def test_VerifWeHaveDataForEachSecond(self):
tick = tk.ticker()
tick.PrepareFile('1mintestdata.csv')
startDate = tick.Data.index[0]
endDate = tick.Data.index[-1]
dataSize = len(tick.Data['price'])
numSeconds = endDate - startDate
min =(numSeconds + 1)/60
self.assertEqual(min, dataSize)
def GetTicker(self, Pair = PairType.BtcNis):
url = self.Url + "Exchanges/" + str(Pair) + "/Ticker.json"
response = self.DownloadString(url)
_json = json.loads(response.decode("utf-8"))
return Ticker(_json['h'], _json['l'], _json['ll'], _json['a'], _json['av'])
def main():
for ticker_id in Ticker.getListVN30():
file = '../data/VNX/' + ticker_id + '/Price.csv'
ticker_data = pd.read_csv(file)
data = np.array(ticker_data)
getResult(ticker_id, data)
def index(stock):
print(stock)
tic = Ticker.Ticker(stock)
date = tic.data.index
_open = tic.data['Open']
close = tic.data['Close']
high = tic.data['High']
low = tic.data['Low']
volume = tic.data['Volume']
ao = tic.data['ao']
ac = tic.data['ac']
ad = tic.data['a/d']
atr = tic.data['atr']
bep = tic.data['bears_power']
bup = tic.data['bulls_power']
cci = tic.data['cci']
dem = tic.data['dem']
ema = tic.data['ema']
frc = tic.data['frc']
cncs = tic.data['chikou_span']
cnts = tic.data['tenkan_sen']
cnks = tic.data['kijun_sen']
cnssa = tic.data['senkou_span_a']
cnssb = tic.data['senkou_span_b']
bw_mfi = tic.data['bw_mfi']
mfi = tic.data['mfi']
momentum = tic.data['momentum']
macd_v = tic.data['macd_value']
macd_s = tic.data['macd_signal']
bbu = tic.data['bollinger_up']
bbm = tic.data['bollinger_mid']
bbb = tic.data['bollinger_bottom']
sma = tic.data['sma']
fr_h = tic.data['fractal_highs']
fr_l = tic.data['fractal_lows']
arr = []
print('len', len(tic.data))
for i in range(len(tic.data)):
dic = {}
dic['open'] = _open[i]
#dic['date'] = date[i].__str__()
dic['date'] = date[i].strftime("%Y-%m-%-d")
#print(dic['open'])
dic['close'] = close[i]
dic['high'] = high[i]
dic['low'] = low[i]
dic['volume'] = volume[i]
dic['awesome_oss'] = ao[i]
dic['accel_oss'] = ac[i]
dic['accum_dist'] = ad[i]
dic['avg_true_range'] = atr[i]
dic['bears_power'] = bep[i]
dic['bulls_power'] = bup[i]
dic['commodity_chan_index'] = cci[i]
dic['demarker'] = dem[i]
dic['exp_moving_avg'] = ema[i]
dic['force_index'] = frc[i]
dic['chikou_span'] = cncs[i]
dic['tenkan_sen'] = cnts[i]
dic['kijun_sen'] = cnks[i]
dic['senkou_span_a'] = cnssa[i]
dic['senkou_span_b'] = cnssb[i]
dic['market_facilitation_index'] = bw_mfi[i]
dic['momentum'] = momentum[i]
dic['money_flow_index'] = mfi[i]
dic['macd_value'] = macd_v[i]
dic['macd_signal'] = macd_s[i]
dic['bollinger_up'] = bbu[i]
dic['bollinger_mid'] = bbm[i]
dic['bollinger_bottom'] = bbb[i]
dic['sma'] = sma[i]
dic['fract_high'] = fr_h[i]
dic['fract_low'] = fr_l[i]
arr.append(dic)
for g in arr:
for key, value in g.items():
if key == 'date':
continue
if value > 0:
g[key] = int(value * 1000) / 1000
else:
g[key] = None
res = {}
res['data'] = arr
return res
import numpy as np
import pandas as pd
import Ticker
import platform
import os
import datetime
import time
import common_vars as _v
os.chdir('../')
path = os.getcwd()
blue_chip_tickers = Ticker.getListBlueChips2020()
close_col_index = 4
open_col_index = 1
date_col_index = 0
budget = 5000 # 5tr
test_from_date = "2020-01-01" # Y-m-d
from_date = time.strptime(test_from_date, "%Y-%m-%d")
buyAndSellDays = [[0, 2], [0, 3], [0, 4], [1, 3], [1, 4], [1, 0], [2,
4], [2, 0],
[2, 1], [3, 0], [3, 1], [3, 2], [4, 1], [4, 2], [4, 3]]
ticker_id = 'BID'
best_profit = 0
best_buy_day = -1
best_sell_day = -1
best_profit_ticker = ''
highlight = ''
if platform.system() == 'Windows':
file = path + "\\data\\VNX\\" + ticker_id + '\\Price.csv'
if platform.system() != 'Windows':
file = path + '/data/VNX/' + ticker_id + '/Price.csv'
def test_PrepareFile(self):
tick = tk.ticker()
tick.PrepareFile('1mintestdata.csv')
self.assertTrue(True)