def __init__(self, backlight, display):
self.record_channels = [(2,3), (4,5), (6,7), (8,10), (11,12), (13, 14), (0, 1)]
self.chord_channel, self.melody_channel = self.record_channels[-1]
self.drum_channel = 9 #This is imposed by General MIDI
self.p = None #Polyphony; Assigned by Polyphony itself, upon initializatinon
self.b = backlight
self.d = display
self.f = flash.Flash(8)
self.recorded = 0 #bit map
self.playing = 0 #bit map
self.recording = None #channel number
self.recording_start_timestamp = None
#*#self.records = [[],[],[],[],[],[],[],[]]
self.record_lengths = [0]*8
self.cursors = [0]*8
self.durations = [0]*8
self.loop_start = [0]*8 #Timestamps
self.toggle_play_waitlist = 0 #bit map
self.loop_names = ["C", "D", "E", "F", "G", "A"]
#TODO: load recorded tracks status here
#Check & fix inconsitent flash disk state
if self.f.check_erased(self.loop_exists):
#Whole flash is being erased. Make sure we don't expect any tracks
self.recorded = 0
indicator.Indicator(self.d, ["flash_blank", "flash_w"], self.indicator_status) #The indicator registers itself with display
import TradeData as td
import indicator as ind
from datetime import datetime as dt
from dateutil.relativedelta import *
# download data from yahoo daily data, 1min, 2min
myTd = td.TradeData()
myTd.get_new('')
# #
myTd.get_2min('', dt.now() + relativedelta(days=-5), dt.now())
myTd.get_min('', dt.now() + relativedelta(days=-4), dt.now())
#
# # # calculate indicator
MyInd = ind.Indicator()
MyInd.ema()
MyInd.kdj()
MyInd.rsi(tickers=[])
MyInd.demark9Point()
MyInd.KDJDaysInRange()
MyInd.RSIDaysInRange()
def __init__(self):
indicator.Indicator()
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import indicator
class Init():
def __init__(self):
indicator.Indicator()
indicator.Indicator()
import pandas as pd
import stock_price as sp
import exploratory_data_analysis as eda
import indicator
# # test for web crawler
# sp.download_stock_price('AAPL')
#
# x = sp.dataframe_of_single_stock('TSLA')
# print(x)
#
# y = sp.dataframe_of_stocks(['BIDU', 'SINA'])
# print(y)
#
# df = pd.read_csv('company_list.csv')
# list_of_stock_symbol = df['Symbol'][:5] # first twenty stocks in the company list provided.
# z = sp.dataframe_of_stocks(list_of_stock_symbol)
# print(z)
# # test for EDA
# x = eda.EDA(['AAPL', 'TSLA', 'GS', 'MS'])
# x.compare_close_price()
# x.show_moving_avg()
# x.show_corr_map()
# test for indicator
x = indicator.Indicator('AAPL')
x.get_Volume()
def __init__(self):
self.Price = price.Price()
self.Price.parse()
self.Indicator = indicator.Indicator()
def _handle_coin(self, coin):
decision_point = len(self.interval) - 1
break_point = len(self.interval) - decision_point
buy = 0
force_buy = 0
force_sell = 0
sell = 0
df = None
for i, minute in enumerate(self.interval):
array = np.array(self.public_v2.candles(minute, "t" + coin.upper(), "hist"))[::-1]
df = pd.DataFrame(data=array[:, 0:6],
columns=["date", "open", "close", "high", "low", "volume"])
indicator = ind.Indicator(df)
signal = indicator.rate(coin, minute)
time.sleep(2.0)
if signal >= 1:
if coin in self.available_currencies and i >= break_point and signal < 2:
break
buy = buy + 1
if signal >= 2:
force_buy = force_buy + 1
elif signal <= -1:
if coin not in self.available_currencies and i >= break_point and signal < 2:
break
sell = sell + 1
if signal <= -2:
force_sell = force_sell + 1
if buy == 0 and sell == 0 and i >= break_point:
time.sleep(2.0)
break
if df is None or 'close' not in df:
logging.error(coin + " is missing price data")
return
price = float(df["close"][len(df) - 1])
if coin in self.buy_history and coin in self.available_currencies:
if price > self.buy_history[coin] * self.profit_multiplier:
logging.debug(coin + " IS profitable with price " + str(price) + " > " + str(
self.buy_history[coin] * self.profit_multiplier))
force_sell = force_sell + 1
else:
logging.debug(coin + " is NOT profitable with price " + str(price) + " < " + str(
self.buy_history[coin] * self.profit_multiplier))
self.latest_score[coin] = sell
if coin in self.latest_price:
if self.latest_price[coin] > price:
logging.debug(coin + " price is going down " + str(self.latest_price[coin]) + " -> " + str(price))
force_sell = force_sell + 1
if self.latest_price[coin] < price:
logging.debug(coin + " price is going up " + str(self.latest_price[coin]) + " -> " + str(price))
force_buy = force_buy + 1
if sell == len(self.interval):
force_sell = force_sell + 1
if buy == len(self.interval):
force_buy = force_buy + 1
self.latest_price[coin] = price
if buy == len(self.interval):
force_buy = force_buy + 1
if sell == len(self.interval):
force_sell = force_sell + 1
if coin in self.buy_attempts:
if self.buy_attempts[coin] > 6:
logging.debug(coin + " it's too late to catch the buy train")
buy = 0
force_buy = 0
logging.debug(
coin + " decision: B: " + str(buy) + " FB: " + str(force_buy) + " S: " + str(sell) + " FS: " + str(
force_sell))
if buy >= decision_point or force_buy >= decision_point:
ask = self._get_ask(coin, price)
bought = self._buy_coin(coin, str(ask), force_buy >= decision_point)
if not bought:
if coin not in self.buy_attempts:
self.buy_attempts[coin] = 0
elif self.buy_attempts[coin] < 10:
self.buy_attempts[coin] = self.buy_attempts[coin] + 1
elif coin in self.buy_attempts:
del self.buy_attempts[coin]
elif sell >= decision_point or force_sell >= decision_point:
bid = self._get_bid(coin, price)
sold = self._sell_coin(coin, str(bid), force_sell >= decision_point)
if sold and coin in self.buy_attempts:
self.buy_attempts[coin] = self.buy_attempts[coin] - 1
else:
if coin in self.buy_attempts:
self.buy_attempts[coin] = self.buy_attempts[coin] - 1
if coin in self.buy_attempts and self.buy_attempts[coin] <= 0:
del self.buy_attempts[coin]
import requests
from pandas import DataFrame
import talib.abstract as ta
import talib
import pandas as pd
import numpy as np
import math
import indicator
logging.basicConfig(
level=logging.DEBUG,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)
indicators = indicator.Indicator()
# Backtesting Counter
class Counter:
counter = 0
def get_ticker(pair: str, minimum_date: arrow.Arrow) -> dict:
"""
Request ticker data from Bittrex for a given currency pair
"""
url = 'https://bittrex.com/Api/v2.0/pub/market/GetTicks'
headers = {
'User-Agent':
'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.36',