test: improve tests for row

tests/helpers/__init__.py

@@ -1,5 +1,6 @@
 from ._assertions import (
     assert_cell_operation_works,
+    assert_row_operation_works,
     assert_tables_equal,
     assert_that_tabular_datasets_are_equal,
 )
@@ -38,6 +39,7 @@
 
 __all__ = [
     "assert_cell_operation_works",
+    "assert_row_operation_works",
     "assert_tables_equal",
     "assert_that_tabular_datasets_are_equal",
     "configure_test_with_device",

tests/helpers/_assertions.py

@@ -80,3 +80,25 @@ def assert_cell_operation_works(
     column = Column("A", [input_value])
     transformed_column = column.transform(transformer)
     assert transformed_column == Column("A", [expected_value]), f"Expected: {expected_value}\nGot: {transformed_column}"
+
+
+def assert_row_operation_works(
+    input_value: Any,
+    transformer: Callable[[Table], Table],
+    expected_value: Any,
+) -> None:
+    """
+    Assert that a row operation works as expected.
+
+    Parameters
+    ----------
+    input_value:
+        The value in the input row.
+    transformer:
+        The transformer to apply to the rows.
+    expected_value:
+        The expected value of the transformed row.
+    """
+    table = Table(input_value)
+    transformed_table = transformer(table)
+    assert transformed_table == Table(expected_value), f"Expected: {expected_value}\nGot: {transformed_table}"

tests/safeds/data/tabular/containers/_row/test_column_count.py

@@ -0,0 +1,19 @@
+import pytest
+from safeds.data.tabular.containers import Row, Table
+from safeds.data.tabular.containers._lazy_vectorized_row import _LazyVectorizedRow
+
+
+@pytest.mark.parametrize(
+    ("table", "expected"),
+    [
+        (Table(), 0),
+        (Table({"A": [1, 2, 3]}), 1),
+    ],
+    ids=[
+        "empty",
+        "non-empty",
+    ],
+)
+def test_should_return_the_number_of_columns(table: Table, expected: int) -> None:
+    row: Row[any] = _LazyVectorizedRow(table=table)
+    assert row.column_count == expected

tests/safeds/data/tabular/containers/_row/test_column_names.py

@@ -0,0 +1,24 @@
+import pytest
+from safeds.data.tabular.containers import Row, Table
+from safeds.data.tabular.containers._lazy_vectorized_row import _LazyVectorizedRow
+
+
+@pytest.mark.parametrize(
+    ("table", "expected"),
+    [
+        (Table({}), []),
+        (Table({"A": [1, 2, 3]}), ["A"]),
+        (
+            Table({"A": [1, 2, 3], "B": ["A", "A", "Bla"], "C": [True, True, False], "D": [1.0, 2.1, 4.5]}),
+            ["A", "B", "C", "D"],
+        ),
+    ],
+    ids=[
+        "empty",
+        "one-column",
+        "four-column",
+    ],
+)
+def test_should_return_the_column_names(table: Table, expected: list[str]) -> None:
+    row: Row[any] = _LazyVectorizedRow(table=table)
+    assert row.column_names == expected

tests/safeds/data/tabular/containers/_row/test_contains.py

@@ -0,0 +1,23 @@
+import pytest
+from safeds.data.tabular.containers import Row, Table
+from safeds.data.tabular.containers._lazy_vectorized_row import _LazyVectorizedRow
+
+
+@pytest.mark.parametrize(
+    ("table", "column_name", "expected"),
+    [
+        (Table({}), "A", False),
+        (Table({"A": [1, 2, 3]}), "A", True),
+        (Table({"A": [1, 2, 3], "B": ["A", "A", "Bla"]}), "C", False),
+        (Table({"col1": [1, 2, 3], "B": ["A", "A", "Bla"]}), 1, False),
+    ],
+    ids=[
+        "empty row",
+        "column exists",
+        "column does not exist",
+        "not a string",
+    ],
+)
+def test_should_return_whether_the_row_has_the_column(table: Table, column_name: str, expected: bool) -> None:
+    row: Row[any] = _LazyVectorizedRow(table=table)
+    assert (column_name in row) == expected

tests/safeds/data/tabular/containers/_row/test_eq.py

@@ -0,0 +1,58 @@
+import pytest
+from safeds.data.tabular.containers import Row, Table
+from safeds.data.tabular.containers._lazy_vectorized_row import _LazyVectorizedRow
+
+
+@pytest.mark.parametrize(
+    ("table1", "table2", "expected"),
+    [
+        (Table({"col1": []}), Table({"col1": []}), True),
+        (Table({"col1": [1, 2]}), Table({"col1": [1, 2]}), True),
+        (Table({"col1": [1, 2]}), Table({"col1": [2, 3]}), False),
+        (Table({"col1": [1, 2]}), Table({"col2": [1, 2]}), False),
+        (Table({"col1": ["1", "2"]}), Table({"col1": [1, 2]}), False),
+    ],
+    ids=[
+        "empty rows",
+        "equal rows",
+        "different values",
+        "different columns",
+        "different types",
+    ],
+)
+def test_should_return_whether_two_rows_are_equal(table1: Table, table2: Table, expected: bool) -> None:
+    row1: Row[any] = _LazyVectorizedRow(table=table1)
+    row2: Row[any] = _LazyVectorizedRow(table=table2)
+    assert (row1.__eq__(row2)) == expected
+
+
+@pytest.mark.parametrize(
+    ("table", "expected"),
+    [
+        (Table({"col1": []}), True),
+        (Table({"col1": [1, 2]}), True),
+    ],
+    ids=[
+        "empty table",
+        "filled table",
+    ],
+)
+def test_should_return_true_if_rows_are_strict_equal(table: Table, expected: bool) -> None:
+    row1: Row[any] = _LazyVectorizedRow(table=table)
+    assert (row1.__eq__(row1)) == expected
+
+
+@pytest.mark.parametrize(
+    ("table1", "table2"),
+    [
+        (Table({"col1": []}), Table({"col1": []})),
+        (Table({"col1": [1, 2]}), Table({"col1": [1, 2]})),
+    ],
+    ids=[
+        "empty tables",
+        "filled tables",
+    ],
+)
+def test_should_return_false_if_object_is_other_type(table1: Table, table2: Table) -> None:
+    row1: Row[any] = _LazyVectorizedRow(table=table1)
+    assert (row1.__eq__(table2)) == NotImplemented

tests/safeds/data/tabular/containers/_row/test_get_column_type.py

@@ -0,0 +1,20 @@
+import pytest
+from safeds.data.tabular.containers import Row, Table
+from safeds.data.tabular.containers._lazy_vectorized_row import _LazyVectorizedRow
+from safeds.data.tabular.typing import DataType
+
+
+@pytest.mark.parametrize(
+    ("table", "column_name", "expected"),
+    [
+        (Table({"col1": ["A"]}), "col1", "String"),
+        (Table({"col1": ["a"], "col2": [1]}), "col2", "Int64"),
+    ],
+    ids=[
+        "one column",
+        "two columns",
+    ],
+)
+def test_should_return_the_type_of_the_column(table: Table, column_name: str, expected: DataType) -> None:
+    row: Row[any] = _LazyVectorizedRow(table=table)
+    assert str(row.get_column_type(column_name)) == expected

tests/safeds/data/tabular/containers/_row/test_get_value.py

@@ -0,0 +1,46 @@
+import re
+
+import pytest
+from safeds.data.tabular.containers import Row, Table
+from safeds.data.tabular.containers._lazy_vectorized_row import _LazyVectorizedRow
+from safeds.exceptions import ColumnNotFoundError
+
+from tests.helpers import assert_row_operation_works
+
+
+@pytest.mark.parametrize(
+    ("table_data", "column_name", "target", "expected"),
+    [
+        ({"A": [1, 2]}, "A", 1, {"A": [2]}),
+        ({"A": [1, 2, 3], "B": [4, 5, 2]}, "B", 2, {"A": [1, 2], "B": [4, 5]}),
+    ],
+    ids=[
+        "one column",
+        "two columns",
+    ],
+)
+def test_should_get_correct_item(table_data: dict, column_name: str, target: int, expected: dict) -> None:
+    assert_row_operation_works(
+        table_data,
+        lambda table: table.remove_rows(lambda row: row.get_value(column_name).eq(target)),
+        expected,
+    )
+
+
+@pytest.mark.parametrize(
+    ("table", "column_name"),
+    [
+        (Table(), "A"),
+        (Table({"A": ["a", "aa", "aaa"]}), "B"),
+        (Table({"A": ["b", "aa", "aaa"], "C": ["b", "aa", "aaa"]}), "B"),
+    ],
+    ids=[
+        "empty table",
+        "table with one column",
+        "table with two columns",
+    ],
+)
+def test_should_raise_column_not_found_error(table: Table, column_name: str) -> None:
+    row: Row[any] = _LazyVectorizedRow(table=table)
+    with pytest.raises(ColumnNotFoundError, match=re.escape(f"Could not find column(s):\n    - '{column_name}'")):
+        row.get_value(column_name)

tests/safeds/data/tabular/containers/_row/test_getitem.py

@@ -0,0 +1,46 @@
+import re
+
+import pytest
+from safeds.data.tabular.containers import Row, Table
+from safeds.data.tabular.containers._lazy_vectorized_row import _LazyVectorizedRow
+from safeds.exceptions import ColumnNotFoundError
+
+from tests.helpers import assert_row_operation_works
+
+
+@pytest.mark.parametrize(
+    ("table_data", "column_name", "target", "expected"),
+    [
+        ({"A": [1, 2]}, "A", 1, {"A": [2]}),
+        ({"A": [1, 2, 3], "B": [4, 5, 2]}, "B", 2, {"A": [1, 2], "B": [4, 5]}),
+    ],
+    ids=[
+        "table one column",
+        "table two columns",
+    ],
+)
+def test_should_get_correct_item(table_data: dict, column_name: str, target: int, expected: dict) -> None:
+    assert_row_operation_works(
+        table_data,
+        lambda table: table.remove_rows(lambda row: row[column_name].eq(target)),
+        expected,
+    )
+
+
+@pytest.mark.parametrize(
+    ("table", "column_name"),
+    [
+        (Table(), "A"),
+        (Table({"A": ["a", "aa", "aaa"]}), "B"),
+        (Table({"A": ["b", "aa", "aaa"], "C": ["b", "aa", "aaa"]}), "B"),
+    ],
+    ids=[
+        "empty table",
+        "table with one column",
+        "table with two columns",
+    ],
+)
+def test_should_raise_column_not_found_error(table: Table, column_name: str) -> None:
+    row: Row[any] = _LazyVectorizedRow(table=table)
+    with pytest.raises(ColumnNotFoundError, match=re.escape(f"Could not find column(s):\n    - '{column_name}'")):
+        row[column_name]

tests/safeds/data/tabular/containers/_row/test_has_column.py

@@ -0,0 +1,21 @@
+import pytest
+from safeds.data.tabular.containers import Row, Table
+from safeds.data.tabular.containers._lazy_vectorized_row import _LazyVectorizedRow
+
+
+@pytest.mark.parametrize(
+    ("table", "column_name", "expected"),
+    [
+        (Table(), "A", False),
+        (Table({"A": ["a", "aa", "aaa"]}), "A", True),
+        (Table({"A": ["a", "aa", "aaa"]}), "B", False),
+    ],
+    ids=[
+        "empty table",
+        "table with existing column_name",
+        "table with non existing column_name",
+    ],
+)
+def test_should_have_column_name(table: Table, column_name: str, expected: bool) -> None:
+    row: Row[any] = _LazyVectorizedRow(table=table)
+    assert row.has_column(column_name) == expected

tests/safeds/data/tabular/containers/_row/test_hash.py

@@ -0,0 +1,24 @@
+import pytest
+from safeds.data.tabular.containers import Row, Table
+from safeds.data.tabular.containers._lazy_vectorized_row import _LazyVectorizedRow
+
+
+@pytest.mark.parametrize(
+    ("table1", "table2", "expected"),
+    [
+        (Table(), Table({"A": ["a", "aa", "aaa"]}), False),
+        (Table(), Table(), True),
+        (Table({"A": ["a", "aa", "aaa"]}), Table({"A": ["a", "aa", "aaa"]}), True),
+        (Table({"A": ["a", "aa", "aaa"]}), Table({"B": ["a", "aa", "aaa"]}), False),
+    ],
+    ids=[
+        "empty and different table",
+        "same empty tables",
+        "same tables",
+        "different tables",
+    ],
+)
+def test_should_return_consistent_hashes(table1: Table, table2: Table, expected: bool) -> None:
+    row1: Row[any] = _LazyVectorizedRow(table=table1)
+    row2: Row[any] = _LazyVectorizedRow(table=table2)
+    assert (hash(row1) == hash(row2)) == expected

tests/safeds/data/tabular/containers/_row/test_iter.py

@@ -0,0 +1,22 @@
+import pytest
+from safeds.data.tabular.containers import Row, Table
+from safeds.data.tabular.containers._lazy_vectorized_row import _LazyVectorizedRow
+
+
+@pytest.mark.parametrize(
+    ("table", "expected"),
+    [
+        (Table(), []),
+        (Table({"A": ["a", "aa", "aaa"]}), ["A"]),
+        (Table({"A": ["a", "aa", "aaa"], "B": ["b", "bb", "bbb"], "C": ["c", "cc", "ccc"]}), ["A", "B", "C"]),
+    ],
+    ids=[
+        "empty",
+        "one column",
+        "three columns",
+    ],
+)
+def test_should_return_same_list_of_column_name_with_iter(table: Table, expected: list) -> None:
+    row: Row[any] = _LazyVectorizedRow(table=table)
+    iterable = iter(row)
+    assert list(iterable) == expected

tests/safeds/data/tabular/containers/_row/test_len.py

@@ -0,0 +1,21 @@
+import pytest
+from safeds.data.tabular.containers import Row, Table
+from safeds.data.tabular.containers._lazy_vectorized_row import _LazyVectorizedRow
+
+
+@pytest.mark.parametrize(
+    ("table", "expected"),
+    [
+        (Table(), 0),
+        (Table({"A": ["a", "aa", "aaa"]}), 1),
+        (Table({"A": ["a", "aa", "aaa"], "B": ["b", "bb", "bbb"]}), 2),
+    ],
+    ids=[
+        "empty",
+        "one column",
+        "two columns",
+    ],
+)
+def test_should_have_same_length_as_number_of_columns(table: Table, expected: int) -> None:
+    row: Row[any] = _LazyVectorizedRow(table=table)
+    assert len(row) == expected

tests/safeds/data/tabular/containers/_row/test_schema.py

@@ -0,0 +1,21 @@
+import pytest
+from safeds.data.tabular.containers import Row, Table
+from safeds.data.tabular.containers._lazy_vectorized_row import _LazyVectorizedRow
+
+
+@pytest.mark.parametrize(
+    ("table"),
+    [
+        (Table()),
+        (Table({"A": ["a", "aa", "aaa"]})),
+        (Table({"A": ["a", "aa", "aaa"], "B": ["b", "bb", "bbb"]})),
+    ],
+    ids=[
+        "empty",
+        "one column",
+        "two columns",
+    ],
+)
+def test_should_return_same_schema(table: Table) -> None:
+    row: Row[any] = _LazyVectorizedRow(table=table)
+    assert table.schema == row.schema