def calc_all_macd(table, fast=12, slow=26, sign=9):
log.info('MACD generating for ' + table)
db = SqliteDB().createIndicator(table, 'MACD', 'A', fast, slow, sign)
prices = SqliteDB().getAllPrices(table)
macds = calc_macd(prices, fast, slow, sign)
for i in range(len(prices)):
db.addIndicate(prices[i]['dtlong'], macds['macd'][i], macds['sign'][i],
macds['fast'][i], macds['slow'][i])
db.commit()
log.info('MACD done')
def calc_all_rsi(table, period=14):
log.info('RSI generating for ' + table)
db = SqliteDB().createIndicator(table, 'RSI', 'A', period)
prices = SqliteDB().getAllPrices(table)
rsis = calc_rsi(prices, period)
for i in range(len(prices)):
db.addIndicate(prices[i]['dtlong'], rsis['rsi'][i], rsis['up'][i],
rsis['down'][i])
db.commit()
log.info('RSI done')
def calc_all_kdj(table, kPeriod=5, dPeriod=3, slowing=3):
log.info('KDJ generating for ' + table)
db = SqliteDB().createIndicator(table, 'KDJ', 'A', kPeriod, dPeriod,
slowing)
prices = SqliteDB().getAllPrices(table)
kds = calc_kd(prices, kPeriod, dPeriod, slowing)
for i in range(len(prices)):
db.addIndicate(prices[i]['dtlong'], kds['k'][i], kds['d'][i])
db.commit()
log.info('KDJ done')
def calc_all_bolling(table, period=20, deviate=2):
log.info('Bolling generating for ' + table)
db = SqliteDB().createIndicator(table, 'BOLLING', 'A', period, deviate)
prices = SqliteDB().getAllPrices(table)
bollings = calc_bolling(prices, period, deviate)
for i in range(len(prices)):
db.addIndicate(prices[i]['dtlong'], bollings['boll'][i],
bollings['mean'][i], bollings['upper'][i],
bollings['lower'][i], bollings['std'][i])
db.commit()
log.info('Bolling done')
def tally(ptype, price):
db = SqliteDB()
ret = ''
dLong = time.mktime(price['dt'].timetuple())
dDate = price['dt'].strftime('%Y-%m-%d')
dTime = price['dt'].strftime('%H:%M:%S')
db.addPrice((ptype, dLong, dDate, dTime, price['p'], price['per'],
price['p0'], '', dLong, dDate, dTime))
# calculate the percentage
percent0 = price['per']
# get the price of 3 minutes ago
price3 = db.getPrice(ptype, dLong - 180)
percent3 = 0
if price3:
log.debug(ptype + ',price3,' + str(price3[3]) + ',' + str(price3[0]))
price3 = price3[0]
percent3 = round((price['p'] - price3) * 100 / price3, 3)
# get the price of 30 minutes ago
price30 = db.getPrice(ptype, dLong - 1800)
percent30 = 0
if price30:
log.debug(ptype + ',price30,' + str(price30[3]) + ',' +
str(price30[0]))
price30 = price30[0]
percent30 = round((price['p'] - price30) * 100 / price30, 3)
# get last message information
notper0 = db.getNotice(ptype, 0, dDate)
log.info(ptype + ', percentage 0: ' + str(percent0) + ', last notice: ' +
str(notper0))
#print notper0
if abs(percent0 - notper0) >= 1:
ret = ptype + '0,' + str(price['p']) + ',' + str(percent0) + '%;\n'
db.addNotice(
(ptype, 0, dLong, dDate, dTime, price['p'], percent0, ret, ''))
notcount30 = db.getNoticeCount(ptype, 30, dLong - 1800)
log.info(ptype + ', percentage 30: ' + str(percent30) +
', notice in 30 minutes: ' + str(notcount30))
if notcount30 == 0 and abs(percent30) >= 1:
ret = ret + ptype + '30,' + str(
price['p']) + ',' + str(percent30) + '%;\n'
db.addNotice(
(ptype, 30, dLong, dDate, dTime, price['p'], percent30, ret, ''))
notcount3 = db.getNoticeCount(ptype, 3, dLong - 180)
log.info(ptype + ', percentage 3: ' + str(percent3) +
', notice in 3 minutes: ' + str(notcount3))
if notcount3 == 0 and abs(percent3) >= 0.5:
ret = ret + ptype + '3,' + str(
price['p']) + ',' + str(percent3) + '%;\n'
db.addNotice(
(ptype, 3, dLong, dDate, dTime, price['p'], percent3, ret, ''))
return ret
def latestPrices():
msg = datetime.datetime.now().strftime('%m-%d %H:%M') + ':\n'
dtypes = ['AGG', 'AGTD', 'SHDX']
db = SqliteDB()
dtLong = long(time.time())
for dtype in dtypes:
price = db.getPrice(dtype, dtLong)
msg = msg + dtype + ':' + str(price[0]) + ',' + str(
price[1]) + '%,' + str(price[2]) + ';\n'
log.info('latest prices: ' + msg)
return msg
def calc_all_ma(table, matype, period, weight=0):
log.info('MA generating ' + matype + ' for ' + table)
db = SqliteDB().createIndicator(table, 'MA', matype, period, weight)
prices = SqliteDB().getAllPrices(table)
ps = [p['close'] for p in prices]
if matype == 'MA':
mas = calc_ma(ps, period)
elif matype == 'EMA':
mas = calc_ema(ps, period)
elif matype == 'SMA':
mas = calc_sma(ps, period)
elif matype == 'LWMA':
mas = calc_lwma(ps, period)
for i in range(len(prices)):
db.addIndicate(prices[i]['dtlong'], mas[i])
db.commit()
log.info('MA done')
return mas
def importTable(table):
db = SqliteDB()
prices = importToArray(table)
for p in prices:
db.addData(table, (
p['dtlong'],
p['date'],
p['time'],
p['open'],
p['high'],
p['low'],
p['close'],
p['vol'],
p['rmb'],
p['chan'],
p['per'],
))
db.commit()
def batchMonitor():
try:
db = SqliteDB()
db.cleanOldData()
except:
log.exception('dayMonitor Exception Occured!')
