"""SQS computation and scoring API endpoints."""
from __future__ import annotations

import threading
import uuid
from pathlib import Path
from typing import Any

from fastapi import APIRouter, HTTPException
from pydantic import BaseModel

from apps.web.dependencies import get_configs_dir, get_journal_dir, get_runs_dir
from libs.backtest.tracker import (
    _hydrate_split_result,
    compute_public_sqs_v9,
    compute_rqs,
    compute_wfqs_v2,
    load_journal,
    refresh_public_scores,
)

router = APIRouter(prefix="/sqs", tags=["sqs"])

# ---------------------------------------------------------------------------
# In-memory pipeline state
# ---------------------------------------------------------------------------
_pipelines: dict[str, dict[str, Any]] = {}
_pipelines_lock = threading.Lock()


class RescoreRequest(BaseModel):
    target: str


class PipelineRequest(BaseModel):
    target: str


_NO_ENTRY_RESPONSE = {
    "entry_id": None,
    "sqs_score": None,
    "source": None,
    "pending_reason": "no_backtest_data",
    "pillars": {
        "rqs_score": None, "wfqs_v2_score": None,
        "regime_score": None, "regime_source": "none", "core_score": None,
    },
    "gates": {
        "deployment_gate_factor": None,
        "robustness_gate_factor": None,
        "activity_factor": None,
    },
    "breakdown": {},
    "stored_sqs_score": None,
    "scenario_robustness_score": None,
    "overfit_check_score": None,
}


def _registry_fallback(journal_dir: Path, experiment_name: str) -> dict[str, Any] | None:
    """Look up stored SQS from registry when no live journal entry exists."""
    from libs.backtest.domain import ExperimentRegistry
    registry_path = journal_dir / "experiment_registry.json"
    if not registry_path.exists():
        return None
    try:
        registry = ExperimentRegistry.model_validate_json(registry_path.read_text())
    except Exception:
        return None

    matches = [e for e in registry.entries if e.experiment_name == experiment_name]
    if not matches:
        return None
    entry = sorted(matches, key=lambda e: e.timestamp)[-1]

    return {
        "entry_id": entry.entry_id,
        "sqs_score": entry.sqs_score,
        "source": "registry_stored",
        "pending_reason": None if entry.sqs_score is not None else "no_backtest_data",
        "pillars": {
            "rqs_score": entry.rqs_score,
            "wfqs_v2_score": entry.wfqs_v2_score,
            "regime_score": None,
            "regime_source": "stored",
            "core_score": None,
        },
        "gates": {
            "deployment_gate_factor": None,
            "robustness_gate_factor": None,
            "activity_factor": None,
        },
        "breakdown": {},
        "stored_sqs_score": entry.sqs_score,
        "scenario_robustness_score": entry.scenario_robustness_score,
        "overfit_check_score": entry.overfit_check_score,
    }


def _compute_for_entry(entry: Any) -> dict[str, Any]:
    """Run SQS v9 computation on a journal entry and return structured result."""
    train_result = _hydrate_split_result(entry.results.get("train"))
    valid_result = _hydrate_split_result(entry.results.get("valid"))
    test_result = _hydrate_split_result(entry.results.get("test"))

    rqs_score, _ = compute_rqs(train_result, valid_result, test_result)
    wfqs_v2_score, _ = compute_wfqs_v2(entry.walk_forward_summary)

    sqs_score, sqs_breakdown, source = compute_public_sqs_v9(
        train_result, valid_result, test_result,
        walk_forward_summary=entry.walk_forward_summary,
        robustness_matrix_summary=entry.robustness_matrix_summary,
        out_of_time_robustness_summary=entry.out_of_time_robustness_summary,
        common_window_summary=entry.common_window_summary,
        reset_common_window_summary=entry.reset_common_window_summary,
        scenario_robustness_score=entry.scenario_robustness_score,
        rqs_score=rqs_score,
        wfqs_v2_score=wfqs_v2_score,
    )

    regime_src = (
        "scenario_rrs" if entry.scenario_robustness_score is not None
        else "oot_quality" if entry.out_of_time_robustness_summary is not None
        else "neutral_50"
    )

    pending_reason = None
    if sqs_score is None:
        pending_key = next((k for k in sqs_breakdown if k.startswith("requires_")), None)
        pending_reason = (
            pending_key.replace("requires_", "").replace("_", " ")
            if pending_key else "missing data"
        )

    return {
        "experiment_name": entry.experiment_name,
        "entry_id": entry.entry_id,
        "sqs_score": sqs_score,
        "source": source,
        "pending_reason": pending_reason,
        "pillars": {
            "rqs_score": rqs_score,
            "wfqs_v2_score": wfqs_v2_score,
            "regime_score": sqs_breakdown.get("regime_score"),
            "regime_source": regime_src,
            "core_score": sqs_breakdown.get("core_score"),
        },
        "gates": {
            "deployment_gate_factor": sqs_breakdown.get("deployment_gate_factor"),
            "robustness_gate_factor": sqs_breakdown.get("gate_factor"),
            "activity_factor": sqs_breakdown.get("activity_factor"),
        },
        "breakdown": sqs_breakdown,
        "stored_sqs_score": entry.sqs_score,
        "scenario_robustness_score": entry.scenario_robustness_score,
        "overfit_check_score": entry.overfit_check_score,
    }


@router.get("/{experiment_name:path}")
def get_sqs(experiment_name: str) -> dict[str, Any]:
    """Compute SQS v9 live for an experiment (read-only, no journal write).

    Falls back to registry-stored SQS when no journal entry exists.
    Never returns 404 — always returns a structured response.
    """
    journal_dir = get_journal_dir()
    journal_path = journal_dir / "improvement_journal.jsonl"

    base = {"experiment_name": experiment_name}

    # 1. Try journal — live recompute
    if journal_path.exists():
        entries = load_journal(journal_path)
        exact = [e for e in entries if e.experiment_name == experiment_name]
        if exact:
            entry = sorted(exact, key=lambda e: e.timestamp)[-1]
            return {**base, **_compute_for_entry(entry)}

    # 2. Fall back to registry (stored values, no live recompute)
    reg = _registry_fallback(journal_dir, experiment_name)
    if reg:
        return {**base, **reg}

    # 3. Nothing available
    return {**base, **_NO_ENTRY_RESPONSE}


def _run_pipeline_thread(pipeline_id: str, experiment_name: str) -> None:
    """Background thread: run train/valid/test + WFV + robustness → record → compute SQS v9."""
    import datetime as _dt

    from libs.backtest.tracker import (
        append_journal_entry,
        build_split_result,
        get_next_entry_id,
        journal_lock,
        rebuild_registry,
    )
    from libs.backtest.domain import JournalEntry

    def _set(updates: dict) -> None:
        with _pipelines_lock:
            _pipelines[pipeline_id].update(updates)

    try:
        configs_dir = get_configs_dir()
        journal_dir = get_journal_dir()
        runs_dir = get_runs_dir()
        journal_path = journal_dir / "improvement_journal.jsonl"
        registry_path = journal_dir / "experiment_registry.json"
        leaderboard_path = journal_dir / "LEADERBOARD.md"
        config_path = configs_dir / f"{experiment_name}.json"

        if not config_path.exists():
            _set({"status": "failed", "error": f"Config not found: {experiment_name}.json"})
            return

        from apps.backtester.run import (
            BacktestRunner,
            _resolve_scoring_fn,
            load_manifest,
            resolve_config,
            run_walk_forward,
            run_robustness_matrix,
        )
        from libs.backtest.snapshots import resolve_snapshot_path
        from libs.backtest.snapshot_store import SnapshotStore
        from libs.common.config import get_settings

        _set({"status": "running", "step": "Loading config…"})
        manifest = load_manifest(str(config_path))
        config = resolve_config(manifest)

        snapshot_request_id = config.requested_snapshot_id or config.dataset_snapshot_id
        snapshot_dir = resolve_snapshot_path(snapshot_request_id)
        if snapshot_dir is None:
            _set({"status": "failed", "error": f"Snapshot not found: '{snapshot_request_id}'"})
            return

        s = get_settings()
        scoring_fn = _resolve_scoring_fn(config)

        # --- Pre-warm merged cache from per-split caches ---
        # Many experiments have per-split PKL caches but no merged cache.
        # _build_merged_snapshot_store (used by run_walk_forward / run_robustness_matrix)
        # would trigger an Oracle API fetch if the merged cache is missing. Pre-warm it here.
        _set({"status": "running", "step": "Loading snapshots…"})
        per_split_data: dict[str, dict] = {}
        for split in ("train", "valid", "test"):
            d = SnapshotStore._try_load_runtime_cache(snapshot_dir, [split], scoring_fn=scoring_fn)
            if d is not None:
                per_split_data[split] = d

        if len(per_split_data) == 3:
            # Check if merged cache is already present
            merged_cached = SnapshotStore._try_load_runtime_cache(
                snapshot_dir, ["train", "valid", "test"], scoring_fn=scoring_fn
            )
            if merged_cached is None:
                # Build and write merged cache from per-split caches
                merged_cands: dict = {}
                merged_bars: dict = {}
                merged_macro: dict = {}
                for d in per_split_data.values():
                    for date, rows in d["candidates_by_exec_date"].items():
                        merged_cands.setdefault(date, []).extend(rows)
                    for sym, bars in d["bars_by_symbol_date"].items():
                        merged_bars.setdefault(sym, {}).update(bars)
                    for date, obs in (d.get("macro_by_date") or {}).items():
                        if date not in merged_macro:
                            merged_macro[date] = obs
                SnapshotStore._write_runtime_cache(
                    snapshot_dir, ["train", "valid", "test"], scoring_fn=scoring_fn,
                    data={
                        "candidates_by_exec_date": merged_cands,
                        "bars_by_symbol_date": merged_bars,
                        "macro_by_date": merged_macro,
                    },
                )

        # --- Run basic backtests, collecting results directly from runner ---
        results: dict[str, Any] = {}
        for split in ("train", "valid", "test"):
            _set({"status": "running", "step": f"Running {split} split…"})
            if split in per_split_data:
                split_store = SnapshotStore(**per_split_data[split])
            else:
                split_store = SnapshotStore.load(
                    snapshot_dir=snapshot_dir, split_name=split,
                    oracle_url=s.stock_oracle_url, db_dsn=s.postgres_dsn,
                    scoring_fn=scoring_fn,
                )
            runner = BacktestRunner(
                manifest=manifest, config=config, store=split_store,
                initial_equity=10_000.0, split_name=split,
            )
            exp_result = runner.run(output_root=str(runs_dir))
            results[split] = build_split_result(split, exp_result.run_id, exp_result.metrics)

        # --- Walk-forward validation (merged cache now warm → fast) ---
        _set({"status": "running", "step": "Running walk-forward validation…"})
        wf_summary = run_walk_forward(
            manifest=manifest, config=config, snapshot_dir_override=None,
            initial_equity=10_000.0, output_root=str(runs_dir),
            train_days=252, test_days=63, step_days=63,
        )

        # --- Robustness matrix (merged cache warm → fast, step_days=63 lightweight) ---
        _set({"status": "running", "step": "Running robustness matrix…"})
        rb_summary = run_robustness_matrix(
            manifest=manifest, config=config, snapshot_dir_override=None,
            initial_equity=10_000.0, output_root=str(runs_dir),
            horizons_days=[63, 126, 252], step_days=63,
        )

        # --- Compute scores ---
        _set({"status": "running", "step": "Computing SQS v9…"})
        rqs_score, rqs_breakdown = compute_rqs(results.get("train"), results.get("valid"), results.get("test"))
        wfqs_v2_score, _ = compute_wfqs_v2(wf_summary)
        # scenario_robustness_score=50.0 → neutral (run `fithia2 rescore-public` for actual scenario score)
        sqs_score, sqs_breakdown, _ = compute_public_sqs_v9(
            results.get("train"), results.get("valid"), results.get("test"),
            walk_forward_summary=wf_summary,
            robustness_matrix_summary=rb_summary,
            scenario_robustness_score=50.0,
            rqs_score=rqs_score,
            wfqs_v2_score=wfqs_v2_score,
        )

        # --- Record to journal ---
        _set({"status": "running", "step": "Recording to journal…"})
        tags = [t for t in experiment_name.replace("-", "_").split("_") if t]
        entry_id = get_next_entry_id(journal_path)
        timestamp = _dt.datetime.now(_dt.timezone.utc).isoformat()
        entry = JournalEntry(
            entry_id=entry_id,
            timestamp=timestamp,
            experiment_name=experiment_name,
            hypothesis="Auto-recorded via web GUI",
            results=results,
            walk_forward_summary=wf_summary,
            robustness_matrix_summary=rb_summary,
            scenario_robustness_score=50.0,
            rqs_score=rqs_score,
            rqs_breakdown=rqs_breakdown,
            sqs_score=sqs_score,
            sqs_breakdown=sqs_breakdown,
            verdict="unknown",
            tags=tags,
        )
        with journal_lock(journal_path):
            append_journal_entry(journal_path, entry)
            rebuild_registry(journal_path, registry_path, leaderboard_path)

        sqs_result = _compute_for_entry(entry)
        _set({"status": "completed", "step": "Done", "result": sqs_result})

    except Exception as exc:
        import traceback as _tb
        _set({"status": "failed", "error": f"{exc}\n{_tb.format_exc()[-800:]}"})


@router.post("/pipeline")
def pipeline_start(req: PipelineRequest) -> dict[str, Any]:
    """Start the auto-backtest pipeline: run train/valid/test → record → compute SQS.

    Returns a pipeline_id to poll with GET /sqs/pipeline/{pipeline_id}.
    If a journal entry already exists, computes SQS immediately (no pipeline).
    """
    experiment_name = req.target
    journal_dir = get_journal_dir()
    journal_path = journal_dir / "improvement_journal.jsonl"
    base = {"experiment_name": experiment_name}

    # Journal entry already exists WITH walk-forward data → compute immediately (no pipeline needed)
    if journal_path.exists():
        entries = load_journal(journal_path)
        exact = [e for e in entries if e.experiment_name == experiment_name]
        if exact:
            entry = sorted(exact, key=lambda e: e.timestamp)[-1]
            if entry.walk_forward_summary is not None:
                return {**base, "pipeline_status": "existing_entry", **_compute_for_entry(entry)}

    # Config must exist before we start
    config_path = get_configs_dir() / f"{experiment_name}.json"
    if not config_path.exists():
        raise HTTPException(status_code=404, detail=f"Experiment config not found: {experiment_name}")

    pipeline_id = str(uuid.uuid4())[:8]
    with _pipelines_lock:
        _pipelines[pipeline_id] = {
            "pipeline_id": pipeline_id,
            "experiment_name": experiment_name,
            "status": "running",
            "step": "Starting…",
            "error": None,
            "result": None,
        }

    thread = threading.Thread(
        target=_run_pipeline_thread,
        args=(pipeline_id, experiment_name),
        daemon=True,
    )
    thread.start()
    return {**base, "pipeline_id": pipeline_id, "pipeline_status": "running", "step": "Starting…"}


@router.get("/pipeline/{pipeline_id}")
def pipeline_poll(pipeline_id: str) -> dict[str, Any]:
    """Poll pipeline status. Returns result when status='completed'."""
    with _pipelines_lock:
        state = _pipelines.get(pipeline_id)
    if state is None:
        raise HTTPException(status_code=404, detail=f"Pipeline not found: {pipeline_id}")
    out = dict(state)
    if out.get("result"):
        out.update(out.pop("result"))
    out["pipeline_status"] = out.pop("status")
    return out


@router.post("/rescore")
def rescore_experiment(req: RescoreRequest) -> dict[str, Any]:
    """Recompute SQS for one experiment, save to journal, rebuild leaderboard."""
    from libs.backtest.tracker import journal_lock, rebuild_registry

    journal_dir = get_journal_dir()
    journal_path = journal_dir / "improvement_journal.jsonl"
    registry_path = journal_dir / "experiment_registry.json"
    leaderboard_path = journal_dir / "LEADERBOARD.md"

    if not journal_path.exists():
        raise HTTPException(status_code=404, detail="Journal not found")

    entries = load_journal(journal_path)
    exact = [e for e in entries if e.experiment_name == req.target]
    if not exact:
        raise HTTPException(
            status_code=404,
            detail=f"No journal entry for '{req.target}'. Run a backtest and record results first (fithia2 rec).",
        )
    entry = sorted(exact, key=lambda e: e.timestamp)[-1]
    target_name = entry.experiment_name

    def _only_this(e: Any) -> bool:
        return e.experiment_name == target_name

    with journal_lock(journal_path):
        updated_count = refresh_public_scores(journal_path, selector=_only_this)
        rebuild_registry(journal_path, registry_path, leaderboard_path)

    fresh_entries = load_journal(journal_path)
    fresh_exact = [e for e in fresh_entries if e.experiment_name == target_name]
    fresh_entry = sorted(fresh_exact, key=lambda e: e.timestamp)[-1]
    result = {
        "experiment_name": target_name,
        **_compute_for_entry(fresh_entry),
        "entries_updated": updated_count,
    }
    return result