def __init__(self, last_date = None):

self.latest_date = ''

self.spy_df = None

self.last_date = last_date

def get_analysis_df(self, sym):

analysis_df = pd.read_csv(ANALYSIS_DIR + sym + '_analysis.csv', index_col = 0)

return analysis_df

def get_quote_symbol_list(self):

quote_symbol_list = []

filelist = [ f for f in os.listdir(DATA_DIR) if f.endswith('.csv') ]

for f in filelist:

sym = f.split('.')[0]

quote_symbol_list.append(sym)

return quote_symbol_list

def get_analysis_symbol_list(self):

analysis_symbol_list = []

filelist = [ f for f in os.listdir(ANALYSIS_DIR) if f.endswith('.csv') and not f.endswith('_renko.csv')]

for f in filelist:

sym = f.split('.')[0]

analysis_symbol_list.append(sym.replace('_analysis', ''))

return analysis_symbol_list

def update_quotes(self, sym_list = None):

if sym_list is None:

return

q = Quote(self.last_date)

self.spy_df, already_up_to_date = q.update('SPY')

if self.spy_df is not None:

latest_date = self.spy_df.index[-1]

else:

latest_date = None

for sym in sym_list:

df, already_up_to_date = q.update(sym, latest_date)

if already_up_to_date == False:

time.sleep(random.randint(1, 5))

def update_analysis(self, symbol_list = None):

a = Analysis()

analysis_symbol_list = []

if symbol_list != None:

for sym in symbol_list:

analysis_symbol_list.append(sym)

else:

filelist = [ f for f in os.listdir(DATA_DIR) if f.endswith('.csv') and not f.endswith('_analysis.csv') and not f.endswith('_renko.csv')]

for f in filelist:

sym = f.split('.')[0]

analysis_symbol_list.append(sym)

for sym in analysis_symbol_list:

print 'Analysing', sym, '....'

if os.path.isfile(ANALYSIS_DIR + sym + '_analysis.csv'):

analysis_df = pd.read_csv(ANALYSIS_DIR + sym + '_analysis.csv', index_col = 0)

if analysis_df.empty is False:

if analysis_df.index[-1] == self.latest_date:

continue

if os.path.isfile(DATA_DIR + sym + '.csv'):

f = sym + '.csv'

df = pd.read_csv(DATA_DIR + f, index_col = 0)

a.analysis(sym, df, self.spy_df)

def run(self, symbol_list = None):

if symbol_list == None:

symbol_list = []

lines = open(config.TRADABLE_STOCKS, 'r').read().split('\n')

for line in lines:

if len(line) > 0:

symbol_list.append(line)

if len(symbol_list) == 0:

print 'Symbol list is empty, so nothing is being done'

return

# ---------------------------------------------------------------------

# Read in existing SPY quote file if exists

# ---------------------------------------------------------------------

if os.path.isfile(DATA_DIR + 'SPY.csv'):

print 'read spy.csv'

self.spy_df = pd.read_csv(DATA_DIR + 'SPY.csv', index_col = 0)

if self.spy_df is not None:

self.latest_date = self.spy_df.index[-1]

else:

self.latest_date = None

self.update_quotes(symbol_list)

self.update_analysis(symbol_list)

r = Report()

r.report(symbol_list)

def ibd_watch_list(self, type):

#

# 'ibd 50'

# 'ibd spotlight'

# 'ibd relative strength'

#

if os.path.isfile(ibd_stock_file):

fp = open(ibd_stock_file, 'r')

stocks = json.loads(fp.read())

fp.close()

else:

stocks = {}

#print json.dumps(stocks, indent=4)

symbol_list = []

for key in stocks.keys():

entry = stocks[key];

if type in entry.keys():

# print entry[type]

symbol_list.append([key, entry[type][-1]])

for sym in symbol_list:

print sym

print len(symbol_list)

diff_list = []

quote_symbol_list = self.get_quote_symbol_list()

for sym in symbol_list:

if sym[0] not in quote_symbol_list:

diff_list.append(sym)

print '============= Diff List ============='

print len(diff_list)

for sym in diff_list:

print sym

return symbol_list

def percent_change_one_symbol(self, sym, pc, vr):

df = pd.read_csv(ANALYSIS_DIR + sym + '_analysis.csv', index_col = 0)

closes = df['close']

last_close = closes[-1]

before_last_close = closes[-2]

percent_change = ((last_close - before_last_close)/before_last_close) * 100

volume = df['volume']

vol_sma50 = df['vol_sma50']

volume_ratio = float(volume[-1])/float(vol_sma50[-1])

rwb = df['rwb']

output_str = sym + ': last_close = ' + str(last_close) + ', before_last_close = ' + str(before_last_close)

output_str = output_str + ', percent_change = ' + str(percent_change) + '%'

output_str = output_str + ', volume_ratio = ' + str(volume_ratio) + ', rwb = ' + str(rwb[-1])

if (percent_change >= pc) and (volume_ratio >= vr) and (rwb[-1] >= 0):

output_str = output_str + ', keep'

result = [sym, percent_change, volume_ratio]

else:

output_str = output_str + ', pass'

result = None

print output_str

return result

def percent_change(self, pc, vr, symbol_list = None):

df = pd.read_csv(DATA_DIR + 'SPY.csv', index_col = 0)

index = df.index

date_string = index[-1]

print 'Today is', date_string

if os.path.isfile(ANALYSIS_DIR + 'percent_mover.json'):

percent_mover = json.loads(open(ANALYSIS_DIR + 'percent_mover.json', 'r').read())

else:

percent_mover = {}

if date_string in percent_mover.keys():

print 'Already scanned, do nothing'

return

else:

print 'Have not scanned today, scanning ...'

scan_symbol_list = []

if symbol_list != None:

for sym in symbol_list:

scan_symbol_list.append(sym)

else:

filelist = [ f for f in os.listdir(DATA_DIR) if f.endswith('.csv') ]

for f in filelist:

sym = f.split('.')[0]

scan_symbol_list.append(sym)

if len(scan_symbol_list) == 0:

print 'Symbol list is empty, nothing to scan'

result = []

for sym in scan_symbol_list:

ret = self.percent_change_one_symbol(sym, pc, vr)

if ret != None:

result.append(ret)

percent_mover[date_string] = result

fp = open(ANALYSIS_DIR + 'percent_mover.json', 'w')

fp.write(json.dumps(percent_mover, indent=4))

fp.close()

if len(result) == 0:

print 'Scan result emtpy'

return None

else:

for item in result:

print item

return result

def earnings(self, symbol_list = None):

scan_symbol_list = []

if symbol_list != None:

for sym in symbol_list:

scan_symbol_list.append(sym)

else:

filelist = [ f for f in os.listdir(DATA_DIR) if f.endswith('.csv') ]

for f in filelist:

sym = f.split('.')[0]

scan_symbol_list.append(sym)

if os.path.isfile(earnings_file):

earnings_db = json.loads(open(earnings_file, 'r').read())

else:

earnings_db = {}

n = Nasdaq()

for sym in scan_symbol_list:

if n.earning(sym) == True: