details: http://www.bx.psu.edu/hg/galaxy/rev/f7dee0438854 changeset: 3173:f7dee0438854 user: Dan Blankenberg dan@bx.psu.edu date: Fri Dec 11 11:11:15 2009 -0500 description: Modify the way that data_source tools and tool_types are handled.
Data source tools are now of the DataSourceTool class. A lot of cleanup here is possible in the existing datasource tool code, see comments.
diffstat:
lib/galaxy/jobs/__init__.py | 6 +- lib/galaxy/tools/__init__.py | 150 +++++++++++++++++++++---------------- 2 files changed, 87 insertions(+), 69 deletions(-)
diffs (243 lines):
diff -r ab7877640903 -r f7dee0438854 lib/galaxy/jobs/__init__.py --- a/lib/galaxy/jobs/__init__.py Thu Dec 10 15:37:00 2009 -0500 +++ b/lib/galaxy/jobs/__init__.py Fri Dec 11 11:11:15 2009 -0500 @@ -377,8 +377,7 @@ param_dict = self.tool.build_param_dict( incoming, inp_data, out_data, self.get_output_fnames(), self.working_directory ) # Certain tools require tasks to be completed prior to job execution # ( this used to be performed in the "exec_before_job" hook, but hooks are deprecated ). - if self.tool.tool_type is not None: - out_data = self.tool.exec_before_job( self.queue.app, inp_data, out_data, param_dict ) + self.tool.exec_before_job( self.queue.app, inp_data, out_data, param_dict ) # Run the before queue ("exec_before_job") hook self.tool.call_hook( 'exec_before_job', self.queue.app, inp_data=inp_data, out_data=out_data, tool=self.tool, param_dict=incoming) @@ -600,8 +599,7 @@ param_dict.update({'__collected_datasets__':collected_datasets}) # Certain tools require tasks to be completed after job execution # ( this used to be performed in the "exec_after_process" hook, but hooks are deprecated ). - if self.tool.tool_type is not None: - self.tool.exec_after_process( self.queue.app, inp_data, out_data, param_dict, job = job ) + self.tool.exec_after_process( self.queue.app, inp_data, out_data, param_dict, job = job ) # Call 'exec_after_process' hook self.tool.call_hook( 'exec_after_process', self.queue.app, inp_data=inp_data, out_data=out_data, param_dict=param_dict, diff -r ab7877640903 -r f7dee0438854 lib/galaxy/tools/__init__.py --- a/lib/galaxy/tools/__init__.py Thu Dec 10 15:37:00 2009 -0500 +++ b/lib/galaxy/tools/__init__.py Fri Dec 11 11:11:15 2009 -0500 @@ -134,6 +134,8 @@ cls = type_elem.get( 'class' ) mod = __import__( module, globals(), locals(), [cls]) ToolClass = getattr( mod, cls ) + elif root.get( 'tool_type', None ) is not None: + ToolClass = tool_types.get( root.get( 'tool_type' ) ) else: ToolClass = Tool return ToolClass( config_file, root, self.app ) @@ -263,6 +265,7 @@ """ Represents a computational tool that can be executed through Galaxy. """ + tool_type = 'default' def __init__( self, config_file, root, app ): """ Load a tool from the config named by `config_file` @@ -296,8 +299,6 @@ self.version = "1.0.0" # Support multi-byte tools self.is_multi_byte = util.string_as_bool( root.get( "is_multi_byte", False ) ) - # Type of tool - self.tool_type = root.get( "tool_type", None ) #Force history to fully refresh after job execution for this tool. Useful i.e. when an indeterminate number of outputs are created by a tool. self.force_history_refresh = util.string_as_bool( root.get( 'force_history_refresh', 'False' ) ) #load input translator, used by datasource tools to change names/values of incoming parameters @@ -696,7 +697,7 @@ rval = dict() for key, param in self.inputs_by_page[page].iteritems(): if not isinstance( param, ToolParameter ): - raise Exception( "'get_param_html_map' only supported for simple paramters" ) + raise Exception( "'get_param_html_map' only supported for simple paramters" ) rval[key] = param.get_html( trans, other_values=other_values ) return rval
@@ -1236,8 +1237,8 @@ param_dict[ "_CHILD___%s___%s" % ( name, child.designation ) ] = DatasetFilenameWrapper( child ) for out_name, output in self.outputs.iteritems(): if out_name not in param_dict and output.filters: - #assume the reason we lack this output is because a filter failed to pass; for tool writing convienence, provide a NoneDataset - param_dict[ out_name ] = NoneDataset( datatypes_registry = self.app.datatypes_registry, ext = output.format ) + #assume the reason we lack this output is because a filter failed to pass; for tool writing convienence, provide a NoneDataset + param_dict[ out_name ] = NoneDataset( datatypes_registry = self.app.datatypes_registry, ext = output.format ) # We add access to app here, this allows access to app.config, etc param_dict['__app__'] = RawObjectWrapper( self.app ) # More convienent access to app.config.new_file_path; we don't need to wrap a string @@ -1345,9 +1346,9 @@ redirect_url += "&%s=%s" % ( p_name, rup_dict[ p_name ] ) # Add the current user email to redirect_url if data.history.user: - USERNAME = str( data.history.user.email ) + USERNAME = str( data.history.user.email ) else: - USERNAME = 'Anonymous' + USERNAME = 'Anonymous' redirect_url += "&USERNAME=%s" % USERNAME return redirect_url
@@ -1365,65 +1366,10 @@ raise
def exec_before_job( self, app, inp_data, out_data, param_dict={} ): - if self.tool_type == 'data_source': - dbkey = param_dict.get( 'dbkey' ) - organism = param_dict.get( 'organism' ) - table = param_dict.get( 'table' ) - description = param_dict.get( 'description' ) - info = param_dict.get( 'info' ) - if description == 'range': - description = param_dict.get( 'position', '' ) - if not description: - description = 'unknown position' - gb_landmark_region = param_dict.get( 'q' ) - data_type = param_dict.get( 'data_type' ) - items = out_data.items() - for name, data in items: - if organism and table and description: - # This is UCSC - data.name = '%s on %s: %s (%s)' % ( data.name, organism, table, description ) - elif gb_landmark_region: - # This is GBrowse - data.name = '%s on %s' % ( data.name, gb_landmark_region ) - data.info = info - data.dbkey = dbkey - if data_type not in app.datatypes_registry.datatypes_by_extension: - # Setting data_type to tabular will force the data to be sniffed in exec_after_process() - data_type = 'tabular' - data = app.datatypes_registry.change_datatype( data, data_type ) - # Store external data source's request parameters temporarily in output file. - # In case the config setting for "outputs_to_working_directory" is True, we must write to - # the DatasetFilenameWrapper object in the param_dict since it's "false_path" attribute - # is the temporary path to the output dataset ( until the job is run ). However, - # even if the "outputs_to_working_directory" setting is False, we can still open the file - # the same way for temporarily storing the request parameters. - out = open( str( param_dict.get( name ) ), 'w' ) - for key, value in param_dict.items(): - print >> out, '%s\t%s' % ( key, value ) - out.close() - out_data[ name ] = data - return out_data + pass
def exec_after_process( self, app, inp_data, out_data, param_dict, job = None ): - if self.tool_type == 'data_source': - name, data = out_data.items()[0] - data.set_size() - if data.state == data.states.OK: - data.name = param_dict.get( 'name', data.name ) - data.info = param_dict.get( 'info', data.name ) - data.dbkey = param_dict.get( 'dbkey', data.dbkey ) - data.extension = param_dict.get( 'data_type', data.extension ) - if data.extension in [ 'txt', 'tabular' ]: - data_type = sniff.guess_ext( data.file_name, sniff_order=app.datatypes_registry.sniff_order ) - if data.extension != data_type: - data = app.datatypes_registry.change_datatype( data, data_type ) - elif not isinstance( data.datatype, datatypes.interval.Bed ) and isinstance( data.datatype, datatypes.interval.Interval ): - data.set_meta() - if data.missing_meta(): - data = app.datatypes_registry.change_datatype( data, 'tabular' ) - data.set_peek() - self.sa_session.add( data ) - self.sa_session.flush() + pass
def collect_associated_files( self, output, job_working_directory ): for name, hda in output.items(): @@ -1559,7 +1505,77 @@ self.sa_session.flush() return primary_datasets
+class DataSourceTool( Tool ): + tool_type = 'data_source' + def exec_before_job( self, app, inp_data, out_data, param_dict={} ): + #TODO: Allow for a generic way for all Tools to have output dataset properties be set to input parameter values + #as defined in a tool XML + dbkey = param_dict.get( 'dbkey' ) + organism = param_dict.get( 'organism' ) + table = param_dict.get( 'table' ) + description = param_dict.get( 'description' ) + info = param_dict.get( 'info' ) + if description == 'range': + description = param_dict.get( 'position', '' ) + if not description: + description = 'unknown position' + gb_landmark_region = param_dict.get( 'q' ) + data_type = param_dict.get( 'data_type' ) + items = out_data.items() + for name, data in items: + if organism and table and description: + # This is UCSC + data.name = '%s on %s: %s (%s)' % ( data.name, organism, table, description ) + elif gb_landmark_region: + # This is GBrowse + data.name = '%s on %s' % ( data.name, gb_landmark_region ) + data.info = info + data.dbkey = dbkey + if data_type not in app.datatypes_registry.datatypes_by_extension: + # Setting data_type to tabular will force the data to be sniffed in exec_after_process() + data_type = 'tabular' + data.change_datatype( data_type ) + # Store external data source's request parameters temporarily in output file. + # In case the config setting for "outputs_to_working_directory" is True, we must write to + # the DatasetFilenameWrapper object in the param_dict since it's "false_path" attribute + # is the temporary path to the output dataset ( until the job is run ). However, + # even if the "outputs_to_working_directory" setting is False, we can still open the file + # the same way for temporarily storing the request parameters. + + ## TODO: Input parameters should be jsonified and written into a <configfile> and passed to data_source.py, + ## instead of writing tab separated key, value pairs to the output file + out = open( str( param_dict.get( name ) ), 'w' ) + for key, value in param_dict.items(): + print >> out, '%s\t%s' % ( key, value ) + out.close() + + def exec_after_process( self, app, inp_data, out_data, param_dict, job = None ): + log.debug('after proc called') + name, data = out_data.items()[0] + data.set_size() + #TODO: these should be already be set before the tool runs: + if data.state == data.states.OK: + data.name = param_dict.get( 'name', data.name ) + data.info = param_dict.get( 'info', data.name ) + data.dbkey = param_dict.get( 'dbkey', data.dbkey ) + data.extension = param_dict.get( 'data_type', data.extension ) + #TODO: these should be possible as part of data_source.py and external set_meta, see the upload tool: + if data.extension in [ 'txt', 'tabular' ]: + data_type = sniff.guess_ext( data.file_name, sniff_order=app.datatypes_registry.sniff_order ) + if data.extension != data_type: + data.change_datatype( data_type ) + elif not isinstance( data.datatype, datatypes.interval.Bed ) and isinstance( data.datatype, datatypes.interval.Interval ): + if data.missing_meta(): + data.change_datatype( 'tabular' ) + data.set_peek() + self.sa_session.add( data ) + self.sa_session.flush() + +class DataDestinationTool( Tool ): + tool_type = 'data_destination' + class SetMetadataTool( Tool ): + tool_type = 'set_metadata' def exec_after_process( self, app, inp_data, out_data, param_dict, job = None ): for name, dataset in inp_data.iteritems(): external_metadata = galaxy.datatypes.metadata.JobExternalOutputMetadataWrapper( job ) @@ -1572,7 +1588,11 @@ self.sa_session.add( dataset ) self.sa_session.flush()
- +#load tool_type to ToolClass mappings +tool_types = {} +for tool_class in [ Tool, DataDestinationTool, SetMetadataTool, DataSourceTool ]: + tool_types[ tool_class.tool_type ] = tool_class + # ---- Utility classes to be factored out -----------------------------------
class BadValue( object ):