def load_fx_market(self):
print("Loading FX market")
self.fx_api = ForeignExchancheCurrencyApi()
self.fx_api.cur1 = self.cur1
self.fx_api.cur2 = self.cur2
self.fx_api.send_amount = self.size
self.fx_api.data_path = os.path.dirname(__file__) # args.basepath
if not (args.nodownload or args.nodownloadFX):
self.fx_api.download()
self.fx_api.write_json()
else:
self.fx_api.read_json()
if args.printjson:
self.fx_api.pretty_print_json()
#requ_amount = self.fx_api.requ_amount()
#print("You will get {requ_amount}{cur2} for {send_amount}{cur1} - {cur1}{cur2}@{rate}".format(
# requ_amount=requ_amount, send_amount=self.fx_api.send_amount,
# cur1=self.fx_api.cur1, cur2=self.fx_api.cur2, rate=requ_amount/self.fx_api.send_amount))
self.fx_rate = self.fx_api.rate()
def load_fx_market(self):
print("Loading FX market")
self.fx_api = ForeignExchancheCurrencyApi()
self.fx_api.cur1 = self.cur1
self.fx_api.cur2 = self.cur2
self.fx_api.send_amount = self.size
self.fx_api.data_path = os.path.dirname(__file__) # args.basepath
if not (args.nodownload or args.nodownloadFX):
self.fx_api.download()
self.fx_api.write_json()
else:
self.fx_api.read_json()
if args.printjson:
self.fx_api.pretty_print_json()
#requ_amount = self.fx_api.requ_amount()
#print("You will get {requ_amount}{cur2} for {send_amount}{cur1} - {cur1}{cur2}@{rate}".format(
# requ_amount=requ_amount, send_amount=self.fx_api.send_amount,
# cur1=self.fx_api.cur1, cur2=self.fx_api.cur2, rate=requ_amount/self.fx_api.send_amount))
self.fx_rate = self.fx_api.rate()
def __init__(self, args):
self.args = args
fx_api = ForeignExchancheCurrencyApi()
fx_api.cur1 = args.send.upper()
fx_api.cur2 = args.requ.upper()
fx_api.data_path = os.path.dirname(__file__) # args.basepath
if args.send_amount == None:
fx_api.send_amount = 1.0
else:
fx_api.send_amount = float(args.send_amount)
if not args.nodownload:
fx_api.download()
fx_api.write_json()
else:
fx_api.read_json()
if args.printjson:
fx_api.pretty_print_json()
requ_amount = fx_api.requ_amount()
print(
"You will get {requ_amount}{cur2} for {send_amount}{cur1} - {cur1}{cur2}@{rate}"
.format(requ_amount=requ_amount,
send_amount=fx_api.send_amount,
cur1=fx_api.cur1,
cur2=fx_api.cur2,
rate=fx_api.rate())) #requ_amount/fx_api.send_amount
def __init__(self, args):
self.args = args
fx_api = ForeignExchancheCurrencyApi()
fx_api.cur1 = args.send.upper()
fx_api.cur2 = args.requ.upper()
fx_api.data_path = os.path.dirname(__file__) # args.basepath
if args.send_amount==None:
fx_api.send_amount = 1.0
else:
fx_api.send_amount = float(args.send_amount)
if not args.nodownload:
fx_api.download()
fx_api.write_json()
else:
fx_api.read_json()
if args.printjson:
fx_api.pretty_print_json()
requ_amount = fx_api.requ_amount()
print("You will get {requ_amount}{cur2} for {send_amount}{cur1} - {cur1}{cur2}@{rate}".format(
requ_amount=requ_amount, send_amount=fx_api.send_amount,
cur1=fx_api.cur1, cur2=fx_api.cur2, rate=fx_api.rate())) #requ_amount/fx_api.send_amount
class ConvertCurrenciesViaBTC:
def __init__(self, args):
self.args = args
self.cur1 = args.cur1.upper() #'EUR' # sent cur
self.cur2 = args.cur2.upper() #'USD' # requ cur
def update(self):
if args.size == None:
self.size = 1
else:
self.size = float(args.size)
self.load_fx_market()
self.load_btc_market()
def load_fx_market(self):
print("Loading FX market")
self.fx_api = ForeignExchancheCurrencyApi()
self.fx_api.cur1 = self.cur1
self.fx_api.cur2 = self.cur2
self.fx_api.send_amount = self.size
self.fx_api.data_path = os.path.dirname(__file__) # args.basepath
if not (args.nodownload or args.nodownloadFX):
self.fx_api.download()
self.fx_api.write_json()
else:
self.fx_api.read_json()
if args.printjson:
self.fx_api.pretty_print_json()
#requ_amount = self.fx_api.requ_amount()
#print("You will get {requ_amount}{cur2} for {send_amount}{cur1} - {cur1}{cur2}@{rate}".format(
# requ_amount=requ_amount, send_amount=self.fx_api.send_amount,
# cur1=self.fx_api.cur1, cur2=self.fx_api.cur2, rate=requ_amount/self.fx_api.send_amount))
self.fx_rate = self.fx_api.rate()
#print(self.fx_rate)
def load_btc_market(self):
print("Loading BTC market")
self.df_markets_btc = pd.read_csv(os.path.join(self.args.basepath,
'markets_btc.csv'),
sep=';')
#self.df_markets_exchangers = pd.read_csv('markets_exchangers.csv', sep=';')
# raise TypeError('unhashable type')
self.df_markets = self.df_markets_btc
#self.df_markets = pd.concat([self.df_markets_btc, self.df_markets_exchangers])
# see https://www.aurumxchange.com/data/rates.json
#self.df_markets.index = range(len(self.df_markets))
#self.df_markets.
#print(self.df_markets)
self.df_markets['active'] = self.df_markets['active'].map(bool)
self.df_markets[
'symbol'] = self.df_markets['cur1'] + '/' + self.df_markets['cur2']
self.df_markets['fullmarketname'] = self.df_markets[
'market'] + '|' + self.df_markets['symbol']
self.df_markets = self.df_markets[self.df_markets['active'] ==
True] # select only active market
self.df_markets['bid'] = None # NaN
self.df_markets['ask'] = None
#self.ob_dict = dict() # dictionary of order books
for i in self.df_markets.index:
market = self.df_markets['market'][i]
fullmarketname = self.df_markets['fullmarketname'][i]
#print(market)
symbol = self.df_markets['symbol'][i]
market_class = "OrderBook_{market}".format(market=market)
ob = eval(market_class)(self.args, symbol)
try:
self.df_markets['bid'][i] = ob.bid(self.size)
except:
print(
" Can't get bid price for {symbol} (market is probably not big enough)"
.format(symbol=symbol)) # NaN instead of bid/ask
self.df_markets['bid'][i] = np.nan
try:
self.df_markets['ask'][i] = ob.ask(self.size)
except:
print(
" Can't get ask for price {symbol} (market is probably not big enough)"
.format(symbol=symbol)) # NaN instead of bid/ask
self.df_markets['ask'][i] = np.nan
"""
stats = ob.get_stats()
for key, value in stats.items():
if i==0:
self.df_markets[key] = None
self.df_markets[key][i] = value
"""
self.df_markets[
'spread'] = self.df_markets['ask'] - self.df_markets['bid']
#self.df_markets = self.df_markets.reindex(self.df_markets['fullmarketname'])
self.df_markets.index = self.df_markets['fullmarketname']
print(self.df_markets)
filename = os.path.join(self.args.basepath,
"data_out_markets/_markets.csv")
self.df_markets.to_csv(filename)
markets_buy = self.df_markets[self.df_markets['cur2'] == self.cur1]
markets_sell = self.df_markets[self.df_markets['cur2'] == self.cur2]
self.df_matrix = pd.DataFrame(index=markets_buy['fullmarketname'],
columns=markets_sell['fullmarketname'])
self.df_ask = self.df_matrix.copy(
) # pd.DataFrame(index=markets_buy['fullmarketname'], columns=markets_sell['fullmarketname']) #self.df_matrix
self.df_bid = self.df_matrix.copy(
) # pd.DataFrame(index=markets_buy['fullmarketname'], columns=markets_sell['fullmarketname']) #self.df_matrix
for mk_buy in markets_buy.index:
self.df_ask.ix[mk_buy] = self.df_markets.ix[mk_buy]['ask']
for mk_sell in markets_sell.index:
self.df_bid[mk_sell] = self.df_markets.ix[mk_sell][
'bid'] # ToImprove: this can probably be done outside this for loop
filename = os.path.join(self.args.basepath,
"data_out_markets/_markets_matrix_ask.csv")
self.df_ask.to_csv(filename)
filename = os.path.join(self.args.basepath,
"data_out_markets/_markets_matrix_bid.csv")
self.df_bid.to_csv(filename)
self.df_matrix = self.df_bid / self.df_ask
print(self.df_matrix)
filename = os.path.join(self.args.basepath,
"data_out_markets/_markets_matrix.csv")
self.df_matrix.to_csv(filename)
self.df_convert_opportunities_all = pd.DataFrame(
self.df_matrix.unstack(), columns=['rate'])
self.df_convert_opportunities_all = self.df_convert_opportunities_all[
self.df_convert_opportunities_all['rate'] > -100]
self.df_convert_opportunities_all = self.df_convert_opportunities_all.sort(
'rate', ascending=False)
self.df_convert_opportunities_all.index.names = [
'market_sell', 'market_buy'
]
self.df_convert_opportunities_all = self.df_convert_opportunities_all.swaplevel(
0, 1,
axis=0) # swap to have market_buy as first hierarchical index
#print(self.df_convert_opportunities_all)
self.df_convert_opportunities_all['rateFX'] = self.fx_rate
self.df_convert_opportunities_all['rel diff (fx-btc)'] = (
self.df_convert_opportunities_all['rate'] -
self.fx_rate) / self.fx_rate * 100.0
#self.df_convert_opportunities_all[self.cur1] = 'ToDo'
#self.df_convert_opportunities_all[self.cur2] = 'ToDo'
#print("{cur1}/{cur2} = {fx_rate}".format(cur1=self.cur1, cur2=self.cur2, fx_rate=self.fx_rate))
self.df_convert_opportunities_all = self.df_convert_opportunities_all.sort(
'rate', ascending=False)
filename = os.path.join(self.args.basepath,
"data_out_markets/_currency_exch_via_btc.csv")
self.df_convert_opportunities_all.to_csv(filename)
self.df_convert_opportunities_all = self.df_convert_opportunities_all.sort(
'rate', ascending=True)
print(self.df_convert_opportunities_all)
class ConvertCurrenciesViaBTC:
def __init__(self, args):
self.args = args
self.cur1 = args.cur1.upper() #'EUR' # sent cur
self.cur2 = args.cur2.upper() #'USD' # requ cur
def update(self):
if args.size==None:
self.size = 1
else:
self.size = float(args.size)
self.load_fx_market()
self.load_btc_market()
def load_fx_market(self):
print("Loading FX market")
self.fx_api = ForeignExchancheCurrencyApi()
self.fx_api.cur1 = self.cur1
self.fx_api.cur2 = self.cur2
self.fx_api.send_amount = self.size
self.fx_api.data_path = os.path.dirname(__file__) # args.basepath
if not (args.nodownload or args.nodownloadFX):
self.fx_api.download()
self.fx_api.write_json()
else:
self.fx_api.read_json()
if args.printjson:
self.fx_api.pretty_print_json()
#requ_amount = self.fx_api.requ_amount()
#print("You will get {requ_amount}{cur2} for {send_amount}{cur1} - {cur1}{cur2}@{rate}".format(
# requ_amount=requ_amount, send_amount=self.fx_api.send_amount,
# cur1=self.fx_api.cur1, cur2=self.fx_api.cur2, rate=requ_amount/self.fx_api.send_amount))
self.fx_rate = self.fx_api.rate()
#print(self.fx_rate)
def load_btc_market(self):
print("Loading BTC market")
self.df_markets_btc = pd.read_csv(os.path.join(self.args.basepath, 'markets_btc.csv'), sep=';')
#self.df_markets_exchangers = pd.read_csv('markets_exchangers.csv', sep=';')
# raise TypeError('unhashable type')
self.df_markets = self.df_markets_btc
#self.df_markets = pd.concat([self.df_markets_btc, self.df_markets_exchangers])
# see https://www.aurumxchange.com/data/rates.json
#self.df_markets.index = range(len(self.df_markets))
#self.df_markets.
#print(self.df_markets)
self.df_markets['active'] = self.df_markets['active'].map(bool)
self.df_markets['symbol'] = self.df_markets['cur1'] + '/' + self.df_markets['cur2']
self.df_markets['fullmarketname'] = self.df_markets['market'] + '|' + self.df_markets['symbol']
self.df_markets = self.df_markets[self.df_markets['active']==True] # select only active market
self.df_markets['bid'] = None # NaN
self.df_markets['ask'] = None
#self.ob_dict = dict() # dictionary of order books
for i in self.df_markets.index:
market = self.df_markets['market'][i]
fullmarketname = self.df_markets['fullmarketname'][i]
#print(market)
symbol = self.df_markets['symbol'][i]
market_class = "OrderBook_{market}".format(market=market)
ob = eval(market_class)(self.args, symbol)
try:
self.df_markets['bid'][i] = ob.bid(self.size)
except:
print(" Can't get bid price for {symbol} (market is probably not big enough)".format(symbol=symbol)) # NaN instead of bid/ask
self.df_markets['bid'][i] = np.nan
try:
self.df_markets['ask'][i] = ob.ask(self.size)
except:
print(" Can't get ask for price {symbol} (market is probably not big enough)".format(symbol=symbol)) # NaN instead of bid/ask
self.df_markets['ask'][i] = np.nan
"""
stats = ob.get_stats()
for key, value in stats.items():
if i==0:
self.df_markets[key] = None
self.df_markets[key][i] = value
"""
self.df_markets['spread'] = self.df_markets['ask'] - self.df_markets['bid']
#self.df_markets = self.df_markets.reindex(self.df_markets['fullmarketname'])
self.df_markets.index = self.df_markets['fullmarketname']
print(self.df_markets)
filename = os.path.join(self.args.basepath, "data_out_markets/_markets.csv")
self.df_markets.to_csv(filename)
markets_buy = self.df_markets[self.df_markets['cur2']==self.cur1]
markets_sell = self.df_markets[self.df_markets['cur2']==self.cur2]
self.df_matrix = pd.DataFrame(index=markets_buy['fullmarketname'], columns=markets_sell['fullmarketname'])
self.df_ask = self.df_matrix.copy() # pd.DataFrame(index=markets_buy['fullmarketname'], columns=markets_sell['fullmarketname']) #self.df_matrix
self.df_bid = self.df_matrix.copy() # pd.DataFrame(index=markets_buy['fullmarketname'], columns=markets_sell['fullmarketname']) #self.df_matrix
for mk_buy in markets_buy.index:
self.df_ask.ix[mk_buy] = self.df_markets.ix[mk_buy]['ask']
for mk_sell in markets_sell.index:
self.df_bid[mk_sell] = self.df_markets.ix[mk_sell]['bid'] # ToImprove: this can probably be done outside this for loop
filename = os.path.join(self.args.basepath, "data_out_markets/_markets_matrix_ask.csv")
self.df_ask.to_csv(filename)
filename = os.path.join(self.args.basepath, "data_out_markets/_markets_matrix_bid.csv")
self.df_bid.to_csv(filename)
self.df_matrix = self.df_bid/self.df_ask
print(self.df_matrix)
filename = os.path.join(self.args.basepath, "data_out_markets/_markets_matrix.csv")
self.df_matrix.to_csv(filename)
self.df_convert_opportunities_all = pd.DataFrame(self.df_matrix.unstack(), columns=['rate'])
self.df_convert_opportunities_all = self.df_convert_opportunities_all[self.df_convert_opportunities_all['rate']>-100]
self.df_convert_opportunities_all = self.df_convert_opportunities_all.sort('rate', ascending=False)
self.df_convert_opportunities_all.index.names = ['market_sell', 'market_buy']
self.df_convert_opportunities_all = self.df_convert_opportunities_all.swaplevel(0, 1, axis=0) # swap to have market_buy as first hierarchical index
#print(self.df_convert_opportunities_all)
self.df_convert_opportunities_all['rateFX'] = self.fx_rate
self.df_convert_opportunities_all['rel diff (fx-btc)'] = (self.df_convert_opportunities_all['rate'] - self.fx_rate) / self.fx_rate * 100.0
#self.df_convert_opportunities_all[self.cur1] = 'ToDo'
#self.df_convert_opportunities_all[self.cur2] = 'ToDo'
#print("{cur1}/{cur2} = {fx_rate}".format(cur1=self.cur1, cur2=self.cur2, fx_rate=self.fx_rate))
self.df_convert_opportunities_all = self.df_convert_opportunities_all.sort('rate', ascending=False)
filename = os.path.join(self.args.basepath, "data_out_markets/_currency_exch_via_btc.csv")
self.df_convert_opportunities_all.to_csv(filename)
self.df_convert_opportunities_all = self.df_convert_opportunities_all.sort('rate', ascending=True)
print(self.df_convert_opportunities_all)
