pybis.py

                fetchopts
            ]
        }
        resp = self._post_request(self.as_v3, request)
        if len(resp) == 0:
            raise ValueError("No group found!")

        for permid in resp:
            group = resp[permid]
            parse_jackson(group)

            if only_data:
                return group
            else:
                return Group(self, data=group)
        


    def get_groups(self, **search_args):
        """ Get openBIS AuthorizationGroups. Returns a «Things» object.

        Usage::
            groups = e.get.groups()
            groups[0]             # select first group
            groups['GROUP_NAME']  # select group with this code
            for group in groups:
                ...               # a Group object
            groups.df             # get a DataFrame object of the group list
            print(groups)         # print a nice ASCII table (eg. in IPython)
            groups                # HTML table (in a Jupyter notebook)

        """

        criteria = []
        for search_arg in ['code', 'description', 'registrator']:
            if search_arg in search_args:
                pass
                #sub_crit = get_search_type_for_entity(search_arg)
                #criteria.append(sub_crit)

        search_criteria = get_search_type_for_entity('authorizationGroup')
        search_criteria['criteria'] = criteria
                
        fetchopts = fetch_option['authorizationGroup']
        for option in ['roleAssignments', 'registrator', 'users']:
            fetchopts[option] = fetch_option[option]
        request = {
            "method": "searchAuthorizationGroups",
            "params": [
                self.token,
                search_criteria,
                fetchopts
            ],
        }
        resp = self._post_request(self.as_v3, request)
        if len(resp['objects']) == 0:
            raise ValueError("No groups found!")

        objects = resp['objects']
        parse_jackson(objects)

        groups = DataFrame(resp['objects'])

        groups['permId'] = groups['permId'].map(extract_permid)
        groups['registrator'] = groups['registrator'].map(extract_person)
        groups['users'] = groups['users'].map(extract_users)
        groups['registrationDate'] = groups['registrationDate'].map(format_timestamp)
        groups['modificationDate'] = groups['modificationDate'].map(format_timestamp)
        p = Things(
            self, entity='group', 
            df=groups[['permId', 'code', 'description', 'users', 'registrator', 'registrationDate', 'modificationDate']],
            identifier_name='permId'
        )
        return p


    def get_persons(self, **search_args):
        """ Get openBIS users
        """

        search_criteria = get_search_criteria('person', **search_args)
        fetchopts = {}
        for option in ['space']:
            fetchopts[option] = fetch_option[option]
        request = {
            "method": "searchPersons",
            "params": [
                self.token,
                search_criteria,
                fetchopts
            ],
        }
        resp = self._post_request(self.as_v3, request)
        if len(resp['objects']) == 0:
            raise ValueError("No persons found!")

        objects = resp['objects']
        parse_jackson(objects)

        persons = DataFrame(resp['objects'])
        persons['permId'] = persons['permId'].map(extract_permid)
        persons['registrationDate'] = persons['registrationDate'].map(format_timestamp)
        persons['space'] = persons['space'].map(extract_nested_permid)
        p = Things(
            self, entity='person', 
            df=persons[['permId', 'userId', 'firstName', 'lastName', 'email', 'space', 'registrationDate', 'active']],
            identifier_name='permId'
        )
        return p

    def get_person(self, userId, only_data=False):
        """ Get a person (user)
        """
         
        ids = [{
            "@type": "as.dto.person.id.PersonPermId",
            "permId": userId
        }]

        fetchopts = {}
        for option in ['space', 'roleAssignments', 'project']:
            fetchopts[option] = fetch_option[option]

        request = {
            "method": "getPersons",
            "params": [
                self.token,
                ids,
                fetchopts,
            ],
        }
        
        resp = self._post_request(self.as_v3, request)
        if len(resp) == 0:
            raise ValueError("No person found!")


        #persons['roleAssignments'] = persons['roleAssignments'].map(extract_role_assignments)
        for permid in resp:
            person = resp[permid]
            parse_jackson(person)

            if only_data:
                return person
            else:
                return Person(self, data=person)


    def get_spaces(self, code=None):
        """ Get a list of all available spaces (DataFrame object). To create a sample or a
        dataset, you need to specify in which space it should live.
        """

        search_criteria = _subcriteria_for_code(code, 'space')
        fetchopts = {}
        request = {
            "method": "searchSpaces",
            "params": [self.token,
                       search_criteria,
                       fetchopts,
                       ],
        }
        resp = self._post_request(self.as_v3, request)
        if resp is not None:
            spaces = DataFrame(resp['objects'])
            spaces['registrationDate'] = spaces['registrationDate'].map(format_timestamp)
            spaces['modificationDate'] = spaces['modificationDate'].map(format_timestamp)
            sp = Things(
                self,
                'space',
                spaces[['code', 'description', 'registrationDate', 'modificationDate']]
            )
            return sp
        else:
            raise ValueError("No spaces found!")

    def get_space(self, code, only_data=False):
        """ Returns a Space object for a given identifier.
        """

        code = str(code).upper()
        fetchopts = {"@type": "as.dto.space.fetchoptions.SpaceFetchOptions"}
        for option in ['registrator']:
            fetchopts[option] = fetch_option[option]

        request = {
            "method": "getSpaces",
            "params": [
                self.token,
                [{
                    "permId": code,
                    "@type": "as.dto.space.id.SpacePermId"
                }],
                fetchopts
            ],
        }
        resp = self._post_request(self.as_v3, request)
        if len(resp) == 0:
            raise ValueError("No such space: %s" % code)

        for permid in resp:
            if only_data:
                return resp[permid]
            else:
                return Space(self, data=resp[permid])

    def get_samples(self, code=None, permId=None, space=None, project=None, experiment=None, type=None,
                    withParents=None, withChildren=None, tags=None, props=None, **properties):
        """ Get a list of all samples for a given space/project/experiment (or any combination)
        """

        sub_criteria = []
        if space:
            sub_criteria.append(_gen_search_criteria({
                "space": "Space",
                "operator": "AND",
                "code": space
            })
            )
        if project:
            exp_crit = _subcriteria_for_code(experiment, 'experiment')
            proj_crit = _subcriteria_for_code(project, 'project')
            exp_crit['criteria'] = []
            exp_crit['criteria'].append(proj_crit)
            sub_criteria.append(exp_crit)
        if experiment:
            sub_criteria.append(_subcriteria_for_code(experiment, 'experiment'))
        if properties is not None:
            for prop in properties:
                sub_criteria.append(_subcriteria_for_properties(prop, properties[prop]))
        if type:
            sub_criteria.append(_subcriteria_for_code(type, 'sample_type'))
        if tags:
            sub_criteria.append(_subcriteria_for_tags(tags))
        if code:
            sub_criteria.append(_criteria_for_code(code))
        if permId:
            sub_criteria.append(_common_search("as.dto.common.search.PermIdSearchCriteria", permId))
        if withParents:
            if not isinstance(withParents, list):
                withParents = [withParents]
            for parent in withParents:
                sub_criteria.append(
                    _gen_search_criteria({
                        "sample": "SampleParents",
                        "identifier": parent
                    })
                )
        if withChildren:
            if not isinstance(withChildren, list):
                withChildren = [withChildren]
            for child in withChildren:
                sub_criteria.append(
                    _gen_search_criteria({
                        "sample": "SampleChildren",
                        "identifier": child
                    })
                )

        criteria = {
            "criteria": sub_criteria,
            "@type": "as.dto.sample.search.SampleSearchCriteria",
            "operator": "AND"
        }

        # build the various fetch options
        fetchopts = fetch_option['sample']

        for option in ['tags', 'properties', 'registrator', 'modifier', 'experiment']:
            fetchopts[option] = fetch_option[option]

        request = {
            "method": "searchSamples",
            "params": [self.token,
                       criteria,
                       fetchopts,
                       ],
        }
        resp = self._post_request(self.as_v3, request)
        if len(resp['objects']) == 0:
            raise ValueError("no samples found!")

        objects = resp['objects']
        parse_jackson(objects)

        samples = DataFrame(objects)
        samples['registrationDate'] = samples['registrationDate'].map(format_timestamp)
        samples['modificationDate'] = samples['modificationDate'].map(format_timestamp)
        samples['registrator'] = samples['registrator'].map(extract_person)
        samples['modifier'] = samples['modifier'].map(extract_person)
        samples['identifier'] = samples['identifier'].map(extract_identifier)
        samples['permId'] = samples['permId'].map(extract_permid)
        samples['experiment'] = samples['experiment'].map(extract_nested_identifier)
        samples['sample_type'] = samples['type'].map(extract_nested_permid)

        attrs = ['identifier', 'permId', 'experiment', 'sample_type',
                 'registrator', 'registrationDate', 'modifier', 'modificationDate']

        if props is not None:
            for prop in props:
                samples[prop.upper()] = samples['properties'].map(lambda x: x.get(prop.upper(), ''))
                attrs.append(prop.upper())

        ss = samples[attrs]
        return Things(self, 'sample', ss, 'identifier')

    get_objects = get_samples # Alias

    def get_experiments(self, code=None, type=None, space=None, project=None, tags=None, is_finished=None, props=None, **properties):
        """ Searches for all experiment which match the search criteria. Returns a
        «Things» object which can be used in many different situations.

        Usage::
            experiments = get_experiments(project='PROJECT_NAME', props=['NAME','FINISHED_FLAG'])
            experiments[0]  # returns first experiment
            experiments['/MATERIALS/REAGENTS/ANTIBODY_COLLECTION']
            for experiment in experiment:
                # handle every experiment
                ...
            experiments.df      # returns DataFrame object of the experiment list
            print(experiments)  # prints a nice ASCII table
        """

        sub_criteria = []
        if space:
            sub_criteria.append(_subcriteria_for_code(space, 'space'))
        if project:
            sub_criteria.append(_subcriteria_for_code(project, 'project'))
        if code:
            sub_criteria.append(_criteria_for_code(code))
        if type:
            sub_criteria.append(_subcriteria_for_type(type, 'Experiment'))
        if tags:
            sub_criteria.append(_subcriteria_for_tags(tags))
        if is_finished is not None:
            sub_criteria.append(_subcriteria_for_is_finished(is_finished))
        if properties is not None:
            for prop in properties:
                sub_criteria.append(_subcriteria_for_properties(prop, properties[prop]))

        search_criteria = get_search_type_for_entity('experiment')
        search_criteria['criteria'] = sub_criteria
        search_criteria['operator'] = 'AND'

        fetchopts = fetch_option['experiment']
        for option in ['tags', 'properties', 'registrator', 'modifier', 'project']:
            fetchopts[option] = fetch_option[option]

        request = {
            "method": "searchExperiments",
            "params": [
                self.token,
                search_criteria,
                fetchopts,
            ],
        }
        resp = self._post_request(self.as_v3, request)
        if len(resp['objects']) == 0:
            raise ValueError("No experiments found!")

        objects = resp['objects']
        parse_jackson(objects)

        experiments = DataFrame(objects)
        experiments['registrationDate'] = experiments['registrationDate'].map(format_timestamp)
        experiments['modificationDate'] = experiments['modificationDate'].map(format_timestamp)
        experiments['project'] = experiments['project'].map(extract_code)
        experiments['registrator'] = experiments['registrator'].map(extract_person)
        experiments['modifier'] = experiments['modifier'].map(extract_person)
        experiments['identifier'] = experiments['identifier'].map(extract_identifier)
        experiments['permId'] = experiments['permId'].map(extract_permid)
        experiments['type'] = experiments['type'].map(extract_code)

        attrs = ['identifier', 'permId', 'project', 'type',
                 'registrator', 'registrationDate', 'modifier', 'modificationDate']

        if props is not None:
            for prop in props:
                experiments[prop.upper()] = experiments['properties'].map(lambda x: x.get(prop.upper(), ''))
                attrs.append(prop.upper())

        exps = experiments[attrs]
        return Things(self, 'experiment', exps, 'identifier')

    def get_datasets(self,
                     code=None, type=None, withParents=None, withChildren=None, status=None,
                     sample=None, experiment=None, project=None, tags=None, props=None, **properties
                     ):

        sub_criteria = []

        if code:
            sub_criteria.append(_criteria_for_code(code))
        if type:
            sub_criteria.append(_subcriteria_for_type(type, 'DataSet'))
        if withParents:
            sub_criteria.append(_subcriteria_for_permid(withParents, 'DataSet', 'Parents'))
        if withChildren:
            sub_criteria.append(_subcriteria_for_permid(withChildren, 'DataSet', 'Children'))

        if sample:
            sub_criteria.append(_subcriteria_for_code(sample, 'Sample'))
        if experiment:
            sub_criteria.append(_subcriteria_for_code(experiment, 'Experiment'))
        if project:
            exp_crit = _subcriteria_for_code(experiment, 'Experiment')
            proj_crit = _subcriteria_for_code(project, 'Project')
            exp_crit['criteria'] = []
            exp_crit['criteria'].append(proj_crit)
            sub_criteria.append(exp_crit)
        if tags:
            sub_criteria.append(_subcriteria_for_tags(tags))
        if status:
            sub_criteria.append(_subcriteria_for_status(status))
        if properties is not None:
            for prop in properties:
                sub_criteria.append(_subcriteria_for_properties(prop, properties[prop]))

        search_criteria = get_search_type_for_entity('dataset')
        search_criteria['criteria'] = sub_criteria
        search_criteria['operator'] = 'AND'

        fetchopts = {
            "containers": {"@type": "as.dto.dataset.fetchoptions.DataSetFetchOptions"},
            "type": {"@type": "as.dto.dataset.fetchoptions.DataSetTypeFetchOptions"}
        }

        for option in ['tags', 'properties', 'sample', 'experiment', 'physicalData']:
            fetchopts[option] = fetch_option[option]

        request = {
            "method": "searchDataSets",
            "params": [self.token,
                       search_criteria,
                       fetchopts,
                       ],
        }
        resp = self._post_request(self.as_v3, request)
        if len(resp['objects']) == 0:
            raise ValueError("no datasets found!")

        objects = resp['objects']
        parse_jackson(objects)

        datasets = DataFrame(objects)
        datasets['registrationDate'] = datasets['registrationDate'].map(format_timestamp)
        datasets['modificationDate'] = datasets['modificationDate'].map(format_timestamp)
        datasets['experiment'] = datasets['experiment'].map(extract_nested_identifier)
        datasets['sample'] = datasets['sample'].map(extract_nested_identifier)
        datasets['type'] = datasets['type'].map(extract_code)
        datasets['permId'] = datasets['code']
        datasets['location'] = datasets['physicalData'].map(lambda x: x.get('location') if x else '')

        attrs = ['permId', 'properties', 'type', 'experiment', 'sample', 'registrationDate', 'modificationDate',
                 'location']
        if props is not None:
            for prop in props:
                datasets[prop.upper()] = datasets['properties'].map(lambda x: x.get(prop.upper(), ''))
                attrs.append(prop.upper())

        return Things(self, 'dataset', datasets[attrs], 'permId')

    def get_experiment(self, expId, withAttachments=False, only_data=False):
        """ Returns an experiment object for a given identifier (expId).
        """

        fetchopts = {
            "@type": "as.dto.experiment.fetchoptions.ExperimentFetchOptions",
            "type": {
                "@type": "as.dto.experiment.fetchoptions.ExperimentTypeFetchOptions",
            },
        }

        search_request = search_request_for_identifier(expId, 'experiment')
        for option in ['tags', 'properties', 'attachments', 'project', 'samples']:
            fetchopts[option] = fetch_option[option]

        if withAttachments:
            fetchopts['attachments'] = fetch_option['attachmentsWithContent']

        request = {
            "method": "getExperiments",
            "params": [
                self.token,
                [search_request],
                fetchopts
            ],
        }
        resp = self._post_request(self.as_v3, request)
        if len(resp) == 0:
            raise ValueError("No such experiment: %s" % expId)

        for id in resp:
            if only_data:
                return resp[id]
            else:
                return Experiment(
                    openbis_obj = self,
                    type = self.get_experiment_type(resp[expId]["type"]["code"]),
                    data = resp[id]
                )

    def new_experiment(self, type, code, project, props=None, **kwargs):
        """ Creates a new experiment of a given experiment type.
        """
        return Experiment(
            openbis_obj = self, 
            type = self.get_experiment_type(type), 
            project = project,
            data = None,
            props = props,
            code = code, 
            **kwargs
        )

    def update_experiment(self, experimentId, properties=None, tagIds=None, attachments=None):
        params = {
            "experimentId": {
                "permId": experimentId,
                "@type": "as.dto.experiment.id.ExperimentPermId"
            },
            "@type": "as.dto.experiment.update.ExperimentUpdate"
        }
        if properties is not None:
            params["properties"] = properties
        if tagIds is not None:
            params["tagIds"] = tagIds
        if attachments is not None:
            params["attachments"] = attachments

        request = {
            "method": "updateExperiments",
            "params": [
                self.token,
                [params]
            ]
        }
        self._post_request(self.as_v3, request)

    def create_sample(self, space_ident, code, type,
                      project_ident=None, experiment_ident=None, properties=None, attachments=None, tags=None):

        tagIds = _create_tagIds(tags)
        typeId = _create_typeId(type)
        projectId = _create_projectId(project_ident)
        experimentId = _create_experimentId(experiment_ident)

        if properties is None:
            properties = {}

        request = {
            "method": "createSamples",
            "params": [
                self.token,
                [
                    {
                        "properties": properties,
                        "code": code,
                        "typeId": typeId,
                        "projectId": projectId,
                        "experimentId": experimentId,
                        "tagIds": tagIds,
                        "attachments": attachments,
                        "@type": "as.dto.sample.create.SampleCreation",
                    }
                ]
            ],
        }
        resp = self._post_request(self.as_v3, request)
        return self.get_sample(resp[0]['permId'])

    create_object = create_sample # Alias

    def create_external_data_management_system(self, code, label, address, address_type='FILE_SYSTEM'):
        """Create an external DMS.
        :param code: An openBIS code for the external DMS.
        :param label: A human-readable label.
        :param address: The address for accessing the external DMS. E.g., a URL.
        :param address_type: One of OPENBIS, URL, or FILE_SYSTEM
        :return:
        """
        request = {
            "method": "createExternalDataManagementSystems",
            "params": [
                self.token,
                [
                    {
                        "code": code,
                        "label": label,
                        "addressType": address_type,
                        "address": address,
                        "@type": "as.dto.externaldms.create.ExternalDmsCreation",
                    }
                ]
            ],
        }
        resp = self._post_request(self.as_v3, request)
        return self.get_external_data_management_system(resp[0]['permId'])

    def update_sample(self, sampleId, space=None, project=None, experiment=None,
                      parents=None, children=None, components=None, properties=None, tagIds=None, attachments=None):
        params = {
            "sampleId": {
                "permId": sampleId,
                "@type": "as.dto.sample.id.SamplePermId"
            },
            "@type": "as.dto.sample.update.SampleUpdate"
        }
        if space is not None:
            params['spaceId'] = space
        if project is not None:
            params['projectId'] = project
        if properties is not None:
            params["properties"] = properties
        if tagIds is not None:
            params["tagIds"] = tagIds
        if attachments is not None:
            params["attachments"] = attachments

        request = {
            "method": "updateSamples",
            "params": [
                self.token,
                [params]
            ]
        }
        self._post_request(self.as_v3, request)

    update_object = update_sample # Alias

    def delete_entity(self, entity, permid, reason, capitalize=True):
        """Deletes Spaces, Projects, Experiments, Samples and DataSets
        """

        if capitalize:
            entity_capitalized = entity.capitalize()
        else:
            entity_capitalized = entity

        entity_type = "as.dto.{}.id.{}PermId".format(entity.lower(), entity_capitalized)
        request = {
            "method": "delete" + entity_capitalized + 's',
            "params": [
                self.token,
                [
                    {
                        "permId": permid,
                        "@type": entity_type
                    }
                ],
                {
                    "reason": reason,
                    "@type": "as.dto.{}.delete.{}DeletionOptions".format(entity.lower(), entity_capitalized)
                }
            ]
        }
        self._post_request(self.as_v3, request)

    def get_deletions(self):
        request = {
            "method": "searchDeletions",
            "params": [
                self.token,
                {},
                {
                    "deletedObjects": {
                        "@type": "as.dto.deletion.fetchoptions.DeletedObjectFetchOptions"
                    }
                }
            ]
        }
        resp = self._post_request(self.as_v3, request)
        objects = resp['objects']
        parse_jackson(objects)

        new_objs = []
        for value in objects:
            del_objs = extract_deletion(value)
            if len(del_objs) > 0:
                new_objs.append(*del_objs)

        return DataFrame(new_objs)

    def new_project(self, space, code, description=None, **kwargs):
        return Project(self, None, space=space, code=code, description=description, **kwargs)

    def _gen_fetchoptions(self, options):
        fo = {}
        for option in options:
            fo[option] = fetch_option[option]
        return fo

    def get_project(self, projectId, only_data=False):
        options = ['space', 'registrator', 'modifier', 'attachments']
        if is_identifier(projectId) or is_permid(projectId):
            request = self._create_get_request(
                'getProjects', 'project', projectId, options
            )
            resp = self._post_request(self.as_v3, request)
            if only_data:
                return resp[projectId]

            return Project(self, resp[projectId])

        else:
            search_criteria = _gen_search_criteria({
                'project': 'Project',
                'operator': 'AND',
                'code': projectId
            })
            fo = self._gen_fetchoptions(options)
            request = {
                "method": "searchProjects",
                "params": [self.token, search_criteria, fo]
            }
            resp = self._post_request(self.as_v3, request)
            if len(resp['objects']) == 0:
                raise ValueError("No such project: %s" % projectId)
            if only_data:
                return resp['objects'][0]

            return Project(self, resp['objects'][0])

    def get_projects(self, space=None, code=None):
        """ Get a list of all available projects (DataFrame object).
        """

        sub_criteria = []
        if space:
            sub_criteria.append(_subcriteria_for_code(space, 'space'))
        if code:
            sub_criteria.append(_criteria_for_code(code))

        criteria = {
            "criteria": sub_criteria,
            "@type": "as.dto.project.search.ProjectSearchCriteria",
            "operator": "AND"
        }

        fetchopts = {"@type": "as.dto.project.fetchoptions.ProjectFetchOptions"}
        for option in ['registrator', 'modifier', 'leader']:
            fetchopts[option] = fetch_option[option]

        request = {
            "method": "searchProjects",
            "params": [self.token,
                       criteria,
                       fetchopts,
                       ],
        }

        resp = self._post_request(self.as_v3, request)
        objects = resp['objects']
        if len(objects) == 0:
            raise ValueError("No projects found!")
            
        parse_jackson(objects)

        projects = DataFrame(objects)
        if len(projects) is 0:
            raise ValueError("No projects found!")

        projects['registrationDate'] = projects['registrationDate'].map(format_timestamp)
        projects['modificationDate'] = projects['modificationDate'].map(format_timestamp)
        projects['leader'] = projects['leader'].map(extract_person)
        projects['registrator'] = projects['registrator'].map(extract_person)
        projects['modifier'] = projects['modifier'].map(extract_person)
        projects['permId'] = projects['permId'].map(extract_permid)
        projects['identifier'] = projects['identifier'].map(extract_identifier)

        pros = projects[['identifier', 'permId', 'leader', 'registrator', 'registrationDate',
                            'modifier', 'modificationDate']]
        return Things(self, 'project', pros, 'identifier')

    def _create_get_request(self, method_name, entity, permids, options):

        if not isinstance(permids, list):
            permids = [permids]

        type = "as.dto.{}.id.{}".format(entity.lower(), entity.capitalize())
        search_params = []
        for permid in permids:
            # decide if we got a permId or an identifier
            match = re.match('/', permid)
            if match:
                search_params.append(
                    {"identifier": permid, "@type": type + 'Identifier'}
                )
            else:
                search_params.append(
                    {"permId": permid, "@type": type + 'PermId'}
                )

        fo = {}
        for option in options:
            fo[option] = fetch_option[option]

        request = {
            "method": method_name,
            "params": [
                self.token,
                search_params,
                fo
            ],
        }
        return request

    def get_terms(self, vocabulary=None):
        """ Returns information about vocabulary, including its controlled vocabulary
        """

        search_request = {}
        if vocabulary is not None:
            search_request = _gen_search_criteria({
                "vocabulary": "VocabularyTerm",
                "criteria": [{
                    "vocabulary": "Vocabulary",
                    "code": vocabulary
                }]
            })

        fetch_options = {
            "vocabulary": {"@type": "as.dto.vocabulary.fetchoptions.VocabularyFetchOptions"},
            "@type": "as.dto.vocabulary.fetchoptions.VocabularyTermFetchOptions"
        }

        request = {
            "method": "searchVocabularyTerms",
            "params": [self.token, search_request, fetch_options]
        }
        resp = self._post_request(self.as_v3, request)
        parse_jackson(resp)
        return Vocabulary(resp)

    def get_tags(self):
        """ Returns a DataFrame of all 
        """
        request = {
            "method": "searchTags",
            "params": [self.token, {}, {}]
        }
        resp = self._post_request(self.as_v3, request)
        parse_jackson(resp)
        objects = DataFrame(resp['objects'])
        objects['registrationDate'] = objects['registrationDate'].map(format_timestamp)
        return objects[['code', 'registrationDate']]
    
    def _search_semantic_annotations(self, criteria):

        fetch_options = {
            "@type": "as.dto.semanticannotation.fetchoptions.SemanticAnnotationFetchOptions",
            "entityType": {"@type": "as.dto.entitytype.fetchoptions.EntityTypeFetchOptions"},
            "propertyType": {"@type": "as.dto.property.fetchoptions.PropertyTypeFetchOptions"},
            "propertyAssignment": {
                "@type": "as.dto.property.fetchoptions.PropertyAssignmentFetchOptions",
                "entityType" : {
                    "@type" : "as.dto.entitytype.fetchoptions.EntityTypeFetchOptions"
                },
                "propertyType" : {
                    "@type" : "as.dto.property.fetchoptions.PropertyTypeFetchOptions"
                }
            }
        }

        request = {
            "method": "searchSemanticAnnotations",
            "params": [self.token, criteria, fetch_options]
        }

        resp = self._post_request(self.as_v3, request)
        
        if resp is not None:
            objects = resp['objects']
            
            if len(objects) is 0:
                raise ValueError("No semantic annotations found!")
            
            parse_jackson(objects)
            
            for object in objects:
                object['permId'] = object['permId']['permId']
                if object.get('entityType') is not None:
                    object['entityType'] = object['entityType']['code']
                elif object.get('propertyType') is not None:
                    object['propertyType'] = object['propertyType']['code']
                elif object.get('propertyAssignment') is not None:
                    object['entityType'] = object['propertyAssignment']['entityType']['code']
                    object['propertyType'] = object['propertyAssignment']['propertyType']['code']
                object['creationDate'] = format_timestamp(object['creationDate'])
                
            return objects
        else:
            raise ValueError("No semantic annotations found!")

    def get_semantic_annotations(self):
        """ Get a list of all available semantic annotations (DataFrame object).
        """

        objects = self._search_semantic_annotations({})
        attrs = ['permId', 'entityType', 'propertyType', 'predicateOntologyId', 'predicateOntologyVersion', 'predicateAccessionId', 'descriptorOntologyId', 'descriptorOntologyVersion', 'descriptorAccessionId', 'creationDate']
        annotations = DataFrame(objects)
        return Things(self, 'semantic_annotation', annotations[attrs], 'permId')
    
    def get_semantic_annotation(self, permId, only_data = False):

        criteria = {
            "@type" : "as.dto.semanticannotation.search.SemanticAnnotationSearchCriteria",
            "criteria" : [{
                "@type" : "as.dto.common.search.PermIdSearchCriteria",
                "fieldValue" : {
                    "@type" : "as.dto.common.search.StringEqualToValue",
                    "value" : permId
                }
            }]
        }

        objects = self._search_semantic_annotations(criteria)
        object = objects[0]

        if only_data:
            return object
        else:
            return SemanticAnnotation(self, isNew=False, **object)    
    
    def get_sample_types(self, type=None):
        """ Returns a list of all available sample types
        """
        return self._get_types_of(
            "searchSampleTypes",
            "Sample",
            type,
            ["generatedCodePrefix"]
        )

    get_object_types = get_sample_types # Alias

    def get_sample_type(self, type):
        try:
            return self._get_types_of(
                "searchSampleTypes",
                "Sample",
                type,
                ["generatedCodePrefix"]
            )
        except Exception:
            raise ValueError("no such sample type: {}".format(type))

    get_object_type = get_sample_type # Alias

    def get_experiment_types(self, type=None):
        """ Returns a list of all available experiment types
        """
        return self._get_types_of(
            "searchExperimentTypes",
            "Experiment",
            type
        )

    def get_experiment_type(self, type):
        try:
            return self._get_types_of(
                "searchExperimentTypes",
                "Experiment",
                type
            )
        except Exception:
            raise ValueError("No such experiment type: {}".format(type))

    def get_material_types(self, type=None):
        """ Returns a list of all available material types
        """
        return self._get_types_of("searchMaterialTypes", "Material", type)

    def get_material_type(self, type):
        try:
            return self._get_types_of("searchMaterialTypes", "Material", type)
        except Exception:
            raise ValueError("No such material type: {}".format(type))

    def get_dataset_types(self, type=None):
        """ Returns a list (DataFrame object) of all currently available dataset types
        """
        return self._get_types_of("searchDataSetTypes", "DataSet", type, optional_attributes=['kind'])

    def get_dataset_type(self, type):
        try:
            return self._get_types_of("searchDataSetTypes", "DataSet", type, optional_attributes=['kind'])
        except Exception:
            raise ValueError("No such dataSet type: {}".format(type))

    def _get_types_of(self, method_name, entity, type_name=None, additional_attributes=[], optional_attributes=[]):
        """ Returns a list of all available types of an entity.
        If the name of the entity-type is given, it returns a PropertyAssignments object
        """

        search_request = {}
        fetch_options = {}

        if type_name is not None:
            search_request = _gen_search_criteria({