# /// script
# requires-python = ">=3.10"
# dependencies = [
#     "pyarrow>=15.0",
# ]
# ///
"""Convert parameter-golf docs_selected.jsonl to sharded Parquet files.

Reads the 45GB JSONL (15.3M docs with {"text": ...}), splits into
validation (first 50k) and train (remainder), and writes sharded
Parquet files in data/{split}-XXXXX-of-YYYYY.parquet layout that
the HuggingFace dataset viewer auto-detects.

Usage:
    uv run convert_to_parquet.py [--input PATH] [--output-dir PATH] [--rows-per-shard N]
"""

import argparse
import json
import math
import os
from pathlib import Path

import pyarrow as pa
import pyarrow.parquet as pq

DEFAULT_INPUT = os.path.expanduser(
    "~/.cache/huggingface/hub/datasets--willdepueoai--parameter-golf/"
    "snapshots/a85b0e6035c3c94bc23685a07c81a8f3bf89db80/"
    "datasets/docs_selected.jsonl"
)
DEFAULT_OUTPUT = os.path.expanduser("~/parameter-golf/data")
NUM_VAL_DOCS = 50_000
ROWS_PER_SHARD = 50_000

SCHEMA = pa.schema([("text", pa.string())])


def write_shard(rows: list[str], path: Path) -> None:
    table = pa.table({"text": rows}, schema=SCHEMA)
    pq.write_table(table, path, compression="zstd", row_group_size=200_000, write_page_index=True, use_content_defined_chunking=True)


def flush_split(
    rows: list[str],
    shard_idx: int,
    total_shards: int,
    split: str,
    out_dir: Path,
) -> None:
    name = f"{split}-{shard_idx:05d}-of-{total_shards:05d}.parquet"
    write_shard(rows, out_dir / name)


def count_lines(path: str) -> int:
    """Fast line count without loading whole file into memory."""
    count = 0
    with open(path, "rb") as f:
        while chunk := f.raw.read(1 << 20):
            count += chunk.count(b"\n")
    return count


def main() -> None:
    parser = argparse.ArgumentParser(description="Convert JSONL to sharded Parquet")
    parser.add_argument("--input", default=DEFAULT_INPUT, help="Path to docs_selected.jsonl")
    parser.add_argument("--output-dir", default=DEFAULT_OUTPUT, help="Output directory for parquet shards")
    parser.add_argument("--rows-per-shard", type=int, default=ROWS_PER_SHARD, help="Rows per parquet shard")
    parser.add_argument("--num-val-docs", type=int, default=NUM_VAL_DOCS, help="Number of validation documents (taken from start)")
    args = parser.parse_args()

    input_path = os.path.realpath(args.input)
    out_dir = Path(args.output_dir)
    out_dir.mkdir(parents=True, exist_ok=True)

    rows_per_shard = args.rows_per_shard
    num_val = args.num_val_docs

    print(f"Counting lines in {input_path} ...")
    total_docs = count_lines(input_path)
    num_train = total_docs - num_val
    print(f"Total docs: {total_docs:,}  (val: {num_val:,}, train: {num_train:,})")

    val_shards = math.ceil(num_val / rows_per_shard)
    train_shards = math.ceil(num_train / rows_per_shard)
    print(f"Shards — val: {val_shards}, train: {train_shards}")

    val_shard_idx = 0
    train_shard_idx = 0
    buf: list[str] = []
    line_no = 0

    with open(input_path, "r") as f:
        for raw_line in f:
            text = json.loads(raw_line)["text"]
            buf.append(text)
            line_no += 1

            if line_no <= num_val:
                # Validation split
                if len(buf) == rows_per_shard or line_no == num_val:
                    flush_split(buf, val_shard_idx, val_shards, "validation", out_dir)
                    print(f"  wrote validation shard {val_shard_idx + 1}/{val_shards}")
                    val_shard_idx += 1
                    buf = []
            else:
                # Train split
                if len(buf) == rows_per_shard or line_no == total_docs:
                    flush_split(buf, train_shard_idx, train_shards, "train", out_dir)
                    if (train_shard_idx + 1) % 20 == 0 or line_no == total_docs:
                        print(f"  wrote train shard {train_shard_idx + 1}/{train_shards}")
                    train_shard_idx += 1
                    buf = []

    # Flush any remaining rows (shouldn't happen if counts are exact)
    if buf:
        if train_shard_idx < train_shards:
            flush_split(buf, train_shard_idx, train_shards, "train", out_dir)
            print(f"  wrote final train shard {train_shard_idx + 1}/{train_shards}")

    print(f"\nDone! Wrote {val_shard_idx} validation + {train_shard_idx} train shards to {out_dir}")


if __name__ == "__main__":
    main()