def test_taxon_rank_abbr(self):
dwc = darwincore.make_simple_darwin_record_set()
dwc.create_simple_darwin_record()
indexer = darwincore.SimpleDarwinRecordIndexer(dwc.simple_darwin_record)
self.assertEqual(indexer._get_taxon_rank_abbr(), '')
dwc.simple_darwin_record.taxon_rank = 'variety'
self.assertEqual(indexer._get_taxon_rank_abbr(), 'var.')
dwc.simple_darwin_record.taxon_rank = 'subspecies'
self.assertEqual(indexer._get_taxon_rank_abbr(), 'subsp.')
def __init__(self, record_type, field_data, parent_mods=None):
self.dataSeparator = u'||'
self._parent_mods = parent_mods
#dict for keeping track of which fields we've cleared out the parent
# info for. So we can have multiple columns in the spreadsheet w/ the same field.
self._cleared_fields = {}
self._record_type = record_type
if record_type == 'dwc':
self._xml_obj = darwincore.make_simple_darwin_record_set()
self._xml_obj.create_simple_darwin_record()
else:
if parent_mods:
self._xml_obj = parent_mods
else:
self._xml_obj = mods.make_mods()
for field in field_data:
self.add_data(field['xml_path'], field['data'])
def __init__(self, record_type, field_data, parent_mods=None):
self.dataSeparator = u'||'
self._parent_mods = parent_mods
#dict for keeping track of which fields we've cleared out the parent
# info for. So we can have multiple columns in the spreadsheet w/ the same field.
self._cleared_fields = {}
self._record_type = record_type
if record_type == 'dwc':
self._xml_obj = darwincore.make_simple_darwin_record_set()
self._xml_obj.create_simple_darwin_record()
else:
if parent_mods:
self._xml_obj = parent_mods
else:
self._xml_obj = mods.make_mods()
for field in field_data:
self.add_data(field['xml_path'], field['data'])
def test_create(self):
mets = make_mets()
#mods
mods_section = make_mods()
mods_section.title = 'sample'
mets.create_mods()
mets.mods = mods_section
#dwc
dwc_section = make_simple_darwin_record_set()
dwc_section.create_simple_darwin_record()
dwc_section.simple_darwin_record.catalog_number = 'catalog number'
mets.create_dwc()
mets.dwc = dwc_section
#ir
mets.create_ir()
mets.ir.filename = 'sample.txt'
#filesec -> filegrp
mets.create_filesec()
fg = FileGrp()
fg.id = u'GID1'
fg.use = u'image-tiff'
fi = File()
fi.admid = u'TMD1'
fi.groupid = u'GRP1'
fi.id = u'FID1'
fi.MIMETYPE = u'image/tiff'
fi.loctype = u'URL'
fi.href = u'/the/path.tif'
fg.file.append( fi )
mets.filesec.filegrp.append( fg )
#structMap
mets.create_structmap() # not used but required for valid mets
#serialize
created_string = mets.serialize( pretty=True )
#load
loaded = load_xmlobject_from_string(created_string, BDRMets)
#test
self.assertEqual(loaded.mods.title, 'sample')
self.assertEqual(loaded.dwc.simple_darwin_record.catalog_number, 'catalog number')
self.assertEqual(loaded.ir.filename, 'sample.txt')
self.assertEqual( type(loaded.structmap), StructMap )
self.assertEqual( loaded.filesec.filegrp[0].file[0].node.items(), [('ADMID', 'TMD1'), ('GROUPID', 'GRP1'), ('ID', 'FID1')] )
def setUp(self):
self.dwc = darwincore.make_simple_darwin_record_set()
