Merge pull request #808 from quantopian/delta-on-last-requested-date

BUG: Corrects an index error in blaze loader.

tests/pipeline/test_blaze.py

@@ -399,7 +399,7 @@ class BlazeToPipelineTestCase(TestCase):
     @with_extra_sid
     def test_deltas(self, asset_info):
         expr = bz.Data(self.df, name='expr', dshape=self.dshape)
-        deltas = bz.Data(self.df.iloc[:-3], name='deltas', dshape=self.dshape)
+        deltas = bz.Data(self.df, name='deltas', dshape=self.dshape)
         deltas = bz.transform(
             deltas,
             value=deltas.value + 10,
@@ -411,6 +411,8 @@ class BlazeToPipelineTestCase(TestCase):
                                     [1.0, 2.0, 3.0]]),
             '2014-01-03': np.array([[11.0, 12.0, 13.0],
                                     [2.0, 3.0, 4.0]]),
+            '2014-01-04': np.array([[12.0, 13.0, 14.0],
+                                    [12.0, 13.0, 14.0]]),
         })
 
         nassets = len(asset_info)
@@ -422,7 +424,7 @@ class BlazeToPipelineTestCase(TestCase):
 
         with tmp_asset_finder(asset_info) as finder:
             expected_output = pd.DataFrame(
-                list(concatv([12] * nassets, [13] * nassets)),
+                list(concatv([12] * nassets, [13] * nassets, [14] * nassets)),
                 index=pd.MultiIndex.from_product((
                     sorted(expected_views.keys()),
                     finder.retrieve_all(asset_info.index),
@@ -430,6 +432,7 @@ class BlazeToPipelineTestCase(TestCase):
                 columns=('value',),
             )
             dates = self.dates
+            dates = dates.insert(len(dates), dates[-1] + timedelta(days=1))
             self._run_pipeline(
                 expr,
                 deltas,

zipline/pipeline/loaders/blaze.py

@@ -648,11 +648,30 @@ def overwrite_from_dates(asof, dense_dates, sparse_dates, asset_idx, value):
     -------
     overwrite : Float64Overwrite
         The overwrite that will apply the new value to the data.
+
+    Notes
+    -----
+    This is forward-filling all dense dates that are between the asof_date date
+    and the next sparse date after the asof_date.
+
+    For example:
+    let ``asof = pd.Timestamp('2014-01-02')``,
+        ``dense_dates = pd.date_range('2014-01-01', '2014-01-05')``
+        ``sparse_dates = pd.to_datetime(['2014-01', '2014-02', '2014-04'])``
+
+    Then the overwrite will apply to indexes: 1, 2, 3, 4
     """
     first_row = dense_dates.searchsorted(asof)
-    last_row = dense_dates.searchsorted(
-        sparse_dates[sparse_dates.searchsorted(asof, 'right')],
-    ) - 1
+    next_idx = sparse_dates.searchsorted(asof, 'right')
+    if next_idx == len(sparse_dates):
+        # There is no next date in the sparse, this overwrite should apply
+        # through the end of the dense dates.
+        last_row = len(dense_dates) - 1
+    else:
+        # There is a next date in sparse dates. This means that the overwrite
+        # should only apply until the index of this date in the dense dates.
+        last_row = dense_dates.searchsorted(sparse_dates[next_idx]) - 1
+
     if first_row > last_row:
         return