notebooks/src/utils/app_utils.py

"""
App-level utility functions for PopulationHealthScreener.

Import these at the top of the notebook before building any widgets.
"""


def silence_libraries():
    """
    Suppress verbose output from ML libraries before model loading.

    Call once at startup. Sets TRANSFORMERS_VERBOSITY=error,
    TQDM_DISABLE=1, and raises the log level for transformers and torch
    to ERROR so they stay quiet during inference.
    """
    import warnings, os, logging
    warnings.filterwarnings("ignore")
    os.environ['TRANSFORMERS_VERBOSITY'] = 'error'
    os.environ['TQDM_DISABLE'] = '1'
    logging.getLogger("transformers").setLevel(logging.ERROR)
    logging.getLogger("torch").setLevel(logging.ERROR)


def exec_script(path, inputs):
    """
    Run a script from disk inside a fresh namespace.

    Pass inputs as a dict — the script reads them via globals().get().
    The script's local variables stay in the returned namespace;
    nothing bleeds into the caller's scope.

        ns = exec_script('src/search_pubmed.py', {'query_selector': qs, ...})
        table = ns['articles_table']
    """
    import os
    ns = dict(inputs)
    with open(os.path.abspath(os.path.join(os.getcwd(), path))) as f:
        exec(f.read(), ns)
    return ns