Helper utilities for eexp_engine - supporting ProActive and Kubeflow execution environments
Project description
eexp_engine_utils
Helper utilities for the ExtremeXP Experimentation Engine that automatically adapt to different execution environments (Kubeflow, ProActive, Local).
Overview
This package provides a transparent proxy that automatically routes function calls to the appropriate implementation based on your execution environment. No more manual environment checking or conditional imports!
Installation
pip install eexp_engine_utils
Quick Start
from eexp_engine_utils import utils
# Load a dataset
data = utils.load_dataset(variables, resultMap, "input_data")
# Process your data
processed_data = your_processing_function(data)
# Save the result
utils.save_dataset(variables, resultMap, "output_data", processed_data)
That's it! The utils proxy automatically detects your execution environment and routes calls to the correct implementation.
Available Functions
Dataset Management
load_dataset(variables, resultMap, key)- Load a single datasetload_datasets(variables, resultMap, key)- Load multiple datasetssave_dataset(variables, resultMap, key, value)- Save a single datasetsave_datasets(variables, resultMap, key, values, file_names)- Save multiple datasets
Helpers
get_experiment_results(variables)- Get experiment resultsload_dataset_by_path(file_path)- Load from specific pathload_pickled_dataset_by_path(file_path)- Load pickled data
Requirements
- Python >= 3.8
- requests >= 2.25.0
- fsspec >= 2021.0.0
- s3fs >= 2021.0.0
- minio >= 7.0.0
License
Apache License 2.0
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