refactor: rename MultiColumnWindowUDF -> PythonFunctionWindowUDF

The "multi-column" name was a relic of an earlier upstream limitation
where `SimpleWindowUDF` only accepted a single input column. With the
struct now also storing the Python evaluator factory directly for
pickle support, the relevant distinction is no longer column count
but "Python-defined". Rename to match `PythonFunctionScalarUDF` and
`PythonFunctionAggregateUDF` for a consistent naming convention
across all three Python UDF kinds.

Also tighten visibility from `pub` to `pub(crate)`. No external
consumer; the struct only needs to be reachable from `PyWindowUDF`
and the codec.

No functional change.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

Author: timsaucer

crates/core/src/codec.rs

@@ -97,7 +97,7 @@ use pyo3::types::{PyBytes, PyTuple};
 
 use crate::udaf::PythonFunctionAggregateUDF;
 use crate::udf::PythonFunctionScalarUDF;
-use crate::udwf::MultiColumnWindowUDF;
+use crate::udwf::PythonFunctionWindowUDF;
 
 /// Wire-format prefix that tags a `fun_definition` payload as an
 /// inlined Python scalar UDF (cloudpickled tuple of name, callable,
@@ -518,7 +518,11 @@ fn schema_from_ipc_bytes(bytes: &[u8]) -> arrow::error::Result<Schema> {
 // =============================================================================
 
 pub(crate) fn try_encode_python_window_udf(node: &WindowUDF, buf: &mut Vec<u8>) -> Result<bool> {
-    let Some(py_udf) = node.inner().as_any().downcast_ref::<MultiColumnWindowUDF>() else {
+    let Some(py_udf) = node
+        .inner()
+        .as_any()
+        .downcast_ref::<PythonFunctionWindowUDF>()
+    else {
         return Ok(false);
     };
 
@@ -544,15 +548,15 @@ pub(crate) fn try_decode_python_window_udf(buf: &[u8]) -> Result<Option<Arc<Wind
     })
 }
 
-fn encode_python_window_udf(py: Python<'_>, udf: &MultiColumnWindowUDF) -> PyResult<Vec<u8>> {
+fn encode_python_window_udf(py: Python<'_>, udf: &PythonFunctionWindowUDF) -> PyResult<Vec<u8>> {
     let cloudpickle = py.import("cloudpickle")?;
 
     let signature = WindowUDFImpl::signature(udf);
     let input_dtypes: Vec<arrow::datatypes::DataType> = match &signature.type_signature {
         TypeSignature::Exact(types) => types.clone(),
         other => {
             return Err(pyo3::exceptions::PyValueError::new_err(format!(
-                "MultiColumnWindowUDF expected Signature::Exact, got {other:?}"
+                "PythonFunctionWindowUDF expected Signature::Exact, got {other:?}"
             )));
         }
     };
@@ -586,7 +590,7 @@ fn encode_python_window_udf(py: Python<'_>, udf: &MultiColumnWindowUDF) -> PyRes
     blob.extract::<Vec<u8>>()
 }
 
-fn decode_python_window_udf(py: Python<'_>, payload: &[u8]) -> PyResult<MultiColumnWindowUDF> {
+fn decode_python_window_udf(py: Python<'_>, payload: &[u8]) -> PyResult<PythonFunctionWindowUDF> {
     let cloudpickle = py.import("cloudpickle")?;
 
     let tuple = cloudpickle
@@ -614,7 +618,7 @@ fn decode_python_window_udf(py: Python<'_>, payload: &[u8]) -> PyResult<MultiCol
         .first()
         .ok_or_else(|| {
             pyo3::exceptions::PyValueError::new_err(
-                "MultiColumnWindowUDF return schema must contain exactly one field",
+                "PythonFunctionWindowUDF return schema must contain exactly one field",
             )
         })?
         .data_type()
@@ -623,7 +627,7 @@ fn decode_python_window_udf(py: Python<'_>, payload: &[u8]) -> PyResult<MultiCol
     let volatility = datafusion_python_util::parse_volatility(&volatility_str)
         .map_err(|e| pyo3::exceptions::PyValueError::new_err(format!("{e}")))?;
 
-    Ok(MultiColumnWindowUDF::from_parts(
+    Ok(PythonFunctionWindowUDF::from_parts(
         name,
         evaluator,
         input_types,

crates/core/src/udwf.rs

@@ -233,7 +233,7 @@ impl PyWindowUDF {
         let return_type = return_type.0;
         let input_types: Vec<DataType> = input_types.into_iter().map(|t| t.0).collect();
 
-        let function = WindowUDF::from(MultiColumnWindowUDF::new(
+        let function = WindowUDF::from(PythonFunctionWindowUDF::new(
             name,
             evaluator,
             input_types,
@@ -276,15 +276,15 @@ impl PyWindowUDF {
 }
 
 #[derive(Debug)]
-pub struct MultiColumnWindowUDF {
+pub(crate) struct PythonFunctionWindowUDF {
     name: String,
     evaluator: Py<PyAny>,
     signature: Signature,
     return_type: DataType,
 }
 
-impl MultiColumnWindowUDF {
-    pub fn new(
+impl PythonFunctionWindowUDF {
+    pub(crate) fn new(
         name: impl Into<String>,
         evaluator: Py<PyAny>,
         input_types: Vec<DataType>,
@@ -323,8 +323,8 @@ impl MultiColumnWindowUDF {
     }
 }
 
-impl Eq for MultiColumnWindowUDF {}
-impl PartialEq for MultiColumnWindowUDF {
+impl Eq for PythonFunctionWindowUDF {}
+impl PartialEq for PythonFunctionWindowUDF {
     fn eq(&self, other: &Self) -> bool {
         self.name == other.name
             && self.signature == other.signature
@@ -338,7 +338,7 @@ impl PartialEq for MultiColumnWindowUDF {
     }
 }
 
-impl std::hash::Hash for MultiColumnWindowUDF {
+impl std::hash::Hash for PythonFunctionWindowUDF {
     fn hash<H: std::hash::Hasher>(&self, state: &mut H) {
         self.name.hash(state);
         self.signature.hash(state);
@@ -350,7 +350,7 @@ impl std::hash::Hash for MultiColumnWindowUDF {
     }
 }
 
-impl WindowUDFImpl for MultiColumnWindowUDF {
+impl WindowUDFImpl for PythonFunctionWindowUDF {
     fn as_any(&self) -> &dyn Any {
         self
     }