fix: synapse engine blocked by double negative

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "lakebench"
-version = "0.13.2"
+version = "0.13.3"
 authors = [
     { name="Miles Cole" },
 ]

src/lakebench/engines/spark.py

@@ -263,8 +263,8 @@ def get_compute_size(self) -> str:
         vm_host_count = len(set(executor.host() for executor in self.spark.sparkContext._jsc.sc().statusTracker().getExecutorInfos()))
         worker_count = vm_host_count - 1
         worker_cores = os.cpu_count()
-        as_min_workers = sc_conf_dict['spark.dynamicAllocation.initialExecutors'] if sc_conf_dict.get('spark.autoscale.executorResourceInfoTag.enabled', 'false') == 'true' else None
-        as_max_workers = sc_conf_dict['spark.dynamicAllocation.maxExecutors'] if sc_conf_dict.get('spark.autoscale.executorResourceInfoTag.enabled', 'false') == 'true' else None
+        as_min_workers = sc_conf_dict.get('spark.dynamicAllocation.initialExecutors') if sc_conf_dict.get('spark.autoscale.executorResourceInfoTag.enabled', 'false') == 'true' else None
+        as_max_workers = sc_conf_dict.get('spark.dynamicAllocation.maxExecutors') if sc_conf_dict.get('spark.autoscale.executorResourceInfoTag.enabled', 'false') == 'true' else None
         as_enabled = True if as_min_workers != as_max_workers and sc_conf_dict.get('spark.dynamicAllocation.minExecutors', None) != sc_conf_dict.get('spark.dynamicAllocation.maxExecutors', None) else False
         type = "SingleNode" if vm_host_count == 1 and not as_enabled else 'MultiNode'
         workers_word = 'Workers' if worker_count > 1 or (as_max_workers is not None and int(as_max_workers) > 1)  else 'Worker'

src/lakebench/engines/synapse_spark.py

@@ -37,7 +37,7 @@ def __init__(
             compute_stats_all_cols=False
             )        
 
-        if not self.runtime != 'synapse':
+        if self.runtime != 'synapse':
             raise RuntimeError("This engine is only supports Synapse Spark Pools.")
         self.version: str = f"{self.spark.sparkContext.version} (vhd_name=={self.spark.conf.get('spark.synapse.vhd.name')})"
         region = self.spark.conf.get('spark.cluster.region')