Move slow tests to slow and fix test error when pyarrow is missing

Author: evertlammerts

tests/fast/pandas/test_import_cache.py

@@ -1,10 +1,20 @@
+import importlib.util
+
 import pandas as pd
 import pytest
 
 import duckdb
 
 
-@pytest.mark.parametrize("string_dtype", ["python", "pyarrow"])
+@pytest.mark.parametrize(
+    "string_dtype",
+    [
+        "python",
+        pytest.param(
+            "pyarrow", marks=pytest.mark.skipif(not importlib.util.find_spec("pyarrow"), reason="pyarrow not installed")
+        ),
+    ],
+)
 def test_import_cache_explicit_dtype(string_dtype):
     df = pd.DataFrame(  # noqa: F841
         {

tests/fast/test_relation.py

@@ -2,7 +2,6 @@
 import datetime
 import gc
 import os
-import platform
 import tempfile
 
 import numpy as np
@@ -534,15 +533,6 @@ def test_relation_print(self):
             1024,
             2048,
             5000,
-            1000000,
-            pytest.param(
-                10000000,
-                marks=pytest.mark.skipif(
-                    condition=platform.system() == "Emscripten",
-                    reason="Emscripten/Pyodide builds run out of memory at this scale, and error might not "
-                    "thrown reliably",
-                ),
-            ),
         ],
     )
     def test_materialized_relation(self, duckdb_cursor, num_rows):

tests/slow/test_materialized_relation.py

@@ -0,0 +1,52 @@
+import platform
+
+import pytest
+
+
+class TestMaterializedRelationSlow:
+    @pytest.mark.parametrize(
+        "num_rows",
+        [
+            1000000,
+            pytest.param(
+                10000000,
+                marks=pytest.mark.skipif(
+                    condition=platform.system() == "Emscripten",
+                    reason="Emscripten/Pyodide builds run out of memory at this scale, and error might not "
+                    "thrown reliably",
+                ),
+            ),
+        ],
+    )
+    def test_materialized_relation(self, duckdb_cursor, num_rows):
+        # Anything that is not a SELECT statement becomes a materialized relation, so we use `CALL`
+        query = f"call repeat_row(42, 'test', 'this is a long string', true, num_rows={num_rows})"
+        rel = duckdb_cursor.sql(query)
+        res = rel.fetchone()
+        assert res is not None
+
+        res = rel.fetchmany(num_rows)
+        assert len(res) == num_rows - 1
+
+        res = rel.fetchmany(5)
+        assert len(res) == 0
+        res = rel.fetchmany(5)
+        assert len(res) == 0
+        res = rel.fetchone()
+        assert res is None
+
+        rel.execute()
+        res = rel.fetchone()
+        assert res is not None
+
+        res = rel.fetchall()
+        assert len(res) == num_rows - 1
+        res = rel.fetchall()
+        assert len(res) == num_rows
+
+        rel = duckdb_cursor.sql(query)
+        projection = rel.select("column0")
+        assert projection.fetchall() == [(42,) for _ in range(num_rows)]
+
+        filtered = rel.filter("column1 != 'test'")
+        assert filtered.fetchall() == []