Implementing Bigtable union/intersection row filters.

gcloud/bigtable/row.py

@@ -661,3 +661,71 @@ def to_pb(self):
         :returns: The converted current object.
         """
         return data_pb2.RowFilter(apply_label_transformer=self.label)
+
+
+class _FilterCombination(RowFilter):
+    """Chain of row filters.
+
+    Sends rows through several filters in sequence. The filters are "chained"
+    together to process a row. After the first filter is applied, the second
+    is applied to the filtered output and so on for subsequent filters.
+
+    :type filters: list
+    :param filters: List of :class:`RowFilter`
+    """
+
+    def __init__(self, filters=None):
+        if filters is None:
+            filters = []
+        self.filters = filters
+
+    def __eq__(self, other):
+        if not isinstance(other, self.__class__):
+            return False
+        return other.filters == self.filters
+
+
+class RowFilterChain(_FilterCombination):
+    """Chain of row filters.
+
+    Sends rows through several filters in sequence. The filters are "chained"
+    together to process a row. After the first filter is applied, the second
+    is applied to the filtered output and so on for subsequent filters.
+
+    :type filters: list
+    :param filters: List of :class:`RowFilter`
+    """
+
+    def to_pb(self):
+        """Converts the row filter to a protobuf.
+
+        :rtype: :class:`.data_pb2.RowFilter`
+        :returns: The converted current object.
+        """
+        chain = data_pb2.RowFilter.Chain(
+            filters=[row_filter.to_pb() for row_filter in self.filters])
+        return data_pb2.RowFilter(chain=chain)
+
+
+class RowFilterUnion(_FilterCombination):
+    """Union of row filters.
+
+    Sends rows through several filters simultaneously, then
+    merges / interleaves all the filtered results together.
+
+    If multiple cells are produced with the same column and timestamp,
+    they will all appear in the output row in an unspecified mutual order.
+
+    :type filters: list
+    :param filters: List of :class:`RowFilter`
+    """
+
+    def to_pb(self):
+        """Converts the row filter to a protobuf.
+
+        :rtype: :class:`.data_pb2.RowFilter`
+        :returns: The converted current object.
+        """
+        interleave = data_pb2.RowFilter.Interleave(
+            filters=[row_filter.to_pb() for row_filter in self.filters])
+        return data_pb2.RowFilter(interleave=interleave)

gcloud/bigtable/test_row.py

@@ -779,3 +779,146 @@ def test_to_pb(self):
         pb_val = row_filter.to_pb()
         expected_pb = data_pb2.RowFilter(apply_label_transformer=label)
         self.assertEqual(pb_val, expected_pb)
+
+
+class Test_FilterCombination(unittest2.TestCase):
+
+    def _getTargetClass(self):
+        from gcloud.bigtable.row import _FilterCombination
+        return _FilterCombination
+
+    def _makeOne(self, *args, **kwargs):
+        return self._getTargetClass()(*args, **kwargs)
+
+    def test_constructor_defaults(self):
+        row_filter = self._makeOne()
+        self.assertEqual(row_filter.filters, [])
+
+    def test_constructor_explicit(self):
+        filters = object()
+        row_filter = self._makeOne(filters=filters)
+        self.assertTrue(row_filter.filters is filters)
+
+    def test___eq__(self):
+        filters = object()
+        row_filter1 = self._makeOne(filters=filters)
+        row_filter2 = self._makeOne(filters=filters)
+        self.assertEqual(row_filter1, row_filter2)
+
+    def test___eq__type_differ(self):
+        filters = object()
+        row_filter1 = self._makeOne(filters=filters)
+        row_filter2 = object()
+        self.assertNotEqual(row_filter1, row_filter2)
+
+
+class TestRowFilterChain(unittest2.TestCase):
+
+    def _getTargetClass(self):
+        from gcloud.bigtable.row import RowFilterChain
+        return RowFilterChain
+
+    def _makeOne(self, *args, **kwargs):
+        return self._getTargetClass()(*args, **kwargs)
+
+    def test_to_pb(self):
+        from gcloud.bigtable._generated import bigtable_data_pb2 as data_pb2
+        from gcloud.bigtable.row import RowSampleFilter
+        from gcloud.bigtable.row import StripValueTransformerFilter
+
+        row_filter1 = StripValueTransformerFilter(True)
+        row_filter1_pb = row_filter1.to_pb()
+
+        row_filter2 = RowSampleFilter(0.25)
+        row_filter2_pb = row_filter2.to_pb()
+
+        row_filter3 = self._makeOne(filters=[row_filter1, row_filter2])
+        filter_pb = row_filter3.to_pb()
+
+        expected_pb = data_pb2.RowFilter(
+            chain=data_pb2.RowFilter.Chain(
+                filters=[row_filter1_pb, row_filter2_pb],
+            ),
+        )
+        self.assertEqual(filter_pb, expected_pb)
+
+    def test_to_pb_nested(self):
+        from gcloud.bigtable._generated import bigtable_data_pb2 as data_pb2
+        from gcloud.bigtable.row import CellsRowLimitFilter
+        from gcloud.bigtable.row import RowSampleFilter
+        from gcloud.bigtable.row import StripValueTransformerFilter
+
+        row_filter1 = StripValueTransformerFilter(True)
+        row_filter2 = RowSampleFilter(0.25)
+
+        row_filter3 = self._makeOne(filters=[row_filter1, row_filter2])
+        row_filter3_pb = row_filter3.to_pb()
+
+        row_filter4 = CellsRowLimitFilter(11)
+        row_filter4_pb = row_filter4.to_pb()
+
+        row_filter5 = self._makeOne(filters=[row_filter3, row_filter4])
+        filter_pb = row_filter5.to_pb()
+
+        expected_pb = data_pb2.RowFilter(
+            chain=data_pb2.RowFilter.Chain(
+                filters=[row_filter3_pb, row_filter4_pb],
+            ),
+        )
+        self.assertEqual(filter_pb, expected_pb)
+
+
+class TestRowFilterUnion(unittest2.TestCase):
+
+    def _getTargetClass(self):
+        from gcloud.bigtable.row import RowFilterUnion
+        return RowFilterUnion
+
+    def _makeOne(self, *args, **kwargs):
+        return self._getTargetClass()(*args, **kwargs)
+
+    def test_to_pb(self):
+        from gcloud.bigtable._generated import bigtable_data_pb2 as data_pb2
+        from gcloud.bigtable.row import RowSampleFilter
+        from gcloud.bigtable.row import StripValueTransformerFilter
+
+        row_filter1 = StripValueTransformerFilter(True)
+        row_filter1_pb = row_filter1.to_pb()
+
+        row_filter2 = RowSampleFilter(0.25)
+        row_filter2_pb = row_filter2.to_pb()
+
+        row_filter3 = self._makeOne(filters=[row_filter1, row_filter2])
+        filter_pb = row_filter3.to_pb()
+
+        expected_pb = data_pb2.RowFilter(
+            interleave=data_pb2.RowFilter.Interleave(
+                filters=[row_filter1_pb, row_filter2_pb],
+            ),
+        )
+        self.assertEqual(filter_pb, expected_pb)
+
+    def test_to_pb_nested(self):
+        from gcloud.bigtable._generated import bigtable_data_pb2 as data_pb2
+        from gcloud.bigtable.row import CellsRowLimitFilter
+        from gcloud.bigtable.row import RowSampleFilter
+        from gcloud.bigtable.row import StripValueTransformerFilter
+
+        row_filter1 = StripValueTransformerFilter(True)
+        row_filter2 = RowSampleFilter(0.25)
+
+        row_filter3 = self._makeOne(filters=[row_filter1, row_filter2])
+        row_filter3_pb = row_filter3.to_pb()
+
+        row_filter4 = CellsRowLimitFilter(11)
+        row_filter4_pb = row_filter4.to_pb()
+
+        row_filter5 = self._makeOne(filters=[row_filter3, row_filter4])
+        filter_pb = row_filter5.to_pb()
+
+        expected_pb = data_pb2.RowFilter(
+            interleave=data_pb2.RowFilter.Interleave(
+                filters=[row_filter3_pb, row_filter4_pb],
+            ),
+        )
+        self.assertEqual(filter_pb, expected_pb)