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6537d5ed8c
* Use PyArrow Table for query result serialization * Cleanup dev comments * Additional cleanup * WIP: tests * Remove explicit dtype logic from db_engine_specs * Remove obsolete column property * SupersetTable column types * Port SupersetDataFrame methods to SupersetTable * Add test for nullable boolean columns * Support datetime values with timezone offsets * Black formatting * Pylint * More linting/formatting * Resolve issue with timezones not appearing in results * Types * Enable running of tests in tests/db_engine_specs * Resolve application context errors * Refactor and add tests for pyodbc.Row conversion * Appease isort, regardless of isort:skip * Re-enable RESULTS_BACKEND_USE_MSGPACK default based on benchmarks * Dataframe typing and nits * Renames to reduce ambiguity
52 lines
1.9 KiB
Python
52 lines
1.9 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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import numpy as np
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import pandas as pd
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from superset.dataframe import df_to_records
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from superset.db_engine_specs import BaseEngineSpec
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from superset.result_set import SupersetResultSet
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from .base_tests import SupersetTestCase
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class SupersetDataFrameTestCase(SupersetTestCase):
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def test_df_to_records(self):
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data = [("a1", "b1", "c1"), ("a2", "b2", "c2")]
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cursor_descr = (("a", "string"), ("b", "string"), ("c", "string"))
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results = SupersetResultSet(data, cursor_descr, BaseEngineSpec)
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df = results.to_pandas_df()
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self.assertEqual(
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df_to_records(df),
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[{"a": "a1", "b": "b1", "c": "c1"}, {"a": "a2", "b": "b2", "c": "c2"}],
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)
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def test_js_max_int(self):
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data = [(1, 1239162456494753670, "c1"), (2, 100, "c2")]
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cursor_descr = (("a", "int"), ("b", "int"), ("c", "string"))
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results = SupersetResultSet(data, cursor_descr, BaseEngineSpec)
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df = results.to_pandas_df()
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self.assertEqual(
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df_to_records(df),
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[
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{"a": 1, "b": "1239162456494753670", "c": "c1"},
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{"a": 2, "b": 100, "c": "c2"},
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],
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)
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