def getTradingSymbols(self, quote_assets: list = None):
""" Gets All symbols which are tradable (currently)
Params
--
`quote_assets`
a list of all the quote assets we are interested in;
if empty or None, we will return all trading pairs,
indifferent of quote asset
Returns
--
a list of symbols that are currently trading on Binance
"""
url = Binance.BASE_URL + Binance.ENDPOINTS["exchangeInfo"]
data = self._get(url)
if not Binance.isValidResponse(data):
raise ExchangeConnectionException()
symbols_list = []
if quote_assets != None and len(quote_assets) > 0:
for pair in data['symbols']:
if pair['status'] == 'TRADING':
if pair['quoteAsset'] in quote_assets:
symbols_list.append(pair['symbol'])
else:
for pair in data['symbols']:
if pair['status'] == 'TRADING':
symbols_list.append(pair['symbol'])
return symbols_list
def getOHLCV(self, symbol:str, interval:str,
limit:int=1000, end_time:any=False, start_time:any=False, cast_to:type=float):
"""
Gets candlestick data for one symbol
Parameters
--
symbol str:
The symbol for which to get the trading data
interval str:
The interval on which to get the trading data
minutes: '1m' '3m' '5m' '15m' '30m'
hours: '1h' '2h' '4h' '6h' '8h' '12h'
days: '1d' '3d' weeks: '1w' months: '1M'
limit int:
The number of data points (candles) to return
`end_time` bool/int:
The time of the last candle (if False, uses current time)
Returns
--
DataFrame containing OHLCV data.
"""
if limit > 1000:
return self._getSymbolKlinesExtra(
symbol, interval, limit, end_time, cast_to=cast_to)
params = '?&symbol='+symbol+'&interval='+interval+'&limit='+str(limit)
if end_time:
params = params + '&endTime=' + str(int(end_time))
if start_time:
params = params + '&startTime=' + str(int(start_time))
url = Binance.BASE_URL + Binance.ENDPOINTS['klines'] + params
# download data
try:
data = requests.get(url)
except requests.exceptions.ConnectionError:
raise ExchangeConnectionException()
dictionary = json.loads(data.text)
# put in dataframe and clean-up
df = pandas.DataFrame.from_dict(dictionary)
df = df.drop(range(6, 12), axis=1)
# rename columns
col_names = ['time', 'open', 'high', 'low', 'close', 'volume']
df.columns = col_names
# transform values from strings to floats
for col in col_names:
df[col] = df[col].astype(cast_to)
df['date'] = pandas.to_datetime(df['time'] * 1000000, infer_datetime_format=True)
return df
def _get(self, url, params=None, headers=None):
""" Implements a get request for this exchange """
try:
response = requests.get(url, params=params, headers=headers)
payload = json.loads(response.text)
if type(payload) == type([]):
data = dict(payload=payload, url=url)
else:
data = payload
data['url'] = url
except requests.exceptions.ConnectionError:
raise ExchangeConnectionException()
except Exception as e:
print("Exception occured when trying to GET from " + url)
print_exc()
data = {'code': '-1', 'url': url, 'msg': e}
# raise ExchangeConnectionException()
return data