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)
