Updating library to be compatible with latest pandas

spectre/data/dataloader.py

@@ -159,15 +159,20 @@ def load(self, start: Optional[pd.Timestamp] = None, end: Optional[pd.Timestamp]
             end = index[-1]
 
         if index[0] > start:
-            raise ValueError("`start` time cannot less than earliest time of data: {}."
-                             .format(index[0]))
+            raise ValueError(
+                f"`start` time ({start}) cannot be less " \
+                f"than earliest time of data: {index[0]}."
+            )
+
         if index[-1] < end:
-            raise ValueError("`end` time cannot greater than latest time of data: {}."
-                             .format(index[-1]))
+            raise ValueError(
+                f"`end` time ({end}) cannot be greater " \
+                f"than latest time of data: {index[-1]}."
+            )
 
-        start_loc = index.get_loc(start, 'bfill')
+        start_loc = index.get_indexer([start], method='bfill')[0]
         backward_loc = max(start_loc - backwards, 0)
-        end_loc = index.get_loc(end, 'ffill')
+        end_loc = index.get_indexer([end], method='ffill')[0]
         assert end_loc >= start_loc, 'There is no data between `start` and `end`.'
 
         backward_start = index[backward_loc]

spectre/factors/engine.py

@@ -100,13 +100,13 @@ def _prepare_tensor(self, start, end, max_backwards):
         df = self._loader.load(start, end, max_backwards).copy()
         # If possible, pre-screen
         if isinstance(self._filter, StaticAssets):
-            df = df.loc[(slice(None), self._filter.assets), :]
+            df = df.loc[(slice(None), list(self._filter.assets)), :]
             if df.shape[0] == 0:
                 raise ValueError("The assets {} specified by StaticAssets filter, was not found in "
                                  "DataLoader.".format(self._filter.assets))
         # check history data is insufficient
         df.index = df.index.remove_unused_levels()
-        history_win = df.index.levels[0].get_loc(start, 'bfill')
+        history_win = df.index.levels[0].get_indexer([start], method='bfill')[0]
         if history_win < max_backwards:
             warnings.warn("Historical data seems insufficient. "
                           "{} rows of historical data are required, but only {} rows are obtained. "
@@ -353,7 +353,7 @@ def run(self, start: Union[str, pd.Timestamp], end: Union[str, pd.Timestamp],
         # if any factors delayed, return df also should be delayed
         if delayed:
             index = ret.index.levels[0]
-            start_ind = index.get_loc(start, 'bfill')
+            start_ind = index.get_indexer([start], method='bfill')[0]
             if (start_ind + 1) >= len(index):
                 raise ValueError('There is no data between start and end.')
             start = index[start_ind + 1]
@@ -369,7 +369,7 @@ def run_raw(self, start: Union[str, pd.Timestamp], end: Union[str, pd.Timestamp]
         results, shifted_mask, delayed = self._run(start, end, delay_factor)
 
         index = self._dataframe.index.levels[0]
-        start_ind = index.get_loc(start, 'bfill')
+        start_ind = index.get_indexer([start], method='bfill')[0]
         if delayed:  # if any factors delayed, return df also should be delayed
             start_ind += 1
         if start_ind >= len(index):