test-driver: Parallelize OCR

import itertools

import multiprocessing

import os

import shutil

import subprocess

    Perform OCR on a screenshot that contains text.

    Returns a string with all words that could be found.

    """

    return perform_ocr_variants_on_screenshot(screenshot_path, False)[0]

    variants = perform_ocr_variants_on_screenshot(screenshot_path, False)[0]

    if len(variants) != 1:

        raise MachineError(f"Received wrong number of OCR results: {len(variants)}")

    return variants[0]

def perform_ocr_variants_on_screenshot(

    #  1|lstm_only               Neural nets LSTM engine only.

    #  2|tesseract_lstm_combined Legacy + LSTM engines.

    #  3|default                 Default, based on what is available.

    model_ids: list[int] = [0, 1, 2] if variants else [3]

    model_ids: list[int] = [0, 1] if variants else [2]

    # Tesseract runs parallel on up to 4 cores.

    # Docs suggest to run it with OMP_THREAD_LIMIT=1 for hundreds of parallel

    # runs. Our average test run is somewhere inbetween.

    # https://github.com/tesseract-ocr/tesseract/issues/3109

    processes = max(1, int(os.process_cpu_count() / 4))

    with multiprocessing.Pool(processes=processes) as pool:

        image_paths: list[str] = [screenshot_path]

        if variants:

            image_paths.extend(

                pool.starmap(

                    _preprocess_screenshot,

                    [(screenshot_path, False), (screenshot_path, True)],

                )

            )

        return pool.starmap(_run_tesseract, itertools.product(image_paths, model_ids))

    image_paths = [

        screenshot_path,

        _preprocess_screenshot(screenshot_path, negate=False),

        _preprocess_screenshot(screenshot_path, negate=True),

    ]

    def run_tesseract(image: str, model_id: int) -> str:

def _run_tesseract(image: str, model_id: int) -> str:

    ret = subprocess.run(

        [

            "tesseract",

        raise MachineError(f"OCR failed with exit code {ret.returncode}")

    return ret.stdout.decode("utf-8")

    return [

        run_tesseract(image, model_id)

        for image in image_paths

        for model_id in model_ids

    ]

def _preprocess_screenshot(screenshot_path: str, negate: bool = False) -> str:

    if shutil.which("magick") is None: