def new_dataset(spj, element):
ncols = int(element.attrib.pop('ncols',0))
typecodes = element.attrib.pop('typecodes','')
ds = Dataset(**element.attrib)
# metadata
for eMetaitem in element.findall('Metadata/Metaitem'):
key = eMetaitem.attrib['key']
value = eMetaitem.text
ds.metadata[key] = unicode(value)
# actual Table
if element.tag == 'Table':
# Extract additional column information.
# This information will be passed on to 'set_table_import',
# which will pass it on to the internal importer.
column_props = list()
for i in range(ncols):
column_props.append(dict())
for eColumn in element.findall('Column'):
n = int(eColumn.get('n'))
p = column_props[n]
for eInfo in eColumn.findall('Info'):
key = eInfo.get('key', None)
if key is not None:
p[key] = unicode(eInfo.text)
filename = os.path.join('datasets', dataset_filename(ds.key))
# TODO: replace DEFAULT_FF with read value
ds.set_table_import(spj, filename, typecodes, column_props, DEFAULT_FF)
return ds
def new_dataset(spj, element):
ds = Dataset(**element.attrib)
# metadata
for eMetaitem in element.findall('Metadata/Metaitem'):
key = eMetaitem.attrib['key']
value = eMetaitem.text
ds.metadata[key] = unicode(value)
# actual Table
if element.tag == 'Table':
### extract metadata special to Table objects
typecodes = element.get('typecodes', '')
# fill columns, if information is available
columns = list()
for tc in typecodes:
columns.append(Column(data=array((),tc)))
for eColumn in element.findall('Column'):
n = int(eColumn.get('n'))
column = columns[n]
for eInfo in eColumn.findall('Info'):
key = eInfo.get('key', None)
if key is not None:
column.set_value(key, eInfo.text)
filename = os.path.join('datasets', dataset_filename(ds.key))
# TODO: replace DEFAULT_FF with read value
ds.set_table_import(spj, filename, typecodes, columns, DEFAULT_FF)
return ds
