Ejemplo n.º 1
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 def __init__(self, app):
     super(HistoryContentsController, self).__init__(app)
     self.hda_manager = hdas.HDAManager(app)
     self.history_manager = histories.HistoryManager(app)
     self.folder_manager = folders.FolderManager()
     self.hda_serializer = hdas.HDASerializer(app)
     self.hda_deserializer = hdas.HDADeserializer(app)
Ejemplo n.º 2
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    def __init__(self, app, **kwargs):
        super(HistorySerializer, self).__init__(app, **kwargs)

        self.history_manager = self.manager
        self.hda_manager = hdas.HDAManager(app)
        self.hda_serializer = hdas.HDASerializer(app)
        self.history_contents_serializer = history_contents.HistoryContentsSerializer(app)

        self.default_view = 'summary'
        self.add_view('summary', [
            'id',
            'model_class',
            'name',
            'deleted',
            'purged',
            # 'count'
            'url',
            # TODO: why these?
            'published',
            'annotation',
            'tags',
        ])
        self.add_view('detailed', [
            'contents_url',
            'empty',
            'size',
            'user_id',
            'create_time',
            'update_time',
            'importable',
            'slug',
            'username_and_slug',
            'genome_build',
            # TODO: remove the next three - instead getting the same info from the 'hdas' list
            'state',
            'state_details',
            'state_ids',
            # 'community_rating',
            # 'user_rating',
        ], include_keys_from='summary')
        # in the Historys' case, each of these views includes the keys from the previous

        #: ..note: this is a custom view for newer (2016/3) UI and should be considered volatile
        self.add_view('dev-detailed', [
            'contents_url',
            'size',
            'user_id',
            'create_time',
            'update_time',
            'importable',
            'slug',
            'username_and_slug',
            'genome_build',
            # 'contents_states',
            'contents_active',
            'hid_counter',
        ], include_keys_from='summary')
Ejemplo n.º 3
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Ejemplo n.º 4
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    def __init__(self, app):
        super(DCESerializer, self).__init__(app)
        self.hda_serializer = hdas.HDASerializer(app)
        self.dc_serializer = DCSerializer(app, dce_serializer=self)

        self.default_view = 'summary'
        self.add_view('summary', [
            'id', 'model_class', 'element_index', 'element_identifier',
            'element_type', 'object'
        ])
Ejemplo n.º 5
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Ejemplo n.º 6
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 def set_up_managers(self):
     super(HDASerializerTestCase, self).set_up_managers()
     self.hda_serializer = hdas.HDASerializer(self.app)
Ejemplo n.º 7
0
    def display_structured(self, trans, id=None):
        """
        Display a history as a nested structure showing the jobs and workflow
        invocations that created each dataset (if any).
        """
        # Get history
        if id is None:
            id = trans.history.id
        else:
            id = self.decode_id(id)
        # Expunge history from the session to allow us to force a reload
        # with a bunch of eager loaded joins
        trans.sa_session.expunge(trans.history)
        history = trans.sa_session.query(model.History).options(
            joinedload('active_datasets').joinedload('creating_job_associations').joinedload('job').joinedload('workflow_invocation_step').joinedload('workflow_invocation').joinedload('workflow'),
        ).get(id)
        if not (history and ((history.user and trans.user and history.user.id == trans.user.id)
                             or (trans.history and history.id == trans.history.id)
                             or trans.user_is_admin)):
            return trans.show_error_message("Cannot display history structure.")
        # Resolve jobs and workflow invocations for the datasets in the history
        # items is filled with items (hdas, jobs, or workflows) that go at the
        # top level
        items = []
        # First go through and group hdas by job, if there is no job they get
        # added directly to items
        jobs = {}
        for hda in history.active_datasets:
            if hda.visible is False:
                continue
            # Follow "copied from ..." association until we get to the original
            # instance of the dataset
            original_hda = hda
            # while original_hda.copied_from_history_dataset_association:
            #     original_hda = original_hda.copied_from_history_dataset_association
            # Check if the job has a creating job, most should, datasets from
            # before jobs were tracked, or from the upload tool before it
            # created a job, may not
            if not original_hda.creating_job_associations:
                items.append((hda, None))
            # Attach hda to correct job
            # -- there should only be one creating_job_association, so this
            #    loop body should only be hit once
            for assoc in original_hda.creating_job_associations:
                job = assoc.job
                if job in jobs:
                    jobs[job].append((hda, None))
                else:
                    jobs[job] = [(hda, None)]
        # Second, go through the jobs and connect to workflows
        wf_invocations = {}
        for job, hdas in jobs.items():
            # Job is attached to a workflow step, follow it to the
            # workflow_invocation and group
            if job.workflow_invocation_step:
                wf_invocation = job.workflow_invocation_step.workflow_invocation
                if wf_invocation in wf_invocations:
                    wf_invocations[wf_invocation].append((job, hdas))
                else:
                    wf_invocations[wf_invocation] = [(job, hdas)]
            # Not attached to a workflow, add to items
            else:
                items.append((job, hdas))
        # Finally, add workflow invocations to items, which should now
        # contain all hdas with some level of grouping
        items.extend(wf_invocations.items())
        # Sort items by age
        items.sort(key=(lambda x: x[0].create_time), reverse=True)
        # logic taken from mako files
        from galaxy.managers import hdas
        hda_serializer = hdas.HDASerializer(trans.app)
        hda_dicts = []
        id_hda_dict_map = {}
        for hda in history.active_datasets:
            hda_dict = hda_serializer.serialize_to_view(hda, user=trans.user, trans=trans, view='detailed')
            id_hda_dict_map[hda_dict['id']] = hda_dict
            hda_dicts.append(hda_dict)

        html_template = ''
        for entity, children in items:
            html_template += render_item(trans, entity, children)
        return {
            'name': history.name,
            'history_json': hda_dicts,
            'template': html_template
        }