# HG changeset patch
# User fabio
# Date 1496174187 14400
# Node ID babc444d4bd0b6e74c355ade5f76a7c378d069b6
# Parent  39c4f4528c6e74b57317aa5f083d866517973d5f
Uploaded 20170530

diff -r 39c4f4528c6e -r babc444d4bd0 ._gdcwebapp.xml
Binary file ._gdcwebapp.xml has changed
diff -r 39c4f4528c6e -r babc444d4bd0 ._json_data_source_mod.py
Binary file ._json_data_source_mod.py has changed
diff -r 39c4f4528c6e -r babc444d4bd0 gdcwebapp.xml
--- a/gdcwebapp.xml	Tue May 30 12:26:38 2017 -0400
+++ b/gdcwebapp.xml	Tue May 30 15:56:27 2017 -0400
@@ -19,7 +19,7 @@
         <param name="URL" type="hidden" value="" />
     </inputs>
     <outputs>
-        <data name="output1" format="auto" label="${tool.name} Output Data" />
+        <data name="output1" format="auto" label="${tool.name} Output Data" hidden="True" />
         <collection name="list_output" type="list:list" label="${tool.name} Output Collection">
             <discover_datasets pattern="(?P&lt;identifier_0&gt;[^_]+)_(?P&lt;identifier_1&gt;[^_]+)" ext="auto" visible="False" directory="tmp" />
         </collection>
diff -r 39c4f4528c6e -r babc444d4bd0 json_data_source_mod.py
--- a/json_data_source_mod.py	Tue May 30 12:26:38 2017 -0400
+++ b/json_data_source_mod.py	Tue May 30 15:56:27 2017 -0400
@@ -134,15 +134,15 @@
         ext, out_data_name, \
         hda_id, dataset_id = set_up_config_values(json_params)
     extension = query_item.get( 'extension' )
-    #filename = query_item.get( 'url' )
+    url = query_item.get( 'url' )
     filename = query_item.get( 'name' )
 
     check_ext = ""
-    if ( filename.endswith( "gz" ) ):
+    if ( url.endswith( "gz" ) ):
         check_ext = "r:gz"
-    elif ( filename.endswith( "bz2" ) ):
+    elif ( url.endswith( "bz2" ) ):
         check_ext = "r:bz2"
-    elif ( filename.endswith( "tar" ) ):
+    elif ( url.endswith( "tar" ) ):
         check_ext = "r:"
     isArchive = bool( check_ext and check_ext.strip() )
 
@@ -164,14 +164,18 @@
                                                              ds_type='dataset',
                                                              primary=primary) )
     
-    download_from_query( query_item, target_output_filename )
+    if isArchive is False:
+        download_from_query( query_item, target_output_filename )
+    else:
+        target_output_path = os.path.join(appdata_path, filename)
+        download_from_query( query_item, target_output_path )
     if extra_data:
         extra_files_path = ''.join( [ target_output_filename, 'files' ] )
         download_extra_data( extra_data, extra_files_path )
 
     """ the following code handles archives and decompress them in a collection """
     if ( isArchive ):
-        walk_on_archive(target_output_filename, check_ext, query_item.get( 'name' ), appdata_path)
+        walk_on_archive(target_output_path, check_ext, filename, appdata_path)
 
     return True
 
@@ -192,7 +196,7 @@
             hda_id, dataset_id)
 
 
-def download_from_json_data( options, args, json_params=None, json_dataset_url=None ):
+def download_from_json_data( options, args ):
     """ Parse the returned JSON data and download files. Write metadata
     to flat JSON file.
     """
@@ -202,8 +206,7 @@
         os.makedirs(appdata_path)
 
     # read tool job configuration file and parse parameters we need
-    if json_params is None:
-        json_params = json.loads( open( options.json_param_file, 'r' ).read() )
+    json_params = json.loads( open( options.json_param_file, 'r' ).read() )
     
     dataset_url, output_filename, \
         extra_files_path, file_name, \
@@ -214,12 +217,10 @@
 
     # get JSON response from data source
     # TODO: make sure response is not enormous
-    if json_dataset_url is None:
-        query_params = json.loads(urllib.urlopen( dataset_url ).read())
-    else:
-        query_params = json.loads(urllib.urlopen( json_dataset_url ).read())
+    query_params = json.loads(urllib.urlopen( dataset_url ).read())
     # download and write files
-    primary = False
+    #primary = False
+    primary = True
     # query_item, hda_id, output_base_path, dataset_id
     for query_item in query_params:
         if isinstance( query_item, list ):