Order Book with tests

freqtrade/exchange/__init__.py

@@ -409,6 +409,29 @@ class Exchange(object):
         except ccxt.BaseError as e:
             raise OperationalException(e)
 
+    @retrier
+    def get_order_book(self, pair: str, limit: int = 100) -> dict:
+        try:
+            # 20180619: bittrex doesnt support limits -.-
+            # 20180619: binance support limits but only on specific range
+            if self._api.name == 'Binance':
+                limit_range = [5, 10, 20, 50, 100, 500, 1000]
+                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']:

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 +32,26 @@ 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(data: 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(data['bids'], columns=cols)
+    # add cumulative sum column
+    bids_frame['b_sum'] = bids_frame['b_size'].cumsum()
+    cols2 = ['asks', 'a_size']
+    asks_frame = DataFrame(data['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