-
Notifications
You must be signed in to change notification settings - Fork 22
/
get_day_all_stock_infov3.py
executable file
·153 lines (124 loc) · 3.68 KB
/
get_day_all_stock_infov3.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
#
# exec script
# 计算股票昨日涨跌 前50，和100日之前的涨跌对比
# tushare 接口
import os
import sys
import signal
import threading,time
import queue
import pandas as pd
from datetime import datetime
import tushare as ts
import config
import argparse
# 判断是否 是显示，还是重新下载数据计算
# 数据每天只需要下载一次
parser = argparse.ArgumentParser()
parser.add_argument("--display", help="显示本地数据",default='0')
args = parser.parse_args()
display = args.display
####################
#1. 获取股票数据
####################
tspro = ts.pro_api(config.tspro['passwd'])
today = datetime.now()
endday = str(today.year) + str(today.month) + str(today.day)
# print 打印color 表
HEADER = '\033[95m'
OKBLUE = '\033[94m'
OKGREEN = '\033[92m'
WARNING = '\033[93m'
FAIL = '\033[91m'
ENDC = '\033[0m'
BOLD = '\033[1m'
UNDERLINE = '\033[4m'
#所有的股票表计算后的数据表
all_up_down_list=[]
# 处理异常，在出现异常的时候存盘
def handler(signum, frame):
print("是不是想让我退出啊")
make_save_data()
sys.exit()
#存盘并且打印
def make_save_data():
df = pd.DataFrame(all_up_down_list, columns = ['昨日收盘','前日收盘','百日收盘','昨日涨跌','百日涨跌','名称','代码'])
df.to_csv("./datas/stock_up_down_{0}.csv".format(endday),float_format='%.2f',index_label="序号")
#仅仅显示
def display_save_data():
df= pd.read_csv("./datas/stock_up_down_{0}.csv".format(endday))
df = df.sort_values(by="昨日涨跌",ascending=False)
print(df.iloc[0:50])
df = df.sort_values(by="百日涨跌",ascending=False)
print(df.iloc[0:50])
def upordown(code,name):
#df = ts.get_hist_data(code,start='2020-05-01')
df = tspro.daily(ts_code=code, start_date='20200501')
if len(df) < 2:
return
lastday = df.index[0]
lastday2 = df.index[1]
closeld = float(df.close[lastday])
closeld2 = float(df.close[lastday2])
closeld100 = 0.0
delta100 = 0.0
if len(df) > 99:
closeld100 = float(df.close[df.index[99]])
delta100 = float((closeld-closeld100) / closeld100 ) * 100.0
print(OKBLUE)
print("%.2f %.2f %.2f %.2f %.2f %s %s" %(closeld,closeld2,
closeld100,
(closeld-closeld2)/closeld2 * 100.0,
delta100,
name,code)
)
print(ENDC)
all_up_down_list.append([
closeld,closeld2,
closeld100,
(closeld-closeld2)/closeld2 * 100.0,
delta100,
name,code
])
#获取股票的名字和代码号
def getstockinfo(stock):
#2019-12-09,sz.002094,青岛金王,化工,申万一级行业
# 时间，股票代码，名称，类别
d,code,name,skip1,skip2 = stock.split(',')
shsz = code.split('.')[0]
code = code.split('.')[1]
if shsz == 'sh':
shsz = '.SH'
if shsz == 'sz':
shsz = '.SZ'
return code+shsz,name
#获取所有的股票并下载数据
def get_data_thread(n):
for stock in stocklist:
code ,name = getstockinfo(stock)
print('正在获取',name,'代码',code)
q.put((code,name))
q.task_done()
#
# 程序开始，监听信号
#
signal.signal(signal.SIGINT, handler)
signal.signal(signal.SIGHUP, handler)
signal.signal(signal.SIGTERM, handler)
q = queue.Queue()
# 判断是否已经下载了股票分类代码
if not os.path.exists('./datas/stock_industry_check.csv'):
print('正在下载股票库列表....')
os.system('python3 bs_get_industry_check.py')
stocklist = open('./datas/stock_industry_check.csv').readlines()
stocklist = stocklist[1:] #删除第一行
# 判断是仅仅显示，还是需要下载数据计算
if display == '1':
display_save_data()
else :
threading.Thread(target=get_data_thread,args=(1,)).start()
while True:
code,name = q.get()
print('正在分析',name,'代码',code)
upordown(code,name)
make_save_data()