def get_top_inst_list(self, task=None):
"""
获取每日龙虎榜列表(龙虎榜上榜是根据上榜原因定的，因此有的股票可能会有多个原因，存在多条记录)，并保存到文件中
获取当日机构购买详情，不能赋值日期，默认只能获取最近一天的交易详情
Parameters
----------
task:指定任意参数表示获取某一天的龙虎榜，否则为获取当日的龙虎榜
"""
d = self.today if task is None else self.end
top_list_df = ts.top_list(d)
inst_detail_df = ts.inst_detail() if task is None else None
if os.path.exists(u"{}/top_list_data.csv".format(data_path)):
with codecs.open(u"{}/top_list_data.csv".format(data_path), "a+", "utf-8") as f:
top_list_df.to_csv(f, header=False, sep="\t", index=True)
else:
with codecs.open(u"{}/top_list_data.csv".format(data_path), "a+", "utf-8") as f:
top_list_df.to_csv(f, header=True, sep="\t", index=True)
if inst_detail_df is not None:
if os.path.exists(u"{}/inst_detail_data.csv".format(data_path)):
with codecs.open(u"{}/inst_detail_data.csv".format(data_path), "a+", "utf-8") as f:
top_list_df.to_csv(f, header=False, sep="\t", index=True)
else:
with codecs.open(u"{}/inst_detail_data.csv".format(data_path), "a+", "utf-8") as f:
top_list_df.to_csv(f, header=True, sep="\t", index=True)
def store_top_data(self, trading_date=None):
"""龙虎榜数据: 龙虎榜数据接口提供历史龙虎榜上榜股票数据"""
trading_date = self.last_trading_date if trading_date is None else trading_date
# 每日龙虎榜列表
print('top_list...')
top_df = ts.top_list(self.stock_date_format(trading_date))
self.mysqlUtils.append_data(top_df, 'top_list')
# 个股上榜统计
print('cap_tops...')
cap_tops_df = ts.cap_tops()
cap_tops_df['date'] = trading_date
self.mysqlUtils.append_data(cap_tops_df, 'cap_tops')
# 营业部上榜统计
print('broker_tops...')
broker_tops_df = ts.broker_tops()
broker_tops_df['date'] = trading_date
self.mysqlUtils.append_data(broker_tops_df, 'broker_tops')
# 龙虎榜机构席位追踪
print('inst_tops...')
inst_tops_df = ts.inst_tops()
inst_tops_df['date'] = trading_date
self.mysqlUtils.append_data(inst_tops_df, 'inst_tops')
# 龙虎榜机构席位成交明细
print('inst_detail...')
inst_detail_df = ts.inst_detail()
self.mysqlUtils.append_data(inst_detail_df, 'inst_detail')
def job_7():
try:
print("I'm working......龙虎榜数据")
# 每日龙虎榜列表
top_list = ts.top_list(today)
data = pd.DataFrame(top_list)
data.to_sql('top_list',engine,index=True,if_exists='replace')
print("每日龙虎榜列表......done")
# 个股上榜统计
cap_tops = ts.cap_tops()
data = pd.DataFrame(cap_tops)
data.to_sql('cap_tops',engine,index=True,if_exists='replace')
print("个股上榜统计......done")
# 营业部上榜统计
broker_tops = ts.broker_tops()
data = pd.DataFrame(broker_tops)
data.to_sql('broker_tops',engine,index=True,if_exists='replace')
print("营业部上榜统计......done")
# 机构席位追踪
inst_tops = ts.inst_tops()
data = pd.DataFrame(inst_tops)
data.to_sql('inst_tops',engine,index=True,if_exists='replace')
print("机构席位追踪......done")
# 机构成交明细
inst_detail = ts.inst_detail()
data = pd.DataFrame(inst_detail)
data.to_sql('inst_detail',engine,index=True,if_exists='replace')
print("机构成交明细......done")
except Exception as e:
print(e)
def longhu():
db.get_collection('topList').remove()
longhu = ts.top_list()
longhu = longhu.to_json(orient='index', )
longhu = json.loads(longhu)
for k, v in longhu.items():
db.get_collection('topList').insert(v)
def stat_all(tmp_datetime):
datetime_str = (tmp_datetime).strftime("%Y-%m-%d")
datetime_int = (tmp_datetime).strftime("%Y%m%d")
cache_dir = common.bash_stock_tmp % (datetime_str[0:7], datetime_str)
if os.path.exists(cache_dir):
shutil.rmtree(cache_dir)
print("remove cache dir force :", cache_dir)
print("datetime_str:", datetime_str)
print("datetime_int:", datetime_int)
data = ts.top_list(datetime_str)
# 处理重复数据，保存最新一条数据。最后一步处理，否则concat有问题。
#
if not data is None and len(data) > 0:
# 插入数据库。
# del data["reason"]
data["date"] = datetime_int # 修改时间成为int类型。
data = data.drop_duplicates(subset="code", keep="last")
data.head(n=1)
common.insert_db(data, "ts_top_list", False, "`date`,`code`")
else:
print("no data .")
print(datetime_str)
def get_last_ranklist_detail():
"""
:return:
"""
fields = [
'code', 'name', 'pchange', 'amount', 'buy', 'bratio', 'sell', 'sratio',
'reason', 'date'
]
today = (datetime.datetime.today() -
datetime.timedelta(days=1)).strftime('%Y-%m-%d')
top_list = ts.top_list(today)
if top_list is None or not len(top_list):
return
if RankListDailyData.objects.filter(type_date=today).exists():
return
bulk_list = []
for i in range(len(top_list)):
per_dict = dict()
for f in fields:
per_dict.update({f: top_list[f][i]})
r_model = RankListDailyData(code=per_dict.get('code'),
name=per_dict.get('name'),
pcharge=per_dict.get('pchange'),
amount=per_dict.get('amount'),
buy=per_dict.get('buy'),
bratio=per_dict.get('bratio'),
sell=per_dict.get('sell'),
sratio=per_dict.get('sratio'),
reason=compare_by_value_get_key(
RANK_REASON, per_dict.get('reason')),
type_date=per_dict.get('date'))
bulk_list.append(r_model)
RankListDailyData.objects.bulk_create(bulk_list)
def run():
start = datetime.datetime.now()
config = {
'host': '10.60.42.201',
'user': '******',
'password': '******',
'port': 13142,
'database': 'javaEE',
'charset': 'utf8'
}
conn = mysql.connector.connect(**config)
cursor = conn.cursor()
today = datetime.date.today()
today = str(today)
td = ts.top_list('2017-12-01')
params = []
for index, row in td.iterrows():
params.append((row['code'], row['name'], row['pchange'], row['amount'],
row['buy'], row['bratio'], row['sell'], row['sratio'],
row['reason']))
sql = "INSERT INTO winnerlist VALUES (NULL, %s, %s, %s, %s, %s, %s, %s, %s, %s)"
cursor.executemany(sql, params)
cursor.execute("Commit;")
cursor.close()
conn.close()
print datetime.datetime.now() - start
def get_top_list(date):
try:
df = ts.top_list(date)
engine = create_engine('mysql://*****:*****@127.0.0.1/stock?charset=utf8')
df.to_sql('top_list', engine, if_exists='append')
print "message"
except Exception, e:
e.message
def get_top_list():
today = datetime.date.today()
delta = datetime.timedelta(days=1)
ndays_before = today - delta
date_str = ndays_before.strftime('%Y-%m-%d');
logging.info("date: %s", date_str)
df = ts.top_list(date_str)
df.to_sql('top_list', engine, if_exists='append', index=False, index_label='code')
def get_top_list(date):
'''
return long hu bang
:param date: Format is 'YYYY-MM-DD'
:return: long hu bang
'''
df = ts.top_list(date)
df[['pchange', 'amount', 'buy', 'bratio', 'sell', 'sratio']] = df[['pchange', 'amount', 'buy', 'bratio', 'sell', 'sratio']].apply(pd.to_numeric, errors='ignore')
return df
def get_stock_winner(datetime):
"""
获取每日龙虎榜列表
"""
try:
res = ts.top_list(datetime)
return res
except:
return None
def Gettop_list(self):
"""今天是星期六或者星期天 不是交易日 周六做异常判断"""
todays = datetime.date.today()
dayOfWeek = datetime.date.today().weekday()
if dayOfWeek == 5: timess = todays - datetime.timedelta(days=1)
elif dayOfWeek == 6: timess = todays - datetime.timedelta(days=2)
else: timess = todays
dates = ts.top_list('%s' % (timess))
self.SaveCSV(dates, 'toplist.csv')
def getdragontigerdata():
curday = datetime.date.today()
curdate = curday.strftime('%Y%m%d')
print(curdate)
mylogger = getmylogger()
# 每日龙虎榜列表
df = ts.top_list(curday.strftime('%Y-%m-%d'))
if df is not None:
df['date'] = curdate
tosql(df, 'toplistdata', "append", "每日龙虎榜数据", mylogger)
else:
mylogger.info("没有每日龙虎榜数据。")
# 个股上榜统计
for i in [5, 10, 30, 60]:
df = ts.cap_tops(i)
logmsg = "个股上榜数据" + "%d日：" % i
if df is not None:
df['date'] = curdate
df['period'] = i
tosql(df, 'captops', "append", logmsg, mylogger)
else:
mylogger.info("没有" + logmsg)
# 营业部上榜统计
for i in [5, 10, 30, 60]:
df = ts.broker_tops(i)
logmsg = "营业部上榜数据" + "%d日：" % i
if df is not None:
df['date'] = curdate
df['period'] = i
tosql(df, 'brokertops', "append", logmsg, mylogger)
else:
mylogger.info("没有" + logmsg)
# 机构席位追踪
for i in [5, 10, 30, 60]:
df = ts.inst_tops(i)
logmsg = "机构席位追踪数据" + "%d日：" % i
if df is not None:
df['date'] = curdate
df['period'] = i
tosql(df, 'instops', "append", logmsg, mylogger)
else:
mylogger.info("没有" + logmsg)
# 机构成交明细
df = ts.inst_detail()
logmsg = "机构成交明细："
if df is not None:
df['date'] = curdate
tosql(df, 'instdetail', "append", logmsg, mylogger)
else:
mylogger.info("没有机构成交明细。")
def prepare_data():
current_date = time.strftime("%Y-%m-%d")
top_list = ts.top_list(current_date)
if top_list is None or top_list.empty:
return
record_json = top_list.to_json(orient='records')
print(record_json)
collection = mongoConfig.get_collection_default("stock_top_list")
mongoConfig.clear_collection(collection)
mongoConfig.insert_json(collection, json.loads(record_json))
def get_td_list(date=None):
"""
description: 每日榜单
params:
date: 日期
"""
if date is None:
date = time_utils.today()
data = ts.top_list(date)
return data
def lhb_daily(date, pause=0.5):
"""
每日龙虎榜数据
:param date:
:return:
"""
fs = ts.top_list(date, pause=pause)
fs['dif'] = fs.apply(lambda x: float(x.buy) - float(x.sell), axis=1)
return fs
def getLastData(strdate):
date = lastTddate(strdate)
dfLastTradeDay = ts.top_list(lastTddate(date))
strIndex = date.replace("-", "")
listIndex = []
for i in range(len(dfLastTradeDay)):
listIndex.append(strIndex + "{:0>2}".format(i))
dfLastTradeDay.index = listIndex
return dfLastTradeDay
def stk_top_list(dat=str(date.today())):
print("======获取龙虎榜列表============")
print("\n插入数据：" + 'stk_top_list')
try:
df = ts.top_list(retry_count=10,pause=1,date=dat)
# print(df)
df.to_sql('stk_top_list',engine,if_exists='append')
except Exception as e :
print("insert failed." + str(e))
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 GetBillBoardOn(date):
"""
Get BillBoard data according to date.
Args:
date: a data string whose format is "YYYY-MM-DD"
Returns:
"""
return ts.top_list(date)
def __init__(self, init=True):
"""
初始化，筛除688,300，ST，退市股，新股，低价股，下跌股
"""
if init:
self.data = ts.get_today_all() #今日复盘
self.updateNMC(self.data)
# data = ts.get_day_all(date='2021-02-18') #历史复盘
filt = self.data['code'].str.contains('^(?!688|605|300|301|8|43)')
self.data = self.data[filt]
filt = self.data['name'].str.contains('^(?!S|退市|\*ST|N)')
self.data = self.data[filt]
self.data = self.data.drop_duplicates()
data = self.data[self.data['trade'] >= 2]
data = data[data['changepercent'] > -3]
data = data.to_json(orient='records')
db.get_collection('today').remove()
base = db.get_collection('base').find()
industry = {i['code']: i['industry'] for i in base}
self.intersect = {}
for i in eval(data):
db.get_collection('today').insert(i)
res = db.get_collection('today').find()
for i in res:
try:
db.get_collection('today').update_many(
{'code': i['code']},
{'$set': {
'industry': industry[i['code']]
}})
except:
pass
# 剔除新股
try:
newStock = ts.new_stocks()
if not newStock.empty:
newStock = newStock[newStock.ipo_date > '2020-01-01']
for i in newStock['code'].tolist():
db.get_collection('today').remove({'code': i},
multi=True)
except Exception as e:
print('newStock Error', e)
# 剔除停牌
db.get_collection('today').remove({'open': 0})
# 龙虎榜
if not (10 < time.localtime().tm_hour < 18):
db.get_collection('topList').remove()
longhu = ts.top_list()
longhu = longhu.to_json(orient='index', )
longhu = json.loads(longhu)
for k, v in longhu.items():
db.get_collection('topList').insert(v)
def download_top_list(time):
Datas_b= ts.top_list(time)
files_path = '../report/Brokerage/%s'%todaytime
if os.path.exists(files_path) == False: # 判断文件是不是存在
os.mkdir(files_path) # 创建目录
Datas_b.to_csv(files_path+'/%s_top_list_csv.csv'%(todaytime),encoding='gbk')
with pd.ExcelWriter(files_path+'/%s_top_list_xlx.xlsx'%(todaytime)) as writer:
Datas_b.to_excel(writer, sheet_name='Sheet1')
print('\n%s龙虎have been saved'%(todaytime))
def get_lbh_top_list(data):
"""
按日期获取历史当日上榜的个股数据，
如果一个股票有多个上榜原因，则会出现该股票多条数据
"""
df = ts.top_list(data)
print(df)
if df is not None:
res = df.to_sql(lbh_top_list, engine, if_exists='replace')
msg = 'ok' if res is None else res
print('获取历史当日上榜的个股数据: 开始时间：{0} {1}'.format(data, msg) + '\n')
else:
print('获取历史当日上榜的个股数据: 开始时间：{0} {1}'.format(data, 'None') + '\n')
def stk_top_list_detail(dat=str(date.today())):
df = ts.top_list(date=dat,retry_count=3,pause=1)
# print(df)
#http://vip.stock.finance.sina.com.cn/q/api/jsonp.php/var%20details=/InvestConsultService.getLHBComBSData?symbol=300708&tradedate=2018-01-24&type=5
for code in (df[df.reason.str.contains('日涨幅偏离值达到7%的前五只证券')]['code']):
type='01'
url = 'http://vip.stock.finance.sina.com.cn/q/api/jsonp.php/var%20details=/InvestConsultService.getLHBComBSData?symbol=' + code + '&tradedate=' + dat + '&type=' + str(type)
r = requests.get(url)
f = open('r.txt','w+')
f.write(r.text)
# print(r.text)
for line in f.readline():
r1 = line.replace('.*script.*','')
print(r1)
def showTopList():
date = request.args['date']
date = date.encode('ascii') if date else datetime.today()
# logging.error(date)
df = cache.get('topList_%s'%date)
# logging.error('topList_%s'%date)
if df is None:
df = ts.top_list(date=date)
if df is None:
html_tbl = u"<p>这一天没有数据</p>"
else:
cache.set('topList_%s'%date, df, timeout=600)
html_tbl = df.to_html()
return render_template('stock_topList.html', tbl=html_tbl)
def get_top_list_tu(_trade_date):
stock_list = None
count = 0
while count < 2:
count = count + 1
try:
stock_list = ts.top_list(_trade_date)
break
except Exception:
log_error("warn: ts.top_list exception: %d!", count)
time.sleep(5)
return stock_list
def get_top_list(self):
#print(ts.get_day_all())
for i in range(0,10):
now=datetime.datetime.now()
delta=datetime.timedelta(days=i)
n_days=now-delta
tradedate = n_days.strftime('%Y-%m-%d')
ts_data = ts.top_list(tradedate)
if not ts_data is None:
break
df=pd.DataFrame(data=ts_data)
print(df)
return df
def tops_list_worker(engine, sdate, edate):
pid = os.getpid()
tsl.log("pid %i start with %s ~ %s..." % (pid, str(sdate), str(edate)))
cdate = sdate
df = pd.DataFrame()
while cdate <= edate:
if not tsu.is_holiday(cdate):
try:
newdf = ts.top_list(str(cdate))
if df is not None:
df = df.append(newdf, ignore_index=True)
except BaseException, e:
print e
tsl.log("pid %i error on %s" % (pid, str(cdate)))
cdate += datetime.timedelta(days=1)
def intoDB(date='2017-10-20'):
'''
Insert symbols to Mysql
'''
print("[info] getting {}".format(date))
data = ts.top_list(date)
data['date'] = date
data = data.drop_duplicates(['code', 'date'])
print("[info] into mysql")
engine = create_engine('mysql://*****:*****@127.0.0.1/stock?charset=utf8',
encoding='utf-8')
try:
data.to_sql('longhu', engine, if_exists="append", index=False)
except Exception as e:
print("error: {}".format(e))
def stat_all(tmp_datetime):
datetime_str = (tmp_datetime).strftime("%Y-%m-%d")
datetime_int = (tmp_datetime).strftime("%Y%m%d")
print("datetime_str:", datetime_str)
print("datetime_int:", datetime_int)
data = ts.top_list(datetime_str)
# 处理重复数据，保存最新一条数据。最后一步处理，否则concat有问题。
#
if not data is None and len(data) > 0:
# 插入数据库。
#del data["reason"]
data["date"] = datetime_int # 修改时间成为int类型。
data = data.drop_duplicates(subset="code", keep="last")
data.head(n=1)
common.insert_db(data, "ts_top_list", False, "`date`,`code`")
else:
print("no data .")
print(datetime_str)
def get_top_list(date, retry_count=RETRY_COUNT, pause=PAUSE):
"""每日龙虎榜列表"""
logger.info('Begin get TopList. Date is: %s.' % date)
try:
data_df = ts.top_list(date, retry_count, pause)
except Exception as e:
logger.exception('Error get TopList. Date is: %s.' % date)
return None
else:
data_dicts = []
if data_df is None or data_df.empty:
logger.warn('Empty get TopList. Date is: %s.' % date)
else:
data_dicts = [{'code': row[0], 'name': row[1],
'pchange': row[2], 'amount': row[3], 'buy': row[4],
'sell': row[5], 'reason': row[6], 'bratio': row[7],
'sratio': row[8], 'date': row[9]}
for row in data_df.values]
logger.info('Success get TopList. Date is: %s.' % date)
return data_dicts
def top_type(top_type):
today = datetime.datetime.today().strftime('%Y-%m-%d')
if top_type == 'top_list':
top_list = ts.top_list(today)
if top_list is not None:
top_list.to_sql('top_list',
engine,
flavor='mysql',
if_exists='append')
elif top_type == 'cap_tops':
cap_tops = ts.cap_tops()
if cap_tops is not None:
cap_tops['date'] = today
cap_tops.to_sql('top_cap_tops',
engine,
flavor='mysql',
if_exists='append')
elif top_type == 'broker_tops':
broker_tops = ts.broker_tops()
if broker_tops is not None:
broker_tops['date'] = today
broker_tops.to_sql('top_broker_tops',
engine,
flavor='mysql',
if_exists='append')
elif top_type == 'inst_tops':
inst_tops = ts.inst_tops()
if inst_tops is not None:
inst_tops['date'] = today
inst_tops.to_sql('top_inst_tops',
engine,
flavor='mysql',
if_exists='append')
elif top_type == 'inst_detail':
inst_detail = ts.inst_detail()
if inst_detail is not None:
inst_detail.to_sql('top_inst_detail',
engine,
flavor='mysql',
if_exists='append')
def getData_huanshoulv(date, reasonson):
# print(111)
reasons = [
# '无价格涨跌幅限制的证券',
'日换手率达到20%的前五只证券',
# '日涨幅偏离值达到7%的前五只证券',
# '日跌幅偏离值达到7%的前五只证券',
# '有价格涨跌幅限制的日价格振幅达到15%的前三只证券',
# '有价格涨跌幅限制的日换手率达到20%的前三只证券',
# '有价格涨跌幅限制的日收盘价格涨幅偏离值达到7%的前三只证券',
# '连续三个交易日内，涨幅偏离值累计达到12%的ST证券、*ST证券和未完成股改证券',
# '连续三个交易日内，涨幅偏离值累计达到20%的证券',
# '退市整理期',
# '非ST、*ST和S证券连续三个交易日内收盘价格涨幅偏离值累计达到20%的证券'
]
rea = '日换手率达到20%的前五只证券'
df = ts.top_list(date)
# df = df.sort(columns='reason')
name = list(df['name'])
change = list(df['pchange'])
reason = list(df['reason'])
# print(len(code))
# for i in code:
# print(i)
# for i in name:
# print(i)
# for i in reason:
# print(i)
names = []
changes = []
for i in range(0, len(name)):
if reason[i] == rea:
names.append(name[i])
changes.append(change[i])
print(len(names))
for i in names:
print(i)
for i in changes:
print(i)
def QA_fetch_get_lhb(date):
return ts.top_list(date)
def QA_fetch_get_lhb(date): return QATs.top_list(date)
def daily_longhu(self):
# date=self.date
date = '2016-04-05'
df = ts.top_list(date)
df.to_excel(date + ".xlsx")
# 取两融数据
df = ts.sh_margins(start='2015-01-01',end='2016-05-04')
df = ts.sh_margin_details(start='2016-01-01',end='2016-05-04')
df = ts.sh_margin_details(start='2015-01-01', end='2015-04-19', symbol='601989')
df = ts.sz_margins(start='2015-06-01',end='2016-05-04')
# 只能一天天取
df = ts.sz_margin_details('2015-04-20')
# 取 沪深 日，周，分钟
df = ts.get_hist_data('sh', ktype='W')
df = ts.get_hist_data('sz', ktype='60')
df = ts.get_hist_data('cyb')
df = ts.get_hist_data('zxb')
# 龙虎榜
df = ts.top_list('2016-05-04')
# 计算macd
short_win = 12
long_win = 26
macd_win = 9
df = ts.get_hist_data('600405')
d = df['close']
dlist = d.tolist()
# 反向
dlist.reverse()
prices = np.array(dlist)
macd_tmp = tb.MACD(prices,fastperiod=short_win, slowperiod=long_win,signalperiod=macd_win)
MACD = macd_tmp[2]
DEA = macd_tmp[1]
DIF = macd_tmp[0]
def longhuban(self, date):
print(ts.top_list(date))
print(ts.cap_tops())
def longhuban(self, date):
print(ts.top_list(date))
print(ts.cap_tops())
today = str(date.today())
# today = '2016-07-01'
conn = MySQLdb.connect(host="localhost", user="******", passwd="root", db="stock", charset="utf8")
cursor = conn.cursor()
sql = "select calendarDate from trade_cal where isOpen=1 and calendarDate='" + today + "'"
cursor.execute(sql)
dateRes = cursor.fetchone()
if dateRes:
# 每日龙虎榜列表
try:
df = ts.top_list(today)
if df is not None:
for idx in df.index:
temp = df.ix[idx]
sql = "insert into top_list(code,name,pchange,amount,buy,bratio,sell,sratio,reason,date) values(%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)"
param = (temp['code'],temp['name'],temp['pchange'],temp['amount'],temp['buy'],temp['bratio'],temp['sell'],temp['sratio'],temp['reason'],temp['date'])
cursor.execute(sql, param)
conn.commit()
except:
f=open("errors/"+today+".log",'a')
traceback.print_exc(file=f)
f.flush()
f.close()
# 个股上榜统计
try:
__author__='Bill Dan'
import tushare as ts
import pymongo
from pymongo import MongoClient
import json
# conn=pymongo.Connection('127.0.0.1',port=27017)
client = MongoClient()
client = MongoClient('mongodb://localhost:27017/')
db=client.refdata
print 'start...'
df=ts.top_list('2017-03-21')
db.top_list.insert(json.loads(df.to_json(orient='records')))
print 'completed'
import pandas as pd
import tushare as ts
# pd.set_option('display.height', 1000)
pd.set_option('display.max_rows', 500)
pd.set_option('display.max_columns', 500)
pd.set_option('display.width', 1000)
def remove_percent(s):
if '.' in s and '%' in s:
return float(s.strip('%'))
return s
df = ts.top_list('2015-10-30')
df['pchange'] = df['pchange'].replace('%', '', regex=True).astype('float')
# print dir(df)
# print df.sort_values(by='pchange', ascending=False)[df.pchange>8.0]['code']
up_c_top_list = df[df.pchange>7.0]['code'].tolist()
up_n_top_list = df[df.pchange>7.0]['name'].tolist()
for c, n in zip(up_c_top_list, up_n_top_list):
# print c
df1 = ts.get_hist_data(c,start='2015-10-27',end='2015-10-30')
try:
if not df1.empty and df1['close'].tolist()[-1] < df1['ma20'].tolist()[-1]:
print c, n
print df1
except:
pass
def daily_longhu(self):
# date=self.date
date = '2016-04-05'
df = ts.top_list(date)
df.to_excel(date + ".xlsx")
def EveryDayTop(): day=dt.date.today() while ts.is_holiday(str(day)): day=day-dt.timedelta(days=1) df=ts.top_list(str(day)) return [u"%s日龙虎榜列表：(%s条)"%(str(day+dt.timedelta(days=1)),len(df)),df]