346 lines
17 KiB
Python
346 lines
17 KiB
Python
"""مهاجرت‌های سبک دیتابیس — DDL و تبدیل داده‌های قدیمی؛ همه idempotent.
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هم main.py (startup) و هم seed.py این‌ها را صدا می‌زنند تا هر مسیر اجرایی
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دیتابیس موجود را بدون از دست رفتن داده ارتقا دهد.
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"""
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from sqlalchemy import text
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from .database import SessionLocal, engine
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# جدول‌های مجموعه‌ای که ستون position دارند
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POSITION_TABLES = [
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"services", "projects", "articles", "testimonials", "faqs", "team",
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"timeline", "stats", "why_us", "investment_models", "process_steps",
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"offices", "gallery_images", "nav_items",
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]
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# ستون‌های انگلیسی — (جدول، ستون، نوع). ستون‌های JSON بدون default اند تا
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# سطرهای موجود NULL بگیرند (یعنی «ترجمه ثبت نشده») و فرانت به فارسی برگردد.
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EN_COLUMNS: list[tuple[str, str, str]] = [
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("brand", "name_en", "VARCHAR(128)"),
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("brand", "address_en", "TEXT"),
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("services", "title_en", "VARCHAR(256)"),
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("services", "desc_en", "TEXT"),
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("projects", "title_en", "VARCHAR(256)"),
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("projects", "location_en", "VARCHAR(128)"),
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("projects", "year_en", "VARCHAR(64)"),
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("projects", "area_en", "VARCHAR(64)"),
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("projects", "floors_en", "VARCHAR(64)"),
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("projects", "land_area", "VARCHAR(64)"),
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("projects", "pilot_floors", "VARCHAR(32)"),
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("projects", "units_residential", "VARCHAR(32)"),
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("projects", "units_commercial", "VARCHAR(32)"),
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("projects", "units_office", "VARCHAR(32)"),
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("projects", "client_en", "VARCHAR(128)"),
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("projects", "project_type", "VARCHAR(128)"),
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("projects", "project_type_en", "VARCHAR(128)"),
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("projects", "usage", "VARCHAR(128)"),
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("projects", "usage_en", "VARCHAR(128)"),
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("projects", "summary_en", "TEXT"),
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("projects", "body_en", "JSON"),
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("articles", "title_en", "VARCHAR(256)"),
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("articles", "date_en", "VARCHAR(64)"),
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("articles", "category_en", "VARCHAR(64)"),
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("articles", "read_en", "VARCHAR(32)"),
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("articles", "excerpt_en", "TEXT"),
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("articles", "body_en", "JSON"),
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("testimonials", "name_en", "VARCHAR(128)"),
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("testimonials", "role_en", "VARCHAR(128)"),
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("testimonials", "quote_en", "TEXT"),
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("faqs", "question_en", "TEXT"),
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("faqs", "answer_en", "TEXT"),
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("team", "name_en", "VARCHAR(128)"),
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("team", "role_en", "VARCHAR(128)"),
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("team", "bio_en", "TEXT"),
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("timeline", "year_en", "VARCHAR(32)"),
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("timeline", "title_en", "VARCHAR(256)"),
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("timeline", "desc_en", "TEXT"),
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("stats", "suffix_en", "VARCHAR(16)"),
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("stats", "label_en", "VARCHAR(128)"),
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("why_us", "title_en", "VARCHAR(256)"),
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("why_us", "desc_en", "TEXT"),
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("before_after", "title_en", "VARCHAR(256)"),
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("before_after", "lead_en", "TEXT"),
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("before_after", "before_label_en", "VARCHAR(128)"),
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("before_after", "after_label_en", "VARCHAR(128)"),
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("nav_items", "label_en", "VARCHAR(64)"),
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("hero", "kicker_en", "TEXT"),
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("hero", "title_en", "TEXT"),
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("hero", "title_highlight_en", "VARCHAR(128)"),
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("hero", "subtitle_en", "TEXT"),
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("hero", "badge_value_en", "VARCHAR(32)"),
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("hero", "badge_label_en", "TEXT"),
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("hero", "cta_primary_label_en", "VARCHAR(128)"),
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("hero", "cta_secondary_label_en", "VARCHAR(128)"),
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("hero", "scroll_label_en", "VARCHAR(64)"),
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("story", "title_en", "VARCHAR(256)"),
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("story", "paragraphs_en", "JSON"),
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("story", "quote_en", "TEXT"),
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("story", "quote_author_en", "TEXT"),
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("story", "stat1_value_en", "VARCHAR(32)"),
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("story", "stat1_label_en", "VARCHAR(128)"),
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("story", "stat2_value_en", "VARCHAR(32)"),
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("story", "stat2_label_en", "VARCHAR(128)"),
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("story", "link_label_en", "VARCHAR(128)"),
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("story", "bento_en", "JSON"),
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("section_headings", "label_en", "VARCHAR(64)"),
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("section_headings", "title_en", "VARCHAR(256)"),
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("section_headings", "lead_en", "TEXT"),
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("section_headings", "cta_label_en", "VARCHAR(128)"),
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("page_heroes", "title_en", "VARCHAR(256)"),
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("page_heroes", "lead_en", "TEXT"),
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("investment_models", "title_en", "VARCHAR(256)"),
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("investment_models", "desc_en", "TEXT"),
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("investment_models", "points_en", "JSON"),
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("process_steps", "step_en", "VARCHAR(16)"),
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("process_steps", "title_en", "VARCHAR(256)"),
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("process_steps", "desc_en", "TEXT"),
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("offices", "city_en", "VARCHAR(64)"),
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("offices", "address_en", "TEXT"),
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("offices", "hours_en", "VARCHAR(128)"),
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("gallery_images", "alt_en", "TEXT"),
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("status_labels", "label_en", "VARCHAR(64)"),
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("contact_section", "label_en", "VARCHAR(64)"),
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("contact_section", "title_en", "VARCHAR(256)"),
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("contact_section", "lead_en", "TEXT"),
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("contact_section", "address_label_en", "VARCHAR(64)"),
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("contact_section", "phone_label_en", "VARCHAR(64)"),
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("contact_section", "email_label_en", "VARCHAR(64)"),
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("contact_section", "name_label_en", "VARCHAR(64)"),
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("contact_section", "name_placeholder_en", "VARCHAR(128)"),
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("contact_section", "phone_field_label_en", "VARCHAR(64)"),
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("contact_section", "phone_placeholder_en", "VARCHAR(64)"),
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("contact_section", "note_label_en", "VARCHAR(64)"),
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("contact_section", "note_optional_label_en", "VARCHAR(64)"),
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("contact_section", "note_placeholder_en", "VARCHAR(256)"),
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("contact_section", "submit_label_en", "VARCHAR(128)"),
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("contact_section", "sending_label_en", "VARCHAR(64)"),
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("contact_section", "success_title_en", "VARCHAR(256)"),
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("contact_section", "success_text_en", "TEXT"),
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("contact_section", "success_button_label_en", "VARCHAR(128)"),
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("newsletter", "title_en", "VARCHAR(256)"),
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("newsletter", "lead_en", "TEXT"),
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("newsletter", "placeholder_en", "VARCHAR(128)"),
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("newsletter", "button_label_en", "VARCHAR(64)"),
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("newsletter", "sending_label_en", "VARCHAR(64)"),
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("newsletter", "success_text_en", "VARCHAR(256)"),
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("footer", "about_text_en", "TEXT"),
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("footer", "pages_heading_en", "VARCHAR(64)"),
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("footer", "services_heading_en", "VARCHAR(64)"),
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("footer", "contact_heading_en", "VARCHAR(64)"),
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("footer", "copyright_en", "VARCHAR(256)"),
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("footer", "tagline_en", "VARCHAR(256)"),
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("footer", "socials_en", "JSON"),
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("seo_meta", "title_en", "VARCHAR(256)"),
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("seo_meta", "description_en", "TEXT"),
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]
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def run_ddl_migrations() -> None:
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"""ستون‌های جدید — برای PostgreSQL با ADD COLUMN IF NOT EXISTS."""
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if engine.dialect.name != "postgresql":
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return
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with engine.begin() as conn:
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for table in POSITION_TABLES:
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conn.execute(
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text(f"ALTER TABLE {table} ADD COLUMN IF NOT EXISTS position INTEGER NOT NULL DEFAULT 0")
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)
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# مقالات موجود منتشر شده‌اند؛ فقط مقاله‌های تازه می‌توانند پیش‌نویس باشند
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conn.execute(
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text("ALTER TABLE articles ADD COLUMN IF NOT EXISTS status VARCHAR(16) NOT NULL DEFAULT 'published'")
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)
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conn.execute(
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text("ALTER TABLE articles ADD COLUMN IF NOT EXISTS seo_keyphrase VARCHAR(128) NOT NULL DEFAULT ''")
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)
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# نام نویسنده و توضیحات سئوی اختصاصی مقاله — فیلدهایی که پنل قبلاً نمایش می‌داد ولی در دیتابیس نبودند
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conn.execute(
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text("ALTER TABLE articles ADD COLUMN IF NOT EXISTS author VARCHAR(128) NOT NULL DEFAULT ''")
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)
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conn.execute(
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text("ALTER TABLE articles ADD COLUMN IF NOT EXISTS meta_description TEXT NOT NULL DEFAULT ''")
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)
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conn.execute(
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text("ALTER TABLE articles ADD COLUMN IF NOT EXISTS meta_description_en TEXT NOT NULL DEFAULT ''")
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)
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# نقش‌ها — 'admin' همه‌کاره، 'creator' فقط نویسندهٔ محتوا
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conn.execute(
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text("ALTER TABLE admin_users ADD COLUMN IF NOT EXISTS role VARCHAR(16) NOT NULL DEFAULT 'admin'")
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)
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# نویسندهٔ مقاله — نقش creator فقط مقاله‌های خودش را می‌بیند/ویرایش می‌کند
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conn.execute(
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text("ALTER TABLE articles ADD COLUMN IF NOT EXISTS author_id INTEGER")
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)
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# متادیتای تصویر شاخص مقاله + پرسش‌وپاسخ‌های پایان مقاله (سئو)
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conn.execute(
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text("ALTER TABLE articles ADD COLUMN IF NOT EXISTS image_alt VARCHAR(256) NOT NULL DEFAULT ''")
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)
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conn.execute(
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text("ALTER TABLE articles ADD COLUMN IF NOT EXISTS image_title VARCHAR(256) NOT NULL DEFAULT ''")
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)
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conn.execute(text("ALTER TABLE articles ADD COLUMN IF NOT EXISTS faqs JSON"))
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conn.execute(text("ALTER TABLE articles ADD COLUMN IF NOT EXISTS faqs_en JSON"))
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# سطرهای موجود ستون تازه را NULL می‌گیرند — آرایه خالی یعنی «بدون پرسش‌وپاسخ»
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conn.execute(text("UPDATE articles SET faqs = '[]'::json WHERE faqs IS NULL"))
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# ستون‌های انگلیسی — رشته‌ها با پیش‌فرض خالی، JSON بدون پیش‌فرض (NULL = بدون ترجمه)
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for table, column, col_type in EN_COLUMNS:
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if col_type == "JSON":
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conn.execute(text(f"ALTER TABLE {table} ADD COLUMN IF NOT EXISTS {column} JSON"))
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else:
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conn.execute(
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text(f"ALTER TABLE {table} ADD COLUMN IF NOT EXISTS {column} {col_type} NOT NULL DEFAULT ''")
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)
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def paragraphs_to_doc(paragraphs: list) -> dict:
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"""تبدیل لیست پاراگراف‌های متنی (فرمت قدیمی بدنه مقاله) به سند TipTap."""
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content = []
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for para in paragraphs:
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if isinstance(para, str) and para.strip():
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content.append({
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"type": "paragraph",
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"content": [{"type": "text", "text": para}],
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})
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if not content:
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content = [{"type": "paragraph"}]
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return {"type": "doc", "content": content}
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def migrate_article_bodies() -> None:
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"""تبدیل بدنه مقالات از لیست پاراگراف به سند JSON — idempotent."""
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from . import models # lazy — جلوگیری از import حلقه‌ای
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db = SessionLocal()
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try:
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changed = 0
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for article in db.query(models.Article).all():
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if isinstance(article.body, list):
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article.body = paragraphs_to_doc(article.body)
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changed += 1
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db.commit()
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if changed:
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print(f"مقالات تبدیل‌شده به فرمت سند: {changed}")
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finally:
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db.close()
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def _is_empty(value: object) -> bool:
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"""مقدار خالی انگلیسی — یعنی هنوز ترجمه‌ای ثبت نشده و قابل پر کردن است."""
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if value is None or value == "" or value == [] or value == {}:
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return True
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if isinstance(value, dict) and value.get("content") == [{"type": "paragraph"}]:
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return True
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return False
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def _backfill_row(row, en_fields: dict) -> int:
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"""پر کردن فیلدهای خالی *_en یک سطر از دیکشنری ترجمه — تعداد فیلدهای پرشده."""
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filled = 0
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for key, value in en_fields.items():
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if not key.endswith("_en"):
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continue
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if not _is_empty(getattr(row, key, None)):
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continue
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setattr(row, key, value)
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filled += 1
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return filled
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def backfill_en_content() -> None:
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"""پر کردن ترجمه‌های انگلیسی سطرهای موجود از seed_data_en — idempotent.
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تطبیق سطرها: جدول‌های تک‌سطری مستقیم؛ بقیه با کلیدهای طبیعی/متنی فارسی
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(مثلاً slug پروژه، href منو، عنوان خدمت، متن پرسش) — اگر ادمین متن فارسی را
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ویرایش کرده باشد سطر تطبیق نمی‌خورد و ترجمه‌اش خالی می‌ماند تا از پنل پر شود.
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هیچ مقدار انگلیسیِ ثبت‌شده بازنویسی نمی‌شود.
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"""
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from . import models, seed_data, seed_data_en # lazy — جلوگیری از import حلقه‌ای
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# (مدل، فهرست فارسی، فهرست انگلیسی، کلیدهای تطبیق — خالی برای تک‌سطری‌ها)
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PLAN: list[tuple[object, list[dict], list[dict], tuple[str, ...]]] = [
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(models.Brand, [seed_data.BRAND], [seed_data_en.BRAND], ()),
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(models.Hero, [seed_data.HERO], [seed_data_en.HERO], ()),
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(models.StorySection, [seed_data.STORY], [seed_data_en.STORY], ()),
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(models.SectionHeadingContent, seed_data.SECTION_HEADINGS, seed_data_en.SECTION_HEADINGS, ("key", "title")),
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(models.PageHeroContent, seed_data.PAGE_HEROES, seed_data_en.PAGE_HEROES, ("key", "title")),
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(models.NavItem, seed_data.NAV_ITEMS, seed_data_en.NAV_ITEMS, ("href", "label")),
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(models.InvestmentModel, seed_data.INVESTMENT_MODELS, seed_data_en.INVESTMENT_MODELS, ("title",)),
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(models.ProcessStep, seed_data.PROCESS_STEPS, seed_data_en.PROCESS_STEPS, ("title",)),
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(models.Office, seed_data.OFFICES, seed_data_en.OFFICES, ("city",)),
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(models.GalleryImage, seed_data.GALLERY_IMAGES, seed_data_en.GALLERY_IMAGES, ("alt",)),
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(models.StatusLabel, seed_data.STATUS_LABELS, seed_data_en.STATUS_LABELS, ("key",)),
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(models.ContactSectionContent, [seed_data.CONTACT_SECTION], [seed_data_en.CONTACT_SECTION], ()),
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(models.NewsletterSectionContent, [seed_data.NEWSLETTER], [seed_data_en.NEWSLETTER], ()),
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(models.FooterContent, [seed_data.FOOTER], [seed_data_en.FOOTER], ()),
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(models.Service, seed_data.SERVICES, seed_data_en.SERVICES, ("title",)),
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(models.Stat, seed_data.STATS, seed_data_en.STATS, ("label",)),
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(models.Project, seed_data.PROJECTS, seed_data_en.PROJECTS, ("slug", "title")),
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(models.Article, seed_data.ARTICLES, seed_data_en.ARTICLES, ("slug", "title")),
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(models.Testimonial, seed_data.TESTIMONIALS, seed_data_en.TESTIMONIALS, ("name",)),
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(models.Faq, seed_data.FAQS, seed_data_en.FAQS, ("question",)),
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(models.TeamMember, seed_data.TEAM, seed_data_en.TEAM, ("name",)),
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(models.TimelineItem, seed_data.TIMELINE, seed_data_en.TIMELINE, ("title",)),
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(models.WhyUsItem, seed_data.WHY, seed_data_en.WHY, ("title",)),
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(models.BeforeAfter, [seed_data.BEFORE_AFTER], [seed_data_en.BEFORE_AFTER], ()),
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(models.SeoMeta, seed_data.SEO_META, seed_data_en.SEO_META, ("page_key",)),
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]
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db = SessionLocal()
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try:
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total_rows = 0
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total_fields = 0
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unmatched: list[str] = []
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for model, fa_rows, en_rows, match_keys in PLAN:
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rows = db.query(model).all()
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if not rows or not en_rows:
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continue
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table_name = getattr(model, "__tablename__", str(model))
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if not match_keys:
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if len(rows) != 1 or len(en_rows) != 1:
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unmatched.append(table_name)
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continue
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pairs = [(rows[0], en_rows[0])]
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else:
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# برای هر کلید، نگاشت مقدار → سطر ترجمه (اولین کلید برنده است)
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en_lookups: list[dict[object, dict]] = []
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for key in match_keys:
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en_lookups.append({r[key]: r for r in en_rows if r.get(key) is not None})
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pairs = []
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matched_en_ids: set[int] = set()
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for row in rows:
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en_row = None
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for key, lookup in zip(match_keys, en_lookups):
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en_row = lookup.get(getattr(row, key, None))
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if en_row is not None:
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break
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if en_row is not None and id(en_row) not in matched_en_ids:
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matched_en_ids.add(id(en_row))
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pairs.append((row, en_row))
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for row, en_row in pairs:
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# بدنه مقاله انگلیسی هم مثل فارسی از پاراگراف به سند تبدیل می‌شود
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en_fields = dict(en_row)
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if model is models.Article and isinstance(en_fields.get("body_en"), list):
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en_fields["body_en"] = paragraphs_to_doc(en_fields["body_en"])
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filled = _backfill_row(row, en_fields)
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total_fields += filled
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if filled:
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total_rows += 1
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db.commit()
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if total_fields:
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print(f"ترجمه انگلیسی پر شد: {total_fields} فیلد در {total_rows} سطر.")
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if unmatched:
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print("سطرهایی که با seed تطبیق نکردند (از پنل مدیریت ترجمه کنید):")
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for name in unmatched:
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print(f" - {name}")
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finally:
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db.close()
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def run_all() -> None:
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run_ddl_migrations()
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migrate_article_bodies()
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backfill_en_content()
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