def execute(self, model_id, filename, actual_records):
if filename:
self.ctx.log('Sending actuals on data in %s' % filename)
if filename and not fsclient.is_s3_path(filename):
filename = os.path.abspath(filename)
return self._file_actual_to_cloud(filename, model_id)
else:
return self._actuals_to_cloud(actual_records, model_id)
def download_prediction_result(self, results, local_file):
for provider in results.keys():
result = results[provider]
predicted = dict_dig(result, 'data', 'predicted')
if predicted and type(predicted) == str and fsclient.is_s3_path(
predicted):
file_path = os.path.splitext(local_file)[0] + '_predicted.csv'
client = self.create_uploader()
client.download(predicted, file_path)
result['data']['predicted'] = file_path
self.ctx.log(f'{predicted} downloaded to {file_path}')
def load(self, path=None):
if path is None:
path = os.getcwd()
for pname in self.part_names:
filename = os.path.join(path, '%s.yaml' % pname)
if not fsclient.is_s3_path(filename):
filename = os.path.abspath(filename)
if fsclient.is_file_exists(filename):
self.parts[pname] = self._load(filename)
self.is_loaded = True
def verify(data_source_file, config_path=None):
if urllib.parse.urlparse(data_source_file).scheme in ['http', 'https']:
return data_source_file, False
if not fsclient.is_s3_path(data_source_file):
if config_path is None:
config_path = os.getcwd()
data_source_file = os.path.join(config_path, data_source_file)
if not fsclient.is_s3_path(data_source_file):
data_source_file = os.path.abspath(data_source_file)
filename, file_extension = os.path.splitext(data_source_file)
if not file_extension in SUPPORTED_FORMATS:
raise AugerException(
'Source file has to be one of the supported fomats: %s' %
', '.join(SUPPORTED_FORMATS))
if not fsclient.is_file_exists(data_source_file):
raise AugerException(
'Can\'t find file to import: %s' % data_source_file)
return data_source_file, True
def mk_project_folder(self):
if not self.ctx.config.path:
project_path = os.path.join(os.getcwd(), self.project_name)
else:
project_path = self.ctx.config.path
if not fsclient.is_s3_path(project_path):
project_path = os.path.abspath(project_path)
if fsclient.is_folder_exists(project_path):
raise Exception(
'Can\'t create \'%s\'. Folder already exists.' % \
self.project_name)
fsclient.create_folder(project_path)
self.ctx.log('Created project folder %s', self.project_name)
return project_path
def execute(self,
filename,
model_id,
threshold=None,
locally=False,
data=None,
columns=None,
output=None):
if filename and not fsclient.is_s3_path(filename):
self.ctx.log('Predicting on data in %s' % filename)
filename = os.path.abspath(filename)
if locally:
predicted = self._predict_locally(filename, model_id, threshold,
data, columns, output)
else:
predicted = self._predict_on_cloud(filename, model_id, threshold,
data, columns, output)
return predicted