data_to_parquet.py

from pathlib import Path
import pyarrow as pa
import pyarrow.parquet as pq
import sys
import json
import time

from questions_tar_extract import extract_articles
from brute import prepare_with_ripgrep

file_structure_schema = pa.schema([
                                  ('path', pa.string()),
                                  ('content', pa.large_string())
                                  ])

extracted_schema = pa.schema([
                             ('question_score', pa.string()),
                             ('title', pa.string()),
                             ('question_userid', pa.string()),
                             ('question_user', pa.string()),
                             ('question_user_score', pa.string()),
                             ('question_datetime', pa.string()),
                             ('question', pa.string()),
                             ('question_id', pa.string()),
                             ('answer_count', pa.string()),
                             ('answer_id', pa.string()),
                             ('answer_score', pa.string()),
                             ('answer_userid', pa.string()),
                             ('answer_user', pa.string()),
                             ('answer_user_score', pa.string()),
                             ('answer_datetime', pa.string()),
                             ('answer', pa.string())
                             ])

extracted_src_key_order = ["qscore","title","quserid","quser","quserscore","qdatetime","question","qid","answercount","aid","ascore","auserid","auser","auserscore","adatetime","answer"]

script_dir = Path(__file__).resolve().parent

if __name__ == '__main__':
    articles = extract_articles()

    scraped_files_root = articles.name + "_raw"
    
    article_pq_inputs = [[],[]]
    for a in articles.iterdir():
        a = next(next(a.iterdir()).iterdir())
        with open(a, "r") as f:
            content = f.read()
        article_pq_inputs[0].append(str(a))
        article_pq_inputs[1].append(content)

    article_table = pa.Table.from_arrays(article_pq_inputs, schema=file_structure_schema)
    
    pq.write_table(article_table, f"{scraped_files_root}.snappy.parquet", compression='Snappy')

    article_pq_file = Path(f"{scraped_files_root}.snappy.parquet")

    print(f"wrote to cwd: {scraped_files_root}.snappy.parquet ({article_pq_file.stat().st_size / (1024 * 1024):.2f} MiB)")

    extract_file_path = script_dir / "data.jsonl"
    extract_pq_inputs: list[dict[str, str]] | list[list[str]] | None = None
    if not extract_file_path.is_file():
        try:
            rem_attempts = 2
            while rem_attempts > 0:
                user_input = input(f"extracted data not found at {extract_file_path}. run extraction (need ripgrep)? [y/N] ").strip().lower()

                if not user_input or user_input in ['n', 'no']:
                    print("warning: parquet conversion only partially completed because extracted data could not be prepared.")
                    sys.exit(0)
                elif user_input in ['y', 'yes']:
                    chunk_array = prepare_with_ripgrep()
                    with open(script_dir / "data.jsonl", 'w', encoding='utf-8') as f:
                        f.write("\n".join(chunk_array))
                    extract_pq_inputs = list(map(json.loads, chunk_array))
                    break
                else:
                    print(f"warning: unknown response '{user_input if len(user_input) < 4 else f"{user_input[:3]}..."}'. remaining attempts: {rem_attempts}")
                    time.sleep(0.5)
                    rem_attempts -= 1
            if rem_attempts == 0:
                print("fatal: failed to move on after a few attempts")
                sys.exit(1)
        except KeyboardInterrupt:
            print("fatal: received KeyboardInterrupt")
            sys.exit(1)
    else:
        with open(extract_file_path, 'r', encoding='utf-8') as f:
            extract_pq_inputs = list(map(json.loads, f))

    assert extract_pq_inputs is not None

    _extract_pq_inputs = [[] for k in extracted_src_key_order]
    for j, k_j in enumerate(extracted_src_key_order):
        for i in range(len(extract_pq_inputs)):
            _extract_pq_inputs[j].append(extract_pq_inputs[i][k_j])
    extract_pq_inputs = _extract_pq_inputs
            
    extract_table = pa.Table.from_arrays(extract_pq_inputs, schema=extracted_schema)

    pq.write_table(extract_table, "data.snappy.parquet", compression='Snappy')
    
    extract_pq_file = Path("data.snappy.parquet")

    print(f"wrote to cwd: data.snappy.parquet ({extract_pq_file.stat().st_size / (1024 * 1024):.2f} MiB)")