def build_chart_data_for_field(xform,
field,
language_index=0,
choices=None,
group_by=None,
data_view=None):
# check if its the special _submission_time META
if isinstance(field, basestring):
field_label, field_xpath, field_type = FIELD_DATA_MAP.get(field)
else:
# TODO: merge choices with results and set 0's on any missing fields,
# i.e. they didn't have responses
field_label = get_field_label(field, language_index)
field_xpath = field.get_abbreviated_xpath()
field_type = field.type
data_type = DATA_TYPE_MAP.get(field_type, 'categorized')
field_name = field.name if not isinstance(field, basestring) else field
if group_by:
group_by_name = group_by.get_abbreviated_xpath() \
if not isinstance(group_by, basestring) else group_by
if (field_type == common_tags.SELECT_ONE or
field_name == common_tags.SUBMITTED_BY) and \
isinstance(group_by, six.string_types):
result = get_form_submissions_grouped_by_select_one(
xform, field_xpath, group_by_name, field_name, data_view)
elif field_type in common_tags.NUMERIC_LIST and \
isinstance(group_by, six.string_types):
result = get_form_submissions_aggregated_by_select_one(
xform, field_xpath, field_name, group_by_name, data_view)
elif (field_type == common_tags.SELECT_ONE or
field_name == common_tags.SUBMITTED_BY) and \
group_by.type == common_tags.SELECT_ONE:
result = get_form_submissions_grouped_by_select_one(
xform, field_xpath, group_by_name, field_name, data_view)
result = _flatten_multiple_dict_into_one(field_name, group_by_name,
result)
elif field_type in common_tags.NUMERIC_LIST \
and group_by.type == common_tags.SELECT_ONE:
result = get_form_submissions_aggregated_by_select_one(
xform, field_xpath, field_name, group_by_name, data_view)
else:
raise ParseError(u'Cannot group by %s' % group_by_name)
else:
result = get_form_submissions_grouped_by_field(xform, field_xpath,
field_name, data_view)
result = _use_labels_from_field_name(field_name,
field,
data_type,
result,
choices=choices)
if group_by and not isinstance(group_by, six.string_types):
group_by_data_type = DATA_TYPE_MAP.get(group_by.type, 'categorized')
grp_choices = get_field_choices(group_by, xform)
result = _use_labels_from_group_by_name(group_by_name,
group_by,
group_by_data_type,
result,
choices=grp_choices)
if not group_by:
result = sorted(result, key=lambda d: d['count'])
# for date fields, strip out None values
if data_type == 'time_based':
result = [r for r in result if r.get(field_name) is not None]
# for each check if it matches the timezone regexp and convert for js
for r in result:
if timezone_re.match(r[field_name]):
try:
r[field_name] = utc_time_string_for_javascript(
r[field_name])
except ValueError:
pass
return {
'data': result,
'data_type': data_type,
'field_label': field_label,
'field_xpath': field_xpath,
'field_name': field_name,
'field_type': field_type,
'grouped_by': group_by_name if group_by else None
}
def build_chart_data_for_field(xform,
field,
language_index=0,
choices=None,
group_by=None,
data_view=None):
# check if its the special _submission_time META
if isinstance(field, basestring):
field_label, field_xpath, field_type = FIELD_DATA_MAP.get(field)
else:
# TODO: merge choices with results and set 0's on any missing fields,
# i.e. they didn't have responses
field_label = get_field_label(field, language_index)
field_xpath = field.get_abbreviated_xpath()
field_type = field.type
data_type = DATA_TYPE_MAP.get(field_type, 'categorized')
field_name = field.name if not isinstance(field, basestring) else field
if group_by and isinstance(group_by, list):
group_by_name = [
g.get_abbreviated_xpath() if not isinstance(g, basestring) else g
for g in group_by
]
result = get_form_submissions_aggregated_by_select_one(
xform, field_xpath, field_name, group_by_name, data_view)
elif group_by:
group_by_name = group_by.get_abbreviated_xpath() \
if not isinstance(group_by, basestring) else group_by
if (field_type == common_tags.SELECT_ONE or
field_name == common_tags.SUBMITTED_BY) and \
isinstance(group_by, six.string_types):
result = get_form_submissions_grouped_by_select_one(
xform, field_xpath, group_by_name, field_name, data_view)
elif field_type in common_tags.NUMERIC_LIST and \
isinstance(group_by, six.string_types):
result = get_form_submissions_aggregated_by_select_one(
xform, field_xpath, field_name, group_by_name, data_view)
elif (field_type == common_tags.SELECT_ONE or
field_name == common_tags.SUBMITTED_BY) and \
group_by.type == common_tags.SELECT_ONE:
result = get_form_submissions_grouped_by_select_one(
xform, field_xpath, group_by_name, field_name, data_view)
result = _flatten_multiple_dict_into_one(field_name, group_by_name,
result)
elif field_type in common_tags.NUMERIC_LIST \
and group_by.type == common_tags.SELECT_ONE:
result = get_form_submissions_aggregated_by_select_one(
xform, field_xpath, field_name, group_by_name, data_view)
else:
raise ParseError('Cannot group by %s' % group_by_name)
else:
result = get_form_submissions_grouped_by_field(xform, field_xpath,
field_name, data_view)
result = _use_labels_from_field_name(
field_name, field, data_type, result, choices=choices)
if group_by and not isinstance(group_by, six.string_types + (list, )):
group_by_data_type = DATA_TYPE_MAP.get(group_by.type, 'categorized')
grp_choices = get_field_choices(group_by, xform)
result = _use_labels_from_group_by_name(
group_by_name,
group_by,
group_by_data_type,
result,
choices=grp_choices)
elif group_by and isinstance(group_by, list):
for g in group_by:
if isinstance(g, six.string_types):
continue
group_by_data_type = DATA_TYPE_MAP.get(g.type, 'categorized')
grp_choices = get_field_choices(g, xform)
result = _use_labels_from_group_by_name(
g.get_abbreviated_xpath(),
g,
group_by_data_type,
result,
choices=grp_choices)
if not group_by:
result = sorted(result, key=lambda d: d['count'])
# for date fields, strip out None values
if data_type == 'time_based':
result = [r for r in result if r.get(field_name) is not None]
# for each check if it matches the timezone regexp and convert for js
for r in result:
if timezone_re.match(r[field_name]):
try:
r[field_name] = utc_time_string_for_javascript(
r[field_name])
except ValueError:
pass
return {
'data': result,
'data_type': data_type,
'field_label': field_label,
'field_xpath': field_xpath,
'field_name': field_name,
'field_type': field_type,
'grouped_by': group_by_name if group_by else None
}
