def compute_3or5(stock_no):
date_infos = da.dailyrecords.load_by_stockno(stock_no)
date_len = len(date_infos)
rows = []
for i in range(0, date_len):
print i
stock_date = date_infos[i]
d = stock_date.date
dh5 = __compute_trend(date_infos, i, 5, 'high_price')
dh3 = __compute_trend(date_infos, i, 3, 'high_price')
dl5 = __compute_trend(date_infos, i, 5, 'low_price')
dl3 = __compute_trend(date_infos, i, 3, 'low_price')
#未来n天内，收盘价 与 明天开盘价对比
prates = {}
tommorrow_open_price = date_infos[i - 1].open_price
for day in range(2, 6):
prates[day] = None
if i < day: continue
prates[day] = (date_infos[i - day].close_price -
tommorrow_open_price) / tommorrow_open_price
if i > 6:
p = date_infos[i - 6].close_price - date_infos[i - 1].open_price
prate = p / date_infos[i - 1].open_price
print stock_date.date, dh5, dh3, dl5, dl3, p, prate
if date_len > (i + 5):
history_prate_3 = (
stock_date.close_price -
date_infos[i + 3].close_price) / date_infos[i + 3].close_price
history_prate_5 = (
stock_date.close_price -
date_infos[i + 5].close_price) / date_infos[i + 5].close_price
rows.append(
web.storage(pk_id=stock_date.pk_id,
date=stock_date.date,
stock_no=stock_date.stock_no,
high5=dh5,
high3=dh3,
low5=dl5,
low3=dl3,
tmrow_open_price=tommorrow_open_price,
price_rate_2=prates[2],
price_rate_3=prates[3],
price_rate_4=prates[4],
price_rate_5=prates[5],
history_prate_3=history_prate_3,
history_prate_5=history_prate_5))
i = i + 1
dbw.delete('trend_daily', where="stock_no=$stock_no", vars=locals())
dbw.supports_multiple_insert = True
dbw.multiple_insert('trend_daily', rows)
def insert(terms):
if not terms:
return
values = []
for t in terms:
if not t[0].strip(): continue
values.append({'term':t[0],'count':t[1],'idf':t[2],'last_update':datetime.datetime.now()} )
dbw.supports_multiple_insert = True
dbw.multiple_insert(tname, values=values)
def update_v2(l):
dbw.delete('stock_daily_records_tmp',where="pk_id>0",vars=locals())
dbw.supports_multiple_insert = True
dbw.multiple_insert('stock_daily_records_tmp',l)
dbw.query('''update stock_daily_records a,stock_daily_records_tmp t set
a.raise_drop=t.raise_drop,
a.raise_drop_rate=t.raise_drop_rate,
a.volume_updown=t.volume_updown,
a.volume_updown_rate=t.volume_updown_rate,
a.last_update = t.last_update
where a.pk_id=t.pk_id''')
def update_v2(l):
dbw.delete('stock_daily_records_tmp', where="pk_id>0", vars=locals())
dbw.supports_multiple_insert = True
dbw.multiple_insert('stock_daily_records_tmp', l)
dbw.query('''update stock_daily_records a,stock_daily_records_tmp t set
a.raise_drop=t.raise_drop,
a.raise_drop_rate=t.raise_drop_rate,
a.volume_updown=t.volume_updown,
a.volume_updown_rate=t.volume_updown_rate,
a.last_update = t.last_update
where a.pk_id=t.pk_id''')
def import_to_db(params,results):
stock_nos = load_all_stock_nos()
l = []
for r in results:
if r[0] not in stock_nos:
row = {'market_code':params['t'],'stock_no':r[0],'stock_name':r[1],'create_date':datetime.datetime.now(),'last_update':datetime.datetime.now()}
print row
l.append(row)
dbw.supports_multiple_insert = True
dbw.multiple_insert('stock_base_infos',l)
def insert(terms):
if not terms:
return
values = []
for t in terms:
if not t[0].strip(): continue
values.append({
'term': t[0],
'count': t[1],
'idf': t[2],
'last_update': datetime.datetime.now()
})
dbw.supports_multiple_insert = True
dbw.multiple_insert(tname, values=values)
def import_stock_daily_data(market_code,stock_no,data):
stock_dates = load_stock_dates(stock_no)
max_date = max(stock_dates) if stock_dates else '1900-01-01'
l=[]
for row in data:
#if row['date'] <= max_date: break
if row['date'] in stock_dates:
continue
row['stock_market_no'] = market_code
row['stock_no'] = stock_no
row['create_date'] = datetime.datetime.now()
row['last_update'] = datetime.datetime.now()
l.append(row)
print '%s.%s csv len is %s' %(market_code,stock_no,len(data))
print '%s.%s insert len is %s' %(market_code,stock_no,len(l))
dbw.supports_multiple_insert = True
dbw.multiple_insert('stock_daily_records',l)
def import_stock_daily_data(market_code, stock_no, data):
stock_dates = load_stock_dates(stock_no)
max_date = max(stock_dates) if stock_dates else '1900-01-01'
l = []
for row in data:
#if row['date'] <= max_date: break
if row['date'] in stock_dates:
continue
row['stock_market_no'] = market_code
row['stock_no'] = stock_no
row['create_date'] = datetime.datetime.now()
row['last_update'] = datetime.datetime.now()
l.append(row)
print '%s.%s csv len is %s' % (market_code, stock_no, len(data))
print '%s.%s insert len is %s' % (market_code, stock_no, len(l))
dbw.supports_multiple_insert = True
dbw.multiple_insert('stock_daily_records', l)
def compute_3or5(stock_no):
date_infos = da.dailyrecords.load_by_stockno(stock_no)
date_len = len(date_infos)
rows = []
for i in range(0,date_len):
print i
stock_date = date_infos[i]
d = stock_date.date
dh5 = __compute_trend(date_infos,i,5,'high_price')
dh3 = __compute_trend(date_infos,i,3,'high_price')
dl5 = __compute_trend(date_infos,i,5,'low_price')
dl3 = __compute_trend(date_infos,i,3,'low_price')
#未来n天内，收盘价 与 明天开盘价对比
prates = {}
tommorrow_open_price = date_infos[i-1].open_price
for day in range(2,6):
prates[day] = None
if i < day : continue
prates[day] = (date_infos[i-day].close_price - tommorrow_open_price) / tommorrow_open_price
if i > 6:
p = date_infos[i-6].close_price - date_infos[i-1].open_price
prate = p/date_infos[i-1].open_price
print stock_date.date,dh5,dh3,dl5,dl3,p,prate
if date_len > (i+5):
history_prate_3 = (stock_date.close_price - date_infos[i+3].close_price) / date_infos[i+3].close_price
history_prate_5 = (stock_date.close_price - date_infos[i+5].close_price) / date_infos[i+5].close_price
rows.append(web.storage(pk_id=stock_date.pk_id,date=stock_date.date,stock_no=stock_date.stock_no,
high5=dh5,high3=dh3,low5=dl5,low3=dl3,tmrow_open_price=tommorrow_open_price,
price_rate_2=prates[2],price_rate_3=prates[3],price_rate_4=prates[4],price_rate_5=prates[5],
history_prate_3=history_prate_3,history_prate_5=history_prate_5))
i = i + 1
dbw.delete('trend_daily',where="stock_no=$stock_no",vars=locals())
dbw.supports_multiple_insert = True
dbw.multiple_insert('trend_daily',rows)
def import_daily_records(table,rows):
dbw.supports_multiple_insert = True
dbw.multiple_insert(table,rows)
def import_daily_records(table, rows):
dbw.supports_multiple_insert = True
dbw.multiple_insert(table, rows)
