from __future__ import annotations

import sqlite3
from pathlib import Path


SCHEMA = r"""
PRAGMA journal_mode=WAL;
PRAGMA synchronous=NORMAL;
PRAGMA temp_store=MEMORY;

CREATE TABLE IF NOT EXISTS candidates (
  candidate_id TEXT PRIMARY KEY,
  name TEXT,
  location TEXT,
  remote INTEGER,
  experience_years REAL,
  experience_years_eng REAL, -- инженерный опыт (после фильтра HR)
  experience_confidence REAL,
  salary_min INTEGER,
  salary_max INTEGER,
  salary_confidence REAL,
  english_level TEXT,
  roles_json TEXT,
  skills_json TEXT,
  primary_languages_json TEXT,
  backend_focus INTEGER,
  roles_norm TEXT,   -- "|backend|devops|"
  skills_norm TEXT,  -- "|python|k8s|"
  created_at TEXT DEFAULT (datetime('now')),
  updated_at TEXT DEFAULT (datetime('now'))
);

CREATE TABLE IF NOT EXISTS candidate_contacts (
  contact_type TEXT NOT NULL,  -- email/phone/tg/github/linkedin/url
  contact_value TEXT NOT NULL, -- normalized
  candidate_id TEXT NOT NULL,
  created_at TEXT DEFAULT (datetime('now')),
  PRIMARY KEY(contact_type, contact_value),
  FOREIGN KEY(candidate_id) REFERENCES candidates(candidate_id)
);

CREATE INDEX IF NOT EXISTS idx_contacts_candidate ON candidate_contacts(candidate_id);

CREATE TABLE IF NOT EXISTS resumes (
  resume_id TEXT PRIMARY KEY,
  candidate_id TEXT NOT NULL,
  sha256 TEXT,
  simhash TEXT,
  clean_text TEXT NOT NULL,
  raw_text TEXT,
  extraction_json TEXT,
  llm_summary TEXT,
  llm_tags_json TEXT,
  extract_method TEXT,
  extract_quality_score REAL,
  extract_quality_flags TEXT,
  extract_pages_json TEXT,
  doc_type TEXT,
  doc_type_confidence REAL,
  parse_method TEXT,
  parse_version TEXT,
  sections_json TEXT,
  is_active INTEGER DEFAULT 1,
  duplicate_of_resume_id TEXT,
  file_path TEXT,
  file_mtime INTEGER,
  file_size INTEGER,
  created_at TEXT DEFAULT (datetime('now')),
  FOREIGN KEY(candidate_id) REFERENCES candidates(candidate_id)
);

CREATE UNIQUE INDEX IF NOT EXISTS idx_resumes_sha ON resumes(sha256) WHERE sha256 IS NOT NULL;
CREATE INDEX IF NOT EXISTS idx_resumes_candidate ON resumes(candidate_id);
CREATE INDEX IF NOT EXISTS idx_resumes_active ON resumes(is_active);

CREATE TABLE IF NOT EXISTS sources (
  source_id INTEGER PRIMARY KEY AUTOINCREMENT,
  resume_id TEXT NOT NULL,
  export_path TEXT,
  chat_title TEXT,
  message_id TEXT,
  message_date TEXT,
  origin_type TEXT,
  original_file_path TEXT,
  original_file_name TEXT,
  extra_json TEXT,
  created_at TEXT DEFAULT (datetime('now')),
  FOREIGN KEY(resume_id) REFERENCES resumes(resume_id)
);

CREATE TABLE IF NOT EXISTS files_seen (
  sha256 TEXT PRIMARY KEY,
  size INTEGER,
  mtime INTEGER,
  canonical_resume_id TEXT,
  first_seen_at TEXT DEFAULT (datetime('now')),
  last_seen_at TEXT DEFAULT (datetime('now'))
);

CREATE TABLE IF NOT EXISTS simhash_buckets (
  bucket INTEGER NOT NULL,
  band INTEGER NOT NULL,
  resume_id TEXT NOT NULL,
  PRIMARY KEY(bucket, band, resume_id),
  FOREIGN KEY(resume_id) REFERENCES resumes(resume_id)
);

CREATE TABLE IF NOT EXISTS candidate_skills (
  candidate_id TEXT NOT NULL,
  skill_id TEXT NOT NULL,
  skill_label TEXT,
  confidence REAL,
  source TEXT,
  evidence TEXT,
  created_at TEXT DEFAULT (datetime('now')),
  PRIMARY KEY(candidate_id, skill_id),
  FOREIGN KEY(candidate_id) REFERENCES candidates(candidate_id)
);

CREATE TABLE IF NOT EXISTS candidate_roles (
  candidate_id TEXT NOT NULL,
  role TEXT NOT NULL,
  confidence REAL,
  source TEXT,
  evidence TEXT,
  created_at TEXT DEFAULT (datetime('now')),
  PRIMARY KEY(candidate_id, role),
  FOREIGN KEY(candidate_id) REFERENCES candidates(candidate_id)
);

CREATE TABLE IF NOT EXISTS candidate_languages (
  candidate_id TEXT NOT NULL,
  language TEXT NOT NULL,
  level TEXT,
  confidence REAL,
  source TEXT,
  evidence TEXT,
  created_at TEXT DEFAULT (datetime('now')),
  PRIMARY KEY(candidate_id, language),
  FOREIGN KEY(candidate_id) REFERENCES candidates(candidate_id)
);

CREATE TABLE IF NOT EXISTS positions (
  position_id TEXT PRIMARY KEY,
  resume_id TEXT NOT NULL,
  candidate_id TEXT NOT NULL,
  title TEXT,
  company TEXT,
  date_from TEXT,
  date_to TEXT,
  is_current INTEGER,
  description TEXT,
  stack_json TEXT,
  created_at TEXT DEFAULT (datetime('now')),
  FOREIGN KEY(resume_id) REFERENCES resumes(resume_id),
  FOREIGN KEY(candidate_id) REFERENCES candidates(candidate_id)
);

CREATE TABLE IF NOT EXISTS llm_cache (
  cache_key TEXT PRIMARY KEY,
  model TEXT,
  result_json TEXT,
  created_at TEXT DEFAULT (datetime('now'))
);

-- Full-text index (FTS5): contentless
CREATE VIRTUAL TABLE IF NOT EXISTS resumes_fts USING fts5(
  resume_id UNINDEXED,
  candidate_id UNINDEXED,
  clean_text,
  tokenize='unicode61 remove_diacritics 2'
);

-- --- Triggers to keep FTS synced with resumes ---
-- Insert
CREATE TRIGGER IF NOT EXISTS trg_resumes_ai_fts
AFTER INSERT ON resumes
BEGIN
  DELETE FROM resumes_fts WHERE resume_id = NEW.resume_id;
  INSERT INTO resumes_fts(resume_id, candidate_id, clean_text)
  SELECT NEW.resume_id, NEW.candidate_id, NEW.clean_text
  WHERE NEW.is_active = 1;
END;

-- Delete
CREATE TRIGGER IF NOT EXISTS trg_resumes_ad_fts
AFTER DELETE ON resumes
BEGIN
  DELETE FROM resumes_fts WHERE resume_id = OLD.resume_id;
END;

-- Update (text/active/candidate)
CREATE TRIGGER IF NOT EXISTS trg_resumes_au_fts
AFTER UPDATE OF clean_text, is_active, candidate_id ON resumes
BEGIN
  DELETE FROM resumes_fts WHERE resume_id = NEW.resume_id;
  INSERT INTO resumes_fts(resume_id, candidate_id, clean_text)
  SELECT NEW.resume_id, NEW.candidate_id, NEW.clean_text
  WHERE NEW.is_active = 1;
END;
"""


def connect(db_path: str) -> sqlite3.Connection:
    Path(db_path).parent.mkdir(parents=True, exist_ok=True)
    con = sqlite3.connect(db_path)
    con.row_factory = sqlite3.Row
    return con


def _table_exists(con: sqlite3.Connection, name: str) -> bool:
    row = con.execute(
        "SELECT 1 FROM sqlite_master WHERE type IN ('table','view') AND name=? LIMIT 1",
        (name,),
    ).fetchone()
    return row is not None


def _column_exists(con: sqlite3.Connection, table: str, column: str) -> bool:
    cur = con.execute(f"PRAGMA table_info({table})")
    for r in cur.fetchall():
        if r["name"] == column:
            return True
    return False


def _add_column_if_missing(con: sqlite3.Connection, table: str, column: str, ddl_type: str) -> None:
    if not _table_exists(con, table):
        return
    if _column_exists(con, table, column):
        return
    con.execute(f"ALTER TABLE {table} ADD COLUMN {column} {ddl_type}")


def _ensure_fts_backfilled(con: sqlite3.Connection) -> None:
    """
    Если resumes_fts пустая / рассинхронизирована - пересобираем из resumes.
    Это лечит ситуацию: init_db создал FTS, но данные туда никто не залил => search всегда 0.
    """
    if not _table_exists(con, "resumes") or not _table_exists(con, "resumes_fts"):
        return

    try:
        resumes_cnt = int(con.execute("SELECT COUNT(*) AS c FROM resumes WHERE is_active=1").fetchone()["c"])
        fts_cnt = int(con.execute("SELECT COUNT(*) AS c FROM resumes_fts").fetchone()["c"])
    except Exception:
        return

    if resumes_cnt <= 0:
        return

    # Любое несовпадение -> rebuild (убирает и пустоту, и дубли)
    if fts_cnt != resumes_cnt:
        con.execute("DELETE FROM resumes_fts")
        con.execute(
            """
            INSERT INTO resumes_fts(resume_id, candidate_id, clean_text)
            SELECT resume_id, candidate_id, clean_text
            FROM resumes
            WHERE is_active=1
            """
        )
        con.commit()


def init_db(con: sqlite3.Connection) -> None:
    con.executescript(SCHEMA)
    # Lightweight migrations for existing DBs (safe to re-run)
    _add_column_if_missing(con, "candidates", "experience_years_eng", "REAL")
    _add_column_if_missing(con, "candidates", "primary_languages_json", "TEXT")
    _add_column_if_missing(con, "candidates", "backend_focus", "INTEGER")
    _add_column_if_missing(con, "resumes", "llm_summary", "TEXT")
    _add_column_if_missing(con, "resumes", "llm_tags_json", "TEXT")
    _add_column_if_missing(con, "resumes", "extract_method", "TEXT")
    _add_column_if_missing(con, "resumes", "extract_quality_score", "REAL")
    _add_column_if_missing(con, "resumes", "extract_quality_flags", "TEXT")
    _add_column_if_missing(con, "resumes", "extract_pages_json", "TEXT")
    _add_column_if_missing(con, "resumes", "doc_type", "TEXT")
    _add_column_if_missing(con, "resumes", "doc_type_confidence", "REAL")
    _add_column_if_missing(con, "resumes", "parse_method", "TEXT")
    _add_column_if_missing(con, "resumes", "parse_version", "TEXT")
    _add_column_if_missing(con, "resumes", "sections_json", "TEXT")
    if not _table_exists(con, "llm_cache"):
        con.execute(
            """
            CREATE TABLE IF NOT EXISTS llm_cache (
              cache_key TEXT PRIMARY KEY,
              model TEXT,
              result_json TEXT,
              created_at TEXT DEFAULT (datetime('now'))
            )
            """
        )
    con.commit()
    _ensure_fts_backfilled(con)