def bulkloadlivedatabytime(instrument, granularity, start):
# load data from start date to now
# example: bulkloadlivedatabytime('EUR_GBP','M15','2017-08-07T00:00:00Z')
client = API(access_token=access_token)
time = []
value = []
stop_date = datetime.utcnow()
start_date = datetime.strptime(start, "%Y-%m-%dT%H:%M:%SZ")
diff = stop_date - start_date
mins = int(diff.total_seconds() / (60 * 15))
print(mins)
stop = stop_date.strftime("%Y-%m-%dT%H:%M:%SZ")
print(stop)
params = {
"from": start,
"to": stop,
"granularity": granularity,
"count": mins
}
for r in InstrumentsCandlesFactory(instrument=instrument, params=params):
client.request(r)
data = r.response.get('candles')
for k in range(len(data)):
time.append(data[k]['time'])
value.append(data[k]['mid']['c'])
d = {'time': time, instrument: value}
df = pandas.DataFrame(data=d)
return df
def histPrice(self, broker, accountID, pair, t0, t1=None, gran='M10'):
if broker == 'oanda':
t0Str = t0.strftime('%Y-%m-%dT%H:%M:%S') + 'Z'
if t1 == None:
paramshist = \
{
"from": str(t0Str),
"granularity": gran
}
else:
t1Str = t1.strftime('%Y-%m-%dT%H:%M:%S') + 'Z'
paramshist = \
{
"from": str(t0Str),
"to": str(t1Str),
"granularity": gran
}
priceH = pd.DataFrame({
'c': [],
'h': [],
'l': [],
'o': []
},
index=[])
client = API(access_token=cfg.brokerList['oanda']['token'])
for r in InstrumentsCandlesFactory(instrument=pair,
params=paramshist):
rv = dict(client.request(r))["candles"]
for candle in rv:
print(candle)
priceH.loc[pd.Timestamp(candle["time"],
tzinfo='UTC')] = candle["mid"]
return (priceH)
def get_exrate_as_df(instrument='EUR_USD',
granularity='D',
from_=None,
to='2019-03-01',
count=100):
if from_ is None:
params = {
'granularity': granularity,
'to': to,
'count': count,
}
else:
params = {
'granularity': granularity,
'from': from_,
'to': to,
}
api = API(access_token=ACCESS_TOKEN)
r = instruments.InstrumentsCandles(instrument=instrument, params=params)
api.request(r)
data = []
for row in r.response['candles']:
data.append([
row['time'], row['mid']['o'], row['mid']['h'], row['mid']['l'],
row['mid']['c'], row['volume']
])
df = pd.DataFrame(data)
df.columns = ['time', 'open', 'high', 'low', 'close', 'volume']
df = df.set_index('time')
df.index = pd.to_datetime(df.index)
df = df.astype(float)
return df
def TransactionsTransactionDetails(access_token, accountID, transactionID):
'Get the details of a single Account Transaction.'
r = transactions.TransactionDetails(accountID=accountID,
transactionID=transactionID)
client = API(access_token=access_token)
client.request(r)
return readable_output(Munch(r.response)), Munch(r.response)
def get_price_data(pair, config_file, output, **kwargs):
"""Get data from Oanda and put in CSV.
Parameters
----------
pair: str
The instrument pair in which to fetch prices.
config_file : str
Location of configuration file.
output: str
Location and name of output .csv file.
"""
conf = get_config(config_file)
kwargs['price'] = 'BA'
r = instruments.InstrumentsCandles(instrument=pair, params=kwargs)
api = API(access_token=conf['token'])
api.request(r)
prices = []
for _ in r.response['candles']:
prices.append([
_['time'], _['bid']['c'], _['ask']['c'],
float(_['ask']['c']) - float(_['bid']['c'])
])
df = pd.DataFrame(prices)
df.columns = ['time', 'bid', 'ask', 'spread']
df.to_csv(output, sep='\t', index=False)
def InstrumentsPositionBook(access_token, instrument, params): # check
'Get positionbook data for a specified Instrument.'
r = instruments.InstrumentsPositionBook(instrument=instrument,
params=params)
client = API(access_token=access_token)
client.request(r)
return readable_output(Munch(r.response)), Munch(r.response)
def start(self, ignore_heartbeat=False, **kwargs):
# We want the heartbeats by default
client = API(access_token=self.access_token,
environment=self.environment)
params = {"instruments": kwargs["instruments"]}
r = pricing.PricingStream(accountID=kwargs['accountId'], params=params)
logging.info("Request is: %s with instruments: %s", r,
params['instruments'])
while True:
try:
for tick in client.request(r):
logging.info("TICK: %s", tick)
self.on_success(V1compat(tick))
except V20Error as e:
# catch API related errors that may occur
logger.error("V20Error: %s", e)
break
except ConnectionError as e:
logger.error("Connection Error: %s", e)
break
except StreamTerminated as e:
logger.error("StreamTerminated exception: %s", e)
break
except Exception as e:
exc_type, exc_obj, exc_tb = sys.exc_info()
fname = os.path.split(exc_tb.tb_frame.f_code.co_filename)[1]
logger.error("Unknown exception: %s | %s | %s", exc_type,
fname, exc_tb.tb_lineno)
break
def candles(inst, granularity, count, From, to, price, nice, access_token):
api = API(access_token=access_token)
def check_date(s):
dateFmt = "[\d]{4}-[\d]{2}-[\d]{2}T[\d]{2}:[\d]{2}:[\d]{2}Z"
if not re.match(dateFmt, s):
raise ValueError("Incorrect date format: ", s)
return True
if inst:
params = {}
if granularity:
params.update({"granularity": granularity})
if count:
params.update({"count": count})
if From and check_date(From):
params.update({"from": From})
if to and check_date(to):
params.update({"to": to})
if price:
params.update({"price": price})
for i in inst:
r = instruments.InstrumentsCandles(instrument=i, params=params)
rv = api.request(r)
kw = {}
if nice:
kw = {"indent": nice}
# print("{}".format(json.dumps(rv, **kw)))
return rv
def __init__(self, instrument, granularity, units, clargs):
self.accountID, token = authentication()
self.client = API(access_token=token)
self.units = units
self.clargs = clargs
self.pt = PriceTable(instrument, granularity)
# fetch First Candle data
params = {"count": 1, "from": self.clargs.Orbdate}
r = instruments.InstrumentsCandles(instrument=instrument,
params=params)
rv = self.client.request(r)
if len(rv) == 0:
logger.error(
"No candle data available for specified date:{d}".format(
d=self.clargs.Orbdate))
# and calculate indicators
for crecord in rv['candles']:
if crecord['complete'] is True:
self.high = float(crecord['mid']['h'])
self.low = float(crecord['mid']['l'])
ORBdetails = ORB(self.pt, self.client, self.high, self.low)
self.pt.setHandler("onAddItem", ORBdetails.calculate)
self.indicators = [ORBdetails]
self.state = NEUTRAL # overall state based on calculated indicators
self.unit_ordered = False
self._botstate()
def get_candles(instrument, params):
_conf = PyOandaConfig()
_api = API(access_token=_conf.access_token, environment="practice")
_request = instruments.InstrumentsCandles(instrument=instrument, params=params)
_api.request(_request)
return _request.response
def connect_v20(access_token, accountID, instruments):
api = API(access_token=access_token, environment="practice")
s = PricingStream(accountID=accountID, params={"instruments": instruments})
response = api.request(s)
try:
n = 0
for R in api.request(s):
# print (msg['type'])
if R['type'] == 'HEARTBIT':
print(json.dumps(R['type'], indent=2),
json.dumps(R['type']['time'], indent=2))
if R['type'] == 'PRICE':
instrument = json.loads(json.dumps(R['instrument'], indent=2))
status = json.loads(json.dumps(R['status'], indent=2))
timestamp = json.loads(json.dumps(R['time'], indent=2))
closeoutBid = json.loads(json.dumps(R['closeoutBid'],
indent=2))
closeoutAsk = json.loads(json.dumps(R['closeoutAsk'],
indent=2))
askBook = json.loads(json.dumps(R['asks'], indent=2))
# influx_record(R['type'])
print(instrument, timestamp, closeoutBid, closeoutAsk)
position_open(instrument, closeoutBid, closeoutAsk)
# for line in askBook:
# price = json.loads(json.dumps(line["price"], indent=2))
# liquidity = json.loads(json.dumps(line["liquidity"], indent=2))
# print (price,liquidity)
# return instrument,closeoutBid, closeoutAsk
# n += 1
# if n > 125:
# s.terminate("maxrecs received: {}".format(MAXREC))
except V20Error as e:
print("Error: {}".format(e))
def __init__(self, granularity):
""""コンストラクタ
引数:
dt (str): datetime formatted by DT_FMT.
戻り値:
tf_dt (str): changed datetime.
"""
self.__CANDLES = "candles"
self.__MID = "mid"
self.__O = "o"
self.__H = "h"
self.__L = "l"
self.__C = "c"
self.__TIME = "time"
self.__VOLUME = "volume"
self.__OPEN = "open"
self.__HIGHT = "high"
self.__LOW = "low"
self.__CLOSE = "close"
self.__DT_FMT = "%Y-%m-%dT%H:%M:00.000000000Z"
self.__GRANULARITY = granularity
self.__df = []
self.__api = API(access_token=ya.access_token,
environment=oc.OandaEnv.PRACTICE)
def main():
access_token = "df36fd83bc0d3b33010ebbea7feb99d7-5849f313292879ab44e0a824de58e1ad"
api = API(access_token=access_token, environment="practice")
# count = 2000
count = 100
params = {
"count": count, # 足3本取得
"granularity": "M5", # 1分足を取得
"price": "B", # Bidを取得
}
instruments_candles = instruments.InstrumentsCandles(instrument="GBP_USD",
params=params)
try:
api.request(instruments_candles)
response = instruments_candles.response
df = pd.DataFrame([candle["bid"] for candle in response["candles"]],
dtype=np.float64)
df['v'] = [candle["volume"] for candle in response["candles"]]
df.columns = ['Open', 'High', 'Low', 'Close', 'Volume']
df['date'] = [candle["time"] for candle in response["candles"]]
df['date'] = pd.to_datetime(df['date'])
df.set_index('date', inplace=True)
# print(df)
for i in range(int(count / 10)):
mpf.plot(df[i * 10:(i + 1) * 10],
type='candle',
style='nightclouds',
savefig=f'data/candles{i}.png')
# mpf.show()
except V20Error as e:
print("Error: {}".format(e))
def order(self, quote, precision_digits, bet_size, currency, profit, stop):
tp = {"timeInForce": "GTC", "price": str(round(abs(profit), precision_digits))}
sl = {"timeInForce": "GTC", "price": str(round(abs(stop), precision_digits))}
order = {"order": {"units": bet_size, "instrument": currency, "timeInForce": "FOK", "type": "LIMIT",
"positionFill": "DEFAULT", "price": str(round(quote, precision_digits)),
'takeProfitOnFill': tp,
'stopLossOnFill': sl}}
# client
api = API(access_token=self.token)
# create and process order requests
r = orders.OrderCreate(accountID=self.account_id, data=order)
print("processing : {}".format(r))
print("===============================")
print(r.data)
print('end of data r.data')
try:
response = api.request(r)
except V20Error as e:
print("V20Error: {}".format(e))
return False, 0.0, 0
else:
print("Response: {}\n{}".format(r.status_code, json.dumps(response, indent=2)))
try:
return True, response['orderFillTransaction']['price'], response['orderFillTransaction']['id']
except:
# TODO Improve warning and errors syntax and exception treatment
Warning('Order failed to execute. Likely not to have a descent available price.')
return False, 0.0, 0
def getPrice(ticker_type):
accountID = "101-002-12644151-001"
api = API(
access_token=
"1040f3b6997e1c6db66f7bb3bb8b5336-4ec7a67d82e48258fe56ac32c283eb12")
params = {"instruments": ticker_type}
print(ticker_type)
r = pricing.PricingInfo(accountID=accountID, params=params)
rv = api.request(r)
data = pd.DataFrame(r.response["prices"])
data_text = json.dumps(r.response, indent=2)
ask = str(data["asks"])
bid = str(data["bids"])
#print(data_text) Update ** Allow it to be display different amount of digits properly
bid_price = ""
ask_price = ""
for ch in range(4, len(ask)):
if (ask[ch].isdigit() or ask[ch] == ".") and ch < 24:
ask_price += ask[ch]
bid_price += bid[ch]
print("ASK:" + ask_price)
print("BID:" + bid_price)
print("#######################")
return ask_price, bid_price
def f_descarga_precios(date, instrument):
"""
Parameters
---------
instrument: str : instrumento del precio que se requiere
date : date : fecha del dia del precio
Returns
---------
prices: : precios del activo descargado.
Debuggin
---------
instrument : str : cadena de texto con 'EUR_USD'
date = pd.to_datetime("2019-07-06 00:00:00")
"""
# Inicializar api de OANDA
api = API(environment="practice", access_token='107596e9d65c' + '1bbc9175953d917140' + '12-f975c6201dddad03ac1592232c0ea0ea',)
# Convertir en string la fecha
fecha = date.strftime('%Y-%m-%dT%H:%M:%S')
# Parametros para Oanda
r = instruments.InstrumentsCandles(instrument=instrument,
params={"count": 1, "granularity": 'S10', "price": "M", "dailyAlignment": 16, "from": fecha})
# Descargar
response = api.request(r)
# En fomato candles
prices = response.get("candles")
# Regresar el precio de apertura
return prices
def history(instrument, window, collection=False):
instrument = instrument
data = list()
client = API(token)
params = {"count": 500, "granularity": window}
r = InstrumentsCandles(instrument, params)
client.request(r)
resp = r.response
for candle in resp.get('candles'):
dt = candle['time']
Open = candle['mid']['o']
High = candle['mid']['h']
Low = candle['mid']['l']
Close = candle['mid']['c']
Volume = candle['volume']
update = [dt, Open, High, Low, Close, Volume]
data.append(update)
df = pd.DataFrame(data,
columns=['dt', 'Open', 'High', 'Low', 'Close', 'Volume'])
# collect data, useful for research and weekends/holidays when the market isn't open
if collection == True:
title = 'data/%s_%s_history.csv' % (instrument, window)
df.to_csv(title)
return df
def __init__(self, instruments, granularity, prob_threshold, target,
account_name, *args, **kwargs):
PricingStream.__init__(self, *args, **kwargs)
print "loading model..."
self.model = pickle.load(open('mpv12_0025_const.sav', 'rb'))
self.instruments = instruments.split(',')
self.target = target
self.connected = False
self.account_name = account_name
self.granularity = granularity
self.prob_threshold = prob_threshold
self.status = {}
for inst in self.instruments:
self.status[inst] = {
"bid": None,
"ask": None,
"time": None,
"trade_pred": None,
"current_pred": None,
"long": 0,
"short": 0,
"unrealizedPL": 0,
"pending_order": None,
"made_prediction": False,
"tradeID": None
}
print "connecting..."
self.client = API(access_token=access_token, environment=environment)
def get_historical_data_factory(instrument, params):
# filename
p_to = params['to'][:10]
p_from = params['from'][:10]
p_granularity = params['granularity']
filename = f"data/data_oanda_{instrument}_{p_from}_{p_to}_{p_granularity}.csv"
if os.path.isfile(filename):
df2 = pd.read_csv(filename)
df2['datetime'] = pd.to_datetime(df2['datetime'])
df2 = df2.set_index('datetime')
return df2
# Create a Data Feed
client = API(access_token=access_token)
df_list = []
def cnv(response):
# for candle in response.get('candles'):
# print(candle)
candles = [candle['mid'] for candle in response['candles']]
ts = pd.DataFrame(
{'datetime': [candle['time'] for candle in response['candles']]})
vol = pd.DataFrame(
{'volume': [candle['volume'] for candle in response['candles']]})
candles_df = pd.DataFrame(data=candles)
ts_df = pd.DataFrame(data=ts)
vol_df = pd.DataFrame(data=vol)
df = pd.concat([ts_df, candles_df, vol_df], axis=1)
df.rename({
'o': 'open',
'h': 'high',
'l': 'low',
'c': 'close'
},
axis=1,
inplace=True)
df['datetime'] = pd.to_datetime(df['datetime'])
df = df.set_index('datetime')
for col in df.columns:
df[col] = pd.to_numeric(df[col])
df_list.append(df)
for r in InstrumentsCandlesFactory(instrument=instrument, params=params):
# print("FACTORY REQUEST: {} {} {}".format(r, r.__class__.__name__, r.params))
rv = client.request(r)
cnv(rv)
df2 = pd.concat(df_list)
now = datetime.datetime.now()
dt_string = now.strftime("%Y%m%d%H%M%S")
df2.to_csv(filename)
return df2
def __init__(self):
# OANDAアカウント読み込み
self.oanda_account_id = os.environ.get("OANDA_API_ACCOUNT_ID")
self.oanda_access_token = os.environ.get("OANDA_API_ACCESS_TOKEN")
self.api = API(access_token=self.oanda_access_token,
environment="practice")
self.date = ""
class APIClient(object):
def __init__(self, access_token, account_id, environment='practice'):
self.access_token = access_token
self.account_id = account_id
self.client = API(access_token=access_token, environment=environment)
def get_balance(self) -> Balance:
req = accounts.AccountSummary(accountID=self.account_id)
try:
resp = self.client.request(req)
except V20Error as e:
logger.error(f'action=get_balance error={e}')
raise
available = float(resp['account']['balance'])
currency = resp['account']['currency']
return Balance(currency, available)
def get_ticker(self, product_code) -> Ticker:
params = {'instruments': product_code}
req = PricingInfo(accountID=self.account_id, params=params)
try:
resp = self.client.request(req)
except V20Error as e:
logger.error(f'action=get_ticker error={e}')
raise
timestamp = datetime.timestamp(dateutil.parser.parse(resp['time']))
price = resp['prices'][0]
instrument = price['instrument']
bid = float(price['bids'][0]['price'])
ask = float(price['asks'][0]['price'])
volume = 11111
return Ticker(instrument, timestamp, bid, ask, volume)
def __init__(self, config, rpc):
"""
Initializes this module with the given config,
it does basic validation whether the specified
exchange and pairs are valid.
:return: None
"""
self._conf.update(config)
self.account_id, token = \
self._conf["exchange"]["active_account"], \
self._conf["exchange"]["token"]
env = config.get("environment", "practice")
self._api = API(access_token=token, environment=env)
self.rpc = rpc
self._cached_ticker: Dict[str, Any] = {}
# Holds last candle refreshed time of each pair
self._pairs_last_refresh_time: Dict[Tuple[str, str], int] = {}
# Holds all open sell orders for dry_run
self._dry_run_open_orders: Dict[str, Any] = {}
if config['dry_run']:
logger.info('Instance is running with dry_run enabled')
logger.info('Using Exchange Oanda')
self.markets = self.account_instruments()
self.pairs = self.validate_pairs(config['exchange']['pair_whitelist'])
self.order_book = self.oanda_order_book()
def oanda_close_positions(side):
# API取得
api = API(access_token=token)
# 注文内容
if side == "BUY":
order_data = {"shortUnits": "ALL"}
if side == "SELL":
order_data = {"longUnits": "ALL"}
while True:
# 注文実行
try:
r = positions.PositionClose(accountID,
instrument=currency,
data=order_data)
api.request(r)
print_log("\nすべての建玉を決済しました\n決済価格は平均 {}円です".format(
str(data["forming"]["close_price"])))
return order_data
except V20Error as e:
print_log("OANDAのAPIで問題発生" + str(e))
print_log("20秒待機してやり直します")
time.sleep(20)
def position_close_short(self, pair="AUD_USD", unit=1000):
client = API(access_token=self.access_token, environment='live')
ordr = PositionCloseRequest(shortUnits=unit)
r = position.PositionClose(self.accountID,
instrument=pair,
data=ordr.data)
rv = client.request(r)
def __init__(self, instrument, granularity, units, clargs):
self.accountID, token = exampleAuth()
self.client = API(access_token=token)
self.units = units
self.clargs = clargs
self.pt = PriceTable(instrument, granularity)
mavgX = MAx(self.pt, clargs.shortMA, clargs.longMA, clargs.SOK,
clargs.SOD, clargs.SOF)
self.pt.setHandler("onAddItem", mavgX.calculate)
self.indicators = [mavgX]
self.state = NEUTRAL # overall state based on calculated indicators
# fetch initial historical data
params = {"granularity": granularity, "count": self.clargs.longMA}
r = instruments.InstrumentsCandles(instrument=instrument,
params=params)
rv = self.client.request(r)
# and calculate indicators
for crecord in rv['candles']:
if crecord['complete'] is True:
# def addItem(self, dt, ao, ah, al, ac, av, bo, bh, bl, bc, bv):
self.pt.addItem(crecord['time'], float(crecord['mid']['o']),
float(crecord['mid']['h']),
float(crecord['mid']['l']),
float(crecord['mid']['c']),
int(crecord['volume']),
float(crecord['mid']['o']),
float(crecord['mid']['h']),
float(crecord['mid']['l']),
float(crecord['mid']['c']),
int(crecord['volume']))
self._botstate()
def get_live_candles(instrument, params):
"""
@param instrument:
@param params:
@return: dataframe of live candles data
"""
client = API(access_token=access_token)
r = instruments.InstrumentsCandles(instrument=instrument, params=params)
client.request(r)
candles = r.response.get("candles")
data = []
df1 = pd.DataFrame(candles)[['complete', 'volume', 'time']]
df2 = pd.DataFrame(list(pd.DataFrame(candles)['mid']))
df = pd.concat([df1, df2], axis=1)
df.rename(mapper={
'o': 'open',
'h': 'high',
'l': 'low',
'c': 'close'
},
inplace=True,
axis=1)
df['time'] = pd.to_datetime(df['time'])
df[['open', 'high', 'low', 'close']] = df[['open', 'high', 'low',
'close']].apply(pd.to_numeric,
errors='coerce')
return df
def main():
"""
My first attempt at pulling data from Oanda
"""
oanda_environment = 'Practice'
if oanda_environment == 'Live':
# oanda_account_id = os.environ['OANDA_ACCOUNTID']
oanda_access_token = os.environ['OANDA_ACCESS_TOKEN']
# oanda_hostname = "api-fxtrade.oanda.com"
else:
# oanda_account_id = os.environ['OANDA_ACCOUNTID_DEV']
oanda_access_token = os.environ['OANDA_ACCESS_TOKEN_DEV']
# oanda_hostname = "api-fxpractice.oanda.com"
# oanda_port = "443"
client = API(oanda_access_token)
instrument, granularity = "EUR_USD", "M15"
_from = "2021-03-01T00:00:00Z"
params = {"from": _from, "granularity": granularity}
fn = "/tmp/{}.{}.json".format(instrument, granularity)
if os.path.isfile(fn):
os.remove(fn)
with open(fn, "w") as OUT:
# The factory returns a generator generating consecutive
# requests to retrieve full history from date 'from' till 'to'
json_data = list()
for r in InstrumentsCandlesFactory(instrument=instrument,
params=params):
client.request(r)
json_data.extend(r.response.get('candles'))
OUT.write(json.dumps(json_data, indent=2))
def test2():
params = {"count": 10, "granularity": "D"}
api = API(access_token=access_token, environment="practice")
r = instruments.InstrumentsCandles(instrument="USD_JPY", params=params)
rv = api.request(r)
print(rv)
p0 = rv['candles'][0]['mid']['c']
p1 = rv['candles'][1]['mid']['c']
p2 = rv['candles'][2]['mid']['c']
p3 = rv['candles'][3]['mid']['c']
p4 = rv['candles'][4]['mid']['c']
p5 = rv['candles'][5]['mid']['c']
p6 = rv['candles'][6]['mid']['c']
p7 = rv['candles'][7]['mid']['c']
p8 = rv['candles'][8]['mid']['c']
p9 = rv['candles'][9]['mid']['c']
print (p0, p1, p2, p3, p4, p5, p6, p7, p8, p9)
if p0 < p1:
print ('↑')
else:
print ('↓')
def __init__(self, _from, _to, gran, instr):
'''2017-01-01T00:00:00Z 2017-06-30T00:00:00Z H4 EUR_USD'''
client = API(access_token=config['account']['token'])
instrument = instr
params = {"granularity": gran, "from": _from, "to": _to}
for res in InstrumentsCandlesFactory(instrument=instr, params=params):
self.rv = client.request(res)
def oanda():
account_id = ""
access_token = ""
api = API(access_token=access_token, environment="live")
params = {"instruments": "USD_JPY"}
pricing_info = PricingInfo(accountID=account_id, params=params)
oal_ask = 0
oal_ask_pre = 0
oal_bid = 0
oal_bid_pre = 0
try:
while True:
api.request(pricing_info)
response = pricing_info.response
oal_ask_pre = oal_ask
oal_ask = response['prices'][0]['asks']
oal_bid_pre = oal_bid
oal_bid = response['prices'][0]['bids']
if oal_ask != oal_ask_pre:
print("oandaask:" + str(oal_ask) + " oandabid:" + str(oal_bid))
except V20Error as e:
print("Error: {}".format(e))
def test1():
params ={"instruments": "EUR_USD,EUR_JPY"}
# OANDAのデモ口座へのAPI接続
api = API(access_token=access_token, environment="practice")
r = pricing.PricingInfo(accountID=accountID, params=params)
rv = api.request(r)
print(rv['prices'][0]['bids'][0]['price'])
def setUp(self):
"""setup for all tests."""
global access_token
global accountID
global account_cur
global api
# self.maxDiff = None
try:
accountID, account_cur, access_token = unittestsetup.auth()
setattr(sys.modules["oandapyV20.oandapyV20"],
"TRADING_ENVIRONMENTS",
{"practice": {
"stream": "https://test.com",
"api": "https://test.com",
}})
api = API(environment=environment, access_token=access_token)
api.api_url = 'https://test.com'
except Exception as e:
print("%s" % e)
exit(0)
def test__requests_exception(self):
"""force a requests exception."""
from requests.exceptions import RequestException
import oandapyV20.endpoints.accounts as accounts
setattr(sys.modules["oandapyV20.oandapyV20"],
"TRADING_ENVIRONMENTS",
{"practice": {
"stream": "ttps://test.com",
"api": "ttps://test.com",
}})
api = API(environment=environment,
access_token=access_token,
headers={"Content-Type": "application/json"})
text = "No connection " \
"adapters were found for 'ttps://test.com/v3/accounts'"
r = accounts.AccountList()
with self.assertRaises(RequestException) as oErr:
api.request(r)
self.assertEqual("{}".format(oErr.exception), text)