def map_survey(survey_filename, map_filename):
if map_filename != '':
survey.qa = survey.qa_map(map_filename)
survey_name = os.path.splitext(survey_filename)[0].split('-', 1)[0].strip()
ml_file = 'data/' + survey_filename
survey_df = pd.read_csv(ml_file, sep=';', encoding='ISO-8859-1', low_memory=False)
survey_df.fillna(0, inplace=True)
field_map, col_map, header_map = survey.map_columns(survey_name, survey_df.columns)
return field_map, col_map, header_map
def load_survey1(request, survey_filename, map_filename):
if map_filename != '':
survey.qa = survey.qa_map(map_filename)
survey_name = os.path.splitext(survey_filename)[0].split('-', 1)[0].strip()
ml_file = 'data/' + survey_filename
converters = {}
survey_df = pd.read_csv(ml_file,
sep=';',
encoding='ISO-8859-1',
low_memory=False,
dtype=object)
# col_map[column]: (field, question, answer, dashboard)
# field_map[field]: [question=0, answer=1, column=2, field_type=3)]
field_map, col_map, header_map = survey.map_columns(
survey_name, survey_df.columns)
converters = {}
for col, map in col_map.items():
if map[3] == 'text':
converters[col] = str
survey_df = pd.read_csv(ml_file,
sep=';',
encoding='ISO-8859-1',
low_memory=False,
converters=converters)
survey_df.fillna(0, inplace=True)
survey_df.index = survey_df[field_map['resp_id'][0][2]]
bulk_data = []
count = 0
total_count = 0
for resp_id, survey_s in survey_df.iterrows():
resp_id = survey.answer_value_to_string(
survey_s[field_map['resp_id'][0][2]])
blindcode = survey.answer_value_to_string(
survey_s[field_map['blindcode'][0][2]])
#sl = models.SurveyMap()
#sl.resp_id = resp_id+"_"+blindcode
#sl.survey = survey_name
data = {}
#data['_id'] = resp_id+"_"+blindcode
#data['resp_id'] = resp_id+"_"+blindcode
#data['survey'] = survey_name
for field, maps in field_map.items():
# resp_id is the unique id of the record, this is already set above
#if field == 'resp_id':
# continue
# map: 0=question, 1=answer, 2=column, 3=field_type, 4=keys
map = maps[0]
answer_value = survey_s[map[2]]
answer_value = survey.answer_value_to_string(answer_value)
answer_value = survey.answer_value_encode(map[0], map[1], field,
answer_value)
answer_values = [answer_value]
# column mapping, no question
if map[0] == None:
# in case of multiple mapping search for the column that has a value
for ix in range(1, len(maps)):
map = maps[ix]
answer_value_2 = survey_s[map[2]]
answer_value_2 = survey.answer_value_to_string(
answer_value_2)
answer_values.append(answer_value_2)
if (field == 'blindcode'):
if answer_value_2 != '':
answer_value = answer_value + '-' + answer_value_2[:
3]
else:
if len(answer_value_2) > len(answer_value):
answer_value = answer_value_2
if map[3] == 'dict':
answer_value = survey.answer_values_dict(
answer_values, map[4])
#setattr(sl, field, answer_value)
elastic.convert_field(data, field, map, answer_value)
# question mapping, no answer
elif map[1][0] == '_':
#setattr(sl, field, answer_value)
elastic.convert_field(data, field, map, answer_value)
# answer mapping
else:
#setattr(sl, field, {map[1]: answer_value})
#attr = getattr(sl, field)
for ix in range(0, len(maps)):
map = maps[ix]
answer_value = survey_s[map[2]]
answer_value = survey.answer_value_to_string(answer_value)
answer_value = survey.answer_value_encode(
map[0], map[1], field, answer_value)
#attr[map[1]] = answer_value
##attr.append({map[1]: answer_value})
elastic.convert_field(data, field, map, answer_value)
#data = elastic.convert_for_bulk(sl, 'update')
survey.map_header(request, survey_name, data)
data['_id'] = survey.map_id(survey_name, data)
data = elastic.convert_data_for_bulk(data, 'survey', 'survey',
'update')
bulk_data.append(data)
count = count + 1
if count > 100:
bulk(models.client, actions=bulk_data, stats_only=True)
total_count = total_count + count
print("crawl_survey: written another batch, total written {0:d}".
format(total_count))
bulk_data = []
count = 1
#break
bulk(models.client, actions=bulk_data, stats_only=True)
pass