def transform_filter_to_statement(filters, schema):
new_filter = {}
schema_dict = {}
for field in schema:
schema_dict[field['id']] = field
for key in filters.keys():
if key in LOGICAL_OPERATORS:
new_filter[key] = filters[key]
elif type(filters[key]) is list:
values = []
if schema_dict[key]['type'] in NUMERIC_TYPES:
for val in filters[key]:
try:
values.append(float(val))
except TypeError:
values.append(val)
else:
values = filters[key]
new_filter[key] = {'$in': values}
elif type(filters[key]) is dict:
new_filter[key] = filters[key]
else:
if schema_dict[key]['type'] in NUMERIC_TYPES and type(
filters[key]) == str:
try:
if filters[key].startswith('<='):
value = TYPE_CONVERSION_DICT[schema_dict[key]['type']](
filters[key][2:])
new_filter[key] = {'$lte': value}
elif filters[key].startswith('>='):
value = TYPE_CONVERSION_DICT[schema_dict[key]['type']](
filters[key][2:])
new_filter[key] = {'$gte': value}
elif filters[key].startswith('<'):
value = TYPE_CONVERSION_DICT[schema_dict[key]['type']](
filters[key][1:])
new_filter[key] = {'$lt': value}
elif filters[key].startswith('>'):
value = TYPE_CONVERSION_DICT[schema_dict[key]['type']](
filters[key][1:])
new_filter[key] = {'$gt': value}
else:
new_filter[key] = TYPE_CONVERSION_DICT[
schema_dict[key]['type']](filters[key])
except TypeError:
new_filter[key] = filters[key]
else:
try:
new_filter[key] = TYPE_CONVERSION_DICT[
schema_dict[key]['type']](filters[key])
except TypeError:
new_filter[key] = filters[key]
return normalize_json(new_filter)
def transform_query_to_statement(query, schema):
new_filter = {'$or': []}
if type(query) == dict:
for key in query.keys():
new_filter['$or'].append({key: {'$regex': query[key]}})
return new_filter
for field in schema:
if field['type'] == 'text':
new_filter['$or'].append({field['id']: {'$regex': query}})
return normalize_json(new_filter)
def transform_projection(fields, schema):
new_projection = {}
if fields is None:
fields = []
if type(fields) is not list:
fields = fields.split(',')
for field in schema:
if len(fields) == 0 or field['id'] in fields:
new_projection[field['id']] = 1
new_projection['_id'] = 0
return normalize_json(new_projection)
def test_normalize_deep_json(self):
result = normalize_json(DEEP_DICT)
expected_result = '{"address": {"city": "testcity", "country": "at", "street": "teststreet 123", "zip": "1234"}, "firstname": "Florian", "id": 1, "lastname": "Woerister", "mailaddresses": ["*****@*****.**", "*****@*****.**"]}'
assert json.dumps(result) == expected_result
def test_normalize_flat_json(self):
result = normalize_json(FLAT_DICT)
expected_result = '{"firstname": "Florian", "id": 1, "lastname": "Woerister"}'
assert json.dumps(result) == expected_result