"""مهاجرت‌های سبک دیتابیس — DDL و تبدیل داده‌های قدیمی؛ همه idempotent.

هم main.py (startup) و هم seed.py این‌ها را صدا می‌زنند تا هر مسیر اجرایی
دیتابیس موجود را بدون از دست رفتن داده ارتقا دهد.
"""

from sqlalchemy import text

from .database import SessionLocal, engine

# جدول‌های مجموعه‌ای که ستون position دارند
POSITION_TABLES = [
    "services", "projects", "articles", "testimonials", "faqs", "team",
    "timeline", "stats", "why_us", "investment_models", "process_steps",
    "offices", "gallery_images", "nav_items",
]

# ستون‌های انگلیسی — (جدول، ستون، نوع). ستون‌های JSON بدون default اند تا
# سطرهای موجود NULL بگیرند (یعنی «ترجمه ثبت نشده») و فرانت به فارسی برگردد.
EN_COLUMNS: list[tuple[str, str, str]] = [
    ("brand", "name_en", "VARCHAR(128)"),
    ("brand", "address_en", "TEXT"),
    ("services", "title_en", "VARCHAR(256)"),
    ("services", "desc_en", "TEXT"),
    ("projects", "title_en", "VARCHAR(256)"),
    ("projects", "location_en", "VARCHAR(128)"),
    ("projects", "year_en", "VARCHAR(64)"),
    ("projects", "area_en", "VARCHAR(64)"),
    ("projects", "floors_en", "VARCHAR(64)"),
    ("projects", "units_en", "VARCHAR(64)"),
    ("projects", "client_en", "VARCHAR(128)"),
    ("projects", "summary_en", "TEXT"),
    ("projects", "body_en", "JSON"),
    ("articles", "title_en", "VARCHAR(256)"),
    ("articles", "date_en", "VARCHAR(64)"),
    ("articles", "category_en", "VARCHAR(64)"),
    ("articles", "read_en", "VARCHAR(32)"),
    ("articles", "excerpt_en", "TEXT"),
    ("articles", "body_en", "JSON"),
    ("testimonials", "name_en", "VARCHAR(128)"),
    ("testimonials", "role_en", "VARCHAR(128)"),
    ("testimonials", "quote_en", "TEXT"),
    ("faqs", "question_en", "TEXT"),
    ("faqs", "answer_en", "TEXT"),
    ("team", "name_en", "VARCHAR(128)"),
    ("team", "role_en", "VARCHAR(128)"),
    ("team", "bio_en", "TEXT"),
    ("timeline", "year_en", "VARCHAR(32)"),
    ("timeline", "title_en", "VARCHAR(256)"),
    ("timeline", "desc_en", "TEXT"),
    ("stats", "suffix_en", "VARCHAR(16)"),
    ("stats", "label_en", "VARCHAR(128)"),
    ("why_us", "title_en", "VARCHAR(256)"),
    ("why_us", "desc_en", "TEXT"),
    ("before_after", "title_en", "VARCHAR(256)"),
    ("before_after", "lead_en", "TEXT"),
    ("before_after", "before_label_en", "VARCHAR(128)"),
    ("before_after", "after_label_en", "VARCHAR(128)"),
    ("nav_items", "label_en", "VARCHAR(64)"),
    ("hero", "kicker_en", "TEXT"),
    ("hero", "title_en", "TEXT"),
    ("hero", "title_highlight_en", "VARCHAR(128)"),
    ("hero", "subtitle_en", "TEXT"),
    ("hero", "badge_value_en", "VARCHAR(32)"),
    ("hero", "badge_label_en", "TEXT"),
    ("hero", "cta_primary_label_en", "VARCHAR(128)"),
    ("hero", "cta_secondary_label_en", "VARCHAR(128)"),
    ("hero", "scroll_label_en", "VARCHAR(64)"),
    ("story", "title_en", "VARCHAR(256)"),
    ("story", "paragraphs_en", "JSON"),
    ("story", "quote_en", "TEXT"),
    ("story", "quote_author_en", "TEXT"),
    ("story", "stat1_value_en", "VARCHAR(32)"),
    ("story", "stat1_label_en", "VARCHAR(128)"),
    ("story", "stat2_value_en", "VARCHAR(32)"),
    ("story", "stat2_label_en", "VARCHAR(128)"),
    ("story", "link_label_en", "VARCHAR(128)"),
    ("story", "bento_en", "JSON"),
    ("section_headings", "label_en", "VARCHAR(64)"),
    ("section_headings", "title_en", "VARCHAR(256)"),
    ("section_headings", "lead_en", "TEXT"),
    ("section_headings", "cta_label_en", "VARCHAR(128)"),
    ("page_heroes", "title_en", "VARCHAR(256)"),
    ("page_heroes", "lead_en", "TEXT"),
    ("investment_models", "title_en", "VARCHAR(256)"),
    ("investment_models", "desc_en", "TEXT"),
    ("investment_models", "points_en", "JSON"),
    ("process_steps", "step_en", "VARCHAR(16)"),
    ("process_steps", "title_en", "VARCHAR(256)"),
    ("process_steps", "desc_en", "TEXT"),
    ("offices", "city_en", "VARCHAR(64)"),
    ("offices", "address_en", "TEXT"),
    ("offices", "hours_en", "VARCHAR(128)"),
    ("gallery_images", "alt_en", "TEXT"),
    ("status_labels", "label_en", "VARCHAR(64)"),
    ("contact_section", "label_en", "VARCHAR(64)"),
    ("contact_section", "title_en", "VARCHAR(256)"),
    ("contact_section", "lead_en", "TEXT"),
    ("contact_section", "address_label_en", "VARCHAR(64)"),
    ("contact_section", "phone_label_en", "VARCHAR(64)"),
    ("contact_section", "email_label_en", "VARCHAR(64)"),
    ("contact_section", "name_label_en", "VARCHAR(64)"),
    ("contact_section", "name_placeholder_en", "VARCHAR(128)"),
    ("contact_section", "phone_field_label_en", "VARCHAR(64)"),
    ("contact_section", "phone_placeholder_en", "VARCHAR(64)"),
    ("contact_section", "note_label_en", "VARCHAR(64)"),
    ("contact_section", "note_optional_label_en", "VARCHAR(64)"),
    ("contact_section", "note_placeholder_en", "VARCHAR(256)"),
    ("contact_section", "submit_label_en", "VARCHAR(128)"),
    ("contact_section", "sending_label_en", "VARCHAR(64)"),
    ("contact_section", "success_title_en", "VARCHAR(256)"),
    ("contact_section", "success_text_en", "TEXT"),
    ("contact_section", "success_button_label_en", "VARCHAR(128)"),
    ("newsletter", "title_en", "VARCHAR(256)"),
    ("newsletter", "lead_en", "TEXT"),
    ("newsletter", "placeholder_en", "VARCHAR(128)"),
    ("newsletter", "button_label_en", "VARCHAR(64)"),
    ("newsletter", "sending_label_en", "VARCHAR(64)"),
    ("newsletter", "success_text_en", "VARCHAR(256)"),
    ("footer", "about_text_en", "TEXT"),
    ("footer", "pages_heading_en", "VARCHAR(64)"),
    ("footer", "services_heading_en", "VARCHAR(64)"),
    ("footer", "contact_heading_en", "VARCHAR(64)"),
    ("footer", "copyright_en", "VARCHAR(256)"),
    ("footer", "tagline_en", "VARCHAR(256)"),
    ("footer", "socials_en", "JSON"),
    ("seo_meta", "title_en", "VARCHAR(256)"),
    ("seo_meta", "description_en", "TEXT"),
]


def run_ddl_migrations() -> None:
    """ستون‌های جدید — برای PostgreSQL با ADD COLUMN IF NOT EXISTS."""
    if engine.dialect.name != "postgresql":
        return
    with engine.begin() as conn:
        for table in POSITION_TABLES:
            conn.execute(
                text(f"ALTER TABLE {table} ADD COLUMN IF NOT EXISTS position INTEGER NOT NULL DEFAULT 0")
            )
        # مقالات موجود منتشر شده‌اند؛ فقط مقاله‌های تازه می‌توانند پیش‌نویس باشند
        conn.execute(
            text("ALTER TABLE articles ADD COLUMN IF NOT EXISTS status VARCHAR(16) NOT NULL DEFAULT 'published'")
        )
        conn.execute(
            text("ALTER TABLE articles ADD COLUMN IF NOT EXISTS seo_keyphrase VARCHAR(128) NOT NULL DEFAULT ''")
        )
        # ستون‌های انگلیسی — رشته‌ها با پیش‌فرض خالی، JSON بدون پیش‌فرض (NULL = بدون ترجمه)
        for table, column, col_type in EN_COLUMNS:
            if col_type == "JSON":
                conn.execute(text(f"ALTER TABLE {table} ADD COLUMN IF NOT EXISTS {column} JSON"))
            else:
                conn.execute(
                    text(f"ALTER TABLE {table} ADD COLUMN IF NOT EXISTS {column} {col_type} NOT NULL DEFAULT ''")
                )


def paragraphs_to_doc(paragraphs: list) -> dict:
    """تبدیل لیست پاراگراف‌های متنی (فرمت قدیمی بدنه مقاله) به سند TipTap."""
    content = []
    for para in paragraphs:
        if isinstance(para, str) and para.strip():
            content.append({
                "type": "paragraph",
                "content": [{"type": "text", "text": para}],
            })
    if not content:
        content = [{"type": "paragraph"}]
    return {"type": "doc", "content": content}


def migrate_article_bodies() -> None:
    """تبدیل بدنه مقالات از لیست پاراگراف به سند JSON — idempotent."""
    from . import models  # lazy — جلوگیری از import حلقه‌ای

    db = SessionLocal()
    try:
        changed = 0
        for article in db.query(models.Article).all():
            if isinstance(article.body, list):
                article.body = paragraphs_to_doc(article.body)
                changed += 1
        db.commit()
        if changed:
            print(f"مقالات تبدیل‌شده به فرمت سند: {changed}")
    finally:
        db.close()


def _is_empty(value: object) -> bool:
    """مقدار خالی انگلیسی — یعنی هنوز ترجمه‌ای ثبت نشده و قابل پر کردن است."""
    if value is None or value == "" or value == [] or value == {}:
        return True
    if isinstance(value, dict) and value.get("content") == [{"type": "paragraph"}]:
        return True
    return False


def _backfill_row(row, en_fields: dict) -> int:
    """پر کردن فیلدهای خالی *_en یک سطر از دیکشنری ترجمه — تعداد فیلدهای پرشده."""
    filled = 0
    for key, value in en_fields.items():
        if not key.endswith("_en"):
            continue
        if not _is_empty(getattr(row, key, None)):
            continue
        setattr(row, key, value)
        filled += 1
    return filled


def backfill_en_content() -> None:
    """پر کردن ترجمه‌های انگلیسی سطرهای موجود از seed_data_en — idempotent.

    تطبیق سطرها: جدول‌های تک‌سطری مستقیم؛ بقیه با کلیدهای طبیعی/متنی فارسی
    (مثلاً slug پروژه، href منو، عنوان خدمت، متن پرسش) — اگر ادمین متن فارسی را
    ویرایش کرده باشد سطر تطبیق نمی‌خورد و ترجمه‌اش خالی می‌ماند تا از پنل پر شود.
    هیچ مقدار انگلیسیِ ثبت‌شده بازنویسی نمی‌شود.
    """
    from . import models, seed_data, seed_data_en  # lazy — جلوگیری از import حلقه‌ای

    # (مدل، فهرست فارسی، فهرست انگلیسی، کلیدهای تطبیق — خالی برای تک‌سطری‌ها)
    PLAN: list[tuple[object, list[dict], list[dict], tuple[str, ...]]] = [
        (models.Brand, [seed_data.BRAND], [seed_data_en.BRAND], ()),
        (models.Hero, [seed_data.HERO], [seed_data_en.HERO], ()),
        (models.StorySection, [seed_data.STORY], [seed_data_en.STORY], ()),
        (models.SectionHeadingContent, seed_data.SECTION_HEADINGS, seed_data_en.SECTION_HEADINGS, ("key", "title")),
        (models.PageHeroContent, seed_data.PAGE_HEROES, seed_data_en.PAGE_HEROES, ("key", "title")),
        (models.NavItem, seed_data.NAV_ITEMS, seed_data_en.NAV_ITEMS, ("href", "label")),
        (models.InvestmentModel, seed_data.INVESTMENT_MODELS, seed_data_en.INVESTMENT_MODELS, ("title",)),
        (models.ProcessStep, seed_data.PROCESS_STEPS, seed_data_en.PROCESS_STEPS, ("title",)),
        (models.Office, seed_data.OFFICES, seed_data_en.OFFICES, ("city",)),
        (models.GalleryImage, seed_data.GALLERY_IMAGES, seed_data_en.GALLERY_IMAGES, ("alt",)),
        (models.StatusLabel, seed_data.STATUS_LABELS, seed_data_en.STATUS_LABELS, ("key",)),
        (models.ContactSectionContent, [seed_data.CONTACT_SECTION], [seed_data_en.CONTACT_SECTION], ()),
        (models.NewsletterSectionContent, [seed_data.NEWSLETTER], [seed_data_en.NEWSLETTER], ()),
        (models.FooterContent, [seed_data.FOOTER], [seed_data_en.FOOTER], ()),
        (models.Service, seed_data.SERVICES, seed_data_en.SERVICES, ("title",)),
        (models.Stat, seed_data.STATS, seed_data_en.STATS, ("label",)),
        (models.Project, seed_data.PROJECTS, seed_data_en.PROJECTS, ("slug", "title")),
        (models.Article, seed_data.ARTICLES, seed_data_en.ARTICLES, ("slug", "title")),
        (models.Testimonial, seed_data.TESTIMONIALS, seed_data_en.TESTIMONIALS, ("name",)),
        (models.Faq, seed_data.FAQS, seed_data_en.FAQS, ("question",)),
        (models.TeamMember, seed_data.TEAM, seed_data_en.TEAM, ("name",)),
        (models.TimelineItem, seed_data.TIMELINE, seed_data_en.TIMELINE, ("title",)),
        (models.WhyUsItem, seed_data.WHY, seed_data_en.WHY, ("title",)),
        (models.BeforeAfter, [seed_data.BEFORE_AFTER], [seed_data_en.BEFORE_AFTER], ()),
        (models.SeoMeta, seed_data.SEO_META, seed_data_en.SEO_META, ("page_key",)),
    ]

    db = SessionLocal()
    try:
        total_rows = 0
        total_fields = 0
        unmatched: list[str] = []
        for model, fa_rows, en_rows, match_keys in PLAN:
            rows = db.query(model).all()
            if not rows or not en_rows:
                continue
            table_name = getattr(model, "__tablename__", str(model))

            if not match_keys:
                if len(rows) != 1 or len(en_rows) != 1:
                    unmatched.append(table_name)
                    continue
                pairs = [(rows[0], en_rows[0])]
            else:
                # برای هر کلید، نگاشت مقدار → سطر ترجمه (اولین کلید برنده است)
                en_lookups: list[dict[object, dict]] = []
                for key in match_keys:
                    en_lookups.append({r[key]: r for r in en_rows if r.get(key) is not None})
                pairs = []
                matched_en_ids: set[int] = set()
                for row in rows:
                    en_row = None
                    for key, lookup in zip(match_keys, en_lookups):
                        en_row = lookup.get(getattr(row, key, None))
                        if en_row is not None:
                            break
                    if en_row is not None and id(en_row) not in matched_en_ids:
                        matched_en_ids.add(id(en_row))
                        pairs.append((row, en_row))

            for row, en_row in pairs:
                # بدنه مقاله انگلیسی هم مثل فارسی از پاراگراف به سند تبدیل می‌شود
                en_fields = dict(en_row)
                if model is models.Article and isinstance(en_fields.get("body_en"), list):
                    en_fields["body_en"] = paragraphs_to_doc(en_fields["body_en"])
                filled = _backfill_row(row, en_fields)
                total_fields += filled
                if filled:
                    total_rows += 1

        db.commit()
        if total_fields:
            print(f"ترجمه انگلیسی پر شد: {total_fields} فیلد در {total_rows} سطر.")
        if unmatched:
            print("سطرهایی که با seed تطبیق نکردند (از پنل مدیریت ترجمه کنید):")
            for name in unmatched:
                print(f"  - {name}")
    finally:
        db.close()


def run_all() -> None:
    run_ddl_migrations()
    migrate_article_bodies()
    backfill_en_content()