feat: add support of float32 type #1113
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| @@ -466,6 +466,27 @@ def test_w_float_str(self): | |||
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| self.assertEqual(self._callFUT(value_pb, field_type), expected_value) | |||
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| def test_w_float32(self): | |||
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As per FLOAT32 design, the request from client is sent as number_value field. What will happen when the input is float("-inf") or float("nan") which gets encoded to string_value field and the column in table is of type FLOAT32?
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We need to verify both insert and read with this kind of data when column type is FLOAT32.
For read we already have an integration test for FLOAT64 test_execute_sql_w_float_bindings_transfinite . We can copy it for FLOAT32.
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behaviour for float("-inf") or float("nan") is same as FLOAT64, added the skipped test case for manual verification.
| @@ -228,6 +228,11 @@ def _parse_value_pb(value_pb, field_type): | |||
| return float(value_pb.string_value) | |||
| else: | |||
| return value_pb.number_value | |||
| elif type_code == TypeCode.FLOAT32: | |||
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We have integration tests for every type in test_session_api.py. Can we have a test for FLOAT32?
Reference: test_execute_sql_w_float64_bindings and test_execute_sql_w_float_bindings_transfinite
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We should register the same merge method for |
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@ankiaga This query should give you a good indication of what changes are needed for |
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| @@ -90,5 +90,8 @@ def _check_cell_data(found_cell, expected_cell, recurse_into_lists=True): | |||
| for found_item, expected_item in zip(found_cell, expected_cell): | |||
| _check_cell_data(found_item, expected_item) | |||
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| elif isinstance(found_cell, float): | |||
| assert abs(found_cell - expected_cell) < 0.00001 | |||
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Fixes #<issue_number_goes_here> 🦕