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Merge pull request #1475 from dhermes/bigtable-partial-rowdata · googleapis/google-cloud-python@75a395f · GitHub

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Commit 75a395f

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dhermes
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Merge pull request #1475 from dhermes/bigtable-partial-rowdata
Adding Bigtable PartialRowData.
2 parents 4ca596c + aaf1bf5 commit 75a395f

2 files changed

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‎gcloud/bigtable/row_data.py‎

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"""Container for Google Cloud Bigtable Cells and Streaming Row Contents."""
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import six
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from gcloud._helpers import _datetime_from_microseconds
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from gcloud._helpers import _to_bytes
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class Cell(object):
@@ -61,3 +64,48 @@ def __eq__(self, other):
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def __ne__(self, other):
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return not self.__eq__(other)
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class PartialRowData(object):
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"""Representation of partial row in a Google Cloud Bigtable Table.
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These are expected to be updated directly from a
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:class:`._generated.bigtable_service_messages_pb2.ReadRowsResponse`
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:type row_key: bytes
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:param row_key: The key for the row holding the (partial) data.
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"""
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def __init__(self, row_key):
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self._row_key = row_key
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self._cells = {}
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self._committed = False
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self._chunks_encountered = False
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def __eq__(self, other):
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if not isinstance(other, self.__class__):
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return False
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return (other._row_key == self._row_key and
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other._committed == self._committed and
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other._chunks_encountered == self._chunks_encountered and
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other._cells == self._cells)
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def __ne__(self, other):
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return not self.__eq__(other)
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def to_dict(self):
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"""Convert the cells to a dictionary.
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This is intended to be used with HappyBase, so the column family and
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column qualiers are combined (with ``:``).
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:rtype: dict
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:returns: Dictionary containing all the data in the cells of this row.
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"""
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result = {}
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for column_family_id, columns in six.iteritems(self._cells):
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for column_qual, cells in six.iteritems(columns):
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key = (_to_bytes(column_family_id) + b':' +
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_to_bytes(column_qual))
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result[key] = cells
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return result

‎gcloud/bigtable/test_row_data.py‎

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cell1 = self._makeOne(value1, timestamp)
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cell2 = self._makeOne(value2, timestamp)
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self.assertNotEqual(cell1, cell2)
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class TestPartialRowData(unittest2.TestCase):
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def _getTargetClass(self):
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from gcloud.bigtable.row_data import PartialRowData
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return PartialRowData
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def _makeOne(self, *args, **kwargs):
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return self._getTargetClass()(*args, **kwargs)
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def test_constructor(self):
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row_key = object()
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partial_row_data = self._makeOne(row_key)
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self.assertTrue(partial_row_data._row_key is row_key)
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self.assertEqual(partial_row_data._cells, {})
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self.assertFalse(partial_row_data._committed)
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self.assertFalse(partial_row_data._chunks_encountered)
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def test___eq__(self):
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row_key = object()
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partial_row_data1 = self._makeOne(row_key)
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partial_row_data2 = self._makeOne(row_key)
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self.assertEqual(partial_row_data1, partial_row_data2)
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def test___eq__type_differ(self):
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partial_row_data1 = self._makeOne(None)
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partial_row_data2 = object()
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self.assertNotEqual(partial_row_data1, partial_row_data2)
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def test___ne__same_value(self):
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row_key = object()
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partial_row_data1 = self._makeOne(row_key)
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partial_row_data2 = self._makeOne(row_key)
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comparison_val = (partial_row_data1 != partial_row_data2)
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self.assertFalse(comparison_val)
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def test___ne__(self):
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row_key1 = object()
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partial_row_data1 = self._makeOne(row_key1)
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row_key2 = object()
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partial_row_data2 = self._makeOne(row_key2)
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self.assertNotEqual(partial_row_data1, partial_row_data2)
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def test___ne__committed(self):
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row_key = object()
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partial_row_data1 = self._makeOne(row_key)
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partial_row_data1._committed = object()
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partial_row_data2 = self._makeOne(row_key)
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self.assertNotEqual(partial_row_data1, partial_row_data2)
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def test___ne__cells(self):
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row_key = object()
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partial_row_data1 = self._makeOne(row_key)
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partial_row_data1._cells = object()
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partial_row_data2 = self._makeOne(row_key)
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self.assertNotEqual(partial_row_data1, partial_row_data2)
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def test_to_dict(self):
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cell1 = object()
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cell2 = object()
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cell3 = object()
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family_name1 = u'name1'
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family_name2 = u'name2'
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qual1 = b'col1'
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qual2 = b'col2'
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qual3 = b'col3'
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partial_row_data = self._makeOne(None)
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partial_row_data._cells = {
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family_name1: {
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qual1: cell1,
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qual2: cell2,
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},
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family_name2: {
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qual3: cell3,
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},
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}
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result = partial_row_data.to_dict()
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expected_result = {
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b'name1:col1': cell1,
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b'name1:col2': cell2,
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b'name2:col3': cell3,
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}
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self.assertEqual(result, expected_result)

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