Revert "use hasattr instead of version to check whether rolling.rank is implemented"

This reverts commit f2915cc.

Author: qianyun210603

qlib/data/ops.py

@@ -1148,15 +1148,25 @@ class Rank(Rolling):
 
     def __init__(self, feature, N):
         super(Rank, self).__init__(feature, N, "rank")
+        major_version, minor_version, *_ = pd.__version__.split(".")
+        self._load_internal = (
+            self._load_internal_pd14
+            if int(major_version) > 1 or int(major_version) == 1 and int(minor_version) > 3
+            else self._load_internal_pd_below_13
+        )
 
-    def _load_internal(self, instrument, start_index, end_index, *args):
+    def _load_internal_pd14(self, instrument, start_index, end_index, *args):
         series = self.feature.load(instrument, start_index, end_index, *args)
-        rolling_or_expending = series.expanding(min_periods=1) if self.N == 0 else series.rolling(self.N, min_periods=1)
+        if self.N == 0:
+            series = series.expanding(min_periods=1).rank(pct=True)
+        else:
+            series = series.rolling(self.N, min_periods=1).rank(pct=True)
+        return series
 
-        if hasattr(rolling_or_expending, 'rank'):
-            return rolling_or_expending.rank(pct=True)
+    # for compatiblity of python 3.7, which doesn't support pandas 1.4.0+ which implements Rolling.rank
+    def _load_internal_pd_below_13(self, instrument, start_index, end_index, *args):
+        series = self.feature.load(instrument, start_index, end_index, *args)
 
-        # for compatiblity of python 3.7, which doesn't support pandas 1.4.0+ since when Rolling.rank is implemented
         def rank(x):
             if np.isnan(x[-1]):
                 return np.nan
@@ -1165,7 +1175,11 @@ def rank(x):
                 return np.nan
             return percentileofscore(x1, x1[-1]) / 100
 
-        return  rolling_or_expending.apply(rank, raw=True)
+        if self.N == 0:
+            series = series.expanding(min_periods=1).apply(rank, raw=True)
+        else:
+            series = series.rolling(self.N, min_periods=1).apply(rank, raw=True)
+        return series
 
 
 class Count(Rolling):