Files
galaxy/test/api/test_tools.py
T
2014-05-15 13:43:43 -05:00

426 lines
20 KiB
Python

# Test tools API.
from base import api
from operator import itemgetter
from .helpers import DatasetPopulator
from .helpers import DatasetCollectionPopulator
from .helpers import skip_without_tool
class ToolsTestCase( api.ApiTestCase ):
def setUp( self ):
super( ToolsTestCase, self ).setUp( )
self.dataset_populator = DatasetPopulator( self.galaxy_interactor )
self.dataset_collection_populator = DatasetCollectionPopulator( self.galaxy_interactor )
def test_index( self ):
tool_ids = self.__tool_ids()
assert "upload1" in tool_ids
def test_no_panel_index( self ):
index = self._get( "tools", data=dict( in_panel="false" ) )
tools_index = index.json()
# No need to flatten out sections, with in_panel=False, only tools are
# returned.
tool_ids = map( itemgetter( "id" ), tools_index )
assert "upload1" in tool_ids
@skip_without_tool( "cat1" )
def test_show_repeat( self ):
tool_info = self._show_valid_tool( "cat1" )
parameters = tool_info[ "inputs" ]
assert len( parameters ) == 2
assert parameters[ 0 ][ "name" ] == "input1"
assert parameters[ 1 ][ "name" ] == "queries"
repeat_info = parameters[ 1 ]
self._assert_has_keys( repeat_info, "min", "max", "title", "help" )
repeat_params = repeat_info[ "inputs" ]
assert len( repeat_params ) == 1
assert repeat_params[ 0 ][ "name" ] == "input2"
@skip_without_tool( "random_lines1" )
def test_show_conditional( self ):
tool_info = self._show_valid_tool( "random_lines1" )
cond_info = tool_info[ "inputs" ][ 2 ]
self._assert_has_keys( cond_info, "cases", "test_param" )
self._assert_has_keys( cond_info[ "test_param" ], 'name', 'type', 'label', 'help' )
cases = cond_info[ "cases" ]
assert len( cases ) == 2
case1 = cases[ 0 ]
self._assert_has_keys( case1, "value", "inputs" )
assert case1[ "value" ] == "no_seed"
assert len( case1[ "inputs" ] ) == 0
case2 = cases[ 1 ]
self._assert_has_keys( case2, "value", "inputs" )
case2_inputs = case2[ "inputs" ]
assert len( case2_inputs ) == 1
self._assert_has_keys( case2_inputs[ 0 ], 'name', 'type', 'label', 'help' )
assert case2_inputs[ 0 ][ "name" ] == "seed"
def _show_valid_tool( self, tool_id ):
tool_show_response = self._get( "tools/%s" % tool_id, data=dict( io_details=True ) )
self._assert_status_code_is( tool_show_response, 200 )
tool_info = tool_show_response.json()
self._assert_has_keys( tool_info, "inputs", "outputs", "panel_section_id" )
return tool_info
def test_upload1_paste( self ):
history_id = self.dataset_populator.new_history()
payload = self.dataset_populator.upload_payload( history_id, 'Hello World' )
create_response = self._post( "tools", data=payload )
self._assert_has_keys( create_response.json(), 'outputs' )
def test_upload_posix_newline_fixes( self ):
windows_content = "1\t2\t3\r4\t5\t6\r"
posix_content = windows_content.replace("\r", "\n")
result_content = self._upload_and_get_content( windows_content )
self.assertEquals( result_content, posix_content )
def test_upload_disable_posix_fix( self ):
windows_content = "1\t2\t3\r4\t5\t6\r"
result_content = self._upload_and_get_content( windows_content, to_posix_lines=None )
self.assertEquals( result_content, windows_content )
def test_upload_tab_to_space( self ):
table = "1 2 3\n4 5 6\n"
result_content = self._upload_and_get_content( table, space_to_tab="Yes" )
self.assertEquals( result_content, "1\t2\t3\n4\t5\t6\n" )
def test_upload_tab_to_space_off_by_default( self ):
table = "1 2 3\n4 5 6\n"
result_content = self._upload_and_get_content( table )
self.assertEquals( result_content, table )
@skip_without_tool( "cat1" )
def test_run_cat1( self ):
# Run simple non-upload tool with an input data parameter.
history_id = self.dataset_populator.new_history()
new_dataset = self.dataset_populator.new_dataset( history_id, content='Cat1Test' )
inputs = dict(
input1=dataset_to_param( new_dataset ),
)
outputs = self._cat1_outputs( history_id, inputs=inputs )
self.assertEquals( len( outputs ), 1 )
self.dataset_populator.wait_for_history( history_id, assert_ok=True )
output1 = outputs[ 0 ]
output1_content = self._get_content( history_id, dataset=output1 )
self.assertEqual( output1_content.strip(), "Cat1Test" )
@skip_without_tool( "cat1" )
def test_run_cat1_with_two_inputs( self ):
# Run tool with an multiple data parameter and grouping (repeat)
history_id = self.dataset_populator.new_history()
new_dataset1 = self.dataset_populator.new_dataset( history_id, content='Cat1Test' )
new_dataset2 = self.dataset_populator.new_dataset( history_id, content='Cat2Test' )
inputs = {
'input1': dataset_to_param( new_dataset1 ),
'queries_0|input2': dataset_to_param( new_dataset2 )
}
outputs = self._cat1_outputs( history_id, inputs=inputs )
self.assertEquals( len( outputs ), 1 )
self.dataset_populator.wait_for_history( history_id, assert_ok=True )
output1 = outputs[ 0 ]
output1_content = self._get_content( history_id, dataset=output1 )
self.assertEqual( output1_content.strip(), "Cat1Test\nCat2Test" )
@skip_without_tool( "cat1" )
def test_multirun_cat1( self ):
history_id = self.dataset_populator.new_history()
new_dataset1 = self.dataset_populator.new_dataset( history_id, content='123' )
new_dataset2 = self.dataset_populator.new_dataset( history_id, content='456' )
inputs = {
"input1|__multirun__": [
dataset_to_param( new_dataset1 ),
dataset_to_param( new_dataset2 ),
],
}
outputs = self._cat1_outputs( history_id, inputs=inputs )
self.assertEquals( len( outputs ), 2 )
self.dataset_populator.wait_for_history( history_id, assert_ok=True )
output1 = outputs[ 0 ]
output2 = outputs[ 1 ]
output1_content = self._get_content( history_id, dataset=output1 )
output2_content = self._get_content( history_id, dataset=output2 )
self.assertEquals( output1_content.strip(), "123" )
self.assertEquals( output2_content.strip(), "456" )
@skip_without_tool( "cat1" )
def test_multirun_in_repeat( self ):
history_id = self.dataset_populator.new_history()
new_dataset1 = self.dataset_populator.new_dataset( history_id, content='123' )
new_dataset2 = self.dataset_populator.new_dataset( history_id, content='456' )
common_dataset = self.dataset_populator.new_dataset( history_id, content='Common' )
inputs = {
"input1": dataset_to_param( common_dataset ),
'queries_0|input2|__multirun__': [
dataset_to_param( new_dataset1 ),
dataset_to_param( new_dataset2 ),
],
}
outputs = self._cat1_outputs( history_id, inputs=inputs )
self.assertEquals( len( outputs ), 2 )
self.dataset_populator.wait_for_history( history_id, assert_ok=True, timeout=10 )
output1 = outputs[ 0 ]
output2 = outputs[ 1 ]
output1_content = self._get_content( history_id, dataset=output1 )
output2_content = self._get_content( history_id, dataset=output2 )
self.assertEquals( output1_content.strip(), "Common\n123" )
self.assertEquals( output2_content.strip(), "Common\n456" )
@skip_without_tool( "cat1" )
def test_multirun_on_multiple_inputs( self ):
history_id = self.dataset_populator.new_history()
new_dataset1 = self.dataset_populator.new_dataset( history_id, content='123' )
new_dataset2 = self.dataset_populator.new_dataset( history_id, content='456' )
new_dataset3 = self.dataset_populator.new_dataset( history_id, content='789' )
new_dataset4 = self.dataset_populator.new_dataset( history_id, content='0ab' )
inputs = {
"input1|__multirun__": [
dataset_to_param( new_dataset1 ),
dataset_to_param( new_dataset2 ),
],
'queries_0|input2|__multirun__': [
dataset_to_param( new_dataset3 ),
dataset_to_param( new_dataset4 ),
],
}
outputs = self._cat1_outputs( history_id, inputs=inputs )
self.assertEquals( len( outputs ), 4 )
self.dataset_populator.wait_for_history( history_id, assert_ok=True )
outputs_contents = [ self._get_content( history_id, dataset=o ).strip() for o in outputs ]
assert "123\n789" in outputs_contents
assert "456\n789" in outputs_contents
assert "123\n0ab" in outputs_contents
assert "456\n0ab" in outputs_contents
@skip_without_tool( "cat1" )
def test_map_over_collection( self ):
history_id = self.dataset_populator.new_history()
hdca_id = self.__build_pair( history_id, [ "123", "456" ] )
inputs = {
# Such inputs can be simple hdca ids (for GUI) or
# {src: "hdca", id: <hdca_id>} for API. This tests the
# first, next test method tests other.
"input1|__collection_multirun__": hdca_id,
}
create = self._run_cat1( history_id, inputs=inputs, assert_ok=True )
outputs = create[ 'outputs' ]
jobs = create[ 'jobs' ]
implicit_collections = create[ 'implicit_collections' ]
self.assertEquals( len( jobs ), 2 )
self.assertEquals( len( outputs ), 2 )
self.assertEquals( len( implicit_collections ), 1 )
self.dataset_populator.wait_for_history( history_id, assert_ok=True )
output1 = outputs[ 0 ]
output2 = outputs[ 1 ]
output1_content = self._get_content( history_id, dataset=output1 )
output2_content = self._get_content( history_id, dataset=output2 )
self.assertEquals( output1_content.strip(), "123" )
self.assertEquals( output2_content.strip(), "456" )
@skip_without_tool( "cat1" )
def test_map_over_nested_collections( self ):
history_id = self.dataset_populator.new_history()
hdca_id = self.__build_nested_list( history_id )
inputs = {
"input1|__collection_multirun__": dict( src="hdca", id=hdca_id ),
}
create = self._run_cat1( history_id, inputs=inputs, assert_ok=True )
outputs = create[ 'outputs' ]
jobs = create[ 'jobs' ]
implicit_collections = create[ 'implicit_collections' ]
self.assertEquals( len( jobs ), 4 )
self.assertEquals( len( outputs ), 4 )
self.assertEquals( len( implicit_collections ), 1 )
implicit_collection = implicit_collections[ 0 ]
self._assert_has_keys( implicit_collection, "collection_type", "elements" )
assert implicit_collection[ "collection_type" ] == "list:paired"
assert len( implicit_collection[ "elements" ] ) == 2
first_element, second_element = implicit_collection[ "elements" ]
assert first_element[ "element_identifier" ] == "test0"
assert second_element[ "element_identifier" ] == "test1"
first_object = first_element[ "object" ]
assert first_object[ "collection_type" ] == "paired"
assert len( first_object[ "elements" ] ) == 2
first_object_forward_element = first_object[ "elements" ][ 0 ]
self.assertEquals( outputs[ 0 ][ "id" ], first_object_forward_element[ "object" ][ "id" ] )
@skip_without_tool( "cat1" )
def test_map_over_two_collections( self ):
history_id = self.dataset_populator.new_history()
hdca1_id = self.__build_pair( history_id, [ "123", "456" ] )
hdca2_id = self.__build_pair( history_id, [ "789", "0ab" ] )
inputs = {
"input1|__collection_multirun__": hdca1_id,
"queries_0|input2|__collection_multirun__": hdca2_id,
}
outputs = self._cat1_outputs( history_id, inputs=inputs )
self.assertEquals( len( outputs ), 2 )
self.dataset_populator.wait_for_history( history_id, assert_ok=True )
output1 = outputs[ 0 ]
output2 = outputs[ 1 ]
output1_content = self._get_content( history_id, dataset=output1 )
output2_content = self._get_content( history_id, dataset=output2 )
self.assertEquals( output1_content.strip(), "123\n789" )
self.assertEquals( output2_content.strip(), "456\n0ab" )
@skip_without_tool( "cat1" )
def test_cannot_map_over_incompatible_collections( self ):
history_id = self.dataset_populator.new_history()
hdca1_id = self.__build_pair( history_id, [ "123", "456" ] )
hdca2_id = self.dataset_collection_populator.create_list_in_history( history_id ).json()[ "id" ]
inputs = {
"input1|__collection_multirun__": hdca1_id,
"queries_0|input2|__collection_multirun__": hdca2_id,
}
run_response = self._run_cat1( history_id, inputs )
# TODO: Fix this error checking once switch over to new API decorator
# on server.
assert run_response.status_code >= 400
@skip_without_tool( "multi_data_param" )
def test_reduce_collections( self ):
history_id = self.dataset_populator.new_history()
hdca1_id = self.__build_pair( history_id, [ "123", "456" ] )
hdca2_id = self.dataset_collection_populator.create_list_in_history( history_id ).json()[ "id" ]
inputs = {
"f1": "__collection_reduce__|%s" % hdca1_id,
"f2": "__collection_reduce__|%s" % hdca2_id,
}
create = self._run( "multi_data_param", history_id, inputs, assert_ok=True )
outputs = create[ 'outputs' ]
jobs = create[ 'jobs' ]
assert len( jobs ) == 1
assert len( outputs ) == 2
self.dataset_populator.wait_for_history( history_id, assert_ok=True )
output1 = outputs[ 0 ]
output2 = outputs[ 1 ]
output1_content = self._get_content( history_id, dataset=output1 )
output2_content = self._get_content( history_id, dataset=output2 )
assert output1_content.strip() == "123\n456"
assert len( output2_content.strip().split("\n") ) == 3, output2_content
@skip_without_tool( "collection_paired_test" )
def test_subcollection_mapping( self ):
history_id = self.dataset_populator.new_history()
hdca_list_id = self.__build_nested_list( history_id )
inputs = {
"f1|__collection_multirun__": "%s|paired" % hdca_list_id
}
# Following wait not really needed - just getting so many database
# locked errors with sqlite.
self.dataset_populator.wait_for_history( history_id, assert_ok=True )
outputs = self._run_and_get_outputs( "collection_paired_test", history_id, inputs )
assert len( outputs ), 2
self.dataset_populator.wait_for_history( history_id, assert_ok=True )
output1 = outputs[ 0 ]
output2 = outputs[ 1 ]
output1_content = self._get_content( history_id, dataset=output1 )
output2_content = self._get_content( history_id, dataset=output2 )
assert output1_content.strip() == "123\n456", output1_content
assert output2_content.strip() == "789\n0ab", output2_content
@skip_without_tool( "collection_mixed_param" )
def test_combined_mapping_and_subcollection_mapping( self ):
history_id = self.dataset_populator.new_history()
nested_list_id = self.__build_nested_list( history_id )
create_response = self.dataset_collection_populator.create_list_in_history( history_id, contents=["xxx", "yyy"] )
list_id = create_response.json()[ "id" ]
inputs = {
"f1|__collection_multirun__": "%s|paired" % nested_list_id,
"f2|__collection_multirun__": list_id,
}
self.dataset_populator.wait_for_history( history_id, assert_ok=True )
outputs = self._run_and_get_outputs( "collection_mixed_param", history_id, inputs )
assert len( outputs ), 2
self.dataset_populator.wait_for_history( history_id, assert_ok=True )
output1 = outputs[ 0 ]
output2 = outputs[ 1 ]
output1_content = self._get_content( history_id, dataset=output1 )
output2_content = self._get_content( history_id, dataset=output2 )
assert output1_content.strip() == "123\n456\nxxx", output1_content
assert output2_content.strip() == "789\n0ab\nyyy", output2_content
def _cat1_outputs( self, history_id, inputs ):
return self._run_outputs( self._run_cat1( history_id, inputs ) )
def _run_and_get_outputs( self, tool_id, history_id, inputs ):
return self._run_outputs( self._run( tool_id, history_id, inputs ) )
def _run_outputs( self, create_response ):
self._assert_status_code_is( create_response, 200 )
return create_response.json()[ 'outputs' ]
def _run_cat1( self, history_id, inputs, assert_ok=False ):
return self._run( 'cat1', history_id, inputs, assert_ok=assert_ok )
def _run( self, tool_id, history_id, inputs, assert_ok=False ):
payload = self.dataset_populator.run_tool_payload(
tool_id=tool_id,
inputs=inputs,
history_id=history_id,
)
create_response = self._post( "tools", data=payload )
if assert_ok:
self._assert_status_code_is( create_response, 200 )
create = create_response.json()
self._assert_has_keys( create, 'outputs' )
return create
else:
return create_response
def _upload_and_get_content( self, content, **upload_kwds ):
history_id = self.dataset_populator.new_history()
new_dataset = self.dataset_populator.new_dataset( history_id, content=content, **upload_kwds )
self.dataset_populator.wait_for_history( history_id, assert_ok=True )
return self._get_content( history_id, dataset=new_dataset )
def _get_content( self, history_id, **kwds ):
if "dataset_id" in kwds:
dataset_id = kwds[ "dataset_id" ]
else:
dataset_id = kwds[ "dataset" ][ "id" ]
display_response = self._get( "histories/%s/contents/%s/display" % ( history_id, dataset_id ) )
self._assert_status_code_is( display_response, 200 )
return display_response.content
def __tool_ids( self ):
index = self._get( "tools" )
tools_index = index.json()
# In panels by default, so flatten out sections...
tools = []
for tool_or_section in tools_index:
if "elems" in tool_or_section:
tools.extend( tool_or_section[ "elems" ] )
else:
tools.append( tool_or_section )
tool_ids = map( itemgetter( "id" ), tools )
return tool_ids
def __build_nested_list( self, history_id ):
hdca1_id = self.__build_pair( history_id, [ "123", "456" ] )
hdca2_id = self.__build_pair( history_id, [ "789", "0ab" ] )
response = self.dataset_collection_populator.create_list_from_pairs( history_id, [ hdca1_id, hdca2_id ] )
self._assert_status_code_is( response, 200 )
hdca_list_id = response.json()[ "id" ]
return hdca_list_id
def __build_pair( self, history_id, contents ):
create_response = self.dataset_collection_populator.create_pair_in_history( history_id, contents=contents )
hdca_id = create_response.json()[ "id" ]
return hdca_id
def dataset_to_param( dataset ):
return dict(
src='hda',
id=dataset[ 'id' ]
)