Add more tests (#2144)

py-polars/polars/internals/frame.py

@@ -27,7 +27,7 @@
 if sys.version_info >= (3, 8):
     from typing import Literal
 else:
-    from typing_extensions import Literal
+    from typing_extensions import Literal  # pragma: no cover
 
 import numpy as np
 
@@ -221,7 +221,7 @@ def __init__(
 
         elif _PANDAS_AVAILABLE and isinstance(data, pd.DataFrame):
             if not _PYARROW_AVAILABLE:
-                raise ImportError(
+                raise ImportError(  # pragma: no cover
                     "'pyarrow' is required for converting a pandas DataFrame to a polars DataFrame."
                 )
             self._df = pandas_to_pydf(data, columns=columns)
@@ -616,7 +616,7 @@ def to_arrow(self) -> "pa.Table":
             - CategoricalType
         """
         if not _PYARROW_AVAILABLE:
-            raise ImportError(
+            raise ImportError(  # pragma: no cover
                 "'pyarrow' is required for converting a polars DataFrame to an Arrow Table."
             )
         record_batches = self._df.to_arrow()
@@ -1037,7 +1037,7 @@ def to_parquet(
 
         if use_pyarrow:
             if not _PYARROW_AVAILABLE:
-                raise ImportError(
+                raise ImportError(  # pragma: no cover
                     "'pyarrow' is required when using 'to_parquet(..., use_pyarrow=True)'."
                 )
 

py-polars/polars/utils.py

@@ -8,7 +8,7 @@
 if sys.version_info >= (3, 10):
     from typing import TypeGuard
 else:
-    from typing_extensions import TypeGuard
+    from typing_extensions import TypeGuard  # pragma: no cover
 
 
 def _process_null_values(

py-polars/tests/test_df.py

@@ -761,6 +761,12 @@ def test_concat() -> None:
     _ = pl.concat([a, a, a])
     assert a.shape == (2, 2)
 
+    with pytest.raises(ValueError):
+        _ = pl.concat([])  # type: ignore
+
+    with pytest.raises(ValueError):
+        pl.concat([df, df], how="rubbish")
+
 
 def test_arg_where() -> None:
     s = pl.Series([True, False, True, False])
@@ -1035,6 +1041,35 @@ def test_to_json(df: pl.DataFrame) -> None:
     out = pl.read_json(s)
     assert df.frame_equal(out, null_equal=True)
 
+    file = BytesIO()
+    df.to_json(file)
+    file.seek(0)
+    s = file.read().decode("utf8")
+    out = pl.read_json(s)
+    assert df.frame_equal(out, null_equal=True)
+
+
+def test_to_csv() -> None:
+    df = pl.DataFrame(
+        {
+            "foo": [1, 2, 3, 4, 5],
+            "bar": [6, 7, 8, 9, 10],
+            "ham": ["a", "b", "c", "d", "e"],
+        }
+    )
+    expected = "foo,bar,ham\n1,6,a\n2,7,b\n3,8,c\n4,9,d\n5,10,e\n"
+
+    # if no file argument is supplied, to_csv() will return the string
+    s = df.to_csv()
+    assert s == expected
+
+    # otherwise it will write to the file/iobuffer
+    file = BytesIO()
+    df.to_csv(file)
+    file.seek(0)
+    s = file.read().decode("utf8")
+    assert s == expected
+
 
 def test_from_rows() -> None:
     df = pl.from_records([[1, 2, "foo"], [2, 3, "bar"]], orient="row")
@@ -1626,3 +1661,22 @@ def test_pivot_list() -> None:
 
     out = df.groupby("a").pivot("a", "b").first()["a", "1", "2", "3"].sort("a")
     assert out.frame_equal(expected, null_equal=True)
+
+
+@pytest.mark.parametrize("as_series,inner_dtype", [(True, pl.Series), (False, list)])
+def test_to_dict(as_series: bool, inner_dtype: tp.Any) -> None:
+    df = pl.DataFrame(
+        {
+            "A": [1, 2, 3, 4, 5],
+            "fruits": ["banana", "banana", "apple", "apple", "banana"],
+            "B": [5, 4, 3, 2, 1],
+            "cars": ["beetle", "audi", "beetle", "beetle", "beetle"],
+            "optional": [28, 300, None, 2, -30],
+        }
+    )
+
+    s = df.to_dict(as_series=as_series)
+    assert isinstance(s, dict)
+    for v in s.values():
+        assert isinstance(v, inner_dtype)
+        assert len(v) == len(df)

py-polars/tests/test_series.py

@@ -1117,6 +1117,10 @@ def test_compare_series_type_mismatch() -> None:
     with pytest.raises(AssertionError, match="Series are different\n\nType mismatch"):
         testing.assert_series_equal(srs1, srs2)  # type: ignore
 
+    srs3 = pl.Series([1.0, 2.0, 3.0])
+    with pytest.raises(AssertionError, match="Series are different\n\nDtype mismatch"):
+        testing.assert_series_equal(srs1, srs3)
+
 
 def test_compare_series_name_mismatch() -> None:
     srs1 = pl.Series(values=[1, 2, 3], name="srs1")