fix: Restore deleted test file

Author: shuoweil

tests/unit/display/test_html.py

@@ -0,0 +1,191 @@
+# Copyright 2024 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import datetime
+
+import pandas as pd
+import pyarrow as pa
+import pytest
+
+import bigframes as bf
+from bigframes.display.html import _flatten_nested_data
+import bigframes.display.html as bf_html
+
+
+@pytest.mark.parametrize(
+    ("data", "expected_alignments", "expected_strings"),
+    [
+        pytest.param(
+            {
+                "string_col": ["a", "b", "c"],
+                "int_col": [1, 2, 3],
+                "float_col": [1.1, 2.2, 3.3],
+                "bool_col": [True, False, True],
+            },
+            {
+                "string_col": "left",
+                "int_col": "right",
+                "float_col": "right",
+                "bool_col": "left",
+            },
+            ["1.100000", "2.200000", "3.300000"],
+            id="scalars",
+        ),
+        pytest.param(
+            {
+                "timestamp_col": pa.array(
+                    [
+                        datetime.datetime.fromisoformat(value)
+                        for value in [
+                            "2024-01-01 00:00:00",
+                            "2024-01-01 00:00:01",
+                            "2024-01-01 00:00:02",
+                        ]
+                    ],
+                    pa.timestamp("us", tz="UTC"),
+                ),
+                "datetime_col": pa.array(
+                    [
+                        datetime.datetime.fromisoformat(value)
+                        for value in [
+                            "2027-06-05 04:03:02.001",
+                            "2027-01-01 00:00:01",
+                            "2027-01-01 00:00:02",
+                        ]
+                    ],
+                    pa.timestamp("us"),
+                ),
+                "date_col": pa.array(
+                    [
+                        datetime.date(1999, 1, 1),
+                        datetime.date(1999, 1, 2),
+                        datetime.date(1999, 1, 3),
+                    ],
+                    pa.date32(),
+                ),
+                "time_col": pa.array(
+                    [
+                        datetime.time(11, 11, 0),
+                        datetime.time(11, 11, 1),
+                        datetime.time(11, 11, 2),
+                    ],
+                    pa.time64("us"),
+                ),
+            },
+            {
+                "timestamp_col": "left",
+                "datetime_col": "left",
+                "date_col": "left",
+                "time_col": "left",
+            },
+            [
+                "2024-01-01 00:00:00",
+                "2027-06-05 04:03:02.001",
+                "1999-01-01",
+                "11:11:01",
+            ],
+            id="datetimes",
+        ),
+        pytest.param(
+            {
+                "array_col": pd.Series(
+                    [[1, 2, 3], [4, 5, 6], [7, 8, 9]],
+                    dtype=pd.ArrowDtype(pa.list_(pa.int64())),
+                ),
+            },
+            {
+                "array_col": "left",
+            },
+            ["[1, 2, 3]", "[4, 5, 6]", "[7, 8, 9]"],
+            id="array",
+        ),
+        pytest.param(
+            {
+                "struct_col": pd.Series(
+                    [{"v": 1}, {"v": 2}, {"v": 3}],
+                    dtype=pd.ArrowDtype(pa.struct([("v", pa.int64())])),
+                ),
+            },
+            {
+                "struct_col": "left",
+            },
+            ["{'v': 1}", "{'v': 2}", "{'v': 3}"],
+            id="struct",
+        ),
+    ],
+)
+def test_render_html_alignment_and_precision(
+    data, expected_alignments, expected_strings
+):
+    df = pd.DataFrame(data)
+    html = bf_html.render_html(dataframe=df, table_id="test-table")
+
+    for _, align in expected_alignments.items():
+        assert 'th style="text-align: left;"' in html
+        assert f'<td style="text-align: {align};' in html
+
+    for expected_string in expected_strings:
+        assert expected_string in html
+
+
+def test_render_html_precision():
+    data = {"float_col": [3.14159265]}
+    df = pd.DataFrame(data)
+
+    with bf.option_context("display.precision", 4):
+        html = bf_html.render_html(dataframe=df, table_id="test-table")
+        assert "3.1416" in html
+
+    # Make sure we reset to default
+    html = bf_html.render_html(dataframe=df, table_id="test-table")
+    assert "3.141593" in html
+
+
+def test_flatten_nested_data():
+    # Test STRUCT flattening
+    struct_data = pd.DataFrame(
+        {
+            "id": [1, 2],
+            "struct_col": pd.Series(
+                [{"name": "Alice", "age": 30}, {"name": "Bob", "age": 25}],
+                dtype=pd.ArrowDtype(
+                    pa.struct([("name", pa.string()), ("age", pa.int64())])
+                ),
+            ),
+        }
+    )
+
+    flattened, _, _ = _flatten_nested_data(struct_data)
+    assert "struct_col.name" in flattened.columns
+    assert "struct_col.age" in flattened.columns
+    assert flattened["struct_col.name"].tolist() == ["Alice", "Bob"]
+
+
+def test_array_explode():
+    # Test ARRAY explosion
+    array_data = pd.DataFrame(
+        {
+            "id": [1, 2],
+            "array_col": pd.Series(
+                [[10, 20, 30], [40, 50]], dtype=pd.ArrowDtype(pa.list_(pa.int64()))
+            ),
+        }
+    )
+
+    flattened, groups, _ = _flatten_nested_data(array_data)
+    assert len(flattened) == 6  # 3 + 2 array elements, padded to 3*2
+    assert "0" in groups  # First original row
+    assert len(groups["0"]) == 3  # Three array elements
+    assert "1" in groups
+    assert len(groups["1"]) == 3