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fix(viz): improve dtype inference logic (#12933)

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This commit is contained in:
Ville Brofeldt
2021-02-04 20:47:27 +02:00
committed by GitHub
parent b472d1841c
commit ac73991913
5 changed files with 72 additions and 40 deletions
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43
tests/utils_tests.py
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@@ -23,10 +23,12 @@ import hashlib
import json
import os
import re
from typing import Any, Tuple, List
from unittest.mock import Mock, patch
from tests.fixtures.birth_names_dashboard import load_birth_names_dashboard_with_slices
import numpy
import numpy as np
import pandas as pd
import pytest
from flask import Flask, g
import marshmallow
@@ -44,6 +46,7 @@ from superset.utils.core import (
convert_legacy_filters_into_adhoc,
create_ssl_cert_file,
format_timedelta,
GenericDataType,
get_form_data_token,
get_iterable,
get_email_address_list,
@@ -57,6 +60,7 @@ from superset.utils.core import (
merge_request_params,
parse_ssl_cert,
parse_js_uri_path_item,
extract_dataframe_dtypes,
split,
TimeRangeEndpoint,
validate_json,
@@ -113,9 +117,9 @@ class TestUtils(SupersetTestCase):
json_iso_dttm_ser("this is not a date")
def test_base_json_conv(self):
assert isinstance(base_json_conv(numpy.bool_(1)), bool) is True
assert isinstance(base_json_conv(numpy.int64(1)), int) is True
assert isinstance(base_json_conv(numpy.array([1, 2, 3])), list) is True
assert isinstance(base_json_conv(np.bool_(1)), bool) is True
assert isinstance(base_json_conv(np.int64(1)), int) is True
assert isinstance(base_json_conv(np.array([1, 2, 3])), list) is True
assert isinstance(base_json_conv(set([1])), list) is True
assert isinstance(base_json_conv(Decimal("1.0")), float) is True
assert isinstance(base_json_conv(uuid.uuid4()), str) is True
@@ -1066,3 +1070,34 @@ class TestUtils(SupersetTestCase):
assert get_form_data_token({"token": "token_abcdefg1"}) == "token_abcdefg1"
generated_token = get_form_data_token({})
assert re.match(r"^token_[a-z0-9]{8}$", generated_token) is not None
def test_extract_dataframe_dtypes(self):
cols: Tuple[Tuple[str, GenericDataType, List[Any]], ...] = (
("dt", GenericDataType.TEMPORAL, [date(2021, 2, 4), date(2021, 2, 4)]),
(
"dttm",
GenericDataType.TEMPORAL,
[datetime(2021, 2, 4, 1, 1, 1), datetime(2021, 2, 4, 1, 1, 1)],
),
("str", GenericDataType.STRING, ["foo", "foo"]),
("int", GenericDataType.NUMERIC, [1, 1]),
("float", GenericDataType.NUMERIC, [0.5, 0.5]),
("mixed-int-float", GenericDataType.NUMERIC, [0.5, 1.0]),
("bool", GenericDataType.BOOLEAN, [True, False]),
("mixed-str-int", GenericDataType.STRING, ["abc", 1.0]),
("obj", GenericDataType.STRING, [{"a": 1}, {"a": 1}]),
("dt_null", GenericDataType.TEMPORAL, [None, date(2021, 2, 4)]),
(
"dttm_null",
GenericDataType.TEMPORAL,
[None, datetime(2021, 2, 4, 1, 1, 1)],
),
("str_null", GenericDataType.STRING, [None, "foo"]),
("int_null", GenericDataType.NUMERIC, [None, 1]),
("float_null", GenericDataType.NUMERIC, [None, 0.5]),
("bool_null", GenericDataType.BOOLEAN, [None, False]),
("obj_null", GenericDataType.STRING, [None, {"a": 1}]),
)
df = pd.DataFrame(data={col[0]: col[2] for col in cols})
assert extract_dataframe_dtypes(df) == [col[1] for col in cols]