def get_column_mapping(column_raw, organization, attr_name='column_mapped'):
"""Callable provided to MCM to return a previously mapped field.
:param column_raw: str, the column name of the raw data.
:param organization: Organization inst.
:param attr_name: str, name of attribute on ColumnMapping to pull out.
whether we're looking at a mapping from the perspective of
a raw_column (like we do when creating a mapping), or mapped_column,
(like when we're applying that mapping).
:returns: list of mapped items, float repreresentation of confidence.
"""
from seed.utils.mapping import _get_column_names
if not isinstance(column_raw, list):
column_raw = [column_raw]
cols = Column.objects.filter(
organization=organization, column_name__in=column_raw
)
try:
previous_mapping = ColumnMapping.objects.get(
super_organization=organization,
column_raw__in=cols,
)
except ColumnMapping.DoesNotExist:
return None
column_names = _get_column_names(previous_mapping, attr_name=attr_name)
if previous_mapping.is_direct():
column_names = column_names[0]
return column_names, 100
def get_column_mappings(organization):
"""Returns dict of all the column mappings for an Org's given source type
:param organization: inst, Organization.
:returns dict, list of dict:
Use this when actually performing mapping between datasources, but
only call it after all of the mappings have been saved to the
``ColumnMapping`` table.
"""
from seed.utils.mapping import _get_column_names
source_mappings = ColumnMapping.objects.filter(
super_organization=organization
)
concat_confs = []
mapping = {}
for item in source_mappings:
if not item.column_mapped.all().exists():
continue
key = _get_column_names(item)
value = _get_column_names(item, attr_name='column_mapped')[0]
if isinstance(key, list) and len(key) > 1:
concat_confs.append({
'concat_columns': key,
'target': value,
'delimiter': ' '
})
continue
# These should be lists of one element each.
mapping[key[0]] = value
return mapping, concat_confs
