"""Import a historical Hugging Face dataset checkpoint into a clean snapshot.

This is mainly for legacy datasets that kept their richest data under
`_checkpoints/<snapshot_id>/...` instead of promoting the latest full snapshot
to the dataset root.

The importer:

1. selects a checkpoint from a source HF dataset repo
2. downloads the checkpoint parquet files
3. rewrites small tables to the current local schema when needed
4. regenerates derived artifacts (`links`, `issue_comments`, `pr_comments`)
5. writes a normal local snapshot directory that `analyze` / `pr-scope` can use
6. optionally republishes that clean snapshot
"""

from __future__ import annotations

import re
import shutil
from collections import defaultdict
from collections.abc import Mapping
from datetime import UTC, datetime
from pathlib import Path
from typing import Any

from huggingface_hub import HfApi, hf_hub_download

from slop_farmer.app.publish_dataset_snapshot import publish_dataset_snapshot
from slop_farmer.config import CheckpointImportOptions
from slop_farmer.data.dataset_card import build_hf_dataset_card
from slop_farmer.data.links import build_pr_duplicate_candidate_rows, build_text_link_rows
from slop_farmer.data.parquet_io import (
    SCHEMAS,
    read_json,
    read_parquet_rows,
    write_json,
    write_parquet,
    write_text,
)

CHECKPOINT_PATH_PATTERN = re.compile(
    r"^(?P<root>_?checkpoints)/(?P<snapshot_id>[^/]+)/(?P<filename>[^/]+)$"
)
REQUIRED_CHECKPOINT_FILES = (
    "issues.parquet",
    "pull_requests.parquet",
    "comments.parquet",
    "reviews.parquet",
    "review_comments.parquet",
    "pr_files.parquet",
    "pr_diffs.parquet",
    "events.parquet",
)
SMALL_TABLES = (
    "issues",
    "pull_requests",
    "comments",
    "reviews",
    "review_comments",
    "events",
)
COPIED_TABLES = (
    "pr_files",
    "pr_diffs",
)

__all__ = [
    "import_hf_checkpoint",
    "materialize_checkpoint_snapshot",
]


def import_hf_checkpoint(options: CheckpointImportOptions) -> Path:
    api = HfApi()
    siblings = [
        sibling.rfilename
        for sibling in api.dataset_info(repo_id=options.source_repo_id).siblings or []
    ]
    checkpoint_root, checkpoint_id = _select_checkpoint(
        siblings,
        checkpoint_id=options.checkpoint_id,
        checkpoint_root=options.checkpoint_root,
    )
    checkpoint_files = {
        filename: Path(
            hf_hub_download(
                repo_id=options.source_repo_id,
                repo_type="dataset",
                filename=f"{checkpoint_root}/{checkpoint_id}/{filename}",
            )
        )
        for filename in REQUIRED_CHECKPOINT_FILES
    }
    source_manifest = _maybe_download_json(options.source_repo_id, "manifest.json")
    source_progress = _maybe_download_json(
        options.source_repo_id, f"{checkpoint_root}/{checkpoint_id}/progress.json"
    )
    snapshot_dir = materialize_checkpoint_snapshot(
        checkpoint_files,
        output_root=options.output_dir,
        source_repo_id=options.source_repo_id,
        checkpoint_root=checkpoint_root,
        checkpoint_id=checkpoint_id,
        source_manifest=source_manifest,
        source_progress=source_progress,
        force=options.force,
    )
    if options.publish_repo_id:
        publish_dataset_snapshot(
            snapshot_dir, options.publish_repo_id, private=options.private_hf_repo
        )
    return snapshot_dir


def materialize_checkpoint_snapshot(
    checkpoint_files: Mapping[str, Path],
    *,
    output_root: Path,
    source_repo_id: str,
    checkpoint_root: str,
    checkpoint_id: str,
    source_manifest: Mapping[str, Any] | None = None,
    source_progress: Mapping[str, Any] | None = None,
    force: bool = False,
) -> Path:
    source_manifest = dict(source_manifest or {})
    source_progress = dict(source_progress or {})
    output_root = output_root.resolve()
    snapshot_dir = output_root / "snapshots" / _snapshot_dir_name(source_repo_id, checkpoint_id)
    if snapshot_dir.exists():
        if not force:
            raise FileExistsError(f"Snapshot already exists: {snapshot_dir}")
        shutil.rmtree(snapshot_dir)
    snapshot_dir.mkdir(parents=True, exist_ok=True)

    rows_by_table: dict[str, list[dict[str, Any]]] = {}
    for table_name in SMALL_TABLES:
        rows = read_parquet_rows(checkpoint_files[f"{table_name}.parquet"])
        rows_by_table[table_name] = _project_rows(rows, table_name)
        write_parquet(rows_by_table[table_name], snapshot_dir / f"{table_name}.parquet", table_name)

    for table_name in COPIED_TABLES:
        shutil.copy2(
            checkpoint_files[f"{table_name}.parquet"], snapshot_dir / f"{table_name}.parquet"
        )

    repo_slug = _resolve_repo(rows_by_table, source_manifest, source_progress)
    extracted_at = _resolve_extracted_at(rows_by_table, source_manifest)
    link_rows = _derived_link_rows(
        repo_slug=repo_slug,
        snapshot_id=checkpoint_id,
        extracted_at=extracted_at,
        issues=rows_by_table["issues"],
        pull_requests=rows_by_table["pull_requests"],
        comments=rows_by_table["comments"],
        reviews=rows_by_table["reviews"],
        review_comments=rows_by_table["review_comments"],
        events=rows_by_table["events"],
    )
    write_parquet(link_rows, snapshot_dir / "links.parquet", "links")

    issue_comment_rows, pr_comment_rows = _viewer_comment_rows(
        rows_by_table["comments"], rows_by_table["pull_requests"]
    )
    write_parquet(issue_comment_rows, snapshot_dir / "issue_comments.parquet", "comments")
    write_parquet(pr_comment_rows, snapshot_dir / "pr_comments.parquet", "comments")

    manifest = {
        "repo": repo_slug,
        "snapshot_id": checkpoint_id,
        "extracted_at": extracted_at,
        "imported_at": _iso_now(),
        "source_type": "hf_checkpoint_import",
        "source_hf_repo_id": source_repo_id,
        "source_checkpoint_root": checkpoint_root,
        "source_checkpoint_id": checkpoint_id,
        "source_manifest": source_manifest,
        "source_progress": source_progress,
        "counts": {
            "issues": len(rows_by_table["issues"]),
            "pull_requests": len(rows_by_table["pull_requests"]),
            "comments": len(rows_by_table["comments"]),
            "reviews": len(rows_by_table["reviews"]),
            "review_comments": len(rows_by_table["review_comments"]),
            "pr_files": _parquet_row_count(snapshot_dir / "pr_files.parquet"),
            "pr_diffs": _parquet_row_count(snapshot_dir / "pr_diffs.parquet"),
            "timeline_events": len(rows_by_table["events"]),
            "links": len(link_rows),
        },
        "notes": (
            "Imported from a remote HF dataset checkpoint and regenerated locally derived link/comment views."
        ),
    }
    write_json(manifest, snapshot_dir / "manifest.json")
    write_text(
        _dataset_card(repo_slug, checkpoint_id, source_repo_id, checkpoint_root),
        snapshot_dir / "README.md",
    )
    return snapshot_dir


def _select_checkpoint(
    sibling_paths: list[str],
    *,
    checkpoint_id: str | None,
    checkpoint_root: str | None,
) -> tuple[str, str]:
    candidates: defaultdict[tuple[str, str], set[str]] = defaultdict(set)
    for path in sibling_paths:
        match = CHECKPOINT_PATH_PATTERN.match(path)
        if match is None:
            continue
        root = match.group("root")
        snapshot_id = match.group("snapshot_id")
        filename = match.group("filename")
        candidates[(root, snapshot_id)].add(filename)

    viable = [
        (root, snapshot_id)
        for (root, snapshot_id), filenames in candidates.items()
        if all(filename in filenames for filename in REQUIRED_CHECKPOINT_FILES)
    ]
    if checkpoint_id is not None:
        requested = [
            candidate
            for candidate in viable
            if candidate[1] == checkpoint_id
            and (checkpoint_root is None or candidate[0] == checkpoint_root)
        ]
        if not requested:
            raise ValueError(
                f"Checkpoint {checkpoint_root or '*'}:{checkpoint_id} not found with required files."
            )
        return sorted(requested, key=_checkpoint_sort_key)[-1]

    if checkpoint_root is not None:
        viable = [candidate for candidate in viable if candidate[0] == checkpoint_root]
    if not viable:
        raise ValueError("No viable checkpoint directories were found in the source HF dataset.")
    return sorted(viable, key=_checkpoint_sort_key)[-1]


def _checkpoint_sort_key(candidate: tuple[str, str]) -> tuple[str, int]:
    root, snapshot_id = candidate
    root_priority = 1 if root == "_checkpoints" else 0
    return snapshot_id, root_priority


def _maybe_download_json(repo_id: str, filename: str) -> dict[str, Any]:
    try:
        path = hf_hub_download(repo_id=repo_id, repo_type="dataset", filename=filename)
    except Exception:
        return {}
    return read_json(Path(path))


def _project_rows(rows: list[dict[str, Any]], table_name: str) -> list[dict[str, Any]]:
    field_names = [field.name for field in SCHEMAS[table_name]]
    return [{field_name: row.get(field_name) for field_name in field_names} for row in rows]


def _resolve_repo(
    rows_by_table: Mapping[str, list[dict[str, Any]]],
    source_manifest: Mapping[str, Any],
    source_progress: Mapping[str, Any],
) -> str:
    for table_name in ("issues", "pull_requests", "comments"):
        rows = rows_by_table.get(table_name) or []
        if rows and rows[0].get("repo"):
            return str(rows[0]["repo"])
    return str(source_manifest.get("repo") or source_progress.get("repo") or "")


def _resolve_extracted_at(
    rows_by_table: Mapping[str, list[dict[str, Any]]],
    source_manifest: Mapping[str, Any],
) -> str:
    for table_name in (
        "issues",
        "pull_requests",
        "comments",
        "reviews",
        "review_comments",
        "events",
    ):
        rows = rows_by_table.get(table_name) or []
        if rows and rows[0].get("extracted_at"):
            return str(rows[0]["extracted_at"])
    return str(source_manifest.get("extracted_at") or _iso_now())


def _derived_link_rows(
    *,
    repo_slug: str,
    snapshot_id: str,
    extracted_at: str,
    issues: list[dict[str, Any]],
    pull_requests: list[dict[str, Any]],
    comments: list[dict[str, Any]],
    reviews: list[dict[str, Any]],
    review_comments: list[dict[str, Any]],
    events: list[dict[str, Any]],
) -> list[dict[str, Any]]:
    owner, repo_name = repo_slug.split("/", 1)
    link_rows: list[dict[str, Any]] = []
    for issue_row in issues:
        link_rows.extend(
            build_text_link_rows(
                repo=repo_slug,
                owner=owner,
                repo_name=repo_name,
                source_type="issue",
                source_number=int(issue_row["number"]),
                source_id=issue_row.get("github_id"),
                body=issue_row.get("body"),
                snapshot_id=snapshot_id,
                extracted_at=extracted_at,
            )
        )
    for pr_row in pull_requests:
        link_rows.extend(
            build_text_link_rows(
                repo=repo_slug,
                owner=owner,
                repo_name=repo_name,
                source_type="pull_request",
                source_number=int(pr_row["number"]),
                source_id=pr_row.get("github_id"),
                body=pr_row.get("body"),
                snapshot_id=snapshot_id,
                extracted_at=extracted_at,
            )
        )
    for comment_row in comments:
        parent_number = comment_row.get("parent_number")
        if parent_number is None:
            continue
        link_rows.extend(
            build_text_link_rows(
                repo=repo_slug,
                owner=owner,
                repo_name=repo_name,
                source_type="comment",
                source_number=int(parent_number),
                source_id=comment_row.get("github_id"),
                body=comment_row.get("body"),
                snapshot_id=snapshot_id,
                extracted_at=extracted_at,
            )
        )
    for review_row in reviews:
        link_rows.extend(
            build_text_link_rows(
                repo=repo_slug,
                owner=owner,
                repo_name=repo_name,
                source_type="review",
                source_number=int(review_row["pull_request_number"]),
                source_id=review_row.get("github_id"),
                body=review_row.get("body"),
                snapshot_id=snapshot_id,
                extracted_at=extracted_at,
            )
        )
    for review_comment_row in review_comments:
        link_rows.extend(
            build_text_link_rows(
                repo=repo_slug,
                owner=owner,
                repo_name=repo_name,
                source_type="review_comment",
                source_number=int(review_comment_row["pull_request_number"]),
                source_id=review_comment_row.get("github_id"),
                body=review_comment_row.get("body"),
                snapshot_id=snapshot_id,
                extracted_at=extracted_at,
            )
        )
    link_rows.extend(
        build_pr_duplicate_candidate_rows(
            repo=repo_slug,
            pull_requests=pull_requests,
            link_rows=link_rows,
            snapshot_id=snapshot_id,
            extracted_at=extracted_at,
        )
    )
    for event in events:
        source_issue_number = event.get("source_issue_number")
        if not source_issue_number:
            continue
        link_rows.append(
            {
                "repo": repo_slug,
                "source_type": event["parent_kind"],
                "source_number": event["parent_number"],
                "source_github_id": None,
                "target_owner": owner,
                "target_repo": repo_name,
                "target_number": source_issue_number,
                "link_type": f"timeline:{event['event']}",
                "link_origin": "timeline",
                "snapshot_id": snapshot_id,
                "extracted_at": extracted_at,
            }
        )
    return sorted(
        _dedupe_link_rows(link_rows),
        key=lambda row: (
            str(row.get("source_type") or ""),
            int(row.get("source_number") or 0),
            int(row.get("source_github_id") or 0),
            str(row.get("target_owner") or ""),
            str(row.get("target_repo") or ""),
            int(row.get("target_number") or 0),
            str(row.get("link_type") or ""),
            str(row.get("link_origin") or ""),
        ),
    )


def _dedupe_link_rows(rows: list[dict[str, Any]]) -> list[dict[str, Any]]:
    deduped: dict[tuple[Any, ...], dict[str, Any]] = {}
    for row in rows:
        key = (
            row.get("repo"),
            row.get("source_type"),
            row.get("source_number"),
            row.get("source_github_id"),
            row.get("target_owner"),
            row.get("target_repo"),
            row.get("target_number"),
            row.get("link_type"),
            row.get("link_origin"),
        )
        deduped[key] = row
    return list(deduped.values())


def _viewer_comment_rows(
    comments: list[dict[str, Any]],
    pull_requests: list[dict[str, Any]],
) -> tuple[list[dict[str, Any]], list[dict[str, Any]]]:
    pr_numbers = {int(row["number"]) for row in pull_requests if row.get("number") is not None}
    issue_comments: list[dict[str, Any]] = []
    pr_comments: list[dict[str, Any]] = []
    for row in comments:
        parent_number = row.get("parent_number")
        parent_kind = row.get("parent_kind")
        if parent_kind == "pull_request" or parent_number in pr_numbers:
            pr_comments.append(row)
        else:
            issue_comments.append(row)
    return issue_comments, pr_comments


def _dataset_card(
    repo_slug: str, snapshot_id: str, source_repo_id: str, checkpoint_root: str
) -> str:
    return build_hf_dataset_card(
        repo_slug,
        snapshot_id,
        notes=[
            f"source HF dataset: `{source_repo_id}`",
            f"source checkpoint root: `{checkpoint_root}`",
            "links were regenerated locally from text references and timeline events",
        ],
    )


def _snapshot_dir_name(source_repo_id: str, checkpoint_id: str) -> str:
    return f"hf-{source_repo_id.replace('/', '--')}-{checkpoint_id}"


def _iso_now() -> str:
    return datetime.now(tz=UTC).replace(microsecond=0).isoformat().replace("+00:00", "Z")


def _parquet_row_count(path: Path) -> int:
    import pyarrow.parquet as pq

    return pq.read_metadata(path).num_rows