def OnTimerCtrl(win, debug=False):
"""
定时器响应函数
:return:
"""
# 清屏
wx.PostEvent(
win,
ResultEvent(id=MSG_UPDATE_ID_S,
data='检测时间：' + get_current_datetime_str() + '\n\n'))
# 不在交易时间不使能定时器
if not is_in_trade_time():
wx.PostEvent(
win, ResultEvent(id=MSG_UPDATE_ID_A, data='控制台定时器：当前不属于交易时间！\n'))
return
buy_stk_list = list(
set(readConfig()['buy_stk'] + readConfig()['index_stk']))
if debug:
print('OnTimerCtrl_4')
# 局部变量
note_list = []
# 对股票进行检查
for stk in buy_stk_list:
str_gui = JudgeSingleStk(stk_code=stk,
stk_amount_last=400,
qq='',
gui=True)
if len(str_gui['note']):
note_list.append(str_gui['note'])
# 打印流水信息
if len(str_gui['msg']):
wx.PostEvent(win,
ResultEvent(id=MSG_UPDATE_ID_A, data=str_gui['msg']))
# 根据情况打印提示信息，并闪动
if len(note_list):
# 清屏
wx.PostEvent(
win,
ResultEvent(id=NOTE_UPDATE_ID_S,
data='检测时间：' + get_current_datetime_str() + '\n\n'))
# 打印提示
for note in note_list:
wx.PostEvent(
win,
ResultEvent(id=NOTE_UPDATE_ID_A, data=ChangeFontColor(note)))
# 闪动图标提醒
wx.PostEvent(win, ResultEvent(id=FLASH_WINDOW_ID, data=None))
def on_timer_ctrl(win, debug=False):
"""
控制台定时器响应函数
:return:
"""
# 清屏
wx.PostEvent(win, ResultEvent(id=MSG_UPDATE_ID_S, data='检测时间：' + get_current_datetime_str() + '\n\n'))
# 不在交易时间不使能定时器
if (not is_in_trade_time()) & (not debug):
wx.PostEvent(win, ResultEvent(
id=MSG_UPDATE_ID_A,
data='控制台定时器：当前不属于交易时间！\n'))
return
buy_stk_list = list(set(read_config()['buy_stk'] + read_config()['index_stk']))
# 局部变量
note_list = []
# 对stk进行检查
for stk in buy_stk_list:
str_gui = judge_single_stk(stk_code=stk, stk_amount_last=400, qq='', gui=True, debug=True)
if len(str_gui['note']):
note_list.append(str_gui['note'])
# 打印流水信息
if len(str_gui['msg']):
wx.PostEvent(win, ResultEvent(
id=MSG_UPDATE_ID_A,
data=str_gui['msg']))
# 打印日志
debug_print_txt('timer_ctrl_log', 'total',
get_current_datetime_str() + ':\n' +
'提示消息：\n' + str(note_list) + '\n' + '流水消息：\n' + str(str_gui['msg']))
# 根据情况打印提示信息，并闪动
if len(note_list):
# 清屏
wx.PostEvent(win, ResultEvent(
id=NOTE_UPDATE_ID_S,
data='检测时间：' + get_current_datetime_str() + '\n\n'))
# 打印提示
for note in note_list:
wx.PostEvent(win, ResultEvent(
id=NOTE_UPDATE_ID_A,
data=change_font_color(note)))
# 闪动图标提醒
wx.PostEvent(win, ResultEvent(
id=FLASH_WINDOW_ID,
data=None))
def add_b_opt(self, price, amount):
"""
记录买入操作
:return:
"""
b_opt = self.get_config_value('b_opt')
if pd.isnull(b_opt):
b_opt = [dict(time=get_current_datetime_str(), p=price, amount=amount)]
else:
b_opt = b_opt.append(dict(time=get_current_datetime_str(), p=price, amount=amount))
self.set_config_value('b_opt', b_opt)
def get_last_m_stray(self):
"""
找出上一次穿越m线的情况
:return:
"""
# 取出一副本，再进行drop操作
df = self.data.dropna(axis=0)
if df.empty:
return '近期无穿越M%s均线（freq=%s）的行为' % (str(self.m), self.freq)
# 取出最后一个转折点
df_pot = df[df.apply(lambda x: x['pn_pot_' + str(self.m)], axis=1)]
if df_pot.empty:
return '近期无穿越M%s均线（freq=%s）的行为' % (str(self.m), self.freq)
last_pot = df_pot.tail(1)
self.last_result = last_pot['m_pn_' + str(self.m)].values[0]
return self.last_m_pot_note(
get_current_datetime_str(),
last_pot['datetime'].values[0],
last_pot['m_pn_' + str(self.m)].values[0])
def add_s_opt(self, price, amount):
"""
记录卖出操作
:return:
"""
s_opt = self.get_config_value('s_opt')
if pd.isnull(s_opt):
s_opt = [
dict(time=get_current_datetime_str(), p=price, amount=amount)
]
else:
s_opt = s_opt.append(
dict(time=get_current_datetime_str(), p=price, amount=amount))
self.set_config_value('s_opt', s_opt)
def flash_window(self, evt=None):
# 打印此次提示的时间
self.on_update_note_tc_a(
'以上提示发生时间：' + get_current_datetime_str() +
'\n----------------------------------------\n\n')
win32gui.FlashWindowEx(self.handle, 2, 3, 400)
def add_opt_to_json_sub(input_str, json_file_url_, tc):
# 返回字符串
return_str = []
# 已有文件，打开读取
if os.path.exists(json_file_url_):
with open(json_file_url_, 'r') as _f:
_opt_record = json.load(_f)
else:
_opt_record = {}
# 解析输入
stk_name, opt, amount, p = input_str.split(' ')
stk_code = name2code(stk_name)
p, amount = float(p), float(amount)
# 对输入格式进行检查
if amount % 100 != 0:
tc.AppendText('格式错误！参考格式：\n美的集团 卖出 400 51.3')
return
if stk_code in _opt_record.keys():
opt_r_stk = _opt_record[stk_code]
else:
opt_r_stk = {
'b_opt': [],
'p_last': None,
'has_flashed_flag': True,
'total_earn': 0,
'last_prompt_point': -1
}
if opt == '买入':
opt_r_stk['b_opt'].append(dict(time=get_current_datetime_str(), p=p, amount=amount))
if opt == '卖出':
if len(opt_r_stk['b_opt']) > 0:
opt_r_stk, earn_this = sale_stk_sub(opt_r_stk, amount, p, tc)
return_str.append('earn：' + str(earn_this) + '\n')
opt_r_stk['p_last'] = p
opt_r_stk['has_flashed_flag'] = True
# 保存数据
_opt_record[stk_code] = opt_r_stk
with open(json_file_url_, 'w') as _f:
json.dump(_opt_record, _f)
# 返回
return return_str
def is_in_trade_time():
"""
判断是否在交易时间，即
09:30~11:30
13:00~15:00
:return:
"""
r = get_current_datetime_str()
h, m, s = r.split(' ')[1].split(':')
t = int(h + m)
if ((t > 930) & (t < 1130)) | ((t > 1300) & (t < 1500)):
return True
else:
return False
def on_timer_pic(win, pool, debug=False):
"""
图片定时器响应函数（闲置）
:return:
"""
global last_upt_t
upt_flag, last_upt_t = is_time_h_macd_update(last_upt_t)
wx.PostEvent(win, ResultEvent(id=LAST_TIME_UPDATE_ID, data=last_upt_t))
if not upt_flag:
wx.PostEvent(win, ResultEvent(id=MSG_UPDATE_ID_A, data='图片更新定时器：“小时图片”更新时间点未到！\n'))
return
# 清屏
wx.PostEvent(win, ResultEvent(id=NOTE_UPDATE_ID_S, data='检测时间：' + get_current_datetime_str() + '\n\n'))
# 生成更新的图片
wx.PostEvent(win, ResultEvent(id=MSG_UPDATE_ID_A, data='开始更新小时图片...\n'))
pic_dict = {'h_macd': gen_kind_pic('h', pool), 'h_idx': gen_kind_pic('h_idx', pool)}
wx.PostEvent(win, ResultEvent(id=HOUR_UPDATE_ID, data=pic_dict))
wx.PostEvent(win, ResultEvent(id=MSG_UPDATE_ID_A, data='小时图片更新完成！\n'))
# 拐点检测
window_flash_flag = False
for stk in list(set(read_config()['buy_stk'] + read_config()['concerned_stk'] + read_config()['index_stk'])):
# 阈值条件不满足，该stk直接pass
if not read_opt_json(stk, opt_record_file_url)['threshold_satisfied_flag']:
wx.PostEvent(win, ResultEvent(id=MSG_UPDATE_ID_A, data=code2name(stk) + '阈值条件不满足，不进行拐点检测\n'))
continue
hour_idx_str = check_single_stk_hour_idx_wx(stk, source='jq', debug=True)
if len(hour_idx_str):
window_flash_flag = True
for str_tmp in hour_idx_str:
wx.PostEvent(win, ResultEvent(id=NOTE_UPDATE_ID_A, data=change_font_color(str_tmp)))
# 窗口闪烁
if window_flash_flag:
wx.PostEvent(win, ResultEvent(id=FLASH_WINDOW_ID, data=None))
wx.PostEvent(win, ResultEvent(id=MSG_UPDATE_ID_A, data=note_sar_inflection_point))
def on_timer(self, event):
fig, ax = plt.subplots(ncols=1, nrows=1, figsize=(6, 4))
plt.title('图' + get_current_datetime_str())
output = BytesIO() # BytesIO实现了在内存中读写byte
fig.canvas.print_png(output)
# fig.savefig(output, dpi=100)
output.seek(0)
img = wx.Image(output, wx.BITMAP_TYPE_ANY)
output.close()
# plt.close()
imageRenderer = MyImageRenderer(wx.Bitmap(img))
self.grid.SetCellRenderer(0, 1, imageRenderer)
self.grid.SetColSize(1, img.GetWidth() + 2)
self.grid.SetRowSize(0, img.GetHeight() + 2)
self.frame.Refresh()
def debug_print_txt(file_name, stk, value, enable=True):
"""
:param file_name:
:param stk:
:param value:
:return:
"""
if not enable:
return
file_dir = data_dir + 'Debug_log/' + get_current_date_str()
file_url = file_dir + '/' + file_name + '_' + stk + '.txt'
# 如果文件夹不存在，创建
if not os.path.exists(file_dir):
os.makedirs(file_dir)
with open(file_url, 'a+') as f:
f.write(get_current_datetime_str() + ':\n' + value + '\n')
def down_minute_data(stk_code, freq):
try:
df = get_k_data_JQ(stk_code,
count=300,
end_date=add_date_str(get_current_date_str(),
1),
freq=freq)
# 去掉volume为空的行
df = df.loc[df.apply(lambda x: not (x['volume'] == 0), axis=1), :]
# 增加指标计算
df = add_stk_index_to_df(df)
if str(df.index[-1]) > get_current_datetime_str():
df = df[:-1]
return df
except Exception as e_:
# self.log = self.log + '函数down_minute_data：\n %s\n' % str(e_)
print('函数down_minute_data：\n %s\n' % str(e_))
return pd.DataFrame()
def plot_w_m(df_w, df_m):
"""
:param df_w:
:param df_m:
:return:
"""
""" --------------------------------------- 生成图片 -------------------------------------"""
fig, ax = subplots(ncols=1, nrows=4)
ax[0].plot(range(0, len(df_w['date'])),
df_w['close'],
'g*--',
label='close')
ax[1] = GenPic.plot_macd(ax[1], df_w, 'week')
ax[1].plot(range(0, len(df_w['date'])),
[0 for x in range(0, len(df_w['date']))],
'r--',
label='week_MACD')
ax[2].plot(range(0, len(df_m['date'])),
df_m['close'],
'g*--',
label='close')
ax[3] = GenPic.plot_macd(ax[3], df_m, 'month')
ax[3].plot(range(0, len(df_m['date'])),
[0 for x in range(0, len(df_m['date']))],
'r--',
label='month_MACD')
# 设置默认标题
title_tmp = '上次更新时间：%s' % str(get_current_datetime_str())
ax[0].set_title(title_tmp)
fig.tight_layout() # 调整整体空白
plt.subplots_adjust(wspace=0, hspace=0.15) # 调整子图间距
return fig, ax
def save_opt_info(self):
"""
将操作日志打印到json
:return:
"""
if opt_lock.acquire():
try:
opt_record.append({
'stk_code': self.stk_code,
'p_now': self.current_price,
'sale_reseau': self.thh_sale,
'buy_reseau': self.thh_buy,
'p_last': self.last_p,
# 'opt': opt,
'date_time': get_current_datetime_str()
})
except Exception as e:
print('函数 JudgeSingleStk:写入操作记录失败！原因：\n' + str(e))
finally:
opt_lock.release()
def gen_hour_macd_values(stk_code, source='jq', title=''):
if source == 'jq':
# df_30 = get_k_data_JQ(stk_code, start_date=add_date_str(get_current_date_str(), -20),
# end_date=add_date_str(get_current_date_str(), 1), freq='30m')
# df_60 = get_k_data_JQ(stk_code, start_date=add_date_str(get_current_date_str(), -20),
# end_date=add_date_str(get_current_date_str(), 1), freq='60m')
df_30 = get_k_data_JQ(stk_code, count=120,
end_date=add_date_str(get_current_date_str(), 1), freq='30m')
df_60 = get_k_data_JQ(stk_code, count=120,
end_date=add_date_str(get_current_date_str(), 1), freq='60m')
elif source == 'ts':
df_30 = my_pro_bar(stk_code, start=add_date_str(get_current_date_str(), -20), freq='30min')
df_60 = my_pro_bar(stk_code, start=add_date_str(get_current_date_str(), -20), freq='60min')
# 去掉volume为空的行
df_30 = df_30.loc[df_30.apply(lambda x: not (x['volume'] == 0), axis=1), :]
df_60 = df_60.loc[df_60.apply(lambda x: not (x['volume'] == 0), axis=1), :]
df_30['MACD'], _, _ = talib.MACD(df_30.close,
fastperiod=12, slowperiod=26,
signalperiod=9)
df_60['MACD'], _, _ = talib.MACD(df_60.close,
fastperiod=12, slowperiod=26,
signalperiod=9)
# 生成图片
df_30 = df_30.dropna()
df_60 = df_60.dropna()
if str(df_60.index[-1]) > get_current_datetime_str():
df_30 = df_30[:-1]
df_60 = df_60[:-1]
return df_30, df_60
def gen_kind_pic(kind, pool):
"""
造图片，存本地
:param kind:
h:小时
h_idx:小时idx
d:天
wm:周、月
idx: 指数
:return:
返回的图片应该 执行page和行号，便于更新！
以多层字典的方式返回结果，第一层区分page，第二层区分行号！
"""
r_dic = {'Index': {}, 'Buy': {}, 'Concerned': {}}
dict_stk_hour = copy.deepcopy(dict_stk_list)
jq_login()
""" 在外部下载需要的数据，防止多进程中重复连接聚宽 """
for page in dict_stk_hour.keys():
for stk_info in dict_stk_list[page]:
stk = stk_info[1]
if kind is 'h':
r_dic[page][stk + '_d'] = GenPic.gen_hour_macd_values(stk)
elif kind is 'h_idx':
r_dic[page][stk + '_d'] = GenPic.gen_hour_macd_values(stk)[0]
elif kind is 'd':
r_dic[page][stk + '_d'] = get_k_data_JQ(stk, 400)
elif kind is 'wm':
r_dic[page][stk + '_d'] = get_k_data_JQ(
stk, count=400).reset_index()
elif kind is 'd_idx':
r_dic[page][stk + '_d'] = get_k_data_JQ(stk, 400)
jq.logout()
""" 生成pic """
for page in dict_stk_hour.keys():
for stk_info in dict_stk_list[page]:
stk = stk_info[1]
# 保存路径
save_dir = hist_pic_dir + get_current_date_str(
) + '/' + stk + kind + '/'
file_name = get_current_datetime_str()[:-3].replace(
':', '').replace(' ', '').replace('-', '') + '.png'
if not os.path.exists(save_dir):
os.makedirs(save_dir)
if kind is 'h':
r_dic[page][stk + '_res'] = pool.apply_async(
GenPic.gen_hour_macd_pic_local,
(r_dic[page][stk + '_d'], stk, save_dir + file_name))
elif kind is 'h_idx':
r_dic[page][stk + '_res'] = pool.apply_async(
GenPic.gen_hour_index_pic_local,
(r_dic[page][stk + '_d'], stk, save_dir + file_name))
elif kind is 'd':
r_dic[page][stk + '_res'] = pool.apply_async(
GenPic.gen_day_pic_local,
(r_dic[page][stk + '_d'], stk, save_dir + file_name))
elif kind is 'wm':
r_dic[page][stk + '_res'] = pool.apply_async(
GenPic.gen_w_m_macd_pic_local,
(r_dic[page][stk + '_d'], stk, save_dir + file_name))
elif kind is 'd_idx':
r_dic[page][stk + '_res'] = pool.apply_async(
GenPic.gen_idx_pic_local,
(r_dic[page][stk + '_d'], stk, save_dir + file_name))
# if kind is 'h':
# r_dic[page][stk + '_res'] = pool.apply_async(gen_hour_macd_pic_local, (
# r_dic[page][stk + '_d'], stk, 'jq', '', save_dir + file_name))
#
# elif kind is 'h_idx':
# r_dic[page][stk + '_res'] = pool.apply_async(gen_hour_index_pic_local,
# (r_dic[page][stk + '_d'], stk, save_dir + file_name))
# elif kind is 'd':
# r_dic[page][stk + '_res'] = pool.apply_async(gen_day_pic_local,
# (r_dic[page][stk + '_d'], stk, save_dir + file_name))
# elif kind is 'wm':
# r_dic[page][stk + '_res'] = pool.apply_async(gen_w_m_macd_pic_local,
# (r_dic[page][stk + '_d'], stk, save_dir + file_name))
# elif kind is 'd_idx':
# r_dic[page][stk + '_res'] = pool.apply_async(gen_idx_pic_local,
# (r_dic[page][stk + '_d'], stk, save_dir + file_name))
# 在字典中保存图片路径
r_dic[page][stk + '_url'] = save_dir + file_name
return r_dic
def get_t_now():
r = get_current_datetime_str()
h, m, s = r.split(' ')[1].split(':')
return int(h + m)
while True:
input_str = input('输入你的命令：')
# 按空格解析命令
input_split = input_str.split(' ')
if len(input_split) == 4: # 插入命令
sql_str_no_reap = 'insert into ' +\
table_history + ' (stk_code, stk_name, amount, price, opt, input_time, reap_flag) values(' + \
"'" + input_split[0] + "'" + ',' + \
"'" + getNameByStkCode(g_total_stk_info_mysql, input_split[0]) + "'" + ',' + \
str(input_split[2]) + ',' + \
str(input_split[3]) + ',' + \
"'" + str(input_split[1]) + "'" + ',' + \
"'" + get_current_datetime_str() + "'" + ',' + \
"false" + \
');'
sql_str_reap = 'insert into ' +\
table_history + ' (stk_code, stk_name, amount, price, opt, input_time, reap_flag) values(' + \
"'" + input_split[0] + "'" + ',' + \
"'" + getNameByStkCode(g_total_stk_info_mysql, input_split[0]) + "'" + ',' + \
str(input_split[2]) + ',' + \
str(input_split[3]) + ',' + \
"'" + str(input_split[1]) + "'" + ',' + \
"'" + get_current_datetime_str() + "'" + ',' + \
"true" + \
');'
"""
300183 buy 300 13.25
# encoding=utf-8
"""
不用盖楼，复制下面的码，打开淘宝或者天猫，直接领红包，一般是几块钱，运气好的更高！
"""
note_str2 = \
"""
【快来兑换你的双11红I包，可赢额外红I包】https://m.tb.cn/h.etQyNSR?sm=64355a 嚸↑↓擊鏈ㄣ接，再选择瀏覽●噐○咑閞ヽ；或復ず■淛整句话￥orm1YuW897g￥后咑閞手机天猫
"""
qun_list = \
list(set(get_all_win_by_name('找工作'))) + \
list(set(get_all_win_by_name('军事'))) + \
list(set(get_all_win_by_name('租房')))
while (get_current_datetime_str()[-8:] >=
'06:00:00') & (get_current_datetime_str()[-8:] <= '23:00:00'):
for qun in qun_list:
try:
send_qq(qun, note_str1)
time.sleep(0.5)
send_qq(qun, note_str2)
time.sleep(0.5)
# send_qq(qun, note_str3)
# time.sleep(1.5)
print(qun + '： 消息发送成功！\n------------------------\n\n')
except Exception as e:
print(qun + '： 消息发送失败！\n原因:\n' + str(e) +
'\n------------------------\n\n')
print('\n\n================== 大循环完成 ==================\n\n完成时间：' +
def gen_hour_macd_pic(stk_data, debug=False, stk_code=''):
if debug:
print('进入GenPic.gen_hour_macd_pic函数！')
debug_print_txt('macd_hour_pic',
stk_code,
'\n----------------------\n\n',
enable=debug)
# 生成小时macd数据
# df_30, df_60 = gen_hour_macd_values(stk_code, source=source, title=title)
df_30, df_60 = stk_data
if debug:
debug_print_txt('macd_hour_pic',
stk_code,
'df_30原始数据:\n' + str(df_30) + '\n\n' +
'df_60原始数据:\n' + str(df_60) + '\n\n',
enable=debug)
# 根据情况设置背景色
m30 = df_30.tail(3)['MACD'].values
m60 = df_60.tail(3)['MACD'].values
if debug:
debug_print_txt(
'macd_hour_pic', stk_code, 'm30原始数据:\n' + str(m30) + '\n\n' +
'm60原始数据:\n' + str(m60) + '\n\n')
if (m30[1] == np.min(m30)) | (m60[1] == np.min(m60)):
# 设置背景红
GenPic.set_background_color('b_r')
elif (m30[1] == np.max(m30)) | (m60[1] == np.max(m60)):
# 设置背景绿
GenPic.set_background_color('b_g')
else:
GenPic.set_background_color()
# 调整显示长度
df_30 = df_30.tail(40)
df_60 = df_60.tail(40)
fig, ax = plt.subplots(ncols=1, nrows=4)
ax[0].plot(range(0, len(df_30)),
df_30['close'],
'g*--',
label='close_30min')
ax[1] = GenPic.plot_macd(ax[1], df_30, '30min')
ax[2].plot(range(0, len(df_60)),
df_60['close'],
'g*--',
label='close_60min')
ax[3] = GenPic.plot_macd(ax[3], df_60, '60min')
# 设置下标
ax[1] = addXticklabel_list(
ax[1],
list([str(x)[-9:-3] for x in df_30['datetime']]),
15,
rotation=0,
fontsize=6)
ax[3] = addXticklabel_list(
ax[3],
list([str(x)[-9:-3] for x in df_60['datetime']]),
15,
rotation=0,
fontsize=6)
for ax_sig in ax:
ax_sig.legend(loc='best')
# 设置默认标题
title = stk_code + ' ' + code2name(stk_code) + '/上次更新时间：%s' % str(
get_current_datetime_str())
# 设置标题
if m30[1] == np.min(m30):
title = stk_code + '半小时MACD低点！'
elif m60[1] == np.min(m60):
title = stk_code + '小时MACD低点！'
elif m30[1] == np.max(m30):
title = stk_code + '半小时MACD高点！'
elif m60[1] == np.max(m60):
title = stk_code + '小时MACD高点！'
ax[0].set_title(title)
if debug:
debug_print_txt('macd_hour_pic', stk_code, '结论:' + title + '\n\n')
fig.tight_layout()
plt.subplots_adjust(wspace=0, hspace=0.15) # 调整子图间距
return fig
# encoding=utf-8
# encoding=utf-8
def gen_idx_pic(stk_df, stk_code=''):
"""
打印常用指标
"""
# 按升序排序
stk_df = stk_df.sort_values(by='date', ascending=True)
"""
增加指标
'RSI5', 'RSI12', 'RSI30'
'SAR'
'slowk', 'slowd'
'upper', 'middle', 'lower'
'MOM'
"""
stk_df_ = add_stk_index_to_df(stk_df).tail(60)
GenPic.set_background_color(bc='w')
result_analysis = []
# 检查SAR
attention = False
sar_tail_origin = stk_df_.tail(2)
sar_tail = sar_tail_origin.copy()
sar_tail['compare'] = sar_tail_origin.apply(
lambda x: x['SAR'] - x['close'], axis=1)
title_tmp = stk_code + ' ' + code2name(stk_code)
if sar_tail.head(1)['compare'].values[0] * sar_tail.tail(
1)['compare'].values[0] < 0:
if sar_tail.tail(1)['SAR'].values[0] < sar_tail.tail(
1)['close'].values[0]:
title_tmp = stk_code + ' ' + code2name(
stk_code) + ' 注意 SAR 指标翻转，后续数天可能上涨！'
result_analysis.append(title_tmp +
RankNote.print_day_close_rank(stk_df))
GenPic.set_background_color(bc='b_r')
else:
title_tmp = stk_code + ' ' + code2name(
stk_code) + ' 注意 SAR 指标翻转，后续数天可能下跌！'
result_analysis.append(title_tmp +
RankNote.print_day_close_rank(stk_df))
GenPic.set_background_color(bc='b_g')
attention = True
fig, ax = plt.subplots(nrows=5, ncols=1)
ax[0].plot(range(0, len(stk_df_['date'])),
stk_df_['RSI5'],
'b--',
label='RSI5线',
linewidth=1)
ax[0].plot(range(0, len(stk_df_['date'])),
stk_df_['RSI12'],
'r--',
label='RSI12线',
linewidth=1)
ax[0].plot(range(0, len(stk_df_['date'])),
stk_df_['RSI30'],
'g*--',
label='RSI30',
linewidth=0.5,
markersize=1)
ax[0].plot(range(0, len(stk_df_['date'])),
[20 for a in range(len(stk_df_['date']))],
'b--',
linewidth=0.3)
ax[0].plot(range(0, len(stk_df_['date'])),
[80 for a in range(len(stk_df_['date']))],
'b--',
linewidth=0.3)
ax[0].set_ylim(0, 100)
ax[1].plot(range(0, len(stk_df_['date'])),
stk_df_['SAR'],
'r--',
label='SAR',
linewidth=0.5,
markersize=1)
ax[1].plot(range(0, len(stk_df_['date'])),
stk_df_['close'],
'g*--',
label='close',
linewidth=0.5,
markersize=1)
ax[2].plot(range(0, len(stk_df_['date'])),
stk_df_['slowk'],
'g*--',
label='slowk',
linewidth=0.5,
markersize=1)
ax[2].plot(range(0, len(stk_df_['date'])),
stk_df_['slowd'],
'r*--',
label='slowd',
linewidth=0.5,
markersize=1)
ax[2].plot(range(0, len(stk_df_['date'])),
[20 for a in range(len(stk_df_['date']))],
'b--',
linewidth=0.3)
ax[2].plot(range(0, len(stk_df_['date'])),
[80 for a in range(len(stk_df_['date']))],
'b--',
linewidth=0.3)
ax[2].set_ylim(0, 100)
ax[3].plot(range(0, len(stk_df_['date'])),
stk_df_['upper'],
'r*--',
label='布林上线',
linewidth=0.5,
markersize=1)
ax[3].plot(range(0, len(stk_df_['date'])),
stk_df_['middle'],
'b*--',
label='布林均线',
linewidth=0.5,
markersize=1)
ax[3].plot(range(0, len(stk_df_['date'])),
stk_df_['lower'],
'g*--',
label='布林下线',
linewidth=0.5,
markersize=1)
ax[4].plot(range(0, len(stk_df_['date'])),
stk_df_['MOM'],
'g*--',
label='MOM',
linewidth=0.5,
markersize=1)
# 准备下标
xlabel_series = stk_df_.apply(lambda x: x['date'][2:].replace('-', ''),
axis=1)
ax[4] = add_axis(ax[4], xlabel_series, 40, rotation=45, fontsize=10)
# 设置默认标题
title_tmp = stk_code + ' ' + code2name(stk_code) + '/上次更新时间：%s' % str(
get_current_datetime_str())
ax[0].set_title(title_tmp)
for ax_sig in ax:
ax_sig.legend(loc='best', fontsize=5)
fig.tight_layout() # 调整整体空白
plt.subplots_adjust(wspace=0, hspace=0) # 调整子图间距
ax[0].set_title(title_tmp)
return fig, ax, attention, result_analysis
# encoding=utf-8
def gen_day_pic(stk_df, stk_code=''):
"""
函数功能：给定stk的df，已经确定stk当前处于拐点状态，需要将当前stk的信息打印成图片，便于人工判断！
:param stk_df 从tushare下载下来的原生df
:param root_save_dir 配置文件中定义的存储路径
:return: 返回生成图片的路径
"""
"""
规划一下都画哪些图
1、该stk整体走势，包括60日均线、20日均线和收盘价
2、stk近几天的MACD走势
"""
"""
在原数据的基础上增加均线和MACD
"""
# 按升序排序
stk_df = stk_df.sort_values(by='date', ascending=True)
stk_df['M20'] = stk_df['close'].rolling(window=20).mean()
stk_df['M60'] = stk_df['close'].rolling(window=60).mean()
stk_df['MACD'], stk_df['MACDsignal'], stk_df['MACDhist'] = talib.MACD(
stk_df.close, fastperiod=12, slowperiod=26, signalperiod=9)
# 检查日级别的MACD是否有异常
attention = False
MACD_list = stk_df.tail(3)['MACD'].values
if MACD_list[1] == np.min(MACD_list):
attention = True
# 设置背景红
GenPic.set_background_color('b_r')
elif MACD_list[1] == np.max(MACD_list):
attention = True
# 设置背景绿
GenPic.set_background_color('b_g')
else:
GenPic.set_background_color()
fig, ax = plt.subplots(nrows=4, ncols=1)
ax[0].plot(range(0, len(stk_df['date'])),
stk_df['M20'],
'b--',
label='20日均线',
linewidth=1)
ax[0].plot(range(0, len(stk_df['date'])),
stk_df['M60'],
'r--',
label='60日均线',
linewidth=1)
ax[0].plot(range(0, len(stk_df['date'])),
stk_df['close'],
'g*--',
label='收盘价',
linewidth=0.5,
markersize=1)
# ax[1].bar(range(0, len(stk_df['date'])), stk_df['MACD'], label='MACD')
ax[1] = GenPic.plot_macd(ax[1], stk_df, 'day')
# 准备下标
xticklabels_all_list = list(stk_df['date'].sort_values(ascending=True))
xticklabels_all_list = [
x.replace('-', '')[2:] for x in xticklabels_all_list
]
for ax_sig in ax[0:2]:
ax_sig = addXticklabel_list(ax_sig,
xticklabels_all_list,
30,
rotation=45)
ax_sig.legend(loc='best', fontsize=5)
# 画出最近几天的情况（均线以及MACD）
stk_df_current = stk_df.tail(plot_current_days_amount)
ax[2].plot(range(0, len(stk_df_current['date'])),
stk_df_current['M20'],
'b--',
label='20日均线',
linewidth=2)
ax[2].plot(range(0, len(stk_df_current['date'])),
stk_df_current['M60'],
'r--',
label='60日均线',
linewidth=2)
ax[2].plot(range(0, len(stk_df_current['date'])),
stk_df_current['close'],
'g*-',
label='收盘价',
linewidth=1,
markersize=5)
ax[3] = GenPic.plot_macd(ax[3], stk_df_current, 'day')
# 设置默认标题
title_tmp = stk_code + ' ' + code2name(stk_code) + '/上次更新时间：%s' % str(
get_current_datetime_str())
ax[0].set_title(title_tmp)
# 设置标题并返回分析结果
result_analysis = []
if MACD_list[1] == np.min(MACD_list):
title_tmp = stk_code + ' ' + code2name(
stk_code) + ' 日级别 MACD 低点！后续数天可能上涨！'
ax[0].set_title(title_tmp)
result_analysis.append(title_tmp +
RankNote.print_day_close_rank(stk_df))
elif MACD_list[1] == np.max(MACD_list):
title_tmp = stk_code + ' ' + code2name(
stk_code) + ' 日级别 MACD 高点！后续数天可能下跌！'
ax[0].set_title(title_tmp)
result_analysis.append(title_tmp +
RankNote.print_day_close_rank(stk_df))
# 准备下标
xticklabels_all_list = list(
stk_df_current['date'].sort_values(ascending=True))
xticklabels_all_list = [
x.replace('-', '')[4:] for x in xticklabels_all_list
]
for ax_sig in ax[2:4]:
ax_sig = addXticklabel_list(ax_sig,
xticklabels_all_list,
25,
rotation=0)
ax_sig.legend(loc='best', fontsize=2.5)
fig.tight_layout() # 调整整体空白
plt.subplots_adjust(wspace=0, hspace=0.15) # 调整子图间距
# plt.close()
return fig, ax, attention, result_analysis
# coding=utf-8
def prepare_trade_record(self, input_str, json_file_url_):
# 返回字符串
return_str = []
# 已有文件，打开读取
if os.path.exists(json_file_url_):
with open(json_file_url_, 'r') as _f:
_opt_record = json.load(_f)
else:
_opt_record = {}
# 解析输入
stk_code, opt, amount, p = input_str.split(' ')
#stk_code = name2code(stk_name)
stk_name = code2name(stk_code)
p, amount = float(p), float(amount)
# 对输入格式进行检查
#debug_print_txt('main_log', '', input_str +' ' + json_file_url_ + 'inside prepare_trade_record \n',True)
if amount % 100 != 0:
#tc.AppendText('格式错误！参考格式：\n美的集团 卖出 400 51.3')
return
if stk_code in _opt_record.keys():
opt_r_stk = _opt_record[stk_code]
else:
opt_r_stk = {
'b_opt': [],
's_opt': [],
'b_suggest': None,
's_suggest': None,
'p_last': None,
'has_flashed_flag': False,
'total_earn': 0,
'last_prompt_point': -1
}
# 初步只支持每日一次操作
if opt_r_stk['has_flashed_flag'] == True:
return
if opt == '买入':
opt_r_stk['b_opt'].clear()
opt_r_stk['b_opt'].append(dict(time=get_current_datetime_str(), p=p, amount=amount, status='PRICE', entrust_no=0))
opt_r_stk['b_suggest'] = stk_name + ' 真买 ' + '%0.0f' % amount + ' ' + str(p)
if opt == '卖出':
#if len(opt_r_stk['b_opt']) > 0:
opt_r_stk['s_opt'].clear()
opt_r_stk['s_opt'].append(dict(time=get_current_datetime_str(), p=p, amount=amount, status='PRICE', entrust_no=0))
opt_r_stk['s_suggest'] = stk_name + ' 真卖 ' + '%0.0f' % amount + ' ' + str(p)
#opt_r_stk, earn_this = sale_stk_sub(opt_r_stk, amount, p, tc)
#return_str.append('earn：' + str(earn_this) + '\n')
opt_r_stk['p_last'] = p
opt_r_stk['has_flashed_flag'] = False
# 保存数据
_opt_record[stk_code] = opt_r_stk
with open(json_file_url_, 'w') as _f:
#json.dump(_opt_record, _f)
json.dump(_opt_record, _f, ensure_ascii=False, indent = 2, separators=(',', ': '))
# 返回
#debug_print_txt('main_log', '', stk_code +' end of prepare_trade_record \n',True)
return return_str
def time_now():
print(str(get_current_datetime_str()))
# encoding=utf-8
