Prevent threaded Dask workers in DistRDF backend

bindings/distrdf/python/DistRDF/Backends/Dask/Backend.py

@@ -104,6 +104,20 @@ def __init__(self, daskclient: Optional[Client] = None):
         # N is the number of cores on the local machine.
         self.client = (daskclient if daskclient is not None else
                        Client(LocalCluster(n_workers=os.cpu_count(), threads_per_worker=1, processes=True)))
+
+        workers = self.client.scheduler_info().get("workers", None)
+
+        if workers is None:
+            return
+
+        for worker in workers.values():
+            threads = worker.get("nthreads", 1)
+
+            if threads > 1:
+                raise RuntimeError(
+                    "DistRDF with Dask does not support threaded workers. "
+                    "Please use processes=True and threads_per_worker=1."
+                )
 
     def optimize_npartitions(self) -> int:
         """

roottest/python/distrdf/backends/check_backend.py

@@ -59,6 +59,27 @@ def test_optimize_npartitions(self, payload):
             backend = Backend.SparkBackend(sparkcontext=connection)
             assert backend.optimize_npartitions() == 2
 
+    def test_dask_backend_handles_missing_workers(self, payload):
+        """
+        Check that DaskBackend initialization succeeds when scheduler_info
+        does not provide worker information.
+        """
+        connection, backend = payload
+
+        if backend != "dask":
+            return
+
+        from ROOT._distrdf.Backends.Dask import Backend
+
+        original_scheduler_info = connection.scheduler_info
+
+        try:
+            connection.scheduler_info = lambda: {}
+            backend = Backend.DaskBackend(daskclient=connection)
+            assert backend.client is connection
+        finally:
+            connection.scheduler_info = original_scheduler_info
+
 
 class TestInitialization:
     """Check initialization method in the Dask backend"""