def cat_stk_opt_record(input_str, json_file_url, tc):
if opt_record_lock.acquire():
r = '未知错误'
try:
r = cat_stk_b_opt_sub(stk_name=input_str.split(' ')[1], json_file_url=json_file_url)
except Exception as e:
r = '读写opt_record.json文件失败！原因：\n' + str(e)
finally:
opt_record_lock.release()
text_append_color(tc, r + '\n')
def cat_stk(kind, tc):
"""
查看相关stk列表
:param kind:
:return:
"""
stk_list = read_config()[kind]
stk_name = str([code2name(x) for x in stk_list])
text_append_color(tc, stk_name.replace('[', '').replace(']', '').replace(',', '\n'))
def sea_select_thread(tc):
try:
jq_login()
sc = ExecuteSelectRole()
sc.sea_select(tc)
except Exception as e_:
text_append_color(tc, '海选功能执行失败！原因：\n%s\n' % str(e_))
finally:
text_append_color(tc, '\n请输入命令：\n', color=wx.YELLOW)
def add_opt(input_str, json_file_url, tc):
if opt_record_lock.acquire():
r = ['未知错误']
try:
r = add_opt_to_json_sub(input_str, json_file_url, tc)
except Exception as e:
r = ['读写opt_record.json文件失败！原因：\n' + str(e)]
finally:
opt_record_lock.release()
for str_ in r:
text_append_color(tc, str_ + '\n')
def sale_stk_sub(stk_record, s_amount, s_p, tc):
"""
:param stk_record:
:return:
"""
opt_r_stk = stk_record
# 本次盈利
earn_this = 0
if len(opt_r_stk['b_opt']) > 0:
p_min = np.min([x['p'] for x in opt_r_stk['b_opt']])
opt_r_stk['b_opt'].sort(key=lambda x: x['p'] == p_min, reverse=False)
# 循环清算
while True:
if opt_r_stk['b_opt'][-1]['amount'] <= s_amount:
# 注销
b_pop = opt_r_stk['b_opt'].pop(-1)
# 清算
s_amount = s_amount - b_pop['amount']
# 计算盈利
earn_this = earn_this + b_pop['amount'] * (s_p - b_pop['p'])
else:
# 清算
opt_r_stk['b_opt'][-1]['amount'] = opt_r_stk['b_opt'][-1]['amount'] - s_amount
# 计算盈利
earn_this = earn_this + s_amount * (s_p - opt_r_stk['b_opt'][-1]['p'])
break
# 判断是否有
if len(opt_r_stk['b_opt']) < 1:
if s_amount > 0:
text_append_color(tc, '异常： 可卖标的数量超过持有量！\n')
break
opt_r_stk['total_earn'] = opt_r_stk['total_earn'] + earn_this
return opt_r_stk, earn_this
def data_prepare(self, k_kind, tc):
"""
根据k线类型检查下载数据
:param k_kind:
:return:
"""
t_s = time.time()
text_append_color(tc, '\n开始准备 %s 数据！\n' % k_kind)
k_kind = self.k_kind_format(k_kind)
if (k_kind == 'd') | (k_kind == '日线'):
# 增加日线数据
if not self.day_data_enable:
_ = [x.down_day_data() for x in self.stk_list_ss]
# 过滤掉空值
self.stk_list_ss = list(
filter(lambda x: not x.day_data.empty, self.stk_list_ss))
self.day_data_enable = True
text_append_color(
tc,
'\n%s 数据准备完成！总共耗时%s分钟\n' % (k_kind, minute_reckon(t_s)))
return '数据准备完毕！'
elif (k_kind == 'w') | (k_kind == 'm') | (k_kind == '周线') | (k_kind
== '月线'):
# 增加日线数据
if not self.day_data_enable:
_ = [x.down_day_data() for x in self.stk_list_ss]
# 过滤掉空值
self.stk_list_ss = list(
filter(lambda x: not x.day_data.empty, self.stk_list_ss))
self.day_data_enable = True
# 增加周/月线数据
if not self.week_month_data_enable:
_ = [x.add_week_month_data() for x in self.stk_list_ss]
self.week_month_data_enable = True
elif (k_kind == 'h') | (k_kind == '半小时线'):
# 增加半小时数据
if not self.half_hour_enable:
_ = [x.down_hour_data() for x in self.stk_list_ss]
self.half_hour_enable = True
def plot_opt(stk_code, opt_record, tc):
if len(opt_record) == 0:
text_append_color(tc, code2name(stk_code) + '：没有操作记录！')
return
df = pd.DataFrame(opt_record).set_index('date_time')
# 筛选
df = df[df['stk_code'] == stk_code]
if df.empty:
text_append_color(tc, code2name(stk_code) + '：没有操作记录！')
# 计算上下限
df['sale_pot'] = df.apply(lambda x: x['p_last'] + x['sale_reseau'], axis=1)
df['buy_pot'] = df.apply(lambda x: x['p_last'] + x['buy_reseau'], axis=1)
df.loc[:, ['p_last', 'p_now', 'buy_pot', 'sale_pot']].plot(style=['*', '*', '^--', '^--'])
plt.show()
def add_stk(kind, name, tc):
"""
增加持仓
:param name:
:param tc:
:return:
"""
# 判断输入的是代码是名称
if 'qh' in name:
code = name[2:]
elif name.isdigit():
code = name
else:
code = name2code(name)
if code == '未知代码':
text_append_color(tc, name + ':不识别的股票名字！请尝试使用股票代码！')
return
# 向配置文件中写入 增加持仓的stk代码
stk_now = read_config()[kind]
if code not in stk_now:
stk_now.append(code)
write_config(kind, stk_now)
text_append_color(tc, '增加“' + name + '”成功！')
else:
text_append_color(tc, '增加“' + name + '”失败！已存在！')
def __init__(self, parent, title):
super(DengShen, self).__init__(parent, title=title, size=(700, 500))
# 绑定关闭函数
self.Bind(wx.EVT_CLOSE, self.on_close, parent)
panel = wx.Panel(self)
hbox3 = wx.BoxSizer(wx.HORIZONTAL)
self.t3 = wx.TextCtrl(panel, size=(600, 1000), style=wx.TE_MULTILINE | wx.TE_RICH2)
hbox3.Add(self.t3, 1, wx.EXPAND | wx.ALIGN_LEFT | wx.ALL, 5)
self.t3.Bind(wx.EVT_TEXT_ENTER, self.on_enter_pressed)
self.t3.SetBackgroundColour('Black')
self.t3.SetForegroundColour('Red')
panel.SetSizer(hbox3)
# 打印欢迎语
text_append_color(self.t3, '输入帮助查看详细用法\n')
text_append_color(self.t3, '\n请输入命令：\n', color=wx.YELLOW)
self.Centre()
self.Show()
self.Fit()
def on_enter_pressed(self, event):
# 获取最后一行
input_str = list(filter(lambda x: x != '', event.GetString().split('\n')))[-1]
try:
self.input_analysis(input_str)
text_append_color(self.t3, '\n请输入命令：\n', color=wx.YELLOW)
except Exception as e_:
text_append_color(self.t3, '灯神出错了！原因：\n' + str(e_) + '\n\n')
text_append_color(self.t3, '\n请输入命令：\n', color=wx.YELLOW)
def predict_tomorrow_index(tc, debug=False):
try:
with open(rootPath + '\Function\LSTM\AboutLSTM\stk_max_min.json',
'r') as f:
max_min_info = json.load(f)
stk2name = {'sh': '上证', 'sz': '深证', 'cyb': '创业板'}
for stk in ['sh', 'sz', 'cyb']:
today_df = ts.get_k_data(stk).tail(1)
text_append_color(
tc,
stk2name.get(stk) + ' 今天数据：\n' + today_df.to_string().replace(
'volume', '成交量').replace('date', '日期').replace(
'open', '开盘价').replace('high', '最高点').replace(
'low', '最低点').replace('close', '收盘价') + '\n\n')
close_today = today_df['close'].values[0]
r = [(label, '%0.2f' % predict_tomorrow(stk,
label,
N_STEPS=N_STEPS,
feature_cols=feature_cols,
HIDDEN_SIZE=HIDDEN_SIZE,
NUM_LAYERS=NUM_LAYERS),
max_min_info[stk][label + '_acc'])
for label in ['high', 'low', 'close']]
# 增加与今天收盘价的对比
r_contrast = [
(x[0], x[1], '%0.2f' %
((float(x[1]) - close_today) / close_today * 100) + '%')
for x in r
]
text_append_color(
tc, stk2name[stk] +
'明日预测:\n' + str(r_contrast).replace('high', '最高点').replace(
'low', '最低点').replace('close', '收盘价') + '\n\n')
except Exception as e:
text_append_color(tc, '预测明日大盘操作失败！原因：\n' + str(e))
def delete_stk(kind, name, tc):
"""
从持仓中删除
:param name:
:param tc:
:return:
"""
# 判断输入的是代码是名称
if name.isdigit():
code = name
else:
code = name2code(name)
if code == '未知代码':
text_append_color(tc, name + ':不识别的股票名字！请尝试使用股票代码！')
return
# 向配置文件中删除 增加持仓的stk代码
stk_now = read_config()[kind]
if code in stk_now:
stk_now.remove(code)
write_config(kind, stk_now)
text_append_color(tc, '删除“' + name + '”成功！')
else:
text_append_color(tc, '删除“' + name + '”失败！原先关注列表中没有 ' + name)
# coding=utf-8
def sea_select(self, tc):
"""
执行主函数
:return:
"""
# 判断规则是否为空！
if len(self.rule['filter_rule']) == 0:
text_append_color(tc, '尚未设置过滤规则！无法进行海选！\n')
return
# 判断是否设置的报告存放路径
if self.rule['save_dir'] == '':
text_append_color(tc, '尚未设置海选报告的存放路径，请在灯神中输入“规则-设置报告存放路径”来设置！')
# 将规则转为dataframe
rule_df = pd.DataFrame(self.rule['filter_rule'])
# 根据优先级对规则进行执行
rule_priority_group = list(rule_df.groupby(by='priority'))
# 对优先级进行排序
rule_list = sorted(rule_priority_group, key=lambda x: x[0], reverse=False)
# 根据优先级执行筛选规则
for rule_group_priority in rule_list:
# 提取该优先级的规则df
df_rule = rule_group_priority[1]
for idx in df_rule.index:
text_append_color(tc, '\n开始执行过滤规则 <%s> ...\n' % df_rule.loc[idx, 'describe'] )
text_append_color(tc, self.rule_execute(df_rule.loc[idx, 'kind'], df_rule.loc[idx, 'data'], tc))
text_append_color(tc, '\n经过以上筛选后剩余的标的：\n' + self.get_filter_result())
# 打印结果
if len(self.stk_list_ss) == 0:
text_append_color(tc, '没有满足所有海选规则的标的，不需要打印结果报告！')
else:
pdf_gen = SeaSelectPdf()
# 生成图片
text_append_color(tc, '\n开始打印pdf所需要的图片...\n')
pdf_gen.gen_sea_select_pic(self.stk_list_ss)
# 生成pdf
text_append_color(tc, '\n开始生成最终的pdf报告...\n')
pdf_gen.gen_pdf(self.stk_list_ss, self.rule['save_dir'] + '/')
text_append_color(tc, '\n海选结果pdf已经打印，请在：\n' + str(self.rule['save_dir']) + '\n文件夹下查看！\n')
def input_analysis(self, input_str):
text_append_color(self.t3, '\n\n')
if '增加持仓' in input_str:
ipt_split = input_str.split(' ')
# 向配置文件中写入 增加持仓的stk代码
StkConfig.add_stk(kind='buy_stk', name=ipt_split[1], tc=self.t3)
elif '删除持仓' in input_str:
ipt_split = input_str.split(' ')
# 向配置文件中写入 增加持仓的stk代码
StkConfig.delete_stk(kind='buy_stk', name=ipt_split[1], tc=self.t3)
elif '增加关注' in input_str:
ipt_split = input_str.split(' ')
# 向配置文件中写入 增加持仓的stk代码
StkConfig.add_stk(kind='concerned_stk', name=ipt_split[1], tc=self.t3)
elif '查看记录' in input_str:
ipt_split = input_str.split(' ')
# 画图该stk的操作记录
plot_opt(stk_code=name2code(ipt_split[1]), tc=self.t3, opt_record=opt_record)
elif '删除关注' in input_str:
ipt_split = input_str.split(' ')
StkConfig.delete_stk(kind='concerned_stk', name=ipt_split[1], tc=self.t3)
elif '查看关注' in input_str:
StkConfig.cat_stk(kind='concerned_stk', tc=self.t3)
elif '查看持仓' in input_str:
StkConfig.cat_stk(kind='buy_stk', tc=self.t3)
elif '预测明日大盘' in input_str:
# 启动数据处理线程，专用于处理数据，防止软件操作卡顿
index_predict_thread = threading.Thread(target=predict_tomorrow_index, args=(self.t3, False))
index_predict_thread.start()
elif '清理' == input_str:
self.t3.SetValue('')
elif '帮助' == input_str:
text_append_color(self.t3, total_cmd)
elif ('买入' in input_str) | ('卖出' in input_str):
add_opt(input_str, opt_record_file_url, self.t3)
elif ('真买' in input_str) | ('真卖' in input_str):
add_real_trade(input_str, opt_record_file_url, self.t3)
elif '查看b记录' in input_str:
cat_stk_opt_record(
input_str=input_str,
json_file_url=opt_record_file_url,
tc=self.t3)
elif '规则' in input_str:
sc = SelectCmd()
text_append_color(self.t3, sc.rule_input_pro(input_str))
elif '执行海选' == input_str:
def sea_select_thread(tc):
try:
jq_login()
sc = ExecuteSelectRole()
sc.sea_select(tc)
except Exception as e_:
text_append_color(tc, '海选功能执行失败！原因：\n%s\n' % str(e_))
finally:
text_append_color(tc, '\n请输入命令：\n', color=wx.YELLOW)
# 启动数据处理线程，专用于处理数据，防止软件操作卡顿
sea_select_thread = threading.Thread(target=sea_select_thread, args=(self.t3,))
sea_select_thread.start()
else:
text_append_color(self.t3, '没听懂，请明示！')
