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概念与早盘数据查询.py 5.38 KB
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金诺 提交于 2021-07-18 13:07 . 调整结构
import 早盘数据入库 as indb
import prettytable as pt #useage:https://www.cnblogs.com/Mr-Koala/p/6582299.html
import pymysql
import pyecharts #可视化图表输出 useage:https://blog.csdn.net/update7/article/details/89086454
import sys
from dboprater import DB as db
outfile='stockopendata.html' #输出到文件
####################输出分析图表#####################################
def outmap(dataframe):
bar=pyecharts.charts.Bar()
bar.add_dataset(dataframe)
bar.render()
####################以表格的形式输出##################################
def formatresults(tablename,results,header):
#results 查询到的数据集
#header 要输出的表头
tb = pt.PrettyTable()
tb.field_names=header #设置表头
tb.align='l' #对齐方式(c:居中,l居左,r:居右)
#tb.sortby = "日期"
#tb.set_style(pt.DEFAULT)
#tb.horizontal_char = '*'
fw=open(outfile,'w',encoding='utf-8')
if tablename=='stockopendata':
for row in results: # 依次获取每一行数据
date = row['date'] # 第1列
# print(date)
code = row['code']
name = row['name']
kaipanhuanshuoz = row['kaipanhuanshuoz']
kaipanjine = row['kaipanjine']
liangbi = row['liangbi']
xianliang = row['xianliang']
liutongsizhi = row['liutongsizhi']
liutongguyi = row['liutongguyi']
xifenhangye = row['xifenhangye']
# # 打印结果
# print('%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t' % (
# date, code, name, kaipanhuanshuoz, kaipanjine, liangbi, xianliang, liutongsizhi, liutongguyi, xifenhangye))
tb.add_row([date,code,name,kaipanhuanshuoz,kaipanjine,liangbi,xianliang,liutongsizhi,liutongguyi,xifenhangye])
print('记录条数:\t',len(results))
if tablename=='stockinfo':
for row in results: # 依次获取每一行数据
#print(row)
#date = row['date'] # 第1列
# print(date)
mcode = row['mcode']
code = row['code']
name = row['name']
mark = row['mark']
markname=row['markname']
info = str(row['info']).strip()
if len(info)>65:
info = str(row['info']).strip()[0:65]
#value = row['value']
# # 打印结果
# print('%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t' % (
# date, code, name, kaipanhuanshuoz, kaipanjine, liangbi, xianliang, liutongsizhi, liutongguyi, xifenhangye))
tb.add_row([mcode,code,name,mark,markname,info])
s=tb.get_html_string() #获取html格式
print(s,file=fw)
print(tb)
#outmap(tb)
#######################根据条件查询mysql中的数据#######################
def dataselect(tablename,*condiction,**keyscondiction):
#dict=indb.file2dict(indb.configfile) #读取配置信息
conn=db.dbconnect()
cursor= conn.cursor(cursor=pymysql.cursors.DictCursor) #打开游标
condictions= str(keyscondiction).strip('{').strip('}').replace(':','=',1).replace('\'','',2)
#print('condiction',condiction)
#print('keyscondiction',keyscondiction)
if len(condiction) >= 1:
condictions=str(condiction).strip('(').strip(')').replace('\"','',-1).rstrip(',');
#print(condictions)
#condictions =str(condiction).strip('(').strip(')')
if tablename == 'stockopendata':
sql="select date,code ,name ,kaipanhuanshuoz,kaipanjine,liangbi,xianliang,liutongsizhi,liutongguyi,xifenhangye " \
"from "+ tablename +" where "+condictions+";"
if tablename=='stockinfo':
sql = "select code,name,mark,gsld,zycpmc,gainan from " + tablename + " where " + condictions + ";"
#print(sql)
#print(sql)
try:
# 执行SQL语句
cursor.execute(sql)
# fetchall()获取所有记录,形成的是元组,results = cursor.fetchmany(10)获取前10条,results = cursor.fetchone()获取一条数据
results = cursor.fetchall()
#print(results)
if tablename=='stockopendata':
header= ['日期', '股票代码 ', '股票名称 ', '开盘换手Z', '开盘金额', '量比 ', '现量 ', '流通市值 ', '流通股本(亿)', '细分行业']
if tablename=='stockinfo':
header = ['市场代码', '股票代码 ','股票名称', '信息ID','信息名称', '对应信息']
formatresults(tablename,results,header) #格式化输出
except BaseException as be:
print(be)
print("Error: unable to fetch data")
cursor.close()
if __name__ == '__main__':
tablename1='stockopendata'
tablename2='stockinfo'
var=sys.argv #可以接收从外部传入参数
#查个股概念信息,或某概念包含的股票信息
lon=len(var)
if lon==2:
var1=sys.argv[1]
dataselect(tablename2, var1)
elif lon<2:
var1=r"gainan like '%降解塑料%'"
dataselect(tablename2,var1) #传入要查询的条件,例如:name="中直股份‘ ,date='2020-12-01' 支持单条件如 (r"name in ('中直股份','珠江啤酒','深物业A')")
elif lon==3:
var1=sys.argv[1]
var2=sys.argv[2]
dataselect(var1,var2)
else:
print('parameters error!')
#查早盘数据
#dataselect(tablename1, name='科隆股份') #r"name in('','','') " //
#dataselect(tablename2, name='科隆股份')
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