def get_time_series(self, time_series, query_string='', shared_username=None, shared_api_key=None): """Retrieves a time series. The model parameter should be a string containing the time series id or the dict returned by create_time_series. As a time series is an evolving object that is processed until it reaches the FINISHED or FAULTY state, the function will return a dict that encloses the time series values and state info available at the time it is called. If this is a shared time series, the username and sharing api key must also be provided. """ check_resource_type(time_series, TIME_SERIES_PATH, message="A time series id is needed.") time_series_id = get_time_series_id(time_series) if time_series_id: return self._get("%s%s" % (self.url, time_series_id), query_string=query_string, shared_username=shared_username, shared_api_key=shared_api_key)
def create_forecast(self, time_series, input_data=None, args=None, wait_time=3, retries=10): """Creates a new forecast. """ time_series_id = get_time_series_id(time_series) resource_type = get_resource_type(time_series_id) if resource_type == TIME_SERIES_PATH and time_series_id is not None: check_resource(time_series_id, query_string=TINY_RESOURCE, wait_time=wait_time, retries=retries, raise_on_error=True, api=self) else: raise Exception("A time series model id is needed to create a" " forecast. %s found." % resource_type) if input_data is None: input_data = {} create_args = {} if args is not None: create_args.update(args) create_args.update({ "input_data": input_data}) if time_series_id is not None: create_args.update({ "timeseries": time_series_id}) body = json.dumps(create_args) return self._create(self.forecast_url, body, verify=self.verify_prediction)
def delete_time_series(self, time_series): """Deletes a time series. """ check_resource_type(time_series, TIME_SERIES_PATH, message="A time series id is needed.") time_series_id = get_time_series_id(time_series) if time_series_id: return self._delete("%s%s" % (self.url, time_series_id))
def update_time_series(self, time_series, changes): """Updates a time series. """ check_resource_type(time_series, TIME_SERIES_PATH, message="A time series id is needed.") time_series_id = get_time_series_id(time_series) if time_series_id: body = json.dumps(changes) return self._update("%s%s" % (self.url, time_series_id), body)
def update_time_series(self, time_series, changes): """Updates a time series. """ check_resource_type(time_series, TIME_SERIES_PATH, message="A time series id is needed.") time_series_id = get_time_series_id( time_series) if time_series_id: body = json.dumps(changes) return self._update( "%s%s" % (self.url, time_series_id), body)
def get_time_series(self, time_series, query_string='', shared_username=None, shared_api_key=None): """Retrieves a time series. The model parameter should be a string containing the time series id or the dict returned by create_time_series. As a time series is an evolving object that is processed until it reaches the FINISHED or FAULTY state, the function will return a dict that encloses the time series values and state info available at the time it is called. If this is a shared time series, the username and sharing api key must also be provided. """ check_resource_type(time_series, TIME_SERIES_PATH, message="A time series id is needed.") time_series_id = get_time_series_id( time_series) if time_series_id: return self._get("%s%s" % (self.url, time_series_id), query_string=query_string, shared_username=shared_username, shared_api_key=shared_api_key)