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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 dataset
  • load_datasets(variables, resultMap, key) - Load multiple datasets
  • save_dataset(variables, resultMap, key, value) - Save a single dataset
  • save_datasets(variables, resultMap, key, values, file_names) - Save multiple datasets

Helpers

  • get_experiment_results(variables) - Get experiment results
  • load_dataset_by_path(file_path) - Load from specific path
  • load_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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