From db137a86928b4ca1927f28611d30ed22bace51fe Mon Sep 17 00:00:00 2001
From: Stijn de Gooijer <stijndegooijer@gmail.com>
Date: Mon, 21 Oct 2024 21:42:59 +0200
Subject: [PATCH] Clean up debug statements

---
 crates/polars-python/src/cloud.rs | 14 +++-----------
 1 file changed, 3 insertions(+), 11 deletions(-)

diff --git a/crates/polars-python/src/cloud.rs b/crates/polars-python/src/cloud.rs
index 31653e19d5f6..39410a6fa7a1 100644
--- a/crates/polars-python/src/cloud.rs
+++ b/crates/polars-python/src/cloud.rs
@@ -21,22 +21,18 @@ pub fn prepare_cloud_plan(lf: PyLazyFrame, py: Python) -> PyResult<PyObject> {
     Ok(PyBytes::new_bound(py, &bytes).to_object(py))
 }
 
-/// Update a serialized `IRPlan` for use with the GPU engine.
+/// Take a serialized `IRPlan` and execute it on the GPU engine.
 ///
 /// This is done as a Python function because the `NodeTraverser` class created for this purpose
 /// must exactly match the one expected by the `cudf_polars` package.
 #[pyfunction]
 pub fn _execute_ir_plan_with_gpu(ir_plan_ser: Vec<u8>, py: Python) -> PyResult<PyDataFrame> {
-    eprintln!("Update function called");
-
     // Deserialize into IRPlan.
     let reader = Cursor::new(ir_plan_ser);
     let mut ir_plan = ciborium::from_reader::<IRPlan, _>(reader)
         .map_err(to_compute_err)
         .map_err(PyPolarsErr::from)?;
 
-    eprintln!("Deserialized");
-
     // Edit for use with GPU engine.
     gpu_post_opt(
         py,
@@ -46,21 +42,17 @@ pub fn _execute_ir_plan_with_gpu(ir_plan_ser: Vec<u8>, py: Python) -> PyResult<P
     )
     .map_err(PyPolarsErr::from)?;
 
-    eprintln!("Updated");
-
+    // Convert to physical plan.
     let mut physical_plan =
         create_physical_plan(ir_plan.lp_top, &mut ir_plan.lp_arena, &ir_plan.expr_arena)
             .map_err(PyPolarsErr::from)?;
 
-    eprintln!("Physical plan created");
-
+    // Execute the plan.
     let mut state = ExecutionState::new();
     let df = physical_plan
         .execute(&mut state)
         .map_err(PyPolarsErr::from)?;
 
-    eprintln!("Executed");
-
     Ok(df.into())
 }