目標：不做蠟燭圖，只用折線圖繪圖，繪出四條線之間的關系。
注：未使用接口，僅爬蟲學習，不做任何違法操作。
1 """
2 新浪財經，爬取歷史股票數據 3 """
4
5 # -*- coding:utf-8 -*-
6
7 import numpy as np 8 import urllib.request, lxml.html 9 from urllib.request import urlopen 10 from bs4 import BeautifulSoup 11 import re, time 12 import matplotlib.pyplot as plt 13 from datetime import datetime 14 # 繪圖顯示中文設置
15 plt.rcParams['font.sans-serif'] = ['SimHei'] 16 plt.rcParams['axes.unicode_minus'] = False 17
18
19 # 公共模塊，請求頭信息
20 def public(link): 21 r = urllib.request.Request(link) 22
23 ug = 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/49.0.2623.221 Safari/537.36 SE 2.X MetaSr 1.0'
24
25 r.add_header('User-Agent', ug) 26
27 cookie = "SUB=_2AkMsqZjif8NxqwJRmfkRxG7nZYpzyg_EieKa9Wk5JRMyHRl-yD83qkJatRB6Bym2DDqPE870e3uMsySIjHjrMbMNxNqk; " \ 28 "SUBP=0033WrSXqPxfM72-Ws9jqgMF55529P9D9WFXmxLGpAG5k05lCJw6qgYe; " \ 29 "SINAGLOBAL=172.16.92.24_1542789082.401113; " \ 30 "Apache=172.16.92.24_1542789082.401115; UOR=www.baidu.com,blog.sina.com.cn,; " \ 31 "ULV=1542789814434:1:1:1:172.16.92.24_1542789082.401115:; U_TRS1=000000d1.1f4d3546.5bf53673.955fa32e; " \ 32 "U_TRS2=000000d1.1f593546.5bf53673.736853cc; FINANCE2=661413ac85cadaab72ec7e3d842d6a3a; _s_upa=1"
33
34 r.add_header("Cookie", cookie) 35
36 html = urllib.request.urlopen(r, timeout=500).read() 37
38 bsObj = BeautifulSoup(html, "lxml") # 將html對象轉化為BeautifulSoup對象
39
40 return bsObj 41
42
43 # 獲取股票價格
44 def shares_price(code, year, quarter): 45 link = "http://money.finance.sina.com.cn/corp/go.php/vMS_MarketHistory/stockid/%s.phtml?year=%d&jidu=%d" % (code, year, quarter) 46
47 bsObj = public(link) 48 # print(bsObj)
49
50 a = 0 51 # date_list為日期列表，open_list為開盤價列表，high_list為最高價列表，close_list為收盤價列表，low_list為最低價列表
52 price_list, date_list, open_list, high_list, close_list, low_list = [], [], [], [], [], [] 53 # 獲取股票信息
54 jpg_title = re.findall("(.*?\))", bsObj.title.text) 55
56 prices_bs = bsObj.find_all(name='div', attrs={"align": 'center'}) 57 # 獲取並處理價格信息
58 for price_bs in prices_bs: 59 # 去除空格
60 price_bs_1 = price_bs.text.replace("\n\r\n\t\t\t", "") 61 price_bs_2 = price_bs_1.replace("\t\t\t\n", "") 62
63 # 6個字符串為一個列表
64 if a != 6: 65 price_list.append(price_bs_2) 66 a = a + 1
67 else: 68 date_list.append(price_list[0]) 69 open_list.append(price_list[1]) 70 high_list.append(price_list[2]) 71 close_list.append(price_list[3]) 72 low_list.append(price_list[4]) 73 a = 0 74 price_list = [] 75 # 刪除列表頭
76 for b in (date_list, open_list, high_list, close_list, low_list): 77 b.pop(0) 78
79 # 全部倒序排列（由日期遠到近，從左到右排列）
80 for c in (date_list, open_list, high_list, close_list, low_list): 81 c.reverse() 82
83 return date_list, open_list, high_list, close_list, low_list, jpg_title 84
85
86 # 輸入股票代碼，年份，季度
87 code = "002925"
88 year = "2018"
89 quarter = 4
90 # 以下為手動輸入模式，因調試方便默認上面固定模式。
91 # code = input("code：") # 002925
92 # year = input("year：") # 2018
93 # quarter = int(input("quarter："))
94
95 # 列表字符串轉為數值date
96 x = [datetime.strptime(d, '%Y-%m-%d').date() for d in shares_price(code, int(year), quarter)[0]] 97 # 將爬取的數據（字符串）轉化為浮點型
98 open_list = [float(i) for i in shares_price(code, int(year), quarter)[1]] 99 high_list = [float(i) for i in shares_price(code, int(year), quarter)[2]] 100 close_list = [float(i) for i in shares_price(code, int(year), quarter)[3]] 101 low_list = [float(i) for i in shares_price(code, int(year), quarter)[4]] 102
103 # 線條設置
104 plt.plot(x, open_list, label='open', linewidth=1, color='red', marker='o', markerfacecolor='blue', markersize=2) 105 plt.plot(x, high_list, label='high', linewidth=1, color='green', marker='o', markerfacecolor='blue', markersize=2) 106 plt.plot(x, close_list, label='close', linewidth=1, color='blue', marker='o', markerfacecolor='blue', markersize=2) 107 plt.plot(x, low_list, label='low', linewidth=1, color='black', marker='o', markerfacecolor='blue', markersize=2) 108
109 # 取數列最大數值與最小值做圖表的邊界值。
110 plt.ylim(min(low_list)-1, max(high_list)+1) 111 plt.gcf().autofmt_xdate() # 自動旋轉日期標記
112
113 # 打印表頭
114 plt.xlabel('time') 115 plt.ylabel('price') 116 # shares_price(code, int(year), quarter)[5][0]為title中的股票名稱與代碼
117 plt.title('gp_1_{0}.jpg'.format(shares_price(code, int(year), quarter)[5][0])) 118 plt.legend() 119 plt.show()
效果如下：
是不是有另一種看法的感覺？如：黑線下跌后向上的第一個大拐點為買入點。