bin/extract_relevant_structured_data.py

from typing import Iterator, List, Dict, TypeVar
import json
import argparse
from concurrent.futures import ThreadPoolExecutor, ProcessPoolExecutor
from itertools import islice

import smart_open
from tqdm import tqdm
import jmespath

T = TypeVar("T")


def batch_iterator(iterator: Iterator[T], batch_size: int = 50) -> Iterator[List[T]]:
    iterator = iter(iterator)
    while True:
        batch = list(islice(iterator, batch_size))
        if not batch:
            return
        yield batch


def process_chunk(chunk: List, extractor: jmespath.parser.ParsedResult) -> List[Dict]:
    """
    Apply JMESPath to a chunk of JSONL data.
    """
    results: List[Dict] = []
    for line in chunk:
        data = json.loads(line)
        extracted = extractor.search(data)
        if extracted is not None:
            if not isinstance(extracted, list):
                extracted = [extracted]

            for item in extracted:
                item["url"] = data["url"]
                item["schema_type"] = data["schema_type"]
                results.append(item)
    return results


def process_file(
    input_file: str,
    output_file: str,
    chunk_size: int,
    num_threads: int,
    extractor: jmespath.parser.ParsedResult,
):
    """
    Apply JMESPath to a large JSONL file in parallel.
    input_file: path to input JSONL file
    output_file: path to output JSONL file
    chunk_size: number of lines to process at a time
    num_threads: number of threads to use
    extractor: compiled JMESPath expression to apply
    """
    with smart_open.open(input_file, "rt", encoding="utf-8") as reader, smart_open.open(
        output_file, "wt", encoding="utf-8"
    ) as writer:
        with ThreadPoolExecutor(max_workers=num_threads) as executor:
            for chunk in batch_iterator(tqdm(reader), batch_size=chunk_size):
                if not chunk:
                    break

                results = executor.map(process_chunk, [chunk], [extractor])
                for result in results:
                    for item in result:
                        writer.write(json.dumps(item, ensure_ascii=False))
                        writer.write("\n")


if __name__ == "__main__":
    parser = argparse.ArgumentParser(
        description="Apply JMESPath to a large JSONL file in parallel."
    )
    parser.add_argument("input_file", help="path to input JSONL file")
    parser.add_argument("output_file", help="path to output JSONL file")
    parser.add_argument(
        "--chunk-size",
        type=int,
        default=10000,
        help="number of lines to process at a time (default: 10000)",
    )
    parser.add_argument(
        "--num-threads",
        type=int,
        default=4,
        help="number of threads to use (default: 4)",
    )
    args = parser.parse_args()

    jmespath_expression: jmespath.parser.ParsedResult = jmespath.compile(
        """metadata.*[?"@type"=='FAQPage' || "@type"=='HowTo'][]"""
    )

    process_file(
        args.input_file,
        args.output_file,
        args.chunk_size,
        args.num_threads,
        jmespath_expression,
    )