""" Created December 2013 @author: [email protected] This script loads Visomics-style analyses into the Arbor TreeStore database. Requirements: - xmltodict (can be pip installed) """ from ArborFileManagerAPI import ArborFileManager api = ArborFileManager() api.initDatabaseConnection() import json import os import sys import xmltodict # check that analysis directory has been passed in via the command line if len(sys.argv) < 2: print sys.argv[0] + " <path/to/xml_dir>" sys.exit(1) xml_dir = sys.argv[1] xml_files = os.listdir(xml_dir) for xml_file in xml_files: if not xml_file.endswith(".xml"): continue
import tangelo import pymongo import bson.json_util from ArborFileManagerAPI import ArborFileManager api = ArborFileManager() api.initDatabaseConnection() @tangelo.restful def get(*pargs, **query_args): if len(pargs) == 0: return tangelo.HTTPStatusCode(400, "Missing resource type") resource_type = pargs[0] allowed = ["project", "analysis","collection", "workflow"] if resource_type == "project": if len(pargs) == 1: return api.getListOfProjectNames() elif len(pargs) == 2: project = pargs[1] return api.getListOfTypesForProject(project) elif len(pargs) == 3: project = pargs[1] datatype = pargs[2] return api.getListOfDatasetsByProjectAndType(project, datatype) elif len(pargs) == 4: project = pargs[1] datatype = pargs[2] dataset = pargs[3] coll = api.db[api.returnCollectionForObjectByName(project, datatype, dataset)] return bson.json_util.dumps(list(coll.find()))
import tangelo import pymongo import bson.json_util from ArborFileManagerAPI import ArborFileManager api = ArborFileManager() api.initDatabaseConnection() @tangelo.restful def get(*pargs, **query_args): if len(pargs) == 0: return tangelo.HTTPStatusCode(400, "Missing resource type") resource_type = pargs[0] allowed = ["project", "analysis", "collection", "workflow"] if resource_type == "project": if len(pargs) == 1: return api.getListOfProjectNames() elif len(pargs) == 2: project = pargs[1] return api.getListOfTypesForProject(project) elif len(pargs) == 3: project = pargs[1] datatype = pargs[2] return api.getListOfDatasetsByProjectAndType(project, datatype) elif len(pargs) == 4: project = pargs[1] datatype = pargs[2] dataset = pargs[3]