async def METHOD_NAME(self, sources: SourcesContext) -> None:
    # X and Y data
    x = []
    y = []
    # Go through all records that have the feature we're training on and the
    # feature we want to predict.
    async for record in sources.with_features(
        [self.config.features[0].name, self.config.predict.name]
    ):
        x.append(record.feature(self.config.features[0].name))
        y.append(record.feature(self.config.predict.name))
    # Use self.logger to report how many records are being used for training
    self.logger.debug("Number of training records: %d", len(x))
    # Save m, b, and accuracy
    self.storage["regression_line"] = best_fit_line(x, y)
    self.is_trained = True