UNPICK revert empty df check

Author: kosiew

python/tests/test_dataframe.py

@@ -252,13 +252,6 @@ def test_filter(df):
     assert result.column(2) == pa.array([5])
 
 
-def test_show_empty(df, capsys):
-    df_empty = df.filter(column("a") > literal(3))
-    df_empty.show()
-    captured = capsys.readouterr()
-    assert "DataFrame has no rows" in captured.out
-
-
 def test_sort(df):
     df = df.sort(column("b").sort(ascending=False))
 
@@ -2664,32 +2657,3 @@ def trigger_interrupt():
 
     # Make sure the interrupt thread has finished
     interrupt_thread.join(timeout=1.0)
-
-
-def test_show_from_empty_rows(capsys):
-    """Create a DataFrame with a valid schema but zero rows and call show().
-
-    This verifies that showing an empty-but-schema'd DataFrame does not panic
-    and prints a helpful message instead.
-    """
-    # duplicate of test_show_empty; covered elsewhere
-    pass
-
-
-def test_select_where_no_rows(capsys):
-    """Create a DataFrame a:[1,2,3], filter with a>4 to produce zero rows and call show().
-
-    This verifies that a query returning zero rows does not trigger a panic and
-    instead prints a helpful message.
-    """
-    # duplicate of test_show_empty; covered elsewhere
-    pass
-
-
-def test_sql_select_where_no_rows(capsys):
-    """Register a table 't' with a:[1,2,3], run SQL that returns no rows, and call show().
-
-    Ensures SQL path that returns zero rows doesn't panic when showing results.
-    """
-    # duplicate of test_show_empty; covered elsewhere
-    pass

src/dataframe.rs

@@ -998,13 +998,10 @@ impl PyDataFrame {
 fn print_dataframe(py: Python, df: DataFrame) -> PyDataFusionResult<()> {
     // Get string representation of record batches
     let batches = wait_for_future(py, df.collect())??;
-    let result = if batches.is_empty() {
-        "DataFrame has no rows".to_string()
-    } else {
-        match pretty::pretty_format_batches(&batches) {
-            Ok(batch) => format!("DataFrame()\n{batch}"),
-            Err(err) => format!("Error: {:?}", err.to_string()),
-        }
+    let batches_as_string = pretty::pretty_format_batches(&batches);
+    let result = match batches_as_string {
+        Ok(batch) => format!("DataFrame()\n{batch}"),
+        Err(err) => format!("Error: {:?}", err.to_string()),
     };
 
     // Import the Python 'builtins' module to access the print function