def test_read_rows(self):
row = self._table.row(ROW_KEY)
row_alt = self._table.row(ROW_KEY_ALT)
self.rows_to_delete.extend([row, row_alt])
cell1, cell2, cell3, cell4 = self._write_to_row(row, row_alt, row, row_alt)
row.commit()
row_alt.commit()
rows_data = self._table.read_rows()
self.assertEqual(rows_data.rows, {})
rows_data.consume_all()
# NOTE: We should refrain from editing protected data on instances.
# Instead we should make the values public or provide factories
# for constructing objects with them.
row_data = PartialRowData(ROW_KEY)
row_data._chunks_encountered = True
row_data._committed = True
row_data._cells = {COLUMN_FAMILY_ID1: {COL_NAME1: [cell1], COL_NAME2: [cell3]}}
row_alt_data = PartialRowData(ROW_KEY_ALT)
row_alt_data._chunks_encountered = True
row_alt_data._committed = True
row_alt_data._cells = {
COLUMN_FAMILY_ID1: {COL_NAME1: [cell2]},
COLUMN_FAMILY_ID2: {COL_NAME3: [cell4]},
}
expected_rows = {ROW_KEY: row_data, ROW_KEY_ALT: row_alt_data}
self.assertEqual(rows_data.rows, expected_rows)
def test_row_with_results(self):
from google.cloud.bigtable.row_data import PartialRowData
row_key = "row-key"
name = "table-name"
connection = None
table = self._make_one(name, connection)
table._low_level_table = _MockLowLevelTable()
partial_row = PartialRowData(row_key)
table._low_level_table.read_row_result = partial_row
# Set-up mocks.
fake_filter = object()
mock_filters = []
def mock_filter_chain_helper(**kwargs):
mock_filters.append(kwargs)
return fake_filter
fake_pair = object()
mock_cells = []
def mock_cells_to_pairs(*args, **kwargs):
mock_cells.append((args, kwargs))
return [fake_pair]
col_fam = u"cf1"
qual = b"qual"
fake_cells = object()
partial_row._cells = {col_fam: {qual: fake_cells}}
include_timestamp = object()
patch = mock.patch.multiple(
"google.cloud.happybase.table",
_filter_chain_helper=mock_filter_chain_helper,
_cells_to_pairs=mock_cells_to_pairs,
)
with patch:
result = table.row(row_key, include_timestamp=include_timestamp)
# The results come from _cells_to_pairs.
expected_result = {col_fam.encode("ascii") + b":" + qual: fake_pair}
self.assertEqual(result, expected_result)
read_row_args = (row_key, )
read_row_kwargs = {"filter_": fake_filter}
self.assertEqual(table._low_level_table.read_row_calls,
[(read_row_args, read_row_kwargs)])
expected_kwargs = {"filters": [], "versions": 1, "timestamp": None}
self.assertEqual(mock_filters, [expected_kwargs])
to_pairs_kwargs = {"include_timestamp": include_timestamp}
self.assertEqual(mock_cells, [((fake_cells, ), to_pairs_kwargs)])
def test_without_timestamp(self):
from google.cloud.bigtable.row_data import Cell
from google.cloud.bigtable.row_data import PartialRowData
row_data = PartialRowData(b"row-key")
val1 = b"hi-im-bytes"
val2 = b"bi-im-hytes"
row_data._cells[u"fam1"] = {
b"col1": [Cell(val1, None)],
b"col2": [Cell(val2, None)],
}
result = self._call_fut(row_data)
expected_result = {b"fam1:col1": val1, b"fam1:col2": val2}
self.assertEqual(result, expected_result)
def test_read_rows(self):
row = self._table.row(ROW_KEY)
row_alt = self._table.row(ROW_KEY_ALT)
self.rows_to_delete.extend([row, row_alt])
cell1, cell2, cell3, cell4 = self._write_to_row(row, row_alt, row, row_alt)
row.commit()
row_alt.commit()
rows_data = self._table.read_rows()
self.assertEqual(rows_data.rows, {})
rows_data.consume_all()
# NOTE: We should refrain from editing protected data on instances.
# Instead we should make the values public or provide factories
# for constructing objects with them.
row_data = PartialRowData(ROW_KEY)
row_data._chunks_encountered = True
row_data._committed = True
row_data._cells = {COLUMN_FAMILY_ID1: {COL_NAME1: [cell1], COL_NAME2: [cell3]}}
row_alt_data = PartialRowData(ROW_KEY_ALT)
row_alt_data._chunks_encountered = True
row_alt_data._committed = True
row_alt_data._cells = {
COLUMN_FAMILY_ID1: {COL_NAME1: [cell2]},
COLUMN_FAMILY_ID2: {COL_NAME3: [cell4]},
}
expected_rows = {ROW_KEY: row_data, ROW_KEY_ALT: row_alt_data}
self.assertEqual(rows_data.rows, expected_rows)
def test_table_read_rows(data_table, rows_to_delete):
from google.cloud.bigtable.row_data import PartialRowData
row = data_table.direct_row(ROW_KEY)
rows_to_delete.append(row)
row_alt = data_table.direct_row(ROW_KEY_ALT)
rows_to_delete.append(row_alt)
cell1, cell2, cell3, cell4 = _write_to_row(row, row_alt, row, row_alt)
row.commit()
row_alt.commit()
rows_data = data_table.read_rows()
assert rows_data.rows == {}
rows_data.consume_all()
# NOTE: We should refrain from editing protected data on instances.
# Instead we should make the values public or provide factories
# for constructing objects with them.
row_data = PartialRowData(ROW_KEY)
row_data._chunks_encountered = True
row_data._committed = True
row_data._cells = {
COLUMN_FAMILY_ID1: {
COL_NAME1: [cell1],
COL_NAME2: [cell3]
}
}
row_alt_data = PartialRowData(ROW_KEY_ALT)
row_alt_data._chunks_encountered = True
row_alt_data._committed = True
row_alt_data._cells = {
COLUMN_FAMILY_ID1: {
COL_NAME1: [cell2]
},
COLUMN_FAMILY_ID2: {
COL_NAME3: [cell4]
},
}
expected_rows = {ROW_KEY: row_data, ROW_KEY_ALT: row_alt_data}
assert rows_data.rows == expected_rows
def test_with_timestamp(self):
from google.cloud.bigtable.row_data import Cell
from google.cloud.bigtable.row_data import PartialRowData
row_data = PartialRowData(b"row-key")
val1 = b"hi-im-bytes"
ts1_millis = 1221934570148
ts1 = ts1_millis * 1000
val2 = b"bi-im-hytes"
ts2_millis = 1331934880000
ts2 = ts2_millis * 1000
row_data._cells[u"fam1"] = {
b"col1": [Cell(val1, ts1)],
b"col2": [Cell(val2, ts2)],
}
result = self._call_fut(row_data, include_timestamp=True)
expected_result = {
b"fam1:col1": (val1, ts1_millis),
b"fam1:col2": (val2, ts2_millis),
}
self.assertEqual(result, expected_result)
def test_scan_with_results(self):
from google.cloud.bigtable.row_data import PartialRowData
row_key1 = "row-key1"
row1 = PartialRowData(row_key1)
rr_result = _MockPartialRowsData(rows={row_key1: row1}, iterations=1)
include_timestamp = object()
expected_result = [(row_key1, {})]
self._scan_test_helper(
include_timestamp=include_timestamp,
rr_result=rr_result,
expected_result=expected_result,
)
def test_read_row_complete(self):
from google.cloud.bigtable.row_data import Cell
from google.cloud.bigtable.row_data import PartialRowData
chunk = _ReadRowsResponseCellChunkPB(
row_key=self.ROW_KEY,
family_name=self.FAMILY_NAME,
qualifier=self.QUALIFIER,
timestamp_micros=self.TIMESTAMP_MICROS,
value=self.VALUE,
commit_row=True,
)
chunks = [chunk]
expected_result = PartialRowData(row_key=self.ROW_KEY)
family = expected_result._cells.setdefault(self.FAMILY_NAME, {})
column = family.setdefault(self.QUALIFIER, [])
column.append(Cell.from_pb(chunk))
self._read_row_helper(chunks, expected_result)
def test_cells_with_results(self):
from google.cloud.bigtable.row_data import PartialRowData
row_key = "row-key"
name = "table-name"
connection = None
table = self._make_one(name, connection)
table._low_level_table = _MockLowLevelTable()
partial_row = PartialRowData(row_key)
table._low_level_table.read_row_result = partial_row
# These are all passed to mocks.
versions = object()
timestamp = object()
include_timestamp = object()
# Set-up mocks.
fake_filter = object()
mock_filters = []
def mock_filter_chain_helper(**kwargs):
mock_filters.append(kwargs)
return fake_filter
fake_result = object()
mock_cells = []
def mock_cells_to_pairs(*args, **kwargs):
mock_cells.append((args, kwargs))
return fake_result
col_fam = "cf1"
qual = "qual"
fake_cells = object()
partial_row._cells = {col_fam: {qual.encode("utf-8"): fake_cells}}
column = (col_fam + ":" + qual).encode("utf-8")
patch = mock.patch.multiple(
"google.cloud.happybase.table",
_filter_chain_helper=mock_filter_chain_helper,
_cells_to_pairs=mock_cells_to_pairs,
)
with patch:
result = table.cells(
row_key,
column,
versions=versions,
timestamp=timestamp,
include_timestamp=include_timestamp,
)
self.assertEqual(result, fake_result)
read_row_args = (row_key, )
read_row_kwargs = {"filter_": fake_filter}
self.assertEqual(table._low_level_table.read_row_calls,
[(read_row_args, read_row_kwargs)])
filter_kwargs = {
"column": column,
"versions": versions,
"timestamp": timestamp
}
self.assertEqual(mock_filters, [filter_kwargs])
to_pairs_kwargs = {"include_timestamp": include_timestamp}
self.assertEqual(mock_cells, [((fake_cells, ), to_pairs_kwargs)])
def test_rows_with_results(self):
from google.cloud.bigtable.row_data import PartialRowData
row_key1 = "row-key1"
row_key2 = "row-key2"
rows = [row_key1, row_key2]
name = "table-name"
connection = None
table = self._make_one(name, connection)
table._low_level_table = _MockLowLevelTable()
row1 = PartialRowData(row_key1)
# Return row1 but not row2
rr_result = _MockPartialRowsData(rows={row_key1: row1})
table._low_level_table.read_rows_result = rr_result
# Set-up mocks.
fake_row_set = object()
def mock_get_row_set_from_rows(*args): # pylint: disable=unused-argument
return fake_row_set
fake_filter = object()
mock_filters = []
def mock_filter_chain_helper(**kwargs):
mock_filters.append(kwargs)
return fake_filter
fake_pair = object()
mock_cells = []
def mock_cells_to_pairs(*args, **kwargs):
mock_cells.append((args, kwargs))
return [fake_pair]
col_fam = u"cf1"
qual = b"qual"
fake_cells = object()
row1._cells = {col_fam: {qual: fake_cells}}
include_timestamp = object()
patch = mock.patch.multiple(
"google.cloud.happybase.table",
_filter_chain_helper=mock_filter_chain_helper,
_get_row_set_from_rows=mock_get_row_set_from_rows,
_cells_to_pairs=mock_cells_to_pairs,
)
with patch:
result = table.rows(rows, include_timestamp=include_timestamp)
# read_rows_result == PartialRowsData with row_key1
expected_result = {col_fam.encode("ascii") + b":" + qual: fake_pair}
self.assertEqual(result, [(row_key1, expected_result)])
read_rows_args = ()
read_rows_kwargs = {"row_set": fake_row_set, "filter_": fake_filter}
self.assertEqual(table._low_level_table.read_rows_calls,
[(read_rows_args, read_rows_kwargs)])
expected_kwargs = {"filters": [], "versions": 1, "timestamp": None}
self.assertEqual(mock_filters, [expected_kwargs])
to_pairs_kwargs = {"include_timestamp": include_timestamp}
self.assertEqual(mock_cells, [((fake_cells, ), to_pairs_kwargs)])
def _make_partial_row_data(*args, **kwargs):
from google.cloud.bigtable.row_data import PartialRowData
return PartialRowData(*args, **kwargs)
