[#11] Add Bitfinex API

libcryptomarket/api/bitfinex_api.py

@@ -0,0 +1,154 @@
+#!/bin/python
+# import requests
+# import hmac
+# import hashlib
+# import urllib
+# from functools import partial
+
+from libcryptomarket.api.exchange_api import ExchangeApi
+
+
+class BitfinexApi(ExchangeApi):
+    """Bitfinex API.
+    """
+
+    def __init__(self, public_key=None, private_key=None, logger=None):
+        """Constructor.
+
+        :param public_key: Public key.
+        :param private_key: Private key.
+        :param logger: Logger.
+        """
+        ExchangeApi.__init__(self, public_key, private_key, logger)
+
+    @classmethod
+    def get_url(cls):
+        """Get API url.
+        """
+        return "https://api.bitfinex.com/v2"
+
+    @classmethod
+    def get_public_calls(cls):
+        """Get public API calls.
+        """
+        return {
+            'tickers': 'GET',
+            'ticker': 'GET',
+            'trades': 'GET',
+            'book': 'GET',
+            'stat1': 'GET',
+            'candles': 'GET'
+        }
+
+    @classmethod
+    def get_private_calls(cls):
+        """Get public API calls.
+        """
+        return {
+        }
+
+    @classmethod
+    def translate_call_name(cls, name):
+        """Translate API call name.
+
+        The class method name is always underscored (aligned with Python
+        standard.) This method is to translate underscored name to exchange
+        API call name.
+
+        :param name: Method name (underscored).
+        """
+        return name
+
+    def _request_public(self, name, http_method, **kwargs):
+        """Request public API call.
+
+        :param name: Method name.
+        :param http_method: HTTP method (POST, GET, DELETE).
+        """
+        if name == "ticker":
+            symbol = kwargs["symbol"]
+            del kwargs["symbol"]
+            name = '/'.join([name, symbol])
+        elif name == "trades":
+            symbol = kwargs["symbol"]
+            del kwargs["symbol"]
+            name = '/'.join([name, symbol, "hist"])
+        elif name == "book":
+            symbol = kwargs["symbol"]
+            precision = kwargs["precision"]
+            del kwargs["symbol"]
+            del kwargs["precision"]
+            name = "/".join([name, symbol, precision])
+        elif name == "stat1":
+            key = kwargs["key"]
+            size = kwargs["size"]
+            symbol = kwargs["symbol"]
+            section = kwargs["section"]
+            del kwargs["key"]
+            del kwargs["size"]
+            del kwargs["symbol"]
+            del kwargs["section"]
+            name = "/".join([name,
+                             "{}:{}:{}".format(key, size, symbol),
+                             section])
+        elif name == "candles":
+            timeframe = kwargs["timeframe"]
+            symbol = kwargs["symbol"]
+            section = kwargs["section"]
+            del kwargs["timeframe"]
+            del kwargs["symbol"]
+            del kwargs["section"]
+            name = "/".join([name,
+                             "trade:{}:{}".format(timeframe, symbol),
+                             section])
+
+        return self._send_request(
+            command=name, http_method=http_method,
+            public_method=True, params=kwargs)
+
+    def _request_private(self, name, http_method, **kwargs):
+        """Request private API call.
+
+        :param name: Method name.
+        :param http_method: HTTP method (POST, GET, DELETE).
+        """
+        raise NotImplementedError()
+
+    # @classmethod
+    # def _generate_auth(cls, public_key, private_key):
+    #     """Generate authentication.
+
+    #     :param public_key: Public key.
+    #     :param private_key: Private key.
+    #     """
+    #     return None
+
+    # @classmethod
+    # def _generate_headers(cls, command, http_method, params, data,
+    #                       public_key, private_key):
+    #     """Generate headers.
+
+    #     :param command: Command.
+    #     :param http_method: HTTP method, for example GET.
+    #     :param params: Parameters.
+    #     :param data: Data.
+    #     :param public_key: Public key.
+    #     :param private_key: Private key.
+    #     """
+    #     signature = hmac.new(private_key.encode(),
+    #                          urllib.parse.urlencode(data).encode(),
+    #                          digestmod=hashlib.sha512).hexdigest()
+    #     header = {
+    #         'Key': public_key,
+    #         'Sign': signature
+    #     }
+
+    #     return header
+
+    # @classmethod
+    # def _format_data(cls, data):
+    #     """Format the data to exchange desirable format.
+
+    #     :param data: Data.
+    #     """
+    #     return data

libcryptomarket/core.py

@@ -9,6 +9,9 @@ def historical_ticker(source, symbol, period, start_time=None, end_time=None):
     """Return historical ticker.
 
     :param source: Source, an Exchange API object.
+    :param symbol: Symbol, string object.
+    :param period: Period or frequency, followed with exchange protocol, string
+                   object.
     :param start_time: Start time, datetime object.
     :param end_time: Start time, datetime object.
     """
@@ -23,84 +26,178 @@ def historical_ticker(source, symbol, period, start_time=None, end_time=None):
     source_name = source.__class__.__name__.lower().replace("api", "")
 
     if source_name == "poloniex":
-        # Exchange validation
-        if start_time is None and end_time is None:
-            raise ValueError("Start time and end time cannot be both None.")
-
-        request_func = partial(source.return_chart_data, currencyPair=symbol,
-                               period=period)
-
-        if start_time is not None:
-            request_func = partial(request_func,
-                                   start=start_time.timestamp())
-        if end_time is not None:
-            request_func = partial(request_func,
-                                   end=end_time.timestamp())
-        data = request_func()
-        data.raise_for_status()
-        data = pd.DataFrame(data.json())
-        data['date'] = data['date'].apply(
-            lambda x: pd.to_datetime(x, unit='s'))
-        data = data.set_index(['date'])
-        data.index.name = 'datetime'
-        data.columns.name = symbol
-
-        return data
+        return _historical_ticker_poloniex(
+            source=source, symbol=symbol, period=period,
+            start_time=start_time, end_time=end_time)
 
     elif source_name == "gdax":
-        # Exchange validation
-        if (start_time is None) + (end_time is None) not in [0, 2]:
-            # Both start and end time must be provided
-            raise ValueError("Start and end time must be both provided")
-
-        request_func = partial(source.products_candles, product_id=symbol,
-                               granularity=period)
-
-        if start_time is None and end_time is None:
-            # Just get the latest 300 ticks
-            data = request_func()
-            data.raise_for_status()
-            data = pd.DataFrame(data.json())
-
-        else:
-            # Safety net
-            last_datetime = start_time.timestamp()
-
-            data = []
-
-            while start_time <= end_time:
-                tmp_data = request_func(
-                    start=start_time.isoformat(),
-                    end=(start_time +
-                         timedelta(seconds=period * 200)).isoformat())
-                tmp_data.raise_for_status()
-                tmp_data = pd.DataFrame(tmp_data.json())
-
-                # Append into data list
-                data.append(tmp_data)
-
-                # Check to exit
-                if last_datetime >= tmp_data.iloc[0, 0]:
-                    # Same as the previous query
-                    break
-                else:
-                    last_datetime = tmp_data.iloc[0, 0]
-                    start_time = datetime.fromtimestamp(last_datetime)
-
-                sleep(0.333)
-
-            if len(data) > 1:
-                data = pd.concat(data, axis=0)
-            else:
-                data = data[0]
-
-        data.columns = ['datetime', 'low', 'high', 'open', 'close', 'volume']
-        data['datetime'] = pd.to_datetime(data['datetime'], unit='s')
-        data = data.set_index('datetime').sort_index()
-        data = data[~data.index.duplicated(keep='first')]
-
-        return data
-
+        return _historical_ticker_gdax(
+            source=source, symbol=symbol, period=period,
+            start_time=start_time, end_time=end_time)
+    elif source_name == "bitfinex":
+        return _historical_ticker_bitfinex(
+            source=source, symbol=symbol, period=period,
+            start_time=start_time, end_time=end_time)
     else:
         raise ValueError("Source (%s [%s]) does not support historical ticker"
                          % (source, source_name))
+
+
+def _historical_ticker_poloniex(source, symbol, period, start_time, end_time):
+    """Return historical ticker in Poloniex.
+
+    :param source: Source, an Exchange API object.
+    :param symbol: Symbol, string object.
+    :param period: Period or frequency, followed with exchange protocol, string
+                   object.
+    :param start_time: Start time, datetime object.
+    :param end_time: Start time, datetime object.
+    """
+    # Exchange validation
+    if start_time is None and end_time is None:
+        raise ValueError("Start time and end time cannot be both None.")
+
+    request_func = partial(source.return_chart_data, currencyPair=symbol,
+                           period=period)
+
+    if start_time is not None:
+        request_func = partial(request_func,
+                               start=start_time.timestamp())
+    if end_time is not None:
+        request_func = partial(request_func,
+                               end=end_time.timestamp())
+    data = request_func()
+    data.raise_for_status()
+    data = pd.DataFrame(data.json())
+    data['date'] = data['date'].apply(
+        lambda x: pd.to_datetime(x, unit='s'))
+    data = data.set_index(['date'])
+    data.index.name = 'datetime'
+    data.columns.name = symbol
+
+    return data
+
+
+def _historical_ticker_gdax(source, symbol, period, start_time, end_time):
+    """Return historical ticker in GDAX.
+
+    :param source: Source, an Exchange API object.
+    :param symbol: Symbol, string object.
+    :param period: Period or frequency, followed with exchange protocol, string
+                   object.
+    :param start_time: Start time, datetime object.
+    :param end_time: Start time, datetime object.
+    """
+    # Exchange validation
+    if (start_time is None) + (end_time is None) not in [0, 2]:
+        # Both start and end time must be provided
+        raise ValueError("Start and end time must be both provided")
+
+    request_func = partial(source.products_candles, product_id=symbol,
+                           granularity=period)
+
+    if start_time is None and end_time is None:
+        # Just get the latest 300 ticks
+        data = request_func()
+        data.raise_for_status()
+        data = pd.DataFrame(data.json())
+
+    else:
+        # Safety net
+        last_datetime = start_time.timestamp()
+
+        data = []
+
+        while start_time <= end_time:
+            tmp_data = request_func(
+                start=start_time.isoformat(),
+                end=(start_time +
+                     timedelta(seconds=period * 200)).isoformat())
+            tmp_data.raise_for_status()
+            tmp_data = pd.DataFrame(tmp_data.json())
+
+            # Append into data list
+            data.append(tmp_data)
+
+            # Check to exit
+            if last_datetime >= tmp_data.iloc[0, 0]:
+                # Same as the previous query
+                break
+            else:
+                last_datetime = tmp_data.iloc[0, 0]
+                start_time = datetime.fromtimestamp(last_datetime)
+
+            sleep(0.333)
+
+        if len(data) > 1:
+            data = pd.concat(data, axis=0)
+        else:
+            data = data[0]
+
+    data.columns = ['datetime', 'low', 'high', 'open', 'close', 'volume']
+    data['datetime'] = pd.to_datetime(data['datetime'], unit='s')
+    data = data.set_index('datetime').sort_index()
+    data = data[~data.index.duplicated(keep='first')]
+
+    return data
+
+
+def _historical_ticker_bitfinex(source, symbol, period, start_time, end_time):
+    """Return historical ticker in Bitfinex.
+
+    :param source: Source, an Exchange API object.
+    :param symbol: Symbol, string object.
+    :param period: Period or frequency, followed with exchange protocol, string
+                   object.
+    :param start_time: Start time, datetime object.
+    :param end_time: Start time, datetime object.
+    """
+    request_func = partial(source.candles, symbol=symbol, timeframe=period,
+                           section="hist", sort=1, limit=1000)
+
+    if start_time is None and end_time is None:
+        data = request_func()
+        data.raise_for_status()
+        data = pd.DataFrame(data.json())
+    else:
+        # Safety net
+        last_datetime = (
+            0 if start_time is None else start_time.timestamp() * 1000)
+
+        data = []
+
+        while start_time is None or end_time is None or start_time <= end_time:
+            f = request_func
+
+            if start_time is not None:
+                f = partial(f, start=round(start_time.timestamp() * 1000))
+
+            if end_time is not None:
+                f = partial(f, end=round(end_time.timestamp() * 1000))
+
+            tmp_data = f()
+            tmp_data.raise_for_status()
+            tmp_data = tmp_data.json()
+
+            if len(tmp_data) == 0:
+                break
+            elif last_datetime >= tmp_data[-1][0]:
+                print(last_datetime)
+                print(tmp_data[-1][0])
+                break
+            else:
+                last_datetime = tmp_data[-1][0]
+                start_time = datetime.fromtimestamp(
+                    round(last_datetime / 1000 + 1))
+                data.append(pd.DataFrame(tmp_data))
+
+            sleep(1)
+
+        data = pd.concat(data, axis=0)
+
+    data.columns = ["datetime", "open", "close", "high", "low", "volume"]
+    data["datetime"] = pd.to_datetime(data["datetime"], unit="ms")
+    data = data.set_index("datetime").sort_index()
+    data = data[~data.index.duplicated(keep='first')]
+
+    return data