Refactored code from tests to classes

metadata_tools/importxls/dataset_exporter.py

+import pkg_resources
+import json
+import hashlib
+from os import fsencode
+from metadata_tools.importxls.export_utils import get_lines_from_string
+
+
+class DatasetExporter:
+
+    def __init__(self):
+        with open(pkg_resources.resource_filename('metadata_tools',  'resources/elu_institutions.json'), encoding='utf-8') as institutions_file:
+            institutions = json.loads(institutions_file.read())
+            self.institution_dict = {}
+            for inst in institutions:
+                self.institution_dict[inst.get('institution_name')] = inst.get('elu_accession')
+
+        self.h = hashlib.md5()
+        self.predefined_data_types = set([
+            "Omics data",
+            "Genotype data",
+            "Whole genome sequencing",
+            "Exome sequencing",
+            "Genomics variant array",
+            "RNASeq",
+            "Genetic and derived genetic data",
+            "Transcriptome array",
+            "Methylation array",
+            "MicroRNA array",
+            "Metabolomics",
+            "Metagenomics",
+            "Proteomics",
+            "Other omics data",
+            "Clinical Imaging",
+            "Cell Imaging",
+            "Human subject data",
+            "Clinical data",
+            "Lifestyle data",
+            "Socio Economic Data",
+            "Environmental Data",
+            "Other Phenotype data",
+            "Other"
+        ])
+        self.predefined_storage_types = set([
+            'hpc_chaos_home',
+            'hpc_chaos_project',
+            'hpc_gaia_home',
+            'hpc_gaia_project',
+            'hpc_gaia_work',
+            'hpc_iris_home',
+            'hpc_iris_project',
+            'hpc_scratch_personal',
+            'hpc_scratch_project',
+            'hpc_isilon',
+            'atlas_personal',
+            'atlas_project',
+            'hpc_backup_chaos',
+            'hpc_backup_gaia',
+            'bertha',
+            'certon_block',
+            'lcsb_group_server',
+            'lcsb_desktop',
+            'lcsb_laptop',
+            'personal_laptop',
+            'Owncloud',
+            'External Storage  (e.g. Hard disk, DVD)',
+            'Other'
+        ])
+    def get_hash_for_path(self, path):
+        self.h.update(fsencode(path))
+        return str(int(self.h.hexdigest(), 16))
+
+    def lookup_institution_accession(self, institution_name):
+
+        if institution_name not in self.institution_dict.keys():
+            print ('Undefined institution  -- > {}'.format(institution_name))
+            return None
+        else:
+            return self.institution_dict[institution_name]
+
+    def process_data_types(self, xls_data_type_list):
+        result = []
+        data_type_notes = ''
+        for type_name in xls_data_type_list:
+            type_name = type_name.strip()
+            if type_name:
+                if type_name in self.predefined_data_types:
+                    result.append(type_name.replace(" ", "_"))
+                else:
+                    data_type_notes += type_name + '\n'
+        return (result, data_type_notes)
+
+    def is_storage_resource(self, resource):
+
+        if resource in self.predefined_storage_types:
+            return True
+        else:
+            print('Unknow Storage resource --> {}'.format(resource))
+            return False
+
+    def get_storage_location(self, resource, path, category):
+
+        result = {}
+
+        if self.is_application(path):
+            result['storage_resource'] = 'application'
+        elif resource in self.predefined_data_types:
+            result['storage_resource'] = resource
+        else:
+            result['storage_resource'] = 'Other'
+
+        result['location'] = {'location':path}
+        result['category'] = category
+
+        return result
+
+
+    def is_application(self, path):
+
+        if ("transmart" in path.lower()) or ( "redcap" in path.lower()):
+            return True
+        else:
+            return False
+
+    def process_share_list(self, shares):
+        share_list = []
+        for shr in shares:
+            if ";" not in shr:
+                if self.lookup_institution_accession(shr.strip()):
+                    share_list.append({'share_inst': self.lookup_institution_accession(shr.strip())})
+                else:
+                    share_list.append({'share_notes': shr})
+
+            else:
+                infos = shr.split(";")
+
+                share_list.append({'share_inst': self.lookup_institution_accession(infos[0].strip()),
+                                   'share_notes': infos[1].strip()})
+        return share_list
+
+    def add_storage_locations(self, storage_dict, locations_list, category):
+
+        if len(locations_list) % 2 != 0 and len(locations_list) > 0:
+            if len(locations_list) == 1:
+                if self.is_storage_resource(locations_list[0]):
+                    storage_dict.append(self.get_storage_location(locations_list[0],'<missing_info>',category))
+                else:
+                    for line in get_lines_from_string(locations_list[0]):
+                        storage_dict.append(self.get_storage_location('Other',line,category))
+            else:
+                raise ValueError('Uneven Master Data Location Row')
+        elif len(locations_list) % 2 == 0 and len(locations_list) > 0:
+            s = 0
+            e = len(locations_list) // 2
+            while s < e:
+                if self.is_storage_resource(locations_list[s * 2]):
+                    for line in get_lines_from_string(locations_list[s * 2 + 1]):
+                        storage_dict.append(self.get_storage_location(locations_list[s * 2], line, category))
+                else:
+                    for line in get_lines_from_string(locations_list[s * 2]):
+                        storage_dict.append(self.get_storage_location('Other', line, category))
+                s += 1
+
+

metadata_tools/importxls/export_utils.py

+import datetime
+
+def process_yes_no_answer(answer):
+    """
+    convert yes/no answers to boolean we take empty answers as no
+    :param xls_data_type_list:
+    """
+    result = False
+    if answer:
+        if answer == 'Yes':
+            result = True
+    return result
+
+
+def process_yes_no_dontknow_answer(answer):
+    """
+    convert yes/no/dontknow answers to boolean
+    we return empty and dontknow answers as None
+    :param xls_data_type_list:
+    """
+    if answer:
+        if answer == 'Yes':
+            return True
+        elif answer == 'No':
+            return False
+        else:
+            return None
+    else:
+        return None
+
+
+def is_data_sheet(fname):
+    return fname.startswith('from-repository') or fname.startswith('from-collaborator') or fname.startswith(
+        'own-cohort')
+
+
+def get_value_list_from_row(sheet, row_idx):
+    result = []
+    vals = sheet.row[row_idx]
+    data_vals = vals[2:]
+    for val in data_vals:
+        if val:
+            result.append(val)
+    return result
+
+
+def process_possible_date(possible_date):
+    if isinstance(possible_date, datetime.date):
+        return possible_date.strftime("%Y/%m/%d")
+    else:
+        return str(possible_date).replace('.', '/')
+
+
+
+def get_names_from_string(full_name):
+    result = ['', '']
+    name = full_name.strip()
+    if name.endswith(',') or name.endswith(','):
+        name = name[:-1]
+
+    if name is not None:
+        if " " in name:
+            name_list = name.split(" ")
+            len_name = len(name_list)
+            result[0] = name_list[0]
+            if len_name > 1:
+                result[1] = name_list[1]
+            if len_name == 3:
+                result[1] = result[1] + ' ' + name_list[2]
+        else:
+            result[0] = name
+    return result
+
+
+def get_lines_from_string(a_string):
+    result = []
+    stripped = a_string.strip()
+    line_list = stripped.splitlines()
+    for line in line_list:
+        if line:
+            result.append(line)
+    return result
\ No newline at end of file

metadata_tools/importxls/from_collab_exporter.py

+from .dataset_exporter import DatasetExporter
+import pyexcel
+import json
+from metadata_tools.importxls.export_utils import get_value_list_from_row, process_yes_no_answer, \
+    process_yes_no_dontknow_answer, process_possible_date
+
+class FromCollabXlsExporter(DatasetExporter):
+
+    def export(self, full_file_path):
+        submission_id = 'IMP_FC_{}'.format(self.get_hash_for_path(full_file_path))
+        idx = 1
+        print('Processing ----> {}'.format(full_file_path))
+        book = pyexcel.get_book(file_name=full_file_path)
+        while idx < book.number_of_sheets():
+            sheet = book.sheet_by_index(idx)
+            dataset_data = {}
+            dataset_data['source_type'] = 'From_Collaborator'
+            dataset_data['submission_id'] = submission_id
+            dataset_data['local_custodian'] = get_value_list_from_row(sheet, 3)
+
+            dataset_data['title'] = sheet[4, 2]
+            if not dataset_data['title']:
+                print('Missing dataset title ----> {}'.format(full_file_path))
+
+            datatype_info = self.process_data_types(get_value_list_from_row(sheet, 5))
+            dataset_data['data_types'] = datatype_info[0]
+            if datatype_info[1]:
+                dataset_data['data_type_notes'] = datatype_info[1]
+
+            dataset_data['involves_samples'] = process_yes_no_answer(sheet[6, 2])
+
+            if sheet[7, 2]:
+                dataset_data['samples_location'] = sheet[7, 2]
+
+            if sheet[8, 2]:
+                dataset_data['de_identification'] = sheet[8, 2]
+
+            if sheet[9, 2]:
+                dataset_data['subject_categories'] = sheet[9, 2].replace(' & ', '_and_')
+
+            if sheet[10, 2]:
+                dataset_data['has_special_subjects'] = process_yes_no_dontknow_answer(
+                    sheet[10, 2])
+
+            if dataset_data.get('has_special_subjects'):
+                if dataset_data.get('has_special_subjects') == True and sheet[11, 2]:
+                    dataset_data['special_subject_notes'] = sheet[11, 2]
+
+            collab_insts = get_value_list_from_row(sheet, 13)
+            collab_pis = get_value_list_from_row(sheet, 14)
+
+            if (len(collab_insts) == len(collab_pis)) and len(collab_insts) > 0:
+                i = 0
+                src_collab_list = []
+                while i < len(collab_insts):
+
+                    collab_data = {'collab_inst': self.lookup_institution_accession(collab_insts[i]),
+                                   'collab_pi': collab_pis[i],
+                                   'collab_project': sheet[18, 2]}
+
+                    if process_yes_no_dontknow_answer(sheet[17, 2]) == False:
+                        collab_data['collab_role'] = 'controller'
+
+                    elif process_yes_no_dontknow_answer(sheet[17, 2]) == True:
+                        collab_data['collab_role'] = 'joint-controller'
+
+                    src_collab_list.append(collab_data)
+                    i += 1
+                dataset_data['source_collaborations'] = src_collab_list
+            else:
+                print('Mismatched Collab PI-Institution length   {} \n'.format(full_file_path))
+
+            if len(collab_insts)>1:
+                print('Multi source collab ----> {}'.format(full_file_path))
+
+            if sheet[18, 2]:
+                dataset_data['source_project'] = sheet[18, 2]
+
+            use_restrictions = []
+            if process_yes_no_answer(sheet[25, 2]):
+                use_restrictions.append({'ga4gh_code': 'PS',
+                                         'note': 'Use is restricted to projects: ' + ', '.join(
+                                             get_value_list_from_row(sheet, 26))})
+            if process_yes_no_answer(sheet[27, 2]):
+                use_restrictions.append({'ga4gh_code': 'RS-[XX]',
+                                         'note': 'Use is restricted to research areas: ' + ', '.join(
+                                             get_value_list_from_row(sheet, 28))})
+            if process_yes_no_answer(sheet[43, 2]):
+                use_restrictions.append({'ga4gh_code': 'PUB',
+                                         'note': 'Acknowledgement required.'})
+
+            has_time_limis = process_yes_no_dontknow_answer(sheet[41, 2])
+            if has_time_limis and sheet[42, 2]:
+                use_restrictions.append({'ga4gh_code': 'TS-[XX]',
+                                         'note': 'Data is obtained for a limited duration.' + process_possible_date(sheet[42, 2])})
+
+            dataset_data['use_restrictions'] = use_restrictions
+
+            dataset_data['used_by_projects'] = get_value_list_from_row(sheet, 33)
+
+            if process_yes_no_answer(sheet[29, 2]):
+                dataset_data['shares'] = self.process_share_list(get_value_list_from_row(sheet, 30))
+
+
+            storage_locations = []
+
+            master_locations = get_value_list_from_row(sheet, 35)
+            try:
+                self.add_storage_locations(storage_locations, master_locations, 'master')
+            except ValueError as e:
+                print('Invalid Master Data Location Row  {} \n'.format(full_file_path))
+
+            if process_yes_no_answer(sheet[37, 2]):
+                backup_locations = get_value_list_from_row(sheet, 38)
+                try:
+                    self.add_storage_locations(storage_locations, backup_locations, 'backup')
+                except ValueError as e:
+                    print('Uneven Backup Data Location Row {} \n'.format(full_file_path))
+
+            if process_yes_no_answer(sheet[39, 2]):
+                copy_locations = get_value_list_from_row(sheet, 40)
+                try:
+                    self.add_storage_locations(storage_locations, copy_locations, 'copy')
+                except ValueError as e:
+                    print('Uneven Copy Data Location Row {} \n'.format(full_file_path))
+
+            acl_list = get_value_list_from_row(sheet, 36)
+            if len(acl_list) > 0:
+                dataset_data['storage_acl_info'] = ', '.join(acl_list)
+            dataset_data['storage_locations'] = storage_locations
+            idx += 1
+
+            with open('{}_.json'.format(submission_id), 'w') as outfile:
+                json.dump(dataset_data, outfile, indent=4)

metadata_tools/importxls/from_owncohort_exporter.py

+import pyexcel
+import json
+from .dataset_exporter import DatasetExporter
+from metadata_tools.importxls.export_utils import get_value_list_from_row, process_yes_no_answer, \
+    process_yes_no_dontknow_answer, process_possible_date
+
+class FromOwncohortXlsExporter(DatasetExporter):
+
+    def export(self, full_file_path):
+        submission_id = 'IMP_OC_{}'.format(self.get_hash_for_path(full_file_path))
+        book = pyexcel.get_book(file_name=full_file_path)
+        idx = 1
+        print('----> {}'.format(full_file_path))
+        while idx < book.number_of_sheets():
+            sheet = book.sheet_by_index(idx)
+            dataset_data = {}
+            dataset_data['source_type'] = 'Own_Cohort'
+            dataset_data['submission_id'] = submission_id
+            dataset_data['local_custodian'] = get_value_list_from_row(sheet, 3)
+
+            dataset_data['title'] = sheet[4, 2]
+            if not dataset_data['title']:
+                print('Missing dataset title ----> {}'.format(full_file_path))
+            if sheet[5, 2]:
+                dataset_data['source_project'] = sheet[5, 2]
+
+            datatype_info = self.process_data_types(get_value_list_from_row(sheet, 6))
+            dataset_data['data_types'] = datatype_info[0]
+            if datatype_info[1]:
+                dataset_data['data_type_notes'] = datatype_info[1]
+
+
+            dataset_data['involves_samples'] = process_yes_no_answer(sheet[7, 2])
+
+            if sheet[7, 2]:
+                dataset_data['samples_location'] = sheet[8, 2]
+
+            if sheet[9, 2]:
+                dataset_data['de_identification'] = sheet[9, 2]
+
+            if sheet[10, 2]:
+                dataset_data['ombudsman'] = sheet[10, 2]
+
+            if sheet[11, 2]:
+                dataset_data['subject_categories'] = sheet[11, 2].replace(' & ', '_and_')
+
+            if sheet[12, 2]:
+                dataset_data['has_special_subjects'] = process_yes_no_dontknow_answer(
+                    sheet[12, 2])
+
+            if dataset_data.get('has_special_subjects'):
+                if dataset_data.get('has_special_subjects') == True and sheet[13, 2]:
+                    dataset_data['special_subject_notes'] = sheet[13, 2]
+
+            if sheet[19, 2]:
+                dataset_data['consent_status'] = sheet[19, 2]
+
+            dataset_data['used_by_projects'] = get_value_list_from_row(sheet, 22)
+
+            use_restrictions = []
+            if process_yes_no_answer(sheet[21, 2]):
+                use_restrictions.append({'ga4gh_code': 'PS',
+                                         'note': 'Consent form restricts data use to projects ' + ', '.join(
+                                             get_value_list_from_row(sheet, 23))})
+
+            if process_yes_no_answer(sheet[24, 2]):
+                use_restrictions.append({'ga4gh_code': 'RS-[XX]',
+                                         'note': 'Data is consented for research on' + ', '.join(
+                                             get_value_list_from_row(sheet, 25))})
+
+            if process_yes_no_answer(sheet[26, 2]):
+                use_restrictions.append({'ga4gh_code': 'GS-[XX]',
+                                         'note': 'Data is consented for sharing outside LCSB (Within Luxembourg)'})
+
+            if process_yes_no_answer(sheet[29, 2]):
+                use_restrictions.append({'ga4gh_code': 'GS-[XX]',
+                                         'note': 'Data is consented for sharing outside Luxembourg (within EU)'})
+
+            if process_yes_no_answer(sheet[32, 2]):
+                use_restrictions.append({'ga4gh_code': 'GS-[XX]',
+                                         'note': 'Data is consented for sharing outside EU'})
+
+            has_time_limis = process_yes_no_dontknow_answer(sheet[42, 2])
+            if has_time_limis and sheet[43, 2]:
+                use_restrictions.append({'ga4gh_code': 'TS-[XX]',
+                                         'note': 'Data is obtained for a limited duration.' + process_possible_date(sheet[43, 2])})
+
+            dataset_data['use_restrictions'] = use_restrictions
+
+            share_list = []
+
+            if process_yes_no_answer(sheet[27, 2]):
+                share_list += self.process_share_list(get_value_list_from_row(sheet, 28))
+
+            if process_yes_no_answer(sheet[30, 2]):
+                share_list += self.process_share_list(get_value_list_from_row(sheet, 31))
+
+            if process_yes_no_answer(sheet[33, 2]):
+                share_list += self.process_share_list(get_value_list_from_row(sheet, 34))
+
+            dataset_data['shares'] = share_list
+
+            storage_locations = []
+
+            master_locations = get_value_list_from_row(sheet, 36)
+            try:
+                self.add_storage_locations(storage_locations, master_locations, 'master')
+            except ValueError as e:
+                print('Invalid Master Data Location Row  {} \n'.format(full_file_path))
+
+            if process_yes_no_answer(sheet[38, 2]):
+                backup_locations = get_value_list_from_row(sheet, 39)
+                try:
+                    self.add_storage_locations(storage_locations, backup_locations, 'backup')
+                except ValueError as e:
+                    print('Uneven Backup Data Location Row {} \n'.format(full_file_path))
+
+            if process_yes_no_answer(sheet[40, 2]):
+                copy_locations = get_value_list_from_row(sheet, 41)
+                try:
+                    self.add_storage_locations(storage_locations, copy_locations, 'copy')
+                except ValueError as e:
+                    print('Uneven Copy Data Location Row {} \n'.format(full_file_path))
+
+            acl_list = get_value_list_from_row(sheet, 37)
+            if len(acl_list) > 0:
+                dataset_data['storage_acl_info'] = ', '.join(acl_list)
+            dataset_data['storage_locations'] = storage_locations
+            idx += 1
+
+            with open('datasets-{}.json'.format(submission_id), 'w') as outfile:
+                json.dump(dataset_data, outfile, indent=4)
+

metadata_tools/importxls/from_repo_exporter.py

+import pyexcel
+import json
+from .dataset_exporter import DatasetExporter
+from metadata_tools.importxls.export_utils import get_value_list_from_row, process_yes_no_answer, \
+    process_yes_no_dontknow_answer, process_possible_date
+
+
+class FromRepoXlsExporter(DatasetExporter):
+
+    def export(self, full_file_path):
+        submission_id = 'IMP_FR_{}'.format(self.get_hash_for_path(full_file_path))
+        idx = 1
+        print('Processing ----> {}'.format(full_file_path))
+        book = pyexcel.get_book(file_name=full_file_path)
+        while idx < book.number_of_sheets():
+            sheet = book.sheet_by_index(idx)
+            dataset_data = {}
+            dataset_data['source_type'] = 'From_Repository'
+            dataset_data['submission_id'] = submission_id
+            dataset_data['local_custodian'] = get_value_list_from_row(sheet, 2)
+            dataset_data['source_repository'] = self.lookup_institution_accession(sheet[6, 2].strip())
+
+            if sheet[4, 2]:
+                dataset_data['other_external_id'] = sheet[4, 2]
+
+            if sheet[5, 2]:
+                dataset_data['title'] = sheet[5, 2].strip()
+
+            if not dataset_data['title']:
+                print('Missing dataset title ----> {}'.format(full_file_path))
+
+            datatype_info = self.process_data_types(get_value_list_from_row(sheet, 7))
+            dataset_data['data_types'] = datatype_info[0]
+            if datatype_info[1]:
+                dataset_data['data_type_notes'] = datatype_info[1]
+            if datatype_info[1].__contains__('..'):
+                print('INVALID DATA TYPE NOTES----> {}'.format(full_file_path))
+
+            if sheet[8, 2]:
+                dataset_data['de_identification'] = sheet[8, 2]
+
+            if sheet[9, 2]:
+                dataset_data['subject_categories'] = sheet[9, 2].replace(' & ', '_and_')
+
+            if sheet[10, 2]:
+                dataset_data['has_special_subjects'] = process_yes_no_dontknow_answer(
+                    sheet[10, 2])
+
+            if dataset_data.get('has_special_subjects'):
+                if dataset_data.get('has_special_subjects') == True and sheet[11, 2]:
+                    dataset_data['special_subject_notes'] = sheet[11, 2]
+
+            if sheet[14, 2]:
+                dataset_data['access_category'] = sheet[14, 2]
+
+            dataset_data['used_by_projects'] = get_value_list_from_row(sheet, 19)
+
+            use_restrictions = []
+            if process_yes_no_answer(sheet[17, 2]):
+                use_restrictions.append({'ga4gh_code': 'PS',
+                                         'note': 'Contract restricts data use to projects ' + ', '.join(
+                                             get_value_list_from_row(sheet, 18))})
+
+            has_time_limis = process_yes_no_dontknow_answer(sheet[27, 2])