tests/unit_tests/dataframe_test.py

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# pylint: disable=unused-argument, import-outside-toplevel
from datetime import datetime

import pytest
from pandas import Timestamp
from pandas._libs.tslibs import NaT

from superset.dataframe import df_to_records
from superset.superset_typing import DbapiDescription


def test_df_to_records() -> None:
    from superset.db_engine_specs import BaseEngineSpec
    from superset.result_set import SupersetResultSet

    data = [("a1", "b1", "c1"), ("a2", "b2", "c2")]
    cursor_descr: DbapiDescription = [
        (column, "string", None, None, None, None, False) for column in ("a", "b", "c")
    ]
    results = SupersetResultSet(data, cursor_descr, BaseEngineSpec)
    df = results.to_pandas_df()

    assert df_to_records(df) == [
        {"a": "a1", "b": "b1", "c": "c1"},
        {"a": "a2", "b": "b2", "c": "c2"},
    ]


def test_df_to_records_NaT_type() -> None:
    from superset.db_engine_specs import BaseEngineSpec
    from superset.result_set import SupersetResultSet

    data = [(NaT,), (Timestamp("2023-01-06 20:50:31.749000+0000", tz="UTC"),)]
    cursor_descr: DbapiDescription = [
        ("date", "timestamp with time zone", None, None, None, None, False)
    ]
    results = SupersetResultSet(data, cursor_descr, BaseEngineSpec)
    df = results.to_pandas_df()

    assert df_to_records(df) == [
        {"date": None},
        {"date": "2023-01-06 20:50:31.749000+00:00"},
    ]


def test_df_to_records_mixed_emoji_type() -> None:
    from superset.db_engine_specs import BaseEngineSpec
    from superset.result_set import SupersetResultSet

    data = [
        ("What's up?", "This is a string text", 1),
        ("What's up?", "This is a string with an 😍 added", 2),
        ("What's up?", NaT, 3),
        ("What's up?", "Last emoji 😁", 4),
    ]

    cursor_descr: DbapiDescription = [
        ("question", "varchar", None, None, None, None, False),
        ("response", "varchar", None, None, None, None, False),
        ("count", "integer", None, None, None, None, False),
    ]

    results = SupersetResultSet(data, cursor_descr, BaseEngineSpec)
    df = results.to_pandas_df()

    assert df_to_records(df) == [
        {"question": "What's up?", "response": "This is a string text", "count": 1},
        {
            "question": "What's up?",
            "response": "This is a string with an 😍 added",
            "count": 2,
        },
        {
            "question": "What's up?",
            "response": None,
            "count": 3,
        },
        {
            "question": "What's up?",
            "response": "Last emoji 😁",
            "count": 4,
        },
    ]


def test_df_to_records_mixed_accent_type() -> None:
    from superset.db_engine_specs import BaseEngineSpec
    from superset.result_set import SupersetResultSet

    data = [
        ("What's up?", "This is a string text", 1),
        ("What's up?", "This is a string with áccent", 2),
        ("What's up?", NaT, 3),
        ("What's up?", "móre áccent", 4),
    ]

    cursor_descr: DbapiDescription = [
        ("question", "varchar", None, None, None, None, False),
        ("response", "varchar", None, None, None, None, False),
        ("count", "integer", None, None, None, None, False),
    ]

    results = SupersetResultSet(data, cursor_descr, BaseEngineSpec)
    df = results.to_pandas_df()

    assert df_to_records(df) == [
        {"question": "What's up?", "response": "This is a string text", "count": 1},
        {
            "question": "What's up?",
            "response": "This is a string with áccent",
            "count": 2,
        },
        {
            "question": "What's up?",
            "response": None,
            "count": 3,
        },
        {
            "question": "What's up?",
            "response": "móre áccent",
            "count": 4,
        },
    ]


def test_js_max_int() -> None:
    from superset.db_engine_specs import BaseEngineSpec
    from superset.result_set import SupersetResultSet

    data = [(1, 1239162456494753670, "c1"), (2, 100, "c2")]
    cursor_descr: DbapiDescription = [
        ("a", "int", None, None, None, None, False),
        ("b", "int", None, None, None, None, False),
        ("c", "string", None, None, None, None, False),
    ]
    results = SupersetResultSet(data, cursor_descr, BaseEngineSpec)
    df = results.to_pandas_df()

    assert df_to_records(df) == [
        {"a": 1, "b": "1239162456494753670", "c": "c1"},
        {"a": 2, "b": 100, "c": "c2"},
    ]


@pytest.mark.parametrize(
    "input_, expected",
    [
        pytest.param(
            [
                (datetime.strptime("1677-09-22 00:12:43", "%Y-%m-%d %H:%M:%S"), 1),
                (datetime.strptime("2262-04-11 23:47:17", "%Y-%m-%d %H:%M:%S"), 2),
            ],
            [
                {
                    "a": datetime.strptime("1677-09-22 00:12:43", "%Y-%m-%d %H:%M:%S"),
                    "b": 1,
                },
                {
                    "a": datetime.strptime("2262-04-11 23:47:17", "%Y-%m-%d %H:%M:%S"),
                    "b": 2,
                },
            ],
            id="timestamp conversion fail",
        ),
        pytest.param(
            [
                (datetime.strptime("1677-09-22 00:12:44", "%Y-%m-%d %H:%M:%S"), 1),
                (datetime.strptime("2262-04-11 23:47:16", "%Y-%m-%d %H:%M:%S"), 2),
            ],
            [
                {"a": Timestamp("1677-09-22 00:12:44"), "b": 1},
                {"a": Timestamp("2262-04-11 23:47:16"), "b": 2},
            ],
            id="timestamp conversion success",
        ),
    ],
)
def test_max_pandas_timestamp(input_, expected) -> None:
    from superset.db_engine_specs import BaseEngineSpec
    from superset.result_set import SupersetResultSet

    cursor_descr: DbapiDescription = [
        ("a", "datetime", None, None, None, None, False),
        ("b", "int", None, None, None, None, False),
    ]
    results = SupersetResultSet(input_, cursor_descr, BaseEngineSpec)
    df = results.to_pandas_df()

    assert df_to_records(df) == expected