def to_pb(self): """Converts the row filter to a protobuf. First converts to a :class:`.data_pb2.ValueRange` and then uses it to create a row filter protobuf. :rtype: :class:`.data_pb2.RowFilter` :returns: The converted current object. """ value_range_kwargs = {} if self.start_value is not None: if self.inclusive_start: key = 'start_value_inclusive' else: key = 'start_value_exclusive' value_range_kwargs[key] = _to_bytes(self.start_value) if self.end_value is not None: if self.inclusive_end: key = 'end_value_inclusive' else: key = 'end_value_exclusive' value_range_kwargs[key] = _to_bytes(self.end_value) value_range = data_pb2.ValueRange(**value_range_kwargs) return data_pb2.RowFilter(value_range_filter=value_range)
def to_pb(self): """Converts the row filter to a protobuf. First converts to a :class:`.data_pb2.ColumnRange` and then uses it in the ``column_range_filter`` field. :rtype: :class:`.data_pb2.RowFilter` :returns: The converted current object. """ column_range_kwargs = {'family_name': self.column_family_id} if self.start_column is not None: if self.inclusive_start: key = 'start_qualifier_inclusive' else: key = 'start_qualifier_exclusive' column_range_kwargs[key] = _to_bytes(self.start_column) if self.end_column is not None: if self.inclusive_end: key = 'end_qualifier_inclusive' else: key = 'end_qualifier_exclusive' column_range_kwargs[key] = _to_bytes(self.end_column) column_range = data_pb2.ColumnRange(**column_range_kwargs) return data_pb2.RowFilter(column_range_filter=column_range)
def to_pb(self): """Converts the row filter to a protobuf. :rtype: :class:`.data_pb2.RowFilter` :returns: The converted current object. """ return data_pb2.RowFilter(strip_value_transformer=self.flag)
def to_pb(self): """Converts the row filter to a protobuf. :rtype: :class:`.data_pb2.RowFilter` :returns: The converted current object. """ return data_pb2.RowFilter(block_all_filter=self.flag)
def test_to_pb(self): from gcloud.bigtable._generated import bigtable_data_pb2 as data_pb2 row_filter = self._makeOne() expected_pb = data_pb2.RowFilter( value_range_filter=data_pb2.ValueRange()) self.assertEqual(row_filter.to_pb(), expected_pb)
def test_to_pb(self): from gcloud.bigtable._generated import bigtable_data_pb2 as data_pb2 from gcloud.bigtable.row import CellsRowOffsetFilter 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 = CellsRowOffsetFilter(11) row_filter3_pb = row_filter3.to_pb() row_filter4 = self._makeOne(row_filter1, true_filter=row_filter2, false_filter=row_filter3) filter_pb = row_filter4.to_pb() expected_pb = data_pb2.RowFilter( condition=data_pb2.RowFilter.Condition( predicate_filter=row_filter1_pb, true_filter=row_filter2_pb, false_filter=row_filter3_pb, ), ) self.assertEqual(filter_pb, expected_pb)
def to_pb(self): """Converts the row filter to a protobuf. :rtype: :class:`.data_pb2.RowFilter` :returns: The converted current object. """ return data_pb2.RowFilter(apply_label_transformer=self.label)
def to_pb(self): """Converts the row filter to a protobuf. :rtype: :class:`.data_pb2.RowFilter` :returns: The converted current object. """ return data_pb2.RowFilter(value_regex_filter=self.regex)
def to_pb(self): """Converts the row filter to a protobuf. :rtype: :class:`.data_pb2.RowFilter` :returns: The converted current object. """ return data_pb2.RowFilter(cells_per_column_limit_filter=self.num_cells)
def test_to_pb(self): from gcloud.bigtable._generated import bigtable_data_pb2 as data_pb2 flag = True row_filter = self._makeOne(flag) pb_val = row_filter.to_pb() expected_pb = data_pb2.RowFilter(sink=flag) self.assertEqual(pb_val, expected_pb)
def test_to_pb(self): from gcloud.bigtable._generated import bigtable_data_pb2 as data_pb2 label = u'label' row_filter = self._makeOne(label) pb_val = row_filter.to_pb() expected_pb = data_pb2.RowFilter(apply_label_transformer=label) self.assertEqual(pb_val, expected_pb)
def test_to_pb_exclusive_end(self): from gcloud.bigtable._generated import bigtable_data_pb2 as data_pb2 value = b'some-value' row_filter = self._makeOne(end_value=value, inclusive_end=False) val_range_pb = data_pb2.ValueRange(end_value_exclusive=value) expected_pb = data_pb2.RowFilter(value_range_filter=val_range_pb) self.assertEqual(row_filter.to_pb(), expected_pb)
def test_to_pb(self): from gcloud.bigtable._generated import bigtable_data_pb2 as data_pb2 num_cells = 189 row_filter = self._makeOne(num_cells) pb_val = row_filter.to_pb() expected_pb = data_pb2.RowFilter(cells_per_row_limit_filter=num_cells) self.assertEqual(pb_val, expected_pb)
def test_to_pb(self): from gcloud.bigtable._generated import bigtable_data_pb2 as data_pb2 regex = b'value-regex' row_filter = self._makeOne(regex) pb_val = row_filter.to_pb() expected_pb = data_pb2.RowFilter(value_regex_filter=regex) self.assertEqual(pb_val, expected_pb)
def test_to_pb(self): from gcloud.bigtable._generated import bigtable_data_pb2 as data_pb2 column_family_id = u'column-family-id' row_filter = self._makeOne(column_family_id) col_range_pb = data_pb2.ColumnRange(family_name=column_family_id) expected_pb = data_pb2.RowFilter(column_range_filter=col_range_pb) self.assertEqual(row_filter.to_pb(), expected_pb)
def test_to_pb(self): from gcloud.bigtable._generated import bigtable_data_pb2 as data_pb2 sample = 0.25 row_filter = self._makeOne(sample) pb_val = row_filter.to_pb() expected_pb = data_pb2.RowFilter(row_sample_filter=sample) self.assertEqual(pb_val, expected_pb)
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)
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)
def test_to_pb(self): from gcloud.bigtable._generated import bigtable_data_pb2 as data_pb2 from gcloud.bigtable.row import TimestampRange range_ = TimestampRange() row_filter = self._makeOne(range_) pb_val = row_filter.to_pb() expected_pb = data_pb2.RowFilter( timestamp_range_filter=data_pb2.TimestampRange()) self.assertEqual(pb_val, expected_pb)
def to_pb(self): """Converts the row filter to a protobuf. First converts the ``range_`` on the current object to a protobuf and then uses it in the ``timestamp_range_filter`` field. :rtype: :class:`.data_pb2.RowFilter` :returns: The converted current object. """ return data_pb2.RowFilter(timestamp_range_filter=self.range_.to_pb())
def test_to_pb_inclusive_end(self): from gcloud.bigtable._generated import bigtable_data_pb2 as data_pb2 column_family_id = u'column-family-id' column = b'column' row_filter = self._makeOne(column_family_id, end_column=column) col_range_pb = data_pb2.ColumnRange( family_name=column_family_id, end_qualifier_inclusive=column, ) expected_pb = data_pb2.RowFilter(column_range_filter=col_range_pb) self.assertEqual(row_filter.to_pb(), expected_pb)
def to_pb(self): """Converts the row filter to a protobuf. :rtype: :class:`.data_pb2.RowFilter` :returns: The converted current object. """ condition_kwargs = {'predicate_filter': self.base_filter.to_pb()} if self.true_filter is not None: condition_kwargs['true_filter'] = self.true_filter.to_pb() if self.false_filter is not None: condition_kwargs['false_filter'] = self.false_filter.to_pb() condition = data_pb2.RowFilter.Condition(**condition_kwargs) return data_pb2.RowFilter(condition=condition)
def test_to_pb(self): from gcloud.bigtable._generated import bigtable_data_pb2 as data_pb2 from gcloud.bigtable.row_filters import RowSampleFilter from gcloud.bigtable.row_filters 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_filters import CellsRowLimitFilter from gcloud.bigtable.row_filters import RowSampleFilter from gcloud.bigtable.row_filters 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)