ma_up_rate'], '--', label='volume_30ma_up_rate', color='blue') # 量增长斜率
plt.title(title)
plt.legend(loc='upper left')
# plt.show()
png_name = generatePngName(stock_code)
plt.savefig(png_name)
plt.close()
plt.plot(kl_pd.index,
kl_pd['p_change_30ma'],
label='p_change_30ma',
color='red') # 基础均线增长斜率
plt.plot(bench_kl_pd.index,
bench_kl_pd['p_change_30ma'],
label='bench_p_change_30ma',
color='green') # 大盘增长斜率
plt.plot(kl_pd.index, kl_pd['zero_line'], label='0_line',
color='black') # 0线
plt.title(title)
plt.legend(loc='upper left')
png_name = generatePngName(stock_code)
plt.savefig(png_name)
plt.close()
pass