def reload_configuration()

in mozetl/taar/taar_ensemble.py [0:0]
39 lines of code
2 McCabe index (conditional complexity)

def reload_configuration():
    """
    Configuration needs to be reloaded on a per worker node basis.
    This is an unfortunate a side effect of re-using the TAAR library which
    expects to be using python-decouple to load the configuration
    from enviroment variables.
    """
    from taar.recommenders import s3config

    # Locale Recommender Overrides
    # This *Must* be called just prior to instantiating the individual recommenders in the
    # ETL enviroment.
    s3config.TAAR_LOCALE_BUCKET = os.environ["TAAR_LOCALE_BUCKET"] = "telemetry-parquet"
    s3config.TAAR_LOCALE_KEY = os.environ[
        "TAAR_LOCALE_KEY"
    ] = "taar/locale/top10_dict.json"

    # Similarity Recommender configuration overrides
    s3config.TAAR_SIMILARITY_BUCKET = os.environ[
        "TAAR_SIMILARITY_BUCKET"
    ] = "telemetry-parquet"
    s3config.TAAR_SIMILARITY_DONOR_KEY = os.environ[
        "TAAR_SIMILARITY_DONOR_KEY"
    ] = "taar/similarity/donors.json"
    s3config.TAAR_SIMILARITY_LRCURVES_KEY = os.environ[
        "TAAR_SIMILARITY_LRCURVES_KEY"
    ] = "taar/similarity/lr_curves.json"

    # Collaborative Recommender Overrides
    s3config.TAAR_ITEM_MATRIX_BUCKET = os.environ[
        "TAAR_ITEM_MATRIX_BUCKET"
    ] = "telemetry-public-analysis-2"
    s3config.TAAR_ITEM_MATRIX_KEY = os.environ[
        "TAAR_ITEM_MATRIX_KEY"
    ] = "telemetry-ml/addon_recommender/item_matrix.json"
    s3config.TAAR_ADDON_MAPPING_BUCKET = os.environ[
        "TAAR_ADDON_MAPPING_BUCKET"
    ] = "telemetry-public-analysis-2"
    s3config.TAAR_ADDON_MAPPING_KEY = os.environ[
        "TAAR_ADDON_MAPPING_KEY"
    ] = "telemetry-ml/addon_recommender/addon_mapping.json"

    from taar.recommenders import LocaleRecommender
    from taar.recommenders import SimilarityRecommender
    from taar.recommenders import CollaborativeRecommender

    reload(sys.modules["taar.recommenders"])

    # Force reload of recommender modules
    [
        reload(sys.modules[rec_cls.__module__])
        for rec_cls in [
            LocaleRecommender,
            SimilarityRecommender,
            CollaborativeRecommender,
        ]
    ]