"""FTS5-based log search with severity, source, and pattern filters."""
from __future__ import annotations

import json
import logging
import sqlite3
from dataclasses import dataclass
from pathlib import Path

logger = logging.getLogger(__name__)


@dataclass(frozen=True)
class SearchResult:
    entry_id: str
    source_id: str
    sequence: int
    timestamp_iso: str | None
    severity: str | None
    repeat_count: int
    out_of_order: bool
    matched_patterns: list[str]
    text: str
    rank: float


def build_fts_index(db_path: Path) -> None:
    """Build (or rebuild) the FTS5 index from log_entries. Safe to re-run.

    Drops and recreates the table if the schema is stale (missing sequence column).
    """
    conn = sqlite3.connect(str(db_path))
    conn.execute("PRAGMA journal_mode=WAL")

    # Check whether existing table has the sequence column; rebuild if not.
    needs_rebuild = False
    try:
        conn.execute("SELECT sequence FROM log_fts LIMIT 0")
    except sqlite3.OperationalError:
        needs_rebuild = True

    if needs_rebuild:
        conn.execute("DROP TABLE IF EXISTS log_fts")

    conn.executescript("""
        CREATE VIRTUAL TABLE IF NOT EXISTS log_fts USING fts5(
            text,
            entry_id      UNINDEXED,
            source_id     UNINDEXED,
            sequence      UNINDEXED,
            severity      UNINDEXED,
            timestamp_iso UNINDEXED,
            matched_patterns UNINDEXED,
            repeat_count  UNINDEXED,
            out_of_order  UNINDEXED,
            tokenize = 'porter ascii'
        );
    """)
    # Only insert rows not already indexed
    conn.execute("""
        INSERT INTO log_fts(text, entry_id, source_id, sequence, severity,
                            timestamp_iso, matched_patterns,
                            repeat_count, out_of_order)
        SELECT e.text, e.id, e.source_id, e.sequence, e.severity,
               e.timestamp_iso, e.matched_patterns,
               e.repeat_count, e.out_of_order
        FROM log_entries e
        WHERE e.id NOT IN (SELECT entry_id FROM log_fts WHERE entry_id IS NOT NULL)
    """)
    conn.commit()
    conn.close()


def search(
    db_path: Path,
    query: str,
    severity: str | None = None,
    source_filter: str | None = None,
    pattern_filter: str | None = None,
    since: str | None = None,
    until: str | None = None,
    limit: int = 20,
    include_repeats: bool = False,
) -> list[SearchResult]:
    """Full-text search with optional filters. Returns results ranked by relevance."""
    conn = sqlite3.connect(str(db_path))
    conn.execute("PRAGMA journal_mode=WAL")
    conn.row_factory = sqlite3.Row

    conditions = ["log_fts MATCH ?"]
    params: list = [query]

    if severity:
        conditions.append("severity = ?")
        params.append(severity.upper())
    if source_filter:
        conditions.append("source_id LIKE ?")
        params.append(f"%{source_filter}%")
    if pattern_filter:
        conditions.append("matched_patterns LIKE ?")
        params.append(f'%"{pattern_filter}"%')
    if since:
        conditions.append("timestamp_iso >= ?")
        params.append(since)
    if until:
        conditions.append("timestamp_iso <= ?")
        params.append(until)
    if not include_repeats:
        conditions.append("repeat_count = 1")

    where = " AND ".join(conditions)
    params.append(limit)

    try:
        rows = conn.execute(
            f"""
            SELECT entry_id, source_id, sequence, timestamp_iso, severity,
                   repeat_count, out_of_order, matched_patterns, text, rank
            FROM log_fts
            WHERE {where}
            ORDER BY rank
            LIMIT ?
            """,
            params,
        ).fetchall()
    except sqlite3.OperationalError as e:
        logger.warning("FTS query failed (%s) — index may not be built yet", e)
        conn.close()
        return []

    results = [
        SearchResult(
            entry_id=r["entry_id"],
            source_id=r["source_id"],
            sequence=r["sequence"],
            timestamp_iso=r["timestamp_iso"],
            severity=r["severity"],
            repeat_count=r["repeat_count"],
            out_of_order=bool(r["out_of_order"]),
            matched_patterns=json.loads(r["matched_patterns"] or "[]"),
            text=r["text"],
            rank=r["rank"],
        )
        for r in rows
    ]
    conn.close()
    return results


def list_sources(db_path: Path) -> list[dict]:
    """Return distinct sources with entry counts and time ranges."""
    conn = sqlite3.connect(str(db_path))
    conn.execute("PRAGMA journal_mode=WAL")
    rows = conn.execute("""
        SELECT
            source_id,
            COUNT(*) as entry_count,
            MIN(timestamp_iso) as earliest,
            MAX(timestamp_iso) as latest,
            SUM(CASE WHEN severity IN ('ERROR','CRITICAL','EMERGENCY','ALERT') THEN 1 ELSE 0 END) as error_count
        FROM log_entries
        GROUP BY source_id
        ORDER BY entry_count DESC
    """).fetchall()
    conn.close()
    return [
        {
            "source_id": r[0],
            "entry_count": r[1],
            "earliest": r[2],
            "latest": r[3],
            "error_count": r[4],
        }
        for r in rows
    ]


def format_results(results: list[SearchResult], max_text: int = 300) -> str:
    """Format search results as readable text for LLM context."""
    if not results:
        return "No matching log entries found."

    lines = []
    for r in results:
        ts = r.timestamp_iso or "no-timestamp"
        sev = r.severity or "?"
        src = r.source_id
        flags = []
        if r.repeat_count > 1:
            flags.append(f"repeat×{r.repeat_count}")
        if r.out_of_order:
            flags.append("out-of-order")
        if r.matched_patterns:
            flags.append(f"[{', '.join(r.matched_patterns)}]")
        flag_str = f"  {' '.join(flags)}" if flags else ""

        text = r.text[:max_text] + ("…" if len(r.text) > max_text else "")
        lines.append(f"[{ts} | {src} | {sev}{flag_str}]\n{text}")

    return "\n\n".join(lines)