PBS Upload Tool w/ set_metadata_externally = True fixes

scripts/set_metadata.py

@@ -25,6 +25,7 @@ import galaxy.model.mapping #need to load this before we unpickle, in order to s
 galaxy.model.Job() #this looks REAL stupid, but it is REQUIRED in order for SA to insert parameters into the classes defined by the mappers --> it appears that instantiating ANY mapper'ed class would suffice here
 galaxy.datatypes.metadata.DATABASE_CONNECTION_AVAILABLE = False #Let metadata know that there is no database connection, and to just assume object ids are valid
 from galaxy.util import stringify_dictionary_keys
+from galaxy.util.json import from_json_string
 from sqlalchemy.orm import clear_mappers
 
 def __main__():
@@ -37,13 +38,25 @@ def __main__():
     config_root = sys.argv.pop( 1 )
     datatypes_config = sys.argv.pop( 1 )
     galaxy.model.set_datatypes_registry( galaxy.datatypes.registry.Registry( config_root, datatypes_config ) )
-    
+
+    job_metadata = sys.argv.pop( 1 )
+    ext_override = dict()
+    if job_metadata != "None" and os.path.exists( job_metadata ):
+        for line in open( job_metadata, 'r' ):
+            try:
+                line = stringify_dictionary_keys( from_json_string( line ) )
+                assert line['type'] == 'dataset'
+                ext_override[line['dataset_id']] = line['ext']
+            except:
+                continue
     for filenames in sys.argv[1:]:
         filename_in, filename_kwds, filename_out, filename_results_code, dataset_filename_override = filenames.split( ',' )
         try:
             dataset = cPickle.load( open( filename_in ) ) #load DatasetInstance
             if dataset_filename_override:
                 dataset.dataset.external_filename = dataset_filename_override
+            if ext_override.get( dataset.dataset.id, None ):
+                dataset.extension = ext_override[ dataset.dataset.id ]
             kwds = stringify_dictionary_keys( simplejson.load( open( filename_kwds ) ) )#load kwds; need to ensure our keywords are not unicode
             dataset.datatype.set_meta( dataset, **kwds )
             dataset.metadata.to_JSON_dict( filename_out ) # write out results of set_meta