diff --git a/crates/polars-arrow/src/io/avro/read/deserialize.rs b/crates/polars-arrow/src/io/avro/read/deserialize.rs index dc4c04ed15ea..7c626f2b74ee 100644 --- a/crates/polars-arrow/src/io/avro/read/deserialize.rs +++ b/crates/polars-arrow/src/io/avro/read/deserialize.rs @@ -56,8 +56,7 @@ fn make_mutable( .iter() .map(|field| make_mutable(field.dtype(), None, capacity)) .collect::>>()?; - Box::new(DynMutableStructArray::new(values, dtype.clone())) - as Box + Box::new(DynMutableStructArray::new(values, dtype.clone())) as Box }, other => { polars_bail!(nyi = "Deserializing type {other:#?} is still not implemented") diff --git a/crates/polars-core/src/serde/series.rs b/crates/polars-core/src/serde/series.rs index 3b2415d4d5c2..0fb9d9f05f18 100644 --- a/crates/polars-core/src/serde/series.rs +++ b/crates/polars-core/src/serde/series.rs @@ -290,7 +290,11 @@ impl<'de> Deserialize<'de> for Series { for (f, v) in fields.iter().zip(values.iter()) { if f.dtype() != v.dtype() { - let err = format!("type mismatch for struct. expected: {}, given: {}", f.dtype(), v.dtype()); + let err = format!( + "type mismatch for struct. expected: {}, given: {}", + f.dtype(), + v.dtype() + ); return Err(de::Error::custom(err)); } } diff --git a/crates/polars-expr/src/expressions/window.rs b/crates/polars-expr/src/expressions/window.rs index 46b20c9a34b3..d03467d01da9 100644 --- a/crates/polars-expr/src/expressions/window.rs +++ b/crates/polars-expr/src/expressions/window.rs @@ -588,8 +588,11 @@ impl PhysicalExpr for WindowExpr { .1, ) } else { - let df_right = unsafe { DataFrame::new_no_checks_height_from_first(keys) }; - let df_left = unsafe { DataFrame::new_no_checks_height_from_first(group_by_columns) }; + let df_right = + unsafe { DataFrame::new_no_checks_height_from_first(keys) }; + let df_left = unsafe { + DataFrame::new_no_checks_height_from_first(group_by_columns) + }; Ok(private_left_join_multiple_keys(&df_left, &df_right, true)?.1) } }; diff --git a/crates/polars-ops/src/series/ops/to_dummies.rs b/crates/polars-ops/src/series/ops/to_dummies.rs index ab5015f97864..dfe3ba1a3ddf 100644 --- a/crates/polars-ops/src/series/ops/to_dummies.rs +++ b/crates/polars-ops/src/series/ops/to_dummies.rs @@ -46,11 +46,7 @@ impl ToDummies for Series { }) .collect::>(); - Ok(unsafe { - DataFrame::new_no_checks_height_from_first( - sort_columns(columns), - ) - }) + Ok(unsafe { DataFrame::new_no_checks_height_from_first(sort_columns(columns)) }) } } diff --git a/crates/polars-pipe/src/executors/sources/csv.rs b/crates/polars-pipe/src/executors/sources/csv.rs index cdb80970e253..38484f9c7255 100644 --- a/crates/polars-pipe/src/executors/sources/csv.rs +++ b/crates/polars-pipe/src/executors/sources/csv.rs @@ -218,7 +218,7 @@ impl Source for CsvSource { for data_chunk in &mut out { // The batched reader creates the column containing all nulls because the schema it // gets passed contains the column. - // + // // SAFETY: Columns are only replaced with columns // 1. of the same name, and // 2. of the same length. diff --git a/crates/polars-plan/src/plans/functions/merge_sorted.rs b/crates/polars-plan/src/plans/functions/merge_sorted.rs index de170583e2d9..6397a8374933 100644 --- a/crates/polars-plan/src/plans/functions/merge_sorted.rs +++ b/crates/polars-plan/src/plans/functions/merge_sorted.rs @@ -31,10 +31,8 @@ pub(super) fn merge_sorted(df: &DataFrame, column: &str) -> PolarsResult RecordBatchT> { Field::new("item2".into(), ArrowDataType::Int32, true), ]); - RecordBatchT::new(2, vec![ - Box::new(StructArray::new( - struct_dt.clone(), - 2, - vec![ - Box::new(PrimitiveArray::::from_slice([1, 2])), - Box::new(PrimitiveArray::::from([None, Some(1)])), - ], - None, - )), - Box::new(StructArray::new( - struct_dt, - 2, - vec![ - Box::new(PrimitiveArray::::from_slice([1, 2])), - Box::new(PrimitiveArray::::from([None, Some(1)])), - ], - Some([true, false].into()), - )), - ]) + RecordBatchT::new( + 2, + vec![ + Box::new(StructArray::new( + struct_dt.clone(), + 2, + vec![ + Box::new(PrimitiveArray::::from_slice([1, 2])), + Box::new(PrimitiveArray::::from([None, Some(1)])), + ], + None, + )), + Box::new(StructArray::new( + struct_dt, + 2, + vec![ + Box::new(PrimitiveArray::::from_slice([1, 2])), + Box::new(PrimitiveArray::::from([None, Some(1)])), + ], + Some([true, false].into()), + )), + ], + ) } fn avro_record() -> Record { diff --git a/crates/polars/tests/it/io/parquet/arrow/mod.rs b/crates/polars/tests/it/io/parquet/arrow/mod.rs index 5d259b595d9e..0a573eb4a186 100644 --- a/crates/polars/tests/it/io/parquet/arrow/mod.rs +++ b/crates/polars/tests/it/io/parquet/arrow/mod.rs @@ -1421,20 +1421,23 @@ fn generic_data() -> PolarsResult<(ArrowSchema, RecordBatchT>)> { Field::new("a12".into(), array12.dtype().clone(), true), Field::new("a13".into(), array13.dtype().clone(), true), ]); - let chunk = RecordBatchT::try_new(array1.len(), vec![ - array1.boxed(), - array2.boxed(), - array3.boxed(), - array4.boxed(), - array6.boxed(), - array7.boxed(), - array8.boxed(), - array9.boxed(), - array10.boxed(), - array11.boxed(), - array12.boxed(), - array13.boxed(), - ])?; + let chunk = RecordBatchT::try_new( + array1.len(), + vec![ + array1.boxed(), + array2.boxed(), + array3.boxed(), + array4.boxed(), + array6.boxed(), + array7.boxed(), + array8.boxed(), + array9.boxed(), + array10.boxed(), + array11.boxed(), + array12.boxed(), + array13.boxed(), + ], + )?; Ok((schema, chunk)) } diff --git a/py-polars/tests/unit/dataframe/test_null_count.py b/py-polars/tests/unit/dataframe/test_null_count.py index a9b1141a2a67..507bf0269517 100644 --- a/py-polars/tests/unit/dataframe/test_null_count.py +++ b/py-polars/tests/unit/dataframe/test_null_count.py @@ -23,9 +23,6 @@ def test_null_count(df: pl.DataFrame) -> None: # note: the zero-row and zero-col cases are always passed as explicit examples null_count, ncols = df.null_count(), len(df.columns) - if ncols == 0: - assert null_count.shape == (0, 0) - else: - assert null_count.shape == (1, ncols) - for idx, count in enumerate(null_count.rows()[0]): - assert count == sum(v is None for v in df.to_series(idx).to_list()) + assert null_count.shape == (1, ncols) + for idx, count in enumerate(null_count.rows()[0]): + assert count == sum(v is None for v in df.to_series(idx).to_list())