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 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 main_financial_statistic_process(path):
store_path = os.path.join(path,'statistic/')
if not os.path.exists(store_path):
os.makedirs(store_path)
scu = SCU(path=path)
stock_codes = scu.stock_codes_remove_no_stock_basic()
FFC =financail_factor_statistic(path=path)
sz50 = ts.get_sz50s()
stock_codes = sz50['code']
stock_industry = ts.get_industry_classified()
stock_codes = stock_industry[stock_industry['c_name'].isin(['房地产'])]['code']
#stock_codes = stock_codes.pop('000527')
#stock_codes = ['000001','000002','000004']
statistic_stock_data = {}
statistic_stock_min_len = 100
for stock_code in stock_codes:
print("stock:",stock_code)
FFC.FLS.load_all_financial_one_stock(stock_code)
FFC.FLS.load_all_processed_stock_basic_one_stock([stock_code])
data_processed = FFC.financial_index_calc(stock_code)
(row, colum) = data_processed.shape
if(row<statistic_stock_min_len):
statistic_stock_min_len = row
statistic_stock_data[stock_code] = data_processed
#plt.figure()
#data_processed.plot.bar(data_processed.index)
sum_data = statistic_stock_data[stock_codes[0]].iloc[-statistic_stock_min_len:,:]
for stock_code in stock_codes[1:]:
sum_data = sum_data + statistic_stock_data[stock_code].iloc[-statistic_stock_min_len:,:]
pct_data = sum_data.pct_change(periods=4)
pct_data.to_csv(store_path+'statistic_pct.csv');
sum_data.to_csv(store_path+'statistic_sum.csv');
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 mk_list():
sz50 = tushare.get_sz50s()
hs300 = tushare.get_hs300s()
y = datetime.datetime.now().year
m = datetime.datetime.now().month
d = datetime.datetime.now().day
path ='StockCodeList\\' + str(y) + '_' + str(m) + '_' + str(d) #本地日期作为目录名
isExists=os.path.exists(path)
if not isExists: #如果该目录不存在，创建目录并保存数据
os.makedirs(path)
stocks = sz50,hs300
for i in stocks:
stock_list = []
#print(i)
for j in i.code:
if (j[0] == '0') or (j[0] == '3'):
j = 'SZ' + j
elif j[0] == '6':
j = 'SH' + j
stock_list.append(j)
#保存当天获取的sz50证券池代码用于核对
fss = path +'\\' + 'list' + str(len(i.code)) + '.txt'
f = open(fss,'w')
for j in stock_list:
f.write(j)
f.write('\n')
f.close()
def classify_info_to_sql():
create_classify_table()
a = ts.get_industry_classified()
a.columns = ['code', 'name', 'industry']
b = ts.get_area_classified()
c = ts.get_sz50s()
c = c.iloc[:,1::]
c['sz50'] = '1'
d = ts.get_hs300s()
d = d.iloc[:,1::]
d.columns = ['code','name','hs300_weight']
e = ts.get_zz500s()
e = e.iloc[:,1::]
e.columns = ['code','name','zz500_weight']
result = pd.merge(a, b, how='left', on=None, left_on=None, right_on=None,
left_index=False, right_index=False, sort=True,
suffixes=('_x', '_y'), copy=True, indicator=False)
result = pd.merge(result, c, how='left', on=None, left_on=None, right_on=None,
left_index=False, right_index=False, sort=True,
suffixes=('_x', '_y'), copy=True, indicator=False)
result = pd.merge(result, d, how='left', on=None, left_on=None, right_on=None,
left_index=False, right_index=False, sort=True,
suffixes=('_x', '_y'), copy=True, indicator=False)
result = pd.merge(result, e, how='left', on=None, left_on=None, right_on=None,
left_index=False, right_index=False, sort=True,
suffixes=('_x', '_y'), copy=True, indicator=False)
df_to_mysql('anack_classify',result)
def __get_code_list__(self):
if self.data_source == 'zz500':
return [i for i in ts.get_zz500s()['code']]
elif self.data_source == 'sz50':
return [i for i in ts.get_sz50s()['code']]
elif self.data_source == 'hs300':
return [i for i in ts.get_hs300s()['code']]
def refresh_stock_list(self):
engine = self.__db.get_engine()
logging.info('fetching stock_basics')
df = ts.get_stock_basics()
df.to_sql('stock_basics', engine, if_exists='replace', index=True,
dtype={'code': String(10)})
logging.info('fetching class_list_gem')
gem = ts.get_gem_classified()
gem.to_sql('class_list_gem', engine, if_exists='replace', index=True,
dtype={'code': String(10)})
logging.info('fetching class_list_hs300')
hs300 = ts.get_hs300s()
hs300.to_sql('class_list_hs300', engine, if_exists='replace', index=True,
dtype={'code': String(10)})
logging.info('fetching class_list_sz50')
sz50 = ts.get_sz50s()
sz50.to_sql('class_list_sz50', engine, if_exists='replace', index=True,
dtype={'code': String(10)})
logging.info('fetching class_list_zz500')
zz500 = ts.get_zz500s()
zz500.to_sql('class_list_zz500', engine, if_exists='replace', index=True,
dtype={'code': String(10)})
self.__db.update_log_time('stock_list_fetch_time')
def get_codes(num):
df = ts.get_sz50s()["code"]
codes = df.values
np.random.shuffle(codes)
codes = codes[0:num]
codes = [cc + ".SZ" if cc[0] == '0' else cc + ".SH" for cc in codes]
return list(codes)
def get_sz50s():
try:
df = ts.get_sz50s();
engine = create_engine('mysql://*****:*****@127.0.0.1/stock?charset=utf8')
# df.insert(0,'code','600848')
df.to_sql('sz50s', engine, if_exists='append')
except Exception, e:
e.message
def getZZ50(self):
print("...reading ZZ50 ...")
df1 = ts.get_sz50s()
writer = pd.ExcelWriter(ZZ50)
df = df1.sort_values(by=['code'])
df.to_excel(writer, sheet_name='ZZ50')
writer.save()
print("...saved ZZ50 ...")
def __get_sh50() -> pd.DataFrame:
"""获取 上证50 成分股, 最新日期"""
try:
return ts.get_sz50s().reindex(['code', 'name', 'date'], axis=1)
except Exception as err:
log.error("Could not fetch SH50 data")
log.error(err)
raise err
def zw_stk_down_50():
#上证50成份股，上证规模大、流动性好的50只股票，优质大盘企业
#上证50，指数代码000016
rss = "d:\\tmp\\"
fss = rss + 'stk_sz50.csv'
print(fss)
dat = ts.get_sz50s()
dat.to_csv(fss, index=False, encoding='gbk')
def is_in_sz50():
codes = get_codes(ts.get_sz50s())
def _aux(stock):
"""Stock in SZ50"""
return stock.code in codes
return _aux
def getSz50():
'''
获取上证50成份股
返回值说明：
code：股票代码
name：股票名称
'''
return ts.get_sz50s()
def get_stockcodes(stocktype): #stocktype 股票类型：sh 上证 sz 深证 cyb 创业板
if(stocktype=='cyb'): #创业板
codes=ts.get_gem_classified().code.tolist()
elif (stocktype=='sz'): #深证
codes=ts.get_sme_classified().code.tolist()
elif(stocktype=='sh'): #上证
codes=ts.get_sz50s().code.tolist() #目前只调用了上证50
return codes #返回的股票代码列表
def get_sz50s():
try:
logger.info('get sz50s data starting...')
df = ts.get_sz50s()
logger.info('get sz50s data end...')
except:
logger.exception('some errors between get sz50s data end...')
return df
def test_strategy(self):
data = ts.get_sz50s()
code_set = code_muning(data)
cal_pair_stocks(code_set)
# def test_cal_p_value(self):
# pair_set = set()
# pair_set.add(('600519', '000858'))
# cal_pair_stocks(pair_set)
def get_chengfenggu(self, writeable=False):
s50 = ts.get_sz50s()
if writeable == True:
s50.to_excel('sz50.xls')
list_s50 = s50['code'].values.tolist()
# print(type(s50))
# print(type(list_s50))
# 返回list类型
return list_s50
def get_chengfenggu(self,writeable=False):
s50=ts.get_sz50s()
if writeable==True:
s50.to_excel('sz50.xls')
list_s50=s50['code'].values.tolist()
#print type(s50)
#print type(list_s50)
#返回list类型
return list_s50
def list_component_stock(component_name):
if 'hs300' == component_name:
return ts.get_hs300s()
if 'zz500' == component_name:
return ts.get_zz500s()
if 'sz50' == component_name:
return ts.get_sz50s()
def get_sz50s_classified(self):
"""
'sz50s',##获取上证50成份股
"""
sz50s = ts.get_sz50s()
sz50s['sz50sName'] = 1
sz50s = sz50s[['code','sz50sName']]
sz50s.columns = ['code','sz50sName']
self.data = pd.merge(self.data,sz50s,on=['code'],how='outer')
def test():
ts.get_sz50s()
ts.get_hs300s()
ts.get_zz500s()
ts.realtime_boxoffice()
ts.get_latest_news()
ts.get_notices(tk)
ts.guba_sina()
ts.get_cpi()
ts.get_ppi()
ts.get_stock_basics()
ts.get_concept_classified()
ts.get_money_supply()
ts.get_gold_and_foreign_reserves()
ts.top_list() #每日龙虎榜列表
ts.cap_tops() #个股上榜统计
ts.broker_tops() #营业部上榜统计
ts.inst_tops() # 获取机构席位追踪统计数据
ts.inst_detail()
def get_sz50s():
df = ts.get_sz50s()
if df is None:
logging.info("get sz50 return none.")
return {}
records_dict = df.to_dict(orient='records')
ret = {}
for data in records_dict:
ret[data['code']] = data['name']
return ret
def sz50_cluster():
instruments = ts.get_sz50s()
instruments.set_index('code', inplace=True)
#clusters = compute_cluster(instruments, config.RESULT_PATH, config.DAY_FILE_PATH, 'sz50')
#clusters = cluster_by_ap(instruments, config.RESULT_PATH, config.DAY_FILE_PATH, 'sz50')
clusters = cluster_by_ap_new(instruments, config.INDEX_FILE_PATH, '000016',
config.DAY_FILE_PATH)
write_to_db(clusters=clusters, section='sz50')
async def main():
# In[0]: 输入
ori_df = read()
# In[1]: 沪深 300
result = pd.DataFrame([
await transaction(ori_df, ts.get_hs300s(), 'IF', 300), await
transaction(ori_df, ts.get_sz50s(), 'IH',
300), await transaction(ori_df, ts.get_zz500s(), 'IC', 200)
])
result.columns = ['代码', '现货总市值', '合约市值', '合约数']
print(result)
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 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 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_sz50s()
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 tech_jincha(self):
# 站上5日线
def zs5(his):
ma_n = pd.rolling_mean(his, 5)
temp = his - ma_n
# temp_s包含了前一天站上五日线的股票代码
temp_s = list(temp[temp > 0].iloc[-1, :].dropna().index)
return temp_s
# 站上10日线
def zs10(his):
ma_n = pd.rolling_mean(his, 10)
temp = his - ma_n
temp_s = list(temp[temp > 0].iloc[-1, :].dropna().index)
return temp_s
# 金叉突破
def jc(his):
mas = pd.rolling_mean(his, 5)
mal = pd.rolling_mean(his, 10)
temp = mas - mal
# temp_jc昨天大于0股票代码
# temp_r前天大于0股票代码
temp_jc = list(temp[temp > 0].iloc[-1, :].dropna().index)
temp_r = list(temp[temp > 0].iloc[-2, :].dropna().index)
temp = []
for stock in temp_jc:
if stock not in temp_r:
temp.append(stock)
return temp
# 确定时间范围
end_date = datetime.datetime.now().strftime('%Y-%m-%d')
start_date = datetime.datetime.now() - datetime.timedelta(days=5)
start_date = start_date.strftime('%Y-%m-%d')
# 得到需要遍历的股票列表
#base_df = ts.get_concept_classified()
base_df = ts.get_sz50s()
stock_list = numpy.array(base_df['code'])
his = pd.DataFrame()
for stock in stock_list:
each_his = ts.get_hist_data(stock, start=start_date, end=end_date)
his.append(each_his)
# 求三种条件下的股票代码交集
con1 = zs5(his)
con2 = zs10(his)
con3 = jc(his)
result_stock_list = list(
set(con1).intersection(set(con2)).intersection(set(con3)))
return result_stock_list
def update_sz50_list(cls):
# update hs300(沪深300) list:
tbl_sz50_list = 'sz50_list'
# get the list from Tushare
# TODO: API has issue
sz50_list = ts.get_sz50s()
print('get sz50_list data ok!')
print(sz50_list)
# insert list
cls.insert_to_db_no_duplicate(sz50_list, tbl_sz50_list, cls.engine)
print("Insert sz50_list data ok!")
# close the engine pool
cls.engine.dispose()
def getSZ50CodeList():
df_sz50 = None
try:
df_sz50 = pd.read_sql_table('sz50', con=engine)
except:
pass
if df_sz50 is None or df_sz50.empty:
df_sz50 = ts.get_sz50s()
df_sz50.to_sql('sz50',
con=engine,
if_exists='replace',
index=False,
index_label='code')
return df_sz50['code'].tolist()
def save_sz50s():
"""上证50成分股"""
logger.info('Begin get and save sz50 clssified.')
try:
data_df = ts.get_sz50s()
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]
Sz50.insert_many(data_dicts).execute()
logger.info('Success get and save sz50 classified.')
else:
logger.warn('Empty get and save sz50 classified.')
except Exception as e:
logger.exception('Error get and save sz50 classified.')
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 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 syncSZ50S():
sz50s_df = ts.get_sz50s()
sz50s_df.to_csv(config.SZ50_CodePath, encoding="utf-8")
saveDataFileByCode(sz50s_df)
print("sync and save SZ50 done!")
# Growth Enterprise Market
GEM = ts.get_gem_classified()
GEM.to_csv('./ASHR/DATA/GEM.csv', index = False)
# ST Enterprise
ST = ts.get_st_classified()
ST.to_csv('./ASHR/DATA/ST.csv', index = False)
ts.get_h_data()
# HS 300
HS300S = ts.get_hs300s()
HS300S.to_csv('./ASHR/DATA/HS300S.csv', index = False)
# SZ 50
SZ50S = ts.get_sz50s()
SZ50S.to_csv('./ASHR/DATA/SZ50S.csv', index = False)
# ZZ 500
ZZ500S = ts.get_zz500s()
ZZ500S.to_csv('./ASHR/DATA/ZZ500S.csv', index = False)
#################
# Fund Holdings #
#################
# TODO Data is available quarterly
FundHolding = ts.fund_holdings(CURRENT.year, np.floor((CURRENT.month+2)/3))
####################
print("#0", df)
df = ts.get_hist_data('600848',start='2016-08-05',end='2016-08-23')
print("#1", df)
df = ts.get_hist_data('600848',start='2016-08-05',end='2016-08-23', ktype='W')
print("#2", df)
df = ts.get_hist_data('600848',start='2016-08-05',end='2016-08-23', ktype='M')
print("#3", df)
df = ts.get_hist_data('600848',start='2016-08-05',end='2016-08-23', ktype='5')
print("#4", df)
df = ts.get_hist_data('600848',start='2016-08-05',end='2016-08-23', ktype='15')
print("#5", df)
df = ts.get_hist_data('600848',start='2016-08-05',end='2016-08-23', ktype='30')
print("#6", df)
df = ts.get_hist_data('600848',start='2016-08-05',end='2016-08-23', ktype='60')
print("#7", df)
df = ts.get_index()
printD("ts.get_index", df)
df = ts.get_suspended()
printD("ts.get_suspended()", df)
df = ts.get_sz50s()
printD("ts.get_sz50s", df)
df = ts.get_terminated()
printD("ts.get_terminated", df)
df = ts.get_zz500s()
printD("ts.get_zz500s", df)
def get_sz50s_info(file_path):
sz50s_info = ts.get_sz50s()
sz50s_info.to_csv(file_path, encoding='utf-8')
print '\ndownload sz50s 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 get_sz50s_history():
szs = ts.get_sz50s()
return get_data_by_column(szs)
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_stock_chengfeng(self):
df = ts.get_sz50s()
# print(df)
terminal_stock = ts.get_terminated()
print(terminal_stock)
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 tss = ts.get_terminated() time.sleep(1) # 暂停上市 ss = ts.get_terminated() time.sleep(1) # 股本
