def _load(self):
dir_info = self._data['connect_info'].get('directory')
file_n = self._data['connect_info'].get('file_name')
full_name = os.path.join(dir_info, file_n)
i = 0
with open(full_name, 'r') as txt_file:
csv_d_rdr = csv.DictReader(txt_file)
for r in csv_d_rdr:
if i == 0:
if not Helper.is_empty(self._data['key_columns']):
if not Helper.is_column_list_valid(
self._data['key_columns'], r.keys()):
self._logger.error(
'Specified primary keys don\'t match table columns'
)
raise Exception
self._add_row(r)
i = i + 1
if not Helper.is_empty(self._data['key_columns']):
if not self._check_primary_key_constraint_for_first_load():
self._rows = []
self._logger.error(
'The specified primary keys don\'t comply with primary key constraint'
)
raise Exception
self._logger.debug('CSVDataTable._load: Loaded ' +
str(len(self._rows)) + ' rows')
def find_by_template(self,
template,
field_list=None,
limit=None,
offset=None,
order_by=None):
'''
:param template: A dictionary of the form { 'field1' : value1, 'field2': value2, ...}
:param field_list: A list of request fields of the form, ['fielda', 'fieldb', ...]
:param limit: Do not worry about this for now.
:param offset: Do not worry about this for now.
:param order_by: Do not worry about this for now.
:return: A list containing dictionaries. A dictionary is in the list representing each record
that matches the template. The dictionary only contains the requested fields.
'''
if not Helper.is_empty(template):
if not Helper.is_template_valid(template, self.get_columns()):
self._logger.error(
'Some columns in the specified template don\'t match table columns'
)
raise Exception
if not Helper.is_empty(field_list):
if not Helper.is_column_list_valid(field_list, self.get_columns()):
self._logger.error(
'Some columns in the specified field_list don\'t match table columns'
)
raise Exception
matching_rows = []
for row in self.get_rows():
if limit is not None:
if len(matching_rows) == limit:
break
if Helper.matches_template(row, template):
matching_rows.append(
Helper.extract_needed_fields(field_list, row))
return matching_rows
