fix: enable usage of job grouping in GLS

docs/snakefiles/rules.rst

@@ -1461,6 +1461,8 @@ However, if we would add ``group: "mygroup"`` to rule ``c``, all jobs would end
 Alternatively, groups can be defined via the command line interface.
 This enables to almost arbitrarily partition the DAG, e.g. in order to safe network traffic, see :ref:`here <job_grouping>`.
 
+For execution on the cloud using Google Life Science API and preemptible instances, we expect all rules in the group to be homogenously set as preemptible instances (e.g., with command-line option ``--preemptible-rules``), such that a preemptible VM is requested for the execution of the group job.
+
 Piped output
 ------------
 

snakemake/executors/google_lifesciences.py

@@ -511,12 +511,23 @@ def _generate_job_resources(self, job):
             "Selected machine type {}:{}".format(smallest, selected["description"])
         )
 
+        if job.is_group():
+            preemptible = all(rule in self.preemptible_rules for rule in job.rules)
+            if not preemptible and any(
+                rule in self.preemptible_rules for rule in job.rules
+            ):
+                raise WorkflowError(
+                    "All grouped rules should be homogenously set as preemptible rules"
+                    "(see Defining groups for execution in snakemake documentation)"
+                )
+        else:
+            preemptible = job.rule.name in self.preemptible_rules
         # We add the size for the image itself (10 GB) to bootDiskSizeGb
         virtual_machine = {
             "machineType": smallest,
             "labels": {"app": "snakemake"},
             "bootDiskSizeGb": disk_gb + 10,
-            "preemptible": job.rule.name in self.preemptible_rules,
+            "preemptible": preemptible,
         }
 
         # If the user wants gpus, add accelerators here