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Copy path南向资金分析工具.py
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南向资金分析工具.py
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'''
author by :[email protected]
申明：根据此程序分析做出的买卖，本人不承担投资损失，投资有风险，买卖需谨慎！！
1。数据更新（去取库里的最新日期与网上的最新日期比较，较旧更新数据，否提示数据最新）
2。当日持股变动最大前10股票查询
3。开始净买股票查询
4。个股数据展示（输入名称或代码）
5。退出'''
import bs4, datetime
import requests as req
import re, json, time, sys
import prettytable as pt # 格式化成表格输出到html文件
import tushare as ts
import webbrowser # 打开浏览器
import pymysql
import pandas as pd
from lxml import etree
from pyecharts.charts import Bar, Page, Line
from pyecharts import options as opts
from TradeDay import tradeday
import akshare as ak #api 使用：https://akshare-4gize6tod19f2d2e-1252952517.tcloudbaseapp.com/index.html
from dboprater import DB as db
'''手动安装 talib 去https://www.lfd.uci.edu/~gohlke/pythonlibs/#ta-lib 下载对应的版本“TA_Lib‑0.4.19‑cp37‑cp37m‑win_amd64.whl” 然后 pip3 install TA_Lib‑0.4.19‑cp37‑cp37m‑win_amd64.whl'''
import talib #Technical Analysis Library”, 即技术分析库 是Python金融量化的高级库，涵盖了150多种股票、期货交易软件中常用的技术分析指标，如MACD、RSI、KDJ、动量指标、布林带等等。
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec#分割子图
import mpl_finance as mpf # python中可以用来画出蜡烛图、线图的分析工具，目前已经从matplotlib中独立出来，非常适合用来画K线
from optparse import OptionParser
class southwardAnalysis():
database = 'stock'
tablename = 'southdataanly'
configfile = './config/mysqlconfig.json'
pro = None
jsoncontent = None
def __init__(self):
self.jsoncontent = db.get_config()
self.pro = ts.pro_api(self.jsoncontent['tushare'])
def get_optparse(self):
parser = OptionParser()
parser.add_option("-1", "--updatedata", type='int', dest="1", help="数据更新")
parser.add_option("-2", "--top10inscrese", type='int', dest="2", help="当日持股变动最大前10股票查询")
parser.add_option("-3", "--northbuy", type='int', dest="3", help="南资开始净买股票查询")
parser.add_option("-4", "--stockview", type='int', dest="4", help="个股南资数据展示（输入名称或代码）")
parser.add_option("-5", "--F10", type='int', dest="5", help="打开个股F0（输入名称代码）")
parser.add_option("-6", "--stockbuybank", type='int', dest="6", help="个股持股比例Top10经纪商查询")
parser.add_option("-0", "--0", type='int', dest="0", help="退出")
parser.add_option("-q", "--quiet",action="store_false", dest="verbose", default=True,help="退出")
(options, args) = parser.parse_args()
return options, args
def get_proxy(self):
url = 'https://ip.jiangxianli.com/api/proxy_ip'
try:
r = req.get(url=url)
except BaseException as b:
count = 0
while True:
count += 1
try:
r = req.get(url=url)
if r.status_code != 200:
continue
else:
break
if count >= 3:
break
except BaseException as c:
continue
jsontext = r.json()['data']
ip = jsontext['ip']
port = jsontext['port']
protocol = jsontext['protocol']
proxy = {str(protocol).lower(): str(protocol).lower() + '://' + ip + ':' + port}
return proxy
# 获取南向数据总页数
def get_pages(self, headers, url, params):
response = req.get(url=url, headers=headers, params=params).text
regx = 'pages:(\d{0,3})'
pages = re.findall(regx, response)[0]
return int(pages)
# 获取最新的数据日期
def get_page_newdate(self):
url = 'http://dcfm.eastmoney.com/em_mutisvcexpandinterface/api/js/get?&type=HSGTTRDT&st=DATE&sr=-1&token=894050c76af8597a853f5b408b759f5d&p=1&ps=1'
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.111 Safari/537.36'}
response = req.get(url=url, headers=headers).text
regx = '(\d{4}-\d{2}-\d{2})'
date = re.findall(regx, response, re.M)[0]
return str(date)
# 写文件
def WriteFile(self, southdatainfos):
data = pd.DataFrame(southdatainfos,
columns=['日期', '股票代码 ', '股票名称 ', '持股数亿', '占比', '收盘价 ', '当日涨跌幅 ', '持股市值亿 ', '一日市值变化亿',
'五日市值变化亿', '十日市值变化亿'])
data = data.to_csv()
southdatafile = '南向资金数据.txt'
with open(southdatafile, 'w', encoding='utf-8') as fw:
fw.write(str(data))
# 获取所有南向资金数据
def getsouth(self):
# url='http://data.eastmoney.com/hsgtcg/lz.html'
url = 'http://dcfm.eastmoney.com/EM_MutiSvcExpandInterface/api/js/get'
headers = {
'Accept': '*/*',
'Accept-Encoding': 'gzip, deflate',
'Accept-Language': 'zh - CN, zh; q = 0.9, en; q = 0.8 ',
'Connection': 'keep-alive',
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.111 Safari/537.36',
'Cookie': 'pgv_pvi=3794568192; _qddaz=QD.6ofmf2.j6jr4m.kat8wucp; ct=u_GCXp_V0BUfw6EE3hFHtqMglz3afgkppJcv5vbFImFCEcWBrdbJ1czxMgSRvdgdMHMxnKracqlOZgxC4VNfwrkiwCCnYCNVFUzHMie-NyeUGcc8-NdJwvaXLimNiEt9gsOQO3q161JU2fTSAHZYRo5byr67JKvMwuA_2qSbhls; ut=FobyicMgeV5ghfUPKWOH5wak5fe7PCdYa2maZFrymrOdfN-wAEFtpNp1MzH070EBSmKRLG6vmIcYwEk2SvuUDiGwHB7BHzpaN3m4xMthhPoNqi89FTByaNH4MkRCfEYW4JX960vY0ITlmRY-cPk1PQzTvxCYnVj0Ey0NtYOnUdj24K9O1_tKWeyEDf1k_bIV6hcX360Qn8yYsWTrETZTzGYR7tn62AgnDFAq58DbSa3StLkggc5c7wB94try8c_WEpaHHyl5rA7BBAJZkje3dZ7Q7pZSUWri; pi=3323115305075326%3bc3323115305075326%3b%e8%82%a1%e5%8f%8bjHWZa22110%3bAc4gMB%2bahzpZU8kVvDCm4%2f9QLFcpRepVrDlj4DSAFvQS9L41u5PjbhW1g0ATNFBs2U6jdaiAi0v97coryIUwYaBWyHAUTbi1GDBZdDmkrBugnCGTBDTgPjXURUbrtmze597viYIL2RjHQTBKDzTIQqxuco%2b4pIMvD3B%2f2gF3Z2HSKCRGXGX%2bMcFxewJmIXD8wOJYtqii%3bM4Rnsdjx0lNLDrlCNBv6VhW13wgvkjpsoKd52WM1JsrPCSqUd%2fySTvks6nwUjCNsGby4fYU2Y%2bbjGtRBVly22B%2bqdAhoqGh6XrZIWQGX4LDnpd4CKtckek2Rlq7r9qjcQSdzcprF%2bmmkr9EqKBQVnmt9ppYRhg%3d%3d; uidal=3323115305075326%e8%82%a1%e5%8f%8bjHWZa22110; sid=126018279; _ga=GA1.2.1363410539.1596117007; em_hq_fls=js; AUTH_FUND.EASTMONEY.COM_GSJZ=AUTH*TTJJ*TOKEN; emshistory=%5B%22%E4%BA%BA%E6%B0%94%E6%8E%92%E8%A1%8C%E6%A6%9C%22%2C%22%E6%AF%94%E4%BA%9A%E8%BF%AA%E4%BA%BA%E6%B0%94%E6%8E%92%E5%90%8D%22%2C%22%E5%9F%BA%E9%87%91%E6%8E%92%E8%A1%8C%22%2C%22%E8%BF%913%E4%B8%AA%E6%9C%88%E8%B7%8C%E5%B9%85%E6%9C%80%E5%A4%A7%E7%9A%84%E5%9F%BA%E9%87%91%22%2C%22%E5%85%BB%E8%80%81%E9%87%91%E6%8C%81%E8%82%A1%E5%8A%A8%E5%90%91%E6%9B%9D%E5%85%89%22%2C%22%E5%A4%96%E7%9B%98%E6%9C%9F%E8%B4%A7%22%2C%22A50%22%2C%22%E6%81%92%E7%94%9F%E6%B2%AA%E6%B7%B1%E6%B8%AF%E9%80%9A%E7%BB%86%E5%88%86%E8%A1%8C%E4%B8%9A%E9%BE%99%E5%A4%B4A%22%2C%22%E7%BB%86%E5%88%86%E8%A1%8C%E4%B8%9A%E9%BE%99%E5%A4%B4%22%5D; vtpst=%7c; HAList=d-hk-00288%2Cd-hk-00772%2Cf-0-399006-%u521B%u4E1A%u677F%u6307%2Ca-sz-002008-%u5927%u65CF%u6FC0%u5149%2Ca-sz-002739-%u4E07%u8FBE%u7535%u5F71%2Cf-0-000001-%u4E0A%u8BC1%u6307%u6570%2Cd-hk-00981%2Ca-sz-002082-%u4E07%u90A6%u5FB7%2Ca-sz-300511-%u96EA%u6995%u751F%u7269; st_si=85201197981579; cowCookie=true; waptgshowtime=2021121; qgqp_b_id=3a2c1ce1f45a81a3fa7cc2fbad8e2a24; st_asi=delete; intellpositionL=581px; st_pvi=03400063938128; st_sp=2020-05-23%2013%3A48%3A35; st_inirUrl=https%3A%2F%2Fwww.baidu.com%2Flink; st_sn=60; st_psi=2021012310245852-113300303605-1019447906; intellpositionT=2133.55px'
}
params = {'type': 'HSGTHDSTA',
'token': '894050c76af8597a853f5b408b759f5d',
'filter': '(MARKET=\'S\')',
'st': 'HDDATE',
'sr': -1,
'p': 1,
'ps': 50,
'js': 'var duMsdwGU={pages:(tp),data:(x)}',
'rt': '53908160'}
# 获取北向数据总页数
pages = self.get_pages(headers, url, params)
print('共有数据 %d 页，请稍等......' %pages)
southdatainfos = []
for i in range(1, pages+1, 1): # 南向数据每天只有10页的数据量(取总量)
params = {'type': 'HSGTHDSTA',
'token': '894050c76af8597a853f5b408b759f5d',
'filter': '(MARKET=\'S\')',
'st': 'HDDATE',
'sr': -1,
'p': i,
'ps': 50,
'js': 'var duMsdwGU={pages:(tp),data:(x)}',
'rt': '53908160'}
try:
response = req.get(url=url, headers=headers, params=params)
except BaseException as BE:
print('第%s页 访问异常，重试中！' %i)
time.sleep(2)
count=0
while count<6:
try:
response = req.get(url=url, headers=headers, params=params,proxies=self.get_proxy())
except BaseException as B2:
print(B2)
if response.status_code!=200:
count+1
print('第 %s 次重试获取 %s 页数据异常！' %(count,i))
time.sleep(5)
else:
print('重试成功！！！')
break
bstext = bs4.BeautifulSoup(response.content, 'lxml')
tempdata = bstext.find_all('p')
temp = str(tempdata)
regex = 'data:(.*?)}</p>'
jsondata = str(re.findall(regex, temp, re.M))
# print((jsondata))
data = jsondata.replace('\\r\\n', '', -1).replace('},', '}},', -1).replace('[\'[', '', -1).replace(
']\']', '', -1)
listdata = data.split('},', -1)
# print(listdata)
header = ['日期', '股票代码 ', '股票名称 ', '持股数亿', '占比', '收盘价 ', '当日涨跌幅 ', '持股市值亿 ', '一日市值变化亿', '五日市值变化亿',
'十日市值变化亿']
# print(len(listdata))
'''data: [{
"HDDATE": "2020-12-30T00:00:00", 日期
"HKCODE": "1000145950",
"SCODE": "00700", 代码
"SNAME": "腾讯控股", 名称
"SHAREHOLDSUM": 425931727.0, 持股数
"SHARESRATE": 4.43,占比
"CLOSEPRICE": 559.5,收盘价
"ZDF": 5.4665,当日涨跌幅
"SHAREHOLDPRICE": 238308801256.5, 持股市值
"SHAREHOLDPRICEONE": 19102759903.0,一日市值变化
"SHAREHOLDPRICEFIVE": 2113479276.5,五日市值变化
"SHAREHOLDPRICETEN": 3843934536.5,十日市值变化 '''
southdatainfos.append(listdata)
# print('第%d页下载成功' %i)
time.sleep(1)
print('所有南向数据下载成功！！')
# self.WriteFile(southdatainfos) # 将查询到的数据写一份到本地文件
# 将数据写到文件，以便读取使用，免得每次都要去网上爬，造成大量访问
return southdatainfos
#获取港股日线数据
def getHK_stockQuotes(self,scode):
data = ak.stock_hk_daily(symbol=scode, adjust="qfq") #qfq： 前复权 hfq:后复权
data=pd.DataFrame(data)
return data
# 将下载的数据写数据库
def insertdb(self, southdatainfos):
if len(southdatainfos) == 0:
return
conn = db.dbconnect()
cursor = conn.cursor(cursor=pymysql.cursors.DictCursor)
# 由于每次取的是全量数据，先将表清空
sql1 = 'delete from southdataanly'
cursor.execute(sql1)
conn.commit()
# 执行的sql语句
sql = '''insert into southdataanly (HDDATE,SCODE,SNAME,SHAREHOLDSUM,SHARESRATE,CLOSEPRICE,ZDF,SHAREHOLDPRICE,SHAREHOLDPRICEONE,SHAREHOLDPRICEFIVE,SHAREHOLDPRICETEN) values (%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)'''
for datalist in southdatainfos:
for row in datalist: # 依次获取每一行数据
try:
jsdata = json.loads(row)
HDDATE = str(jsdata['HDDATE'])[0:10]
SCODE = jsdata['SCODE']
SNAME = jsdata['SNAME']
SHAREHOLDSUM = format(jsdata['SHAREHOLDSUM'] / 100000000, '.3f')
SHARESRATE = jsdata['SHARESRATE']
CLOSEPRICE = jsdata['CLOSEPRICE']
ZDF = jsdata['ZDF']
SHAREHOLDPRICE = format(jsdata['SHAREHOLDPRICE'] / 100000000, '.3f')
SHAREHOLDPRICEONE = format(jsdata['SHAREHOLDPRICEONE'] / 100000000, '.3f')
SHAREHOLDPRICEFIVE = format(jsdata['SHAREHOLDPRICEFIVE'] / 100000000, '.3f')
SHAREHOLDPRICETEN = format(jsdata['SHAREHOLDPRICETEN'] / 100000000, '.3f')
values = (
HDDATE, SCODE, SNAME, SHAREHOLDSUM, SHARESRATE, CLOSEPRICE, ZDF, SHAREHOLDPRICE,
SHAREHOLDPRICEONE,
SHAREHOLDPRICEFIVE, SHAREHOLDPRICETEN)
cursor.execute(sql, values)
# print(values,sql)
except BaseException as be:
# print(be)
continue
conn.commit()
conn.commit()
conn.close()
# 按条件查询持续比例与持股市值
def selectdb(self, **kwords): # **kwords :表示可以传入多个键值对， *kwords:表示可传入多个参数
conditions = str(kwords).strip('{').strip('}').replace(':', '=', 1).replace('\'', '', 2)
print(conditions)
conn = db.dbconnect()
cursor = conn.cursor(cursor=pymysql.cursors.DictCursor)
# 执行的sql语句
sql = '''select HDDATE,SCODE,SNAME,SHAREHOLDSUM,SHARESRATE,CLOSEPRICE,ZDF,SHAREHOLDPRICE,SHAREHOLDPRICEONE,SHAREHOLDPRICEFIVE,SHAREHOLDPRICETEN from southdataanly '''
sql = sql + 'where ' + conditions + ' order by HDDATE '
# print(sql)
cursor.execute(sql)
resultset = cursor.fetchall()
cursor.close()
conn.close()
if resultset:
return resultset
else:
print('未查询到数据')
return None
# 查询当最后一个交易日净买前10
def Select_top10(self): # **kwords :表示可以传入多个键值对， *kwords:表示可传入多个参数
newdate = self.get_page_newdate()
# outdate = datetime.datetime.strptime(newdate, "%Y-%m-%d")
# yesterday = str((outdate + datetime.timedelta(days=-1)).strftime("%Y-%m-%d"))
sql = 'select * from southdataanly where Hddate=\'' + newdate + '\' order by SHAREHOLDPRICEONE desc limit 10'
# print(sql)
conn = db.dbconnect()
cursor = conn.cursor(cursor=pymysql.cursors.DictCursor)
cursor.execute(sql)
resultset = cursor.fetchall()
# print(resultset)
if resultset:
return resultset
else:
print('数据不是最新，请更新数据！')
# return None
cursor.close()
conn.close()
return resultset
# 查询开始净买入个股
def Select_Netpurchases(self): # **kwords :表示可以传入多个键值对， *kwords:表示可传入多个参数
newdate = self.get_page_newdate()
outdate = datetime.datetime.strptime(newdate, "%Y-%m-%d")
# yesterday = str((outdate + datetime.timedelta(days=-1)).strftime("%Y-%m-%d"))
yesterday=tradeday.getyestodayTradeday(outdate)
print(newdate,yesterday)
sql = 'select * from southdataanly where hddate=\'' + newdate + '\'and SHAREHOLDPRICEONE>1 and SHAREHOLDPRICEFIVE>-2 and zdf >-2 and SCODE in ( select SCODE from southdataanly where hddate=\'' + yesterday + '\' and SHAREHOLDPRICEONE<0 ) order by SHAREHOLDPRICEFIVE desc'
# print(sql)
conn = db.dbconnect()
cursor = conn.cursor(cursor=pymysql.cursors.DictCursor)
# print(sql)
cursor.execute(sql)
resultset = cursor.fetchall()
if resultset:
return resultset
else:
print('无满足条件数据！')
# return None
cursor.close()
conn.close()
return resultset
# 获取A股日线数据
def get_stock_dateData(self, stockcode, start_date, end_date):
if stockcode[0:2] == '600' or stockcode[0:2] == '68':
stockcode = stockcode + '.SH'
else:
stockcode = stockcode + '.SZ'
# 从tushare 获取日线数据
df = self.pro.daily(ts_code=stockcode, start_date=start_date, end_date=end_date)
df = df.sort_values(by=['trade_date'], ascending=True) # 按日期升序
return df
# 将查询到的数据分析后输出到html
def rendertohtml(self, resultset):
page=Page()
if resultset is None:
print('无数据')
return None
header = ['日期', '股票代码 ', '股票名称 ', '持股数亿', '占比', '收盘价 ', '当日涨跌幅 ', '持股市值亿 ', '一日市值变化亿', '五日市值变化亿', '十日市值变化亿']
tb = pt.PrettyTable()
tb.field_names = header # 设置表头
tb.align = 'c' # 对齐方式（c:居中，l居左，r:居右）
c = Line()
x = ['持股占比']
name = ''
HDDATELIST = []
SHAREHOLDSUMlist = [] # 持股数
SHARESRATElist = [] # 持股占比
SHAREHOLD = [] # 持股数量
zdflist = []
SHAREHOLDPRICEONElist = []
SHAREHOLDPRICEFIVElist = []
SHAREHOLDPRICETENlsit = []
# 取出占比数据
for data in resultset:
# print(data)
HDDATE = data['HDDATE']
# HDDATE = datetime.datetime.strptime(HDDATE1, '%Y-%m-%d').strftime('%Y%m%d')
HDDATELIST.append(HDDATE)
SCODE = data['SCODE']
SHAREHOLDSUM = data['SHAREHOLDSUM']
SHAREHOLDSUMlist.append(SHAREHOLDSUM)
SNAME = data['SNAME']
SHARESRATE = data['SHARESRATE']
SHARESRATElist.append(SHARESRATE)
CLOSEPRICE = data['CLOSEPRICE']
ZDF = data['ZDF']
zdflist.append(ZDF)
SHAREHOLDPRICE = format(data['SHAREHOLDPRICE'], '.3f')
SHAREHOLDPRICEONE = format(data['SHAREHOLDPRICEONE'], '.3f')
SHAREHOLDPRICEONElist.append(SHAREHOLDPRICEONE)
SHAREHOLDPRICEFIVE = format(data['SHAREHOLDPRICEFIVE'], '.3f')
SHAREHOLDPRICEFIVElist.append(SHAREHOLDPRICEFIVE)
SHAREHOLDPRICETEN = format(data['SHAREHOLDPRICETEN'], '.3f')
SHAREHOLDPRICETENlsit.append(SHAREHOLDPRICETEN)
tb.add_row(
[HDDATE, SCODE, SNAME, SHAREHOLDSUM, SHARESRATE, CLOSEPRICE, ZDF, SHAREHOLDPRICE, SHAREHOLDPRICEONE,
SHAREHOLDPRICEFIVE, SHAREHOLDPRICETEN])
OUTFILE = '南向资金_' + SNAME + '.html'
# print(SHARESRATE)
x1 = HDDATELIST
y1 = SHARESRATElist # 将占比数据设置为y轴
y2 = SHAREHOLDSUMlist
y3 = zdflist
y4 = SHAREHOLDPRICEONElist
y5 = SHAREHOLDPRICEFIVElist
y6 = SHAREHOLDPRICETENlsit
# y2 = [1000, 300, 500]
# bar = Bar()
# 设置x轴
c.add_xaxis(xaxis_data=x)
c.add_xaxis(xaxis_data=x1)
# 设置y轴
c.add_yaxis(series_name='持股百分比', y_axis=y1)
# c.add_yaxis(series_name='持股数量亿', y_axis=y2)
# c.add_yaxis(series_name='涨跌幅', y_axis=y3)
c.add_yaxis(series_name='1日市值变动亿', y_axis=y4)
c.add_yaxis(series_name='5日市值变动亿', y_axis=y5)
c.add_yaxis(series_name='10日市值变动亿', y_axis=y6)
c.set_global_opts(title_opts=opts.TitleOpts(title='南向资金持股分析: ' + SNAME))
# 生成html文件
# c.render(path=OUTFILE)
page.add(c)
page.render(path=OUTFILE)
# 如果要输出柱图
'''
bar = Bar()
然后将c 换成bar
'''
#获取港股日线数据并画K线图
getstockdata=self.getHK_stockQuotes(SCODE)
if len(getstockdata)<90:
getstockdata=getstockdata
else:
getstockdata=getstockdata.tail(90) #只后90行
# print(getstockdata)
if getstockdata.items == None:
kline=''
else:
# getstockdata['trade_date'] = pd.to_datetime(getstockdata.index) # 设置字段trade_date 为datetime
# getstockdata = getstockdata.set_index('trade_date') # 设置trade_date为索引
index=getstockdata.index.tolist()
# getstockdata.sort_values(by=[getstockdata.index().to_list,'close'],ascending=False)
# 设置四个绘图区域 包括 K线（均线），成交量，MACD
np.seterr(divide='ignore', invalid='ignore') # 忽略warning
plt.rcParams['font.sans-serif'] = ['SimHei'] # 用来正常显示中文标签
plt.rcParams['axes.unicode_minus'] = False # 用来正常显示负号
fig, ax = plt.subplots(figsize=(9, 6)) # 创建fig对象
# 画绘图区域
gs = gridspec.GridSpec(2, 1, left=0.08, bottom=0.15, right=0.99, top=0.96, wspace=None, hspace=0,
height_ratios=[3.5, 1])
# 添加指标
graph_KAV = fig.add_subplot(gs[0, :]) # K线图
graph_VOL = fig.add_subplot(gs[1, :])
# graph_MACD = fig.add_subplot(gs[2, :])
# graph_KDJ = fig.add_subplot(gs[3, :])
mpf.candlestick2_ochl(graph_KAV, getstockdata.open, getstockdata.close, getstockdata.high, getstockdata.low,
width=0.5, colorup='r', colordown='g') # 绘制K线走势
# mpf.plot(getstockdata.iloc[:100],type='candle') # 绘制K线走势
# 绘制移动平均线图
getstockdata['Ma5'] = getstockdata.close.rolling(
window=5).mean() # pd.rolling_mean(df_stockload.close,window=20)
getstockdata['Ma10'] = getstockdata.close.rolling(
window=10).mean() # pd.rolling_mean(df_stockload.close,window=30)
getstockdata['Ma20'] = getstockdata.close.rolling(
window=20).mean()
graph_KAV.plot(np.arange(0, len(index)), getstockdata['Ma5'], 'black', label='M5', lw=1.0)
graph_KAV.plot(np.arange(0, len(index)), getstockdata['Ma10'], 'green', label='M10', lw=1.0)
graph_KAV.plot(np.arange(0, len(index)), getstockdata['Ma20'], 'blue', label='M20', lw=1.0)
# 添加网格
graph_KAV.grid()
graph_KAV.legend(loc='best')
graph_KAV.set_title(SCODE + ' ' + SNAME + '(日线)')
graph_KAV.set_ylabel(u"价格")
graph_KAV.set_xlim(0, len(index)) # 设置一下x轴的范围
# 绘制成交量图
graph_VOL.bar(np.arange(0, len(index)), getstockdata.volume,
color=['g' if getstockdata.open[x] > getstockdata.close[x] else 'r' for x in
range(0, len(index))])
graph_VOL.set_ylabel(u"成交量")
graph_VOL.set_xlim(0, len(index)) # 设置一下x轴的范围
graph_VOL.set_xticks(range(0, len(index), 1)) # X轴刻度设定 每1天标一个日期
# X-轴每个ticker标签都向右倾斜45度
for label in graph_KAV.xaxis.get_ticklabels():
label.set_visible(False)
for label in graph_VOL.xaxis.get_ticklabels():
label.set_visible(True)
label.set_fontsize(10)
plt.savefig('./Kline.jpg')
kline = '''<img src=./Kline.jpg />'''
# 将数据也输出到文件
s = tb.get_html_string()
with open(OUTFILE, 'a+', encoding='utf-8') as fw:
fw.write(kline)
fw.write(s)
fw.close()
webbrowser.open(OUTFILE) # 调用浏览器打开文件
# 获取表中最新的日期
def getdb_maxdate(self):
sql = 'select max(HDDATE) as "HDDATE" from southdataanly '
conn = db.dbconnect()
cursor = conn.cursor(cursor=pymysql.cursors.DictCursor)
cursor.execute(sql)
result = cursor.fetchall()
# print(result)
for data in result:
data1 = data['HDDATE']
cursor.close()
conn.close()
if data1 is None:
print('表中无数据，请更新数据')
return None
return str(data1)
# 比较数据是否为最新的
def compare_Date(self):
isnewdate = True
pagedate = self.get_page_newdate()
dbdate = self.getdb_maxdate()
if dbdate is None:
return False
if pagedate > dbdate:
isnewdate = False
else:
isnewdate = True
return isnewdate
# 格式化成table
def SouthdataFormat(self, resultset):
# print(resultset)
if resultset is None:
print('无数据')
return None
header = ['日期', '股票代码 ', '股票名称 ', '持股数亿', '占比', '收盘价 ', '当日涨跌幅 ', '持股市值亿 ', '一日市值变化亿', '五日市值变化亿', '十日市值变化亿']
tb = pt.PrettyTable()
tb.field_names = header # 设置表头
tb.align = 'c' # 对齐方式（c:居中，l居左，r:居右）
for data in resultset:
HDDATE = data['HDDATE']
SCODE = data['SCODE']
SHAREHOLDSUM = data['SHAREHOLDSUM']
SNAME = data['SNAME']
SHARESRATE = data['SHARESRATE']
CLOSEPRICE = data['CLOSEPRICE']
ZDF = data['ZDF']
SHAREHOLDPRICE = format(data['SHAREHOLDPRICE'], '.3f')
SHAREHOLDPRICEONE = format(data['SHAREHOLDPRICEONE'], '.3f')
SHAREHOLDPRICEFIVE = format(data['SHAREHOLDPRICEFIVE'], '.3f')
SHAREHOLDPRICETEN = format(data['SHAREHOLDPRICETEN'], '.3f')
tb.add_row(
[HDDATE, SCODE, SNAME, SHAREHOLDSUM, SHARESRATE, CLOSEPRICE, ZDF, SHAREHOLDPRICE, SHAREHOLDPRICEONE,
SHAREHOLDPRICEFIVE, SHAREHOLDPRICETEN])
print(tb.get_string())
#打开F0
def openF10(self,code):
url = 'https://finance.futunn.com/?code=%s&market=hk&skin=1&clienttype=10&direction=1#/profile'
if code.isdigit():
url=url %code
webbrowser.open(url)
else:
pass
#获取经纪商持股数据
def get_participant(self,code, **defineDate):
url = 'https://sc.hkexnews.hk/TuniS/www.hkexnews.hk/sdw/search/searchsdw_c.aspx'
today = time.strftime('%Y-%m-%d', time.localtime())
today = datetime.datetime.strptime(today, "%Y-%m-%d")
if defineDate:
yesterday = defineDate['date']
else:
yesterday =tradeday.getyestodayTradeday(today)
print(today, yesterday)
tb = pt.PrettyTable()
tb.align = 'l' # 对齐方式（c:居中，l居左，r:居右）
page = Page()
c = Line()
data = {
'today': today,
'__EVENTTARGET': 'btnSearch',
'__EVENTARGUMENT': '',
'txtShareholdingDate': yesterday,
'txtStockCode': code,
'txtStockName': '',
'txtParticipantID': '',
'txtParticipantName': ''
}
requst = req.session()
response = requst.post(url=url, data=data)
tree = etree.HTML(response.text)
code = code
txtStockName = tree.xpath('//input[@name="txtStockName"]/@value')
if txtStockName ==[]:
print('无数据,请确认此股票是否存在')
return
txtStockName = txtStockName[0]
print(code, txtStockName)
head = tree.xpath(
'//div[@id="pnlResultNormal"]/div[@class="search-details-table-container table-mobile-list-container"]//table/thead/tr')
header = []
for line in head:
participantid = line.xpath('./th[@data-column-class="col-participant-id"]/text()')[0] # 机构编号
participantname = line.xpath('./th[@data-column-class="col-participant-name"]/text()')[0] # 机构名称
address = line.xpath('./th[@data-column-class="col-address"]/text()')[0] # 机构地址
shareholding = line.xpath('./th[@data-column-class="col-shareholding"]/text()')[0] # 持股数量
shareholding_percent = \
str(line.xpath('./th[@data-column-class="col-shareholding-percent"]/text()')[0]).split('/')[-1][2:].strip() # 持股百分比
header.append(participantid)
header.append(participantname)
# header.append(address)
header.append(shareholding)
header.append(shareholding_percent)
data = []
tempdata = tree.xpath(
'//div[@id="pnlResultNormal"]/div[@class="search-details-table-container table-mobile-list-container"]//table/tbody//tr')
i = 0
for line in tempdata:
i += 1
if i == 10:
break
else:
participantid = line.xpath('./td[@class="col-participant-id"]/div[2]/text()')[0]
participantname = line.xpath('./td[@class="col-participant-name"]/div[2]/text()')[0]
# address=line.xpath('./td[@class="col-address"]/div[2]/text()')[0]
shareholding = line.xpath('./td[@class="col-shareholding text-right"]/div[2]/text()')[0]
shareholding_percent = line.xpath('./td[@class="col-shareholding-percent text-right"]/div[2]/text()')[0]
dict = {'机构编号': participantid, '机构名称': participantname, '持股数量': shareholding, '持股百分比': shareholding_percent}
tb.add_row([participantid, participantname, shareholding, shareholding_percent])
data.append(dict)
pdf = pd.DataFrame(data)
tb.field_names = header # 设置表头
print(tb.get_string())
# print(pdf)
return pdf
def mainMenu(self):
print(
'*****************************************************************************************************\r\n')
print('\t 1。数据更新')
print('\t 2。当日持股变动最大前10股票查询')
print('\t 3。南资开始净买股票查询 ')
print('\t 4。个股南资数据展示（输入名称或代码）')
print('\t 5。个股F10')
print('\t 6。个股持股比例Top10经纪商查询')
print('\t 0。退出\r\n')
print(
'*****************************************************************************************************\r\n')
#主循环入口
def main(self):
SNAME = '建设银行'
SNAME = '小米集团-W'
options,args=self.get_optparse()
var = sys.argv # 可以接收从外部传入参数
while True:
if len(var) > 1:
var1 = str(var[1]).strip(' ')
if var1=='1':
isnew = self.compare_Date() # 判断是否要更新数据
if isnew:
print('数据已是最新')
break
else:
print('数据更新中！')
pagedata = self.getsouth()
self.insertdb(pagedata)
print('数据更新成功！！！')
break
SNAME = var[1]
if SNAME.isdigit():
resultset = self.selectdb(SCODE=SNAME) # 按代码查询南向资金占比
self.SouthdataFormat(resultset)
self.rendertohtml(resultset)
break
else:
resultset = self.selectdb(SNAME=SNAME) # 按名称查询南向资金占比
self.SouthdataFormat(resultset)
self.rendertohtml(resultset)
break
else:
self.mainMenu() #显示主菜单
try:
choise = int(input('请输入：'))
except BaseException as BE:
choise = int(input('输入错误，请重新输入 ：'))
if choise in range(7):
if choise == 1:
isnew = self.compare_Date() # 判断是否要更新数据
if isnew:
print('数据已是最新')
else:
print('数据更新中！')
pagedata = self.getsouth()
self.insertdb(pagedata)
print('数据更新成功！！！')
elif choise == 2:
resultset = self.Select_top10()
self.SouthdataFormat(resultset)
elif choise == 3:
resultset = self.Select_Netpurchases() # 查询南资开始净买的股票
self.SouthdataFormat(resultset)
elif choise == 4:
SNAME = str(input('请输入股票名称或代码:\t')).strip()
if SNAME =='':
SNAME = str(input('请输入股票名称或代码:\t')).strip()
if SNAME.isdigit():
resultset = self.selectdb(SCODE=SNAME) # 按代码查询南向资金占比
self.SouthdataFormat(resultset)
else:
if SNAME=='':
continue
resultset = self.selectdb(SNAME=SNAME) # 按名称查询南向资金占比
self.SouthdataFormat(resultset)
self.rendertohtml(resultset)
elif choise == 5:
SNAME = str(input('请输入股票代码:\t'))
self.openF10(SNAME)
elif choise == 6:
hkcode = str(input('请输入股票代码:\t'))
Hddate = input('请输入要查询的数据日期，E.g: 2021-02-10 默认为最新 \t')
if Hddate:
try:
if ":" in Hddate:
time.strptime(Hddate, "%Y-%m-%d")
else:
time.strptime(Hddate, "%Y-%m-%d")
except:
print('日期输入错误！')
continue
self.get_participant( hkcode, date=Hddate)
else:
self.get_participant(hkcode)
elif choise == 0 or choise=='quit' or choise=='exit' or choise=='q':
exit(0)
else:
print('输入错误\n')
choise = int(input('请输入：'))
if __name__ == '__main__':
Analys = southwardAnalysis()
Analys.main()
# data=Analys.getHK_stockQuotes('00981')
# print(data.sort_values(data.index),'desc')
'''
CREATE TABLE IF NOT EXISTS `southdataanly`(
HDDATE date,
SCODE varchar(8),
SNAME varchar(20),
SHAREHOLDSUM float,
SHARESRATE float,
CLOSEPRICE float,
ZDF float,
SHAREHOLDPRICE float,
SHAREHOLDPRICEONE float,
SHAREHOLDPRICEFIVE float,
SHAREHOLDPRICETEN float
)ENGINE=InnoDB DEFAULT CHARSET=utf8;
create index southdataanlycode on southdataanly(SCODE);
create index southdataanlyHdDate on southdataanly(HDDATE);
create index southdataanlySName on southdataanly(SNAME);
'''