diff --git a/python/tests/data/example_crispri_v2_sample.fastq.gz b/python/tests/data/example_crispri_v2_sample.fastq.gz
new file mode 100644
index 0000000..0ee084d
Binary files /dev/null and b/python/tests/data/example_crispri_v2_sample.fastq.gz differ
diff --git a/python/tests/test_session.py b/python/tests/test_session.py
index 6cd9007..cb2fd69 100644
--- a/python/tests/test_session.py
+++ b/python/tests/test_session.py
@@ -744,6 +744,17 @@ def test_bed_four():
     assert result.to_polars().shape == (10, 4)
 
 
+def test_cripri_example():
+    session = new_session()
+
+    fasta_file = DATA / "example_crispri_v2_sample.fastq.gz"
+    result = session.sql(
+        f"SELECT name, COUNT(*) FROM fastq_scan('{fasta_file}') GROUP BY name"
+    ).to_polars()
+
+    assert len(result) == 25000
+
+
 def test_sdf_file():
     session = new_session()
 
diff --git a/src/execution_result.rs b/src/execution_result.rs
index fce08f3..62445b0 100644
--- a/src/execution_result.rs
+++ b/src/execution_result.rs
@@ -55,6 +55,8 @@ impl ExecutionResult {
     }
 
     /// Returns the schema from the logical plan
+    ///
+    /// Note: This is a logical schema and may not match the physical schema
     fn schema(&self) -> PyArrowType<Schema> {
         PyArrowType(self.df.schema().into())
     }
@@ -94,7 +96,8 @@ impl ExecutionResult {
     /// Convert to Arrow Table
     fn to_arrow(&self, py: Python) -> PyResult<PyObject> {
         let batches = self.collect(py)?.to_object(py);
-        let schema = self.schema().into_py(py);
+
+        let schema = None::<PyArrowType<Schema>>.into_py(py);
 
         // Instantiate pyarrow Table object and use its from_batches method
         let table_class = py.import_bound("pyarrow")?.getattr("Table")?;
@@ -109,6 +112,8 @@ impl ExecutionResult {
         let stream = wait_for_future(py, self.df.as_ref().clone().execute_stream())
             .map_err(error::BioBearError::from)?;
 
+        let schema = stream.schema().to_pyarrow(py)?;
+
         let runtime = Arc::new(Runtime::new()?);
 
         let dataframe_record_batch_stream = DataFrameRecordBatchStream::new(stream, runtime);
@@ -120,10 +125,9 @@ impl ExecutionResult {
 
         let batches = batches.into_pyarrow(py)?;
 
-        let schema = self.schema().into_py(py);
-
         let table_class = py.import_bound("pyarrow")?.getattr("Table")?;
         let args = (batches, schema);
+
         let table: PyObject = table_class.call_method1("from_batches", args)?.into();
 
         let module = py.import_bound("polars")?;