ParquetStorageHandler#
- class ParquetStorageHandler(path)[source]#
Storage handler for Parquet files, with ending .parquet.
Loads and saves results in Parquet format, as follows. Each result is stored as a row in a Parquet file with the following columns:
model_id: The ID of the model.validation_id: The ID of the validation run.folds: A dictionary of fold results,where each key is a fold ID and the value is a dictionary of scores and dataframes.
The results are stored in a tabular format, where each row corresponds to a single model-validation pair.
Columns are the following:
model_id: The ID of the model.validation_id: The ID of the validation run.folds.{fold_id}.scores.{score_name}: The score value for the given fold and score name.folds.{fold_id}.ground_truth: The ground truth dataframe for the given fold.folds.{fold_id}.predictions: The predictions dataframe for the given fold.folds.{fold_id}.train_data: The training data dataframe for the given fold.
Columns
ground_truth,predictions, andtrain_dataare included only if they were requested during benchmarking.- Parameters:
- pathstr or pathlib.Path
Path to the Parquet results file. Must refer to a file with a
.parquetextension, not a directory.
Methods
is_applicable(path)Return whether this handler supports the given results file path.
load()Load benchmark results from the file at
self.path.save(results)Save benchmark results to the Parquet file at
self.path.- save(results: list[ResultObject])[source]#
Save benchmark results to the Parquet file at
self.path.- Parameters:
- resultslist of ResultObject
Benchmark results to persist as one row per model-validation pair.
- static is_applicable(path)[source]#
Return whether this handler supports the given results file path.
- Parameters:
- pathpathlib.Path or None
Path to the results file, or
Nonefor NullStorageHandler. Must refer to a file, not a directory, when notNone.
- Returns:
- bool
Trueif this handler should be used forpath.