import json from pathlib import Path from time import perf_counter from typing import Any, Dict from tqdm.auto import tqdm def folder_to_json(folder_in: Path, folder_out: Path, json_file_name: str): """ Process JSON lines from files in a given folder and write processed data to new ndjson files. Parameters: folder_in (Path): Path to the input folder containing the JSON files to process. folder_out (Path): Path to the output folder for processed ndjson json_file_name (str): Filename The files will be named as {json_base_path}_1.ndjson, {json_base_path}_2.ndjson, and so on. Example: folder_to_json(Path("/path/to/input/folder"), Path("/path/to/output/folder"), "ar_wiki") """ json_out = [] # Initialize list to hold processed JSON data from all files file_counter = 1 # Counter to increment file names process_start = perf_counter() all_files = sorted(folder_in.rglob('*wiki*'), key=lambda x: str(x)) with tqdm(total=len(all_files), desc='Processing', unit='file') as pbar: for file_path in all_files: pbar.set_postfix_str(f"File: {file_path.name} | Dir: {file_path.parent}", refresh=True) with open(file_path, 'r', encoding='utf-8') as f: for line in f: article = json.loads(line) json_out.append(restructure_articles(article)) # If size of json_out is 100,000, dump to file and clear list if len(json_out) == 100_000: append_to_file(json_out, folder_out / f"{json_file_name}_{file_counter}.ndjson") json_out.clear() file_counter += 1 pbar.update(1) if json_out: # Dump any remaining items in json_out to file append_to_file(json_out, folder_out / f"{json_file_name}_{file_counter}.ndjson") time_taken_to_process = perf_counter() - process_start pbar.write(f"Wiki processed in {round(time_taken_to_process, 2)} seconds!") def append_to_file(data: list, path: Path): with open(path, 'w', encoding='utf-8') as outfile: for item in data: json.dump(item, outfile) outfile.write('\n') def restructure_articles(article: Dict[str, Any]) -> Dict[str, Any]: """ Restructures the given article into haystack's format, separating content and meta data. Args: - article (Dict[str, Any]): The article to restructure. Returns: - Dict[str, Any]: The restructured article. """ # Extract content and separate meta data article_out = { 'content': article['text'], 'meta': {k: v for k, v in article.items() if k != 'text'} } return article_out if __name__ == '__main__': proj_dir = Path(__file__).parents[2] folder = proj_dir / 'data/raw/output' file_out = proj_dir / 'data/consolidated/ar_wiki.json' folder_to_json(folder, file_out) print('Done!')