Merge branch 'develop' into ccxt-async

freqtrade/exchange/__init__.py

@@ -154,8 +154,8 @@ class Exchange(object):
                 api.urls['api'] = api.urls['test']
                 logger.info("Enabled Sandbox API on %s", name)
             else:
-                logger.warning(self._api.name, "No Sandbox URL in CCXT, exiting. "
-                                               "Please check your config.json")
+                logger.warning(name, "No Sandbox URL in CCXT, exiting. "
+                                     "Please check your config.json")
                 raise OperationalException(f'Exchange {name} does not provide a sandbox api')
 
     def _load_async_markets(self) -> None:
@@ -370,7 +370,7 @@ class Exchange(object):
                 return data
             except (ccxt.NetworkError, ccxt.ExchangeError) as e:
                 raise TemporaryError(
-                    f'Could not load ticker history due to {e.__class__.__name__}. Message: {e}')
+                    f'Could not load ticker due to {e.__class__.__name__}. Message: {e}')
             except ccxt.BaseError as e:
                 raise OperationalException(e)
         else:
@@ -554,6 +554,37 @@ class Exchange(object):
         except ccxt.BaseError as e:
             raise OperationalException(e)
 
+    @retrier
+    def get_order_book(self, pair: str, limit: int = 100) -> dict:
+        """
+        get order book level 2 from exchange
+
+        Notes:
+        20180619: bittrex doesnt support limits -.-
+        20180619: binance support limits but only on specific range
+        """
+        try:
+            if self._api.name == 'Binance':
+                limit_range = [5, 10, 20, 50, 100, 500, 1000]
+                # get next-higher step in the limit_range list
+                limit = min(list(filter(lambda x: limit <= x, limit_range)))
+                # above script works like loop below (but with slightly better performance):
+                #   for limitx in limit_range:
+                #        if limit <= limitx:
+                #           limit = limitx
+                #           break
+
+            return self._api.fetch_l2_order_book(pair, limit)
+        except ccxt.NotSupported as e:
+            raise OperationalException(
+                f'Exchange {self._api.name} does not support fetching order book.'
+                f'Message: {e}')
+        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+            raise TemporaryError(
+                f'Could not get order book due to {e.__class__.__name__}. Message: {e}')
+        except ccxt.BaseError as e:
+            raise OperationalException(e)
+
     @retrier
     def get_trades_for_order(self, order_id: str, pair: str, since: datetime) -> List:
         if self._conf['dry_run']:
@@ -607,12 +638,3 @@ class Exchange(object):
                 f'Could not get fee info due to {e.__class__.__name__}. Message: {e}')
         except ccxt.BaseError as e:
             raise OperationalException(e)
-
-    def get_amount_lots(self, pair: str, amount: float) -> float:
-        """
-        get buyable amount rounding, ..
-        """
-        # validate that markets are loaded before trying to get fee
-        if not self._api.markets:
-            self._api.load_markets()
-        return self._api.amount_to_lots(pair, amount)

freqtrade/exchange/exchange_helpers.py

@@ -2,6 +2,7 @@
 Functions to analyze ticker data with indicators and produce buy and sell signals
 """
 import logging
+import pandas as pd
 from pandas import DataFrame, to_datetime
 
 logger = logging.getLogger(__name__)
@@ -31,3 +32,27 @@ def parse_ticker_dataframe(ticker: list) -> DataFrame:
     })
     frame.drop(frame.tail(1).index, inplace=True)     # eliminate partial candle
     return frame
+
+
+def order_book_to_dataframe(bids: list, asks: list) -> DataFrame:
+    """
+    Gets order book list, returns dataframe with below format per suggested by creslin
+    -------------------------------------------------------------------
+     b_sum       b_size       bids       asks       a_size       a_sum
+    -------------------------------------------------------------------
+    """
+    cols = ['bids', 'b_size']
+
+    bids_frame = DataFrame(bids, columns=cols)
+    # add cumulative sum column
+    bids_frame['b_sum'] = bids_frame['b_size'].cumsum()
+    cols2 = ['asks', 'a_size']
+    asks_frame = DataFrame(asks, columns=cols2)
+    # add cumulative sum column
+    asks_frame['a_sum'] = asks_frame['a_size'].cumsum()
+
+    frame = pd.concat([bids_frame['b_sum'], bids_frame['b_size'], bids_frame['bids'],
+                       asks_frame['asks'], asks_frame['a_size'], asks_frame['a_sum']], axis=1,
+                      keys=['b_sum', 'b_size', 'bids', 'asks', 'a_size', 'a_sum'])
+    # logger.info('order book %s', frame )
+    return frame