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TimingTasksDriver.py
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TimingTasksDriver.py
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# -*- coding: utf-8 -*-
# @Time : 2020-03-21 11:55
# @Author : Dingzh.tobest
# 文件描述 ： jenkins定时任务驱动程序
# 调用接口，并形成html文件，用于返回每日计算数据
import requests
import json
import os
import sys
import base64
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.pylab import datestr2num
plt.rcParams['font.family'] = ['sans-serif']
plt.rcParams['font.sans-serif'] = ['SimHei']
host_address = 'http://127.0.0.1:8000'
html_template = """
<tr>
<td>%s</td>
<td>%s</td>
<td>%.2f</td>
<td>%.2f</td>
<td>%.2f</td>
<td>%s</td>
<td>%s</td>
<td>%s</td>
<td>%.2f</td>
<td>%s</td>
<td>%s</td>
<td>%s</td>
<td>%.2f</td>
<td>%s</td>
<td>%s</td>
<td>%s</td>
</tr>"""
COLOR_VERY_LOW = '#00FF00'
COLOR_LOW = '#F0E68C'
COLOR_HIGH = '#87CEEB'
COLOR_VERY_HIGH = '#FF4500'
pic_base64 = "data:image/png;base64,"
# 调用每日计算函数
def call_calc_index_analysis_info():
addr = host_address + '/timingtask/calc_index_analysis_info'
r = requests.post(addr)
if r.status_code == 200:
result = json.loads(r.text)
print(result['result'])
else:
raise Exception('更新每日数据接口【call_calc_index_analysis_info】调用失败')
def get_color(ttm_5y, ttm_10y, ttm_history):
ttm_now_color = ''
ttm_percentage_10y_color = ''
ttm_percentage_history_color = ''
if ttm_10y != '' and float(ttm_10y[:-1]) > 60:
if float(ttm_10y[:-1]) > 90:
color_str = COLOR_VERY_HIGH
else:
color_str = COLOR_HIGH
ttm_percentage_10y_color = color_str
ttm_now_color = color_str
elif ttm_10y != '' and float(ttm_10y[:-1]) < 30:
if float(ttm_10y[:-1]) < 10:
color_str = COLOR_VERY_LOW
else:
color_str = COLOR_LOW
ttm_percentage_10y_color = color_str
ttm_now_color = color_str
elif ttm_history != '' and ttm_5y != '' and ttm_10y == '' and float(
ttm_history[:-1]) > 60:
if float(ttm_history[:-1]) > 90:
color_str = COLOR_VERY_HIGH
else:
color_str = COLOR_HIGH
ttm_percentage_history_color = color_str
ttm_now_color = color_str
elif ttm_history != '' and ttm_5y != '' and ttm_10y == '' and float(
ttm_history[:-1]) < 30:
if float(ttm_history[:-1]) < 10:
color_str = COLOR_VERY_LOW
else:
color_str = COLOR_LOW
ttm_percentage_history_color = color_str
ttm_now_color = color_str
return ttm_now_color, ttm_percentage_10y_color, ttm_percentage_history_color
# 调用全部指数的计算结果，生成html结果文件
def call_index_analysis_info_result():
addr = host_address + '/stock/get_stock_info'
r = requests.get(addr)
if r.status_code == 200:
resutl = json.loads(r.text)
html = ""
# 用于存储转化后的数据对象
last_update_date = ""
index_analysis_list = []
for index_info in resutl['index_info_list']:
index_info_dict = {}
info = index_info['fields']
# 拼装返回html的字段
index_name = info['index_name']
start_date = info['start_date']
print('正在获取数据的指数：' + index_name)
# 获取数据的请求参数
aparam = {'index_code': info['index_data_table']}
addr_analysis = host_address + '/stock/get_index_analysis_info'
ar = requests.get(addr_analysis, params=aparam)
if ar.status_code != 200:
raise Exception('获取指数信息【get_index_analysis_info】调用失败：' + info['index_data_table'])
analysis_info = json.loads(ar.text)
history_max_pe = analysis_info['history_max_pe']
history_min_pe = analysis_info['history_min_pe']
pe_ttm_now = analysis_info['pe_ttm_now']
pe_ttm_percentage = analysis_info['pe_ttm_percentage']
pe_ttm_percentage_5y = analysis_info['pe_ttm_percentage_5y']
pe_ttm_percentage_10y = analysis_info['pe_ttm_percentage_10y']
pe_ttm_now_color, pe_ttm_percentage_10y_color, pe_ttm_percentage_color = get_color(pe_ttm_percentage_5y, pe_ttm_percentage_10y, pe_ttm_percentage)
last_update_date = analysis_info['last_analysis_date']
pb_ttm_now = analysis_info['pb_ttm_now']
pb_ttm_percentage = analysis_info['pb_ttm_percentage']
pb_ttm_percentage_5y = analysis_info['pb_ttm_percentage_5y']
pb_ttm_percentage_10y = analysis_info['pb_ttm_percentage_10y']
pb_ttm_now_color, pb_ttm_percentage_10y_color, pb_ttm_percentage_color = get_color(pb_ttm_percentage_5y, pb_ttm_percentage_10y, pb_ttm_percentage)
ps_ttm_now = analysis_info['ps_ttm_now']
ps_ttm_percentage = analysis_info['ps_ttm_percentage']
ps_ttm_percentage_5y = analysis_info['ps_ttm_percentage_5y']
ps_ttm_percentage_10y = analysis_info['ps_ttm_percentage_10y']
# 用于生成数据存储的json数据
index_info_dict['index_code'] = info['index_code']
index_info_dict['index_data_table'] = info['index_data_table']
index_info_dict['index_name'] = index_name
index_info_dict['start_date'] = start_date
index_info_dict['history_max_pe'] = history_max_pe
index_info_dict['history_min_pe'] = history_min_pe
index_info_dict['pe_ttm_now'] = pe_ttm_now
index_info_dict['pe_ttm_percentage'] = pe_ttm_percentage
index_info_dict['pe_ttm_percentage_5y'] = pe_ttm_percentage_5y
index_info_dict['pe_ttm_percentage_10y'] = pe_ttm_percentage_10y
index_info_dict['pb_ttm_now'] = pb_ttm_now
index_info_dict['pb_ttm_percentage'] = pb_ttm_percentage
index_info_dict['pb_ttm_percentage_5y'] = pb_ttm_percentage_5y
index_info_dict['pb_ttm_percentage_10y'] = pb_ttm_percentage_10y
index_info_dict['ps_ttm_now'] = ps_ttm_now
index_info_dict['ps_ttm_percentage'] = ps_ttm_percentage
index_info_dict['ps_ttm_percentage_5y'] = ps_ttm_percentage_5y
index_info_dict['ps_ttm_percentage_10y'] = ps_ttm_percentage_10y
index_analysis_list.append(index_info_dict)
# 用于生成邮件返回的html信息
temp_html = "<tr>"
temp_html += "<td>%s</td>" % index_name
temp_html += "<td>%s</td>" % start_date
temp_html += "<td>%.2f</td>" % history_max_pe
temp_html += "<td>%.2f</td>" % history_min_pe
if pe_ttm_now_color == '':
temp_html += "<td>%.2f</td>" % pe_ttm_now
else:
temp_html += "<td bgcolor=\"%s\">%.2f</td>" % (pe_ttm_now_color, pe_ttm_now)
temp_html += "<td>%s</td>" % pe_ttm_percentage_5y
if pe_ttm_percentage_10y_color == '':
temp_html += "<td>%s</td>" % pe_ttm_percentage_10y
else:
temp_html += "<td bgcolor=\"%s\">%s</td>" % (pe_ttm_percentage_10y_color, pe_ttm_percentage_10y)
if pe_ttm_percentage_color == '':
temp_html += "<td>%s</td>" % pe_ttm_percentage
else:
temp_html += "<td bgcolor=\"%s\">%s</td>" % (pe_ttm_percentage_color, pe_ttm_percentage)
if pb_ttm_now_color == '':
temp_html += "<td>%.2f</td>" % pb_ttm_now
else:
temp_html += "<td bgcolor=\"%s\">%.2f</td>" % (pb_ttm_now_color, pb_ttm_now)
temp_html += "<td>%s</td>" % pb_ttm_percentage_5y
if pb_ttm_percentage_10y_color == '':
temp_html += "<td>%s</td>" % pb_ttm_percentage_10y
else:
temp_html += "<td bgcolor=\"%s\">%s</td>" % (pb_ttm_percentage_10y_color, pb_ttm_percentage_10y)
if pb_ttm_percentage_color == '':
temp_html += "<td>%s</td>" % pb_ttm_percentage
else:
temp_html += "<td bgcolor=\"%s\">%s</td>" % (pb_ttm_percentage_color, pb_ttm_percentage)
temp_html += "<td>%.2f</td>" % ps_ttm_now
temp_html += "<td>%s</td>" % ps_ttm_percentage_5y
temp_html += "<td>%s</td>" % ps_ttm_percentage_10y
temp_html += "<td>%s</td>" % ps_ttm_percentage
temp_html += "</tr>"
html += temp_html
# 生成数据存储的json文件
index_data_dict = {'last_update_date': last_update_date, 'index_analysis_list' : index_analysis_list}
# index_analysis_json = json.dumps(index_data_dict, ensure_ascii=False)
json_file_path = sys.path[0] + '\\index-analysis-data.json'
print(json_file_path)
if os.path.exists(json_file_path):
os.remove(json_file_path)
print('删除历史文件index-analysis-data.json')
with open(json_file_path, 'w', encoding='utf-8') as f:
f.write(json.dumps(index_data_dict, ensure_ascii=False, indent=4))
# 生成邮件发送的html文件
print(html)
print(sys.path[0] + '\\email-template.html')
f = open(sys.path[0] + '\\email-template.html', 'r', encoding='utf-8')
html_temp = f.read()
f.close()
email_html = html_temp.replace('#$%index_analysis_info#$%', html)
email_html = email_html.replace('#$%pic_base64#$%', pic_base64)
if os.path.exists(sys.path[0] + '\\email-html-utf8.html'):
os.remove(sys.path[0] + '\\email-html-utf8.html')
print('删除历史文件email-html-utf8.html')
f2 = open(sys.path[0] + '\\email-html-utf8.html', 'w', encoding='utf-8')
f2.write(email_html)
f2.close()
if os.path.exists(sys.path[0] + '\\email-html.html'):
os.remove(sys.path[0] + '\\email-html.html')
print('删除历史文件email-html.html')
temp_email_html = email_html
f3 = open(sys.path[0] + '\\email-html.html', 'w', encoding='gb18030')
gbk_email_html = str(temp_email_html.encode('gbk'), encoding="gbk")
f3.write(gbk_email_html)
f3.close()
print('生成用于返回email的html文件成功！')
else:
raise Exception('获取指数信息【get_stock_info】调用失败')
# 调用每日计算函数
def get_bond_stocks_pe_infos():
addr = host_address + '/stock/get_stocks_bonds_pe'
r = requests.get(addr)
if r.status_code == 200:
result = json.loads(r.text)
pe_history = json.loads(result['pe_history'])
data = pd.DataFrame(pe_history)
data['bond_yield'] = 100 / data['bond_pe']
data['stock_yield'] = 100 / data['stocks_pe']
x = range(len(data))
x_date = [datestr2num(i) for i in data['trade_date']]
plt.style.use('ggplot')
plt.figure(figsize=(14, 4))
plt.title("10年期国债收益率与全市场股票收益率(%)")
plt.xticks(rotation=45)
plt.ylabel("收益率")
plt.plot_date(x_date, data['bond_yield'], '-', label="10年期国债收益率")
plt.plot_date(x_date, data['stock_yield'], '-', label="全市场股票收益率")
plt.legend()
plt.grid(True)
pic_path = sys.path[0] + '\\bond_stocks_yield.png'
if os.path.exists(pic_path):
os.remove(pic_path)
print('删除历史文件bond_stocks_yield.png')
print('生成图片：' + pic_path)
plt.savefig(pic_path) # 保存图片
with open(pic_path, "rb") as f:
base64_data = base64.b64encode(f.read())
global pic_base64
pic_base64 = pic_base64 + str(base64_data)[2:-1]
print('将图片转化为base64')
print(pic_base64)
else:
raise Exception('更新每日数据接口【get_bond_stocks_pe_infos】调用失败')
if __name__ == '__main__':
# 每日数据计算
call_calc_index_analysis_info()
# 股债收益率
get_bond_stocks_pe_infos()
# 指数分析数据
call_index_analysis_info_result()