def 下载板块数据(self):
# 获取不同分类数据
ts.get_industry_classified().to_csv('./股票数据/基本信息/行业分类.csv')
ts.get_concept_classified().to_csv('./股票数据/基本信息/概念分类.csv')
ts.get_area_classified().to_csv('./股票数据/基本信息/地域分类.csv')
ts.get_sme_classified().to_csv('./股票数据/基本信息/中小板.csv')
ts.get_gem_classified().to_csv('./股票数据/基本信息/创业板.csv')
ts.get_st_classified().to_csv('./股票数据/基本信息/风险警示板.csv')
ts.get_hs300s().to_csv('./股票数据/基本信息/沪深300.csv')
ts.get_sz50s().to_csv('./股票数据/基本信息/上证50.csv')
ts.get_zz500s().to_csv('./股票数据/基本信息/中证500.csv')
def exportSt_classified(fromDate, toDate, code):
df = ts.get_st_classified()
engine = create_engine(sql_str)
# 存入数据库
df.to_sql('st_classified', engine, if_exists='append')
Log.logger.info("st_classified数据导入完成。")
return True
def classification(class_types):
if class_types == 'industry':
industry_classified = ts.get_industry_classified()
industry_classified.to_csv('D:\\ts\\classification\\industry_classified.csv', encoding='gbk')
elif class_types == 'concept':
concept_classified = ts.get_concept_classified()
concept_classified.to_csv('D:\\ts\\classification\\concept_classified.csv', encoding='gbk')
elif class_types == 'area':
area_classified = ts.get_area_classified()
area_classified.to_csv('D:\\ts\\classification\\area_classified.csv', encoding='gbk')
elif class_types == 'sme':
sme_classified = ts.get_sme_classified()
sme_classified.to_csv('D:\\ts\\classification\\sme_classified.csv', encoding='gbk')
elif class_types == 'gem':
gem_classified = ts.get_gem_classified()
gem_classified.to_csv('D:\\ts\\classification\\gem_classified.csv', encoding='gbk')
elif class_types == 'st':
st_classified = ts.get_st_classified()
st_classified.to_csv('D:\\ts\\classification\\st_classified.csv', encoding='gbk')
elif class_types == 'hs300':
hs300s = ts.get_hs300s()
hs300s.to_csv('D:\\ts\\classification\\hs300s.csv', encoding='gbk')
elif class_types == 'sz50':
sz50s = ts.get_sz50s()
sz50s.to_csv('D:\\ts\\classification\\sz50s.csv', encoding='gbk')
elif class_types == 'zz500':
zz500s = ts.get_zz500s()
zz500s.to_csv('D:\\ts\\classification\\zz500s.csv', encoding='gbk')
elif class_types == 'terminated':
terminated = ts.get_terminated()
terminated.to_csv('D:\\ts\\classification\\terminated.csv', encoding='gbk')
elif class_types == 'suspended':
suspended = ts.get_suspended()
suspended.to_csv('D:\\ts\\classification\\suspended.csv', encoding='gbk')
def load_tushare_df(df_type):
file = 'ts.' + df_type + '.dat'
try:
obj = pickle.load(open(file, "rb"))
except:
#print("---load in the fly",df_type)
if df_type == "basic":
obj = ts.get_stock_basics()
elif df_type == "sme":
obj = ts.get_sme_classified()
elif df_type == "gem":
obj = ts.get_gem_classified()
elif df_type == "industry":
#print(ts, pickle)
obj = ts.get_industry_classified(
) #该函数不全,只有2800多个,实际股票有3326,所以换个方法取 get_stock_basics
elif df_type == "st":
obj = ts.get_st_classified()
else:
raise Exception("Error TSshare Type!!!")
pickle.dump(obj, open(file, "wb", 0))
else:
#print("***Read from file %s" % df_type)
pass
return obj
def core_function(self, func):
self.set_data()
mongo = MongoClient("127.0.0.1", 27017)
if (func == "industry_classified"):
df = ts.get_industry_classified()
elif (func == "concept_classified"):
df = ts.get_concept_classified()
elif (func == "area_classified"):
df = ts.get_area_classified()
elif (func == "gem_classified"):
df = ts.get_gem_classified()
elif (func == "sme_classified"):
df = ts.get_sme_classified()
elif (func == "st_classified"):
df = ts.get_st_classified()
elif (func == "hs300s"):
df = ts.get_hs300s()
elif (func == "sz50s"):
df = ts.get_sz50s()
elif (func == "zz500s"):
df = ts.get_zz500s()
print(df)
elif (func == "terminated"):
df = ts.get_terminated()
else:
df = {}
insert_string = df.to_json(orient='records')
items = json.loads(insert_string)
coll = mongo.classify[func]
coll.insert(items)
def get_st_classified():
try:
logger.info('get st data starting...')
df = ts.get_st_classified()
logger.info('get st data end...')
except:
logger.exception('some errors between get st data end...')
return df
def get_st_classified():
try:
df = ts.get_st_classified();
engine = create_engine('mysql://*****:*****@127.0.0.1/stock?charset=utf8')
# df.insert(0,'code','600848')
df.to_sql('st_classified', engine, if_exists='append')
except Exception, e:
e.message
def load_data():
#下载公司基本信息，包括股票代码、pe、市盈率等数据
try:
rs=ts.get_st_classified()
pd.DataFrame.to_sql(rs, table_name, con=conn , flavor='mysql', if_exists='replace',index=True)
except Exception as e:
print(e.message)
print("公司基本分类信息数据出错")
def get_st(f):
# 获取风险警示板的股票列表
if f.get(conf.HDF5_BASIC_ST) is not None:
del f[conf.HDF5_BASIC_ST]
df = ts.get_st_classified()
df = df.drop("name", axis=1)
tool.create_df_dataset(f, conf.HDF5_BASIC_ST, df)
return
def load_data():
#下载公司基本信息，包括股票代码、pe、市盈率等数据
try:
rs=ts.get_st_classified()
pd.DataFrame.to_sql(rs, name=table_name, con=con , schema=db, if_exists='replace',index=True)
except Exception as e:
print(e)
print("公司基本分类信息数据出错")
def get_excluded_stocks():
suspended_stocks = combine_code_from_files('./suspended/')
terminated_stocks = combine_code_from_files('./terminated/')
st_stocks_df = ts.get_st_classified()
st_stocks = list(st_stocks_df.code.values)
new_stocks = get_new_stocks()
unprofitable_stocks = get_unprofitable_stock('pe_ratio.csv')
all_excluded = set(suspended_stocks + terminated_stocks + st_stocks +
new_stocks + unprofitable_stocks)
return [str(i) for i in all_excluded]
def get_st_classified(self):
"""
是否属于警示板分类
"""
st = ts.get_st_classified()
st['stName'] = 1
st = st[['code','stName']]
st.columns = ['code','stName']
self.data = pd.merge(self.data,st,on=['code'],how='outer')
def get_universe(symbol):
'''
获取**当前**全A、指定板块、指数、ST的成分股代码。
Parameters
-----------
symbol 获取类型
Returns
----------
list [ticker,...]
Notes
---------
'A'
全A股
'st'
st股票
'hs300'
沪深300成分股
'cyb'
创业板成分股
'sz50'
上证50成分股
'A-st'
剔除st股票后的全A股
'''
if symbol == 'A':
return ts.get_stock_basics().index.values.tolist()
if symbol == 'st':
return ts.get_st_classified()['code'].values.tolist()
if symbol == 'hs300':
return ts.get_hs300s()['code'].values.tolist()
if symbol == 'cyb':
return ts.get_gem_classified()['code'].values.tolist()
if symbol == 'sz50':
return ts.get_sz50s()['code'].values.tolist()
if symbol == 'A-st':
A = set(ts.get_stock_basics().index.values.tolist())
ST = set(ts.get_st_classified()['code'].values.tolist())
for st in ST:
A.discard(st)
return list(A)
def getStClassified():
'''
风险警示板分类
获取风险警示板股票数据，即查找所有st股票
参数说明：
file_path:文件路径，默认为None即由TuShare提供，可以设定自己的股票文件路径。
返回值说明：
code：股票代码
name：股票名称
'''
return ts.get_st_classified()
def updateIncrm(quant_engine, spider_engine):
# get target latest date
sql_statement = 'select max(`%s`) from `%s`' % (targetTimeStamp,
targetTableName)
target_max_timestamp = pd.read_sql(sql_statement,
quant_engine) # quant schema
target_max_timestamp = target_max_timestamp.iloc[0, 0]
# fetch data from source
tmp_fields = list(map(lambda x: '`%s`' % x, sourceFields))
tmp_fields = ','.join(tmp_fields)
sql_statement = "select %s from `%s` where (`%s` > '%s') and (%s != 'null')" % (
tmp_fields, sourceTableName, sourceTimeStamp, target_max_timestamp,
sourceTimeStamp)
incrm_data = pd.read_sql(sql_statement, spider_engine) # spider schema
if incrm_data.empty:
return
# rename columns
incrm_data = renameDF(incrm_data, sourceFields, targetFields)
# drop duplicates
incrm_data = incrm_data.drop_duplicates(['date', 'code'])
if incrm_data.empty:
return
# start to download data
for tmp_col in targetFieldsNew:
incrm_data.loc[:, tmp_col] = 0 # initialized
# st flag
tmp_stocks = ts.get_st_classified()
incrm_data.loc[incrm_data['code'].isin(tmp_stocks['code']), 'ST_FLAG'] = 1
# CSI500 flag
tmp_stocks = ts.get_zz500s()
incrm_data.loc[incrm_data['code'].isin(tmp_stocks['code']),
'CSI500_FLAG'] = 1
# HS300 flag
tmp_stocks = ts.get_hs300s()
incrm_data.loc[incrm_data['code'].isin(tmp_stocks['code']),
'HS300_FLAG'] = 1
# add time stamp & write data to target
if not incrm_data.empty:
incrm_data[targetNewTimeStamp] = datetime.now() # add time stamp
incrm_data.to_sql(targetTableName,
quant_engine,
index=False,
if_exists='append')
def updaterisk():
riskdatalist=ts.get_st_classified()
riskdata=pd.DataFrame(riskdatalist)
conn= ms.connect(host='localhost',port = 3306,user='******', passwd='123456',db ='investment',charset="utf8")
cur = conn.cursor()
values=[]
for index,row in riskdata.iterrows():
values.append((row['code'],row['name']))
cur.executemany('insert into risk (code,name) values(%s,%s)',values)
conn.commit()
cur.close()
conn.close()
def getstockclassifieddata():
mylogger = getmylogger()
print("start")
scdict = {
'industry': '行业分类',
'concept': '概念分类',
'area': '地域分类',
'sme': '中小板分类',
'gem': '创业板分类',
'st': '风险警示板分类',
'hs300s': '沪深300成份及权重',
'sz50s': '上证50成份股',
'zz500s': '中证500成份股',
'terminated': '终止上市股票列表',
'suspended': '暂停上市股票列表'
}
for sc in scdict:
sctbname = sc
scinfo = scdict[sctbname]
try:
if sc == "industry":
df = ts.get_industry_classified()
elif sc == "concept":
df = ts.get_concept_classified()
elif sc == "area":
df = ts.get_area_classified()
elif sc == "sme":
df = ts.get_sme_classified()
elif sc == "gem":
df = ts.get_gem_classified()
elif sc == "st":
df = ts.get_st_classified()
elif sc == "hs300s":
df = ts.get_hs300s()
elif sc == "zz500s":
df = ts.get_zz500s()
elif sc == "sz50s":
df = ts.get_sz50s()
elif sc == "terminated":
df = ts.get_terminated()
elif sc == "suspended":
df = ts.get_suspended()
else:
mylogger.info("没有执行命令。")
if df is not None:
tosql(df, sctbname, "replace", scinfo, mylogger)
else:
mylogger.info("没有%s数据。" % scinfo)
except Exception:
tracelog = traceback.format_exc()
mylogger.info("获取数据异常。")
mylogger.info(tracelog)
def st_classified(request):
try:
data = ts.get_st_classified()
res = {'columns':[
'股票代码',
'股票名称',
],'data':json.loads(json.dumps(data.values,cls=DateEncoder))}
except(KeyError):
return HttpResponse(KeyError)
else:
return HttpResponse(json.dumps(res),content_type="application/json")
def MBRG():
"""
无 --> result 符合条件的股票集合
算法：排除ST股票以及主营业务收入增长低于40%的股票
"""
b2.log('获取主营业务收入增长数据..........')
print('获取主营业务收入增长数据..........')
#print(readydata('growth')[0])
if readydata('growth') == 0:
#季报数据不一定及时，因此采用试错办法
class FoundException(Exception):
pass
try:
for year in (2016, ):
for season in (4, 3, 2, 1):
try:
ds = ts.get_growth_data(year, season)
except:
print('ERROR: ts.get_growth_data(%d,%d)' %
(year, season))
else:
try:
ds.to_sql('growth', engine, if_exists='replace')
engine.execute(
'''insert into tb_stamp values ('growth',curdate())'''
)
except:
print('ERROR: ds.to_sql(%d,%d)' % (year, season))
continue
else:
raise FoundException()
except FoundException:
pass
b2.log('获取风险警示板股票数据..........')
if not readydata('stcode'):
ds = ts.get_st_classified()
ds.to_sql('stcode', engine, if_exists='replace')
engine.execute('''insert into tb_stamp values ('stcode',curdate())''')
#删除ST股票，删除主营业务收入增长低于40%的股票
#result=engine.execute('select distinct code from growth where mbrg>0 and code not in (select code from stcode)')
result = engine.execute(
'select distinct code from growth where code not in (select code from stcode)'
)
#测试测试
#result=engine.execute('select distinct code from growth where code=002723')
return result
def storagepool(self):
#storage zz500
df=ts.get_zz500s()
self.pool['zz500'].insert_many(json.loads(df.to_json(orient='records')))
#hs300
df=ts.get_hs300s()
self.pool['hz300'].insert_many(json.loads(df.to_json(orient='records')))
#zh50
df=ts.get_sz50s()
self.pool['sz'].insert_many(json.loads(df.to_json(orient='records')))
#st
df=ts.get_st_classified()
self.pool['st'].insert_many(json.loads(df.to_json(orient='records')))
def list(self, stock_block_type):
stock_block = None
if stock_block_type == self.industry:
stock_block = db.get(STOCK_BLOCK_INDUSTRY)
if stock_block is None:
stock_block = ts.get_industry_classified()
db.save(STOCK_BLOCK_INDUSTRY, stock_block)
elif stock_block_type == self.concept:
stock_block = db.get(STOCK_BLOCK_CONCEPT)
if stock_block is None:
stock_block = ts.get_concept_classified()
db.save(STOCK_BLOCK_CONCEPT, stock_block)
elif stock_block_type == self.area:
stock_block = db.get(STOCK_BLOCK_AREA)
if stock_block is None:
stock_block = ts.get_area_classified()
db.save(STOCK_BLOCK_AREA, stock_block)
elif stock_block_type == self.sme:
stock_block = db.get(STOCK_BLOCK_SME)
if stock_block is None:
stock_block = ts.get_sme_classified()
db.save(STOCK_BLOCK_SME, stock_block)
elif stock_block_type == self.gem:
stock_block = db.get(STOCK_BLOCK_GEM)
if stock_block is None:
stock_block = ts.get_gem_classified()
db.save(STOCK_BLOCK_GEM, stock_block)
elif stock_block_type == self.st:
stock_block = db.get(STOCK_BLOCK_ST)
if stock_block is None:
stock_block = ts.get_st_classified()
db.save(STOCK_BLOCK_ST, stock_block)
elif stock_block_type == self.hs300s:
stock_block = db.get(STOCK_BLOCK_HS300S)
if stock_block is None:
stock_block = ts.get_hs300s()
db.save(STOCK_BLOCK_HS300S, stock_block)
elif stock_block_type == self.sz50s:
stock_block = db.get(STOCK_BLOCK_SZ50S)
if stock_block is None:
stock_block = ts.get_sz50s()
db.save(STOCK_BLOCK_SZ50S, stock_block)
elif stock_block_type == self.zz500s:
stock_block = db.get(STOCK_BLOCK_ZZ500S)
if stock_block is None:
stock_block = ts.get_zz500s()
db.save(STOCK_BLOCK_ZZ500S, stock_block)
else:
return None
return stock_block
def update_st(request):
'''更新st板块'''
stock_st.objects.all().delete()
rltobj = ts.get_st_classified()
objlist = []
for i in range(len(rltobj)):
tmpobj = stock_st(code=rltobj.loc[i]['code'],
name=rltobj.loc[i]['name'])
objlist.append(tmpobj)
stock_st.objects.bulk_create(objlist)
return HttpResponse('succ.{0}条!'.format(len(objlist)))
def save_st_classified():
"""获取风险警示板股票数据，即查找所有st股票"""
logger.info('Begin get and save st clssified.')
try:
data_df = ts.get_st_classified()
if data_df is not None and not data_df.empty:
data = data_df.values
data_dicts = [{'code': row[0], 'name': row[1]} for row in data]
StClassified.insert_many(data_dicts).execute()
logger.info('Success get and save st classified.')
else:
logger.warn('Empty get and save st classified.')
except Exception as e:
logger.exception('Error get and save st classified.')
def download_ST_classified(self):
"""
"""
#print('downloading the ST_classified info...')
ST_classified = ts.get_st_classified()
if ST_classified is not None:
filename = 'ST_classified'
ST_classified.to_excel(self.working_folder + filename + '.xlsx',
encoding='GBK')
else:
warning_code = pd.DataFrame({
'return code': ['for all stocks'],
'description': ['ST_classified download failed']
})
self.warning_list = self.warning_list.append(warning_code)
return
def get_stock_codes(markets=['zz500s'], ipo_date=None):
'''
markets: list
e.g.['sme','gem','st','hs300s','sz50s','zz500s','general'];
ipo_date: str
e.g.'2015-03-30'
'''
code_list = []
if 'sme' in markets: #中小板
df = ts.get_sme_classified()
codes = list(df.code)
code_list.extend(codes)
if 'gem' in markets: #创业板
df = ts.get_gem_classified()
codes = list(df.code)
code_list.extend(codes)
if 'st' in markets: #风险板
df = ts.get_st_classified()
codes = list(df.code)
code_list.extend(codes)
if 'hs300s' in markets: #沪深300
df = ts.get_hs300s()
codes = list(df.code)
code_list.extend(codes)
if 'sz50s' in markets: #上证50
df = ts.get_sz50s()
codes = list(df.code)
code_list.extend(codes)
if 'zz500s' in markets: #中证500
df = ts.get_zz500s()
codes = list(df.code)
code_list.extend(codes)
if ipo_date:
new_stock_df = ts.new_stocks()
new_stock_df = new_stock_df[new_stock_df['ipo_date'] > ipo_date]
new_stock_codes = list(new_stock_df.code)
#得到输入时间之后发行的股票
code_list = list(set(code_list))
desired_codes = list(set(code_list) - set(new_stock_codes))
#剔除新股
desired_codes = list(set(code_list))
return desired_codes
def updaterisk():
riskdatalist = ts.get_st_classified()
riskdata = pd.DataFrame(riskdatalist)
conn = ms.connect(host='localhost',
port=3306,
user='******',
passwd='123456',
db='investment',
charset="utf8")
cur = conn.cursor()
values = []
for index, row in riskdata.iterrows():
values.append((row['code'], row['name']))
cur.executemany('insert into risk (code,name) values(%s,%s)', values)
conn.commit()
cur.close()
conn.close()
def MBRG():
"""
无 --> result 符合条件的股票集合
算法：排除ST股票以及主营业务收入增长低于40%的股票
"""
b2.log('获取主营业务收入增长数据..........')
print('获取主营业务收入增长数据..........')
#print(readydata('growth')[0])
if readydata('growth')==0:
#季报数据不一定及时，因此采用试错办法
class FoundException(Exception): pass
try:
for year in (2016,):
for season in (4,3,2,1):
try:
ds=ts.get_growth_data(year,season)
except:
print('ERROR: ts.get_growth_data(%d,%d)'%(year,season))
else:
try:
ds.to_sql('growth',engine,if_exists='replace')
engine.execute('''insert into tb_stamp values ('growth',curdate())''')
except:
print('ERROR: ds.to_sql(%d,%d)'%(year,season))
continue
else:
raise FoundException()
except FoundException: pass
b2.log('获取风险警示板股票数据..........')
if not readydata('stcode'):
ds=ts.get_st_classified()
ds.to_sql('stcode',engine,if_exists='replace')
engine.execute('''insert into tb_stamp values ('stcode',curdate())''')
#删除ST股票，删除主营业务收入增长低于40%的股票
#result=engine.execute('select distinct code from growth where mbrg>0 and code not in (select code from stcode)')
result=engine.execute('select distinct code from growth where code not in (select code from stcode)')
#测试测试
#result=engine.execute('select distinct code from growth where code=002723')
return result
def preload():
stock_block = ts.get_industry_classified()
db.save(STOCK_BLOCK_INDUSTRY, stock_block)
stock_block = ts.get_concept_classified()
db.save(STOCK_BLOCK_CONCEPT, stock_block)
stock_block = ts.get_area_classified()
db.save(STOCK_BLOCK_AREA, stock_block)
stock_block = ts.get_sme_classified()
db.save(STOCK_BLOCK_SME, stock_block)
stock_block = ts.get_gem_classified()
db.save(STOCK_BLOCK_GEM, stock_block)
stock_block = ts.get_st_classified()
db.save(STOCK_BLOCK_ST, stock_block)
stock_block = ts.get_hs300s()
db.save(STOCK_BLOCK_HS300S, stock_block)
stock_block = ts.get_sz50s()
db.save(STOCK_BLOCK_SZ50S, stock_block)
stock_block = ts.get_zz500s()
db.save(STOCK_BLOCK_ZZ500S, stock_block)
def getStockClassfied():
filepath = 'f:\\stockdata\\股票分类数据\\'
index = 0
# 行业分类
df = ts.get_industry_classified()
saveCsv(df, filepath, stockClassList, index)
index += 1
# 概念分类
df = ts.get_concept_classified()
saveCsv(df, filepath, stockClassList, index)
index += 1
# 地域分类
df = ts.get_area_classified()
saveCsv(df, filepath, stockClassList, index)
index += 1
# 中小板分类
df = ts.get_sme_classified()
saveCsv(df, filepath, stockClassList, index)
index += 1
# 创业板分类
df = ts.get_gem_classified()
saveCsv(df, filepath, stockClassList, index)
index += 1
# 风险警示板分类
df = ts.get_st_classified()
saveCsv(df, filepath, stockClassList, index)
index += 1
# 沪深300成份及权重
df = ts.get_hs300s()
saveCsv(df, filepath, stockClassList, index)
index += 1
# 上证50成份股
df = ts.get_sz50s()
saveCsv(df, filepath, stockClassList, index)
index += 1
# 中证500成份股
df = ts.get_zz500s()
saveCsv(df, filepath, stockClassList, index)
index += 1
def get_st():
'''
函数功能：
--------
获取所有风险警示板的公司，即所有st的股票。
输入参数：
--------
无
输出参数：
--------
DataFrame
code,代码
name,名称
'''
# Download data
st = ts.get_st_classified()
# Return Dataframe
return st
def st():
return ts.get_st_classified()
def setStClassified(self, isSave=False, tableName=CLASSIFIED_ST):
df = ts.get_st_classified()
if isSave is True:
df.to_sql(tableName, self.engine_sql, if_exists='append')
return df
def Get_st_classified(self):
dt = ts.get_st_classified()
dt.to_csv('风险警示.csv')
print(dt)
def get_st_info(file_path):
st_info = ts.get_st_classified()
st_info.to_csv(file_path, encoding='utf-8')
print '\ndownload st info finished\n'
Created on 2015年6月4日 @author: Administrator ''' import tushare as ts # 行业分类 ts.get_industry_classified() # 概念分类 ts.get_concept_classified() # 地域分类 ts.get_area_classified() # 获取沪深300当前成份股及所占权重 ts.get_hs300s() # 获取中小板股票数据，即查找所有002开头的股票 ts.get_sme_classified() # 获取创业板股票数据，即查找所有300开头的股票 ts.get_gem_classified() # 获取风险警示板股票数据，即查找所有st股票 ts.get_st_classified() # 获取上证50成份股 ts.get_sz50s() # 获取中证500成份股 ts.get_zz500s()
def load_company_industry_info():
#下载加载行业分类数据
try:
rs=ts.get_industry_classified()
sql.write_frame(rs, "company_industry_classified", con=conn_company_classified , flavor='mysql', if_exists='replace',index=True)
print("下载公司行业分类信息ok")
except:
print("下载公司行业分类信息出错")
#下载加载概念分类数据
try:
rs=ts.get_concept_classified()
sql.write_frame(rs, "company_concept_classified", con=conn_company_classified , flavor='mysql', if_exists='replace',index=True)
print("载公司概念分类信息ok")
except:
print("下载公司概念分类信息出错")
#下载加载地域分类数据
try:
rs=ts.get_area_classified()
sql.write_frame(rs, "company_area_classified", con=conn_company_classified , flavor='mysql', if_exists='replace',index=True)
print("下载公司区域分类信息ok")
except:
print("下载公司区域分类信息出错")
#下载加载中小板分类数据
try:
rs=ts.get_sme_classified()
sql.write_frame(rs, "company_sme_classified", con=conn_company_classified , flavor='mysql', if_exists='replace',index=True)
print("下载中小板分类数据ok")
except:
print("下载中小板分类数据出错")
#下载加载创业板分类数据
try:
rs=ts.get_gem_classified()
sql.write_frame(rs, "company_gem_classified", con=conn_company_classified , flavor='mysql', if_exists='replace',index=True)
print("下载创业板分类数据ok")
except:
print("下载创业板分类数据出错")
#下载加载st板分类数据
try:
rs=ts.get_st_classified()
sql.write_frame(rs, "company_st_classified", con=conn_company_classified , flavor='mysql', if_exists='replace',index=True)
print("下载st板分类数据ok")
except:
print("下载st板分类数据出错")
#下载加载沪深300板分类数据
try:
rs=ts.get_hs300s()
sql.write_frame(rs, "company_hs300_classified", con=conn_company_classified , flavor='mysql', if_exists='replace',index=True)
print("下载加载沪深300板分类数据ok")
except:
print("下载加载沪深300板分类数据出错")
#下载加载上证50板分类数据
try:
rs=ts.get_sz50s()
sql.write_frame(rs, "company_sz50_classified", con=conn_company_classified , flavor='mysql', if_exists='replace',index=True)
print("下载加载上证50板分类数据ok")
except:
print("下载加载上证50板分类数据出错")
#下载加载中证500板分类数据
try:
rs=ts.get_zz500s()
sql.write_frame(rs, "company_zz500_classified", con=conn_company_classified , flavor='mysql', if_exists='replace',index=True)
print("下载加载中证500板分类数据ok")
except:
print("下载加载中证500板分类数据出错")
#下载加载终止上市分类数据
try:
rs=ts.get_terminated()
sql.write_frame(rs, "company_terminated_classified", con=conn_company_classified , flavor='mysql', if_exists='replace',index=True)
print("下载加载终止上市分类数据ok")
except:
print("下载加载终止上市分类数据出错")
#下载加载暂停上市分类数据
try:
rs=ts.get_suspended()
sql.write_frame(rs, "company_suspended_classified", con=conn_company_classified , flavor='mysql', if_exists='replace',index=True)
print("下载加载暂停上市分类数据ok")
except:
print("下载加载暂停上市分类数据出错")
def get_st_info(file_path):
st_info = ts.get_st_classified()
st_info.to_csv(file_path, encoding='utf-8')
print '\ndownload st info finished\n'
def getSTClass(self):
file_name = 'st_class.csv'
path = self.index + self.index_st_class + file_name
data = ts.get_st_classified()
data.to_csv(path, encoding='utf-8')
print(file_name)
def get_st():
"""获取ST股票"""
df = ts.get_st_classified()
print(df)
time.sleep(1)
# 地域分类
areas = ts.get_area_classified()
areas.columns = ('code', 'name', 'area')
time.sleep(1)
# 中小板块
smalls = ts.get_sme_classified()
time.sleep(1)
# 创业版
news = ts.get_gem_classified()
time.sleep(1)
# st版块
sts = ts.get_st_classified()
time.sleep(1)
# 沪深300
hss = ts.get_hs300s()
time.sleep(1)
# 上证50
szs = ts.get_sz50s()
time.sleep(1)
# 中证500
zzs = ts.get_zz500s()
time.sleep(1)
# 终止上市
