{"slug":"pavelzw-sqlalchemy","name":"sqlalchemy","description":"Python SQL toolkit and Object Relational Mapper (ORM). Use when working with databases in Python, defining models, building queries, managing sessions, or interacting with SQL databases using Python objects.","long_description":"---\nname: sqlalchemy\ndescription: Python SQL toolkit and Object Relational Mapper (ORM). Use when working with databases in Python, defining models, building queries, managing sessions, or interacting with SQL databases using Python objects.\nlicense: MIT\n---\n\n# SQLAlchemy Skill\n\nSQLAlchemy is the Python SQL toolkit and Object Relational Mapper that provides the full power and flexibility of SQL. It consists of two main components: **Core** (SQL Expression Language) and **ORM** (Object Relational Mapper).\n\n## When to Use This Skill\n\nUse SQLAlchemy when:\n- Working with relational databases in Python\n- Defining database models as Python classes\n- Building SQL queries programmatically\n- Managing database transactions and sessions\n- Mapping Python objects to database tables\n- Need database-agnostic code that works across PostgreSQL, MySQL, SQLite, etc.\n\n## Installation\n\n```bash\npip install sqlalchemy\n\n# For async support\npip install sqlalchemy[asyncio]\n```\n\n## Architecture Overview\n\n```\n┌─────────────────────────────────────────────────────────────┐\n│                    SQLAlchemy ORM                           │\n│  (Declarative Mapping, Session, Relationships, Unit of Work)│\n├─────────────────────────────────────────────────────────────┤\n│                   SQLAlchemy Core                           │\n│     (SQL Expression Language, Engine, Connection Pool)      │\n├─────────────────────────────────────────────────────────────┤\n│                        DBAPI                                │\n│         (psycopg2, pymysql, sqlite3, etc.)                  │\n└─────────────────────────────────────────────────────────────┘\n```\n\n## Engine and Connection\n\nThe Engine is the starting point for SQLAlchemy applications:\n\n```python\nfrom sqlalchemy import create_engine\n\n# SQLite (in-memory)\nengine = create_engine(\"sqlite://\", echo=True)\n\n# SQLite (file-based)\nengine = create_engine(\"sqlite:///mydatabase.db\")\n\n# PostgreSQL\nengine = create_engine(\"postgresql+psycopg2://user:password@localhost/dbname\")\n\n# MySQL\nengine = create_engine(\"mysql+pymysql://user:password@localhost/dbname\")\n\n# Connection pool settings\nengine = create_engine(\n    \"postgresql+psycopg2://user:password@localhost/dbname\",\n    pool_size=5,           # Number of connections to keep open\n    max_overflow=10,       # Additional connections allowed\n    pool_timeout=30,       # Seconds to wait for connection\n    pool_recycle=1800,     # Recycle connections after N seconds\n)\n```\n\n### Using Connections Directly (Core)\n\n```python\nfrom sqlalchemy import text\n\nwith engine.connect() as conn:\n    result = conn.execute(text(\"SELECT * FROM users WHERE id = :id\"), {\"id\": 1})\n    for row in result:\n        print(row)\n\n    # For write operations, commit explicitly\n    conn.execute(text(\"INSERT INTO users (name) VALUES (:name)\"), {\"name\": \"Alice\"})\n    conn.commit()\n```\n\n## ORM Declarative Mapping\n\n\n```python\nfrom datetime import datetime\nfrom typing import List, Optional\n\nfrom sqlalchemy import ForeignKey, String, func\nfrom sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column, relationship\n\n\nclass Base(DeclarativeBase):\n    pass\n\n\nclass User(Base):\n    __tablename__ = \"user_account\"\n\n    # Primary key with auto-increment\n    id: Mapped[int] = mapped_column(primary_key=True)\n\n    # Required string column with max length\n    name: Mapped[str] = mapped_column(String(30))\n\n    # Optional column (nullable)\n    fullname: Mapped[Optional[str]]\n\n    # Column with default value\n    created_at: Mapped[datetime] = mapped_column(default=func.now())\n\n    # One-to-many relationship\n    addresses: Mapped[List[\"Address\"]] = relationship(\n        back_populates=\"user\",\n        cascade=\"all, delete-orphan\"\n    )\n\n    def __repr__(self) -> str:\n        return f\"User(id={self.id!r}, name={self.name!r})\"\n\n\nclass Address(Base):\n    __tablename__ = \"address\"\n\n    id: Mapped[int] = mapped_column(primary_key=True)\n    email_address: Mapped[str]\n    user_id: Mapped[int] = mapped_column(ForeignKey(\"user_account.id\"))\n\n    # Many-to-one relationship (back reference)\n    user: Mapped[\"User\"] = relationship(back_populates=\"addresses\")\n\n    def __repr__(self) -> str:\n        return f\"Address(id={self.id!r}, email_address={self.email_address!r})\"\n```\n\n### Type Annotation Guide\n\n| Python Type | SQL Type | Nullable |\n|-------------|----------|----------|\n| `Mapped[int]` | INTEGER | NOT NULL |\n| `Mapped[Optional[int]]` | INTEGER | NULL |\n| `Mapped[str]` | VARCHAR | NOT NULL |\n| `Mapped[Optional[str]]` | VARCHAR | NULL |\n| `Mapped[bool]` | BOOLEAN | NOT NULL |\n| `Mapped[datetime]` | DATETIME | NOT NULL |\n| `Mapped[float]` | FLOAT | NOT NULL |\n| `Mapped[bytes]` | BLOB/BYTEA | NOT NULL |\n\n### Creating Tables\n\n```python\n# Create all tables defined in Base.metadata\nBase.metadata.create_all(engine)\n\n# Drop all tables\nBase.metadata.drop_all(engine)\n```\n\n## Session and CRUD Operations\n\n### Session Basics\n\n```python\nfrom sqlalchemy.orm import Session, sessionmaker\n\n# Option 1: Direct Session usage\nwith Session(engine) as session:\n    # ... operations\n    session.commit()\n\n# Option 2: Using sessionmaker (recommended for applications)\nSessionFactory = sessionmaker(bind=engine)\n\nwith SessionFactory() as session:\n    # ... operations\n    session.commit()\n\n# Option 3: With explicit begin/commit/rollback\nwith Session(engine) as session:\n    with session.begin():\n        # Automatically commits on success, rolls back on exception\n        session.add(some_object)\n```\n\n### Create (INSERT)\n\n```python\nwith Session(engine) as session:\n    # Create single object\n    user = User(name=\"alice\", fullname=\"Alice Smith\")\n    session.add(user)\n\n    # Create with related objects\n    user_with_addresses = User(\n        name=\"bob\",\n        fullname=\"Bob Jones\",\n        addresses=[\n            Address(email_address=\"bob@example.com\"),\n            Address(email_address=\"bob@work.com\"),\n        ]\n    )\n    session.add(user_with_addresses)\n\n    # Add multiple objects\n    session.add_all([\n        User(name=\"carol\"),\n        User(name=\"dave\"),\n    ])\n\n    session.commit()\n```\n\n### Read (SELECT)\n\n```python\nfrom sqlalchemy import select\n\nwith Session(engine) as session:\n    # Get by primary key\n    user = session.get(User, 1)\n\n    # Select all\n    stmt = select(User)\n    users = session.scalars(stmt).all()\n\n    # Select with filter\n    stmt = select(User).where(User.name == \"alice\")\n    alice = session.scalars(stmt).first()\n\n    # Select with multiple conditions\n    stmt = select(User).where(\n        User.name.like(\"a%\"),\n        User.id > 5\n    )\n\n    # Select specific columns\n    stmt = select(User.name, User.fullname)\n    rows = session.execute(stmt).all()\n    for name, fullname in rows:\n        print(f\"{name}: {fullname}\")\n\n    # Order by\n    stmt = select(User).order_by(User.name.desc())\n\n    # Limit and offset\n    stmt = select(User).limit(10).offset(20)\n\n    # Count\n    from sqlalchemy import func\n    stmt = select(func.count()).select_from(User)\n    count = session.scalar(stmt)\n```\n\n### Update\n\n```python\nwith Session(engine) as session:\n    # Update via ORM (load then modify)\n    user = session.get(User, 1)\n    user.fullname = \"Alice Johnson\"\n    session.commit()\n\n    # Bulk update\n    from sqlalchemy import update\n    stmt = update(User).where(User.name == \"alice\").values(fullname=\"Alice Updated\")\n    session.execute(stmt)\n    session.commit()\n```\n\n### Delete\n\n```python\nwith Session(engine) as session:\n    # Delete via ORM\n    user = session.get(User, 1)\n    session.delete(user)\n    session.commit()\n\n    # Bulk delete\n    from sqlalchemy import delete\n    stmt = delete(User).where(User.name == \"alice\")\n    session.execute(stmt)\n    session.commit()\n```\n\n## Relationships\n\n### One-to-Many / Many-to-One\n\n```python\nclass Parent(Base):\n    __tablename__ = \"parent\"\n\n    id: Mapped[int] = mapped_column(primary_key=True)\n    children: Mapped[List[\"Child\"]] = relationship(back_populates=\"parent\")\n\n\nclass Child(Base):\n    __tablename__ = \"child\"\n\n    id: Mapped[int] = mapped_column(primary_key=True)\n    parent_id: Mapped[int] = mapped_column(ForeignKey(\"parent.id\"))\n    parent: Mapped[\"Parent\"] = relationship(back_populates=\"children\")\n```\n\n### One-to-One\n\n```python\nclass User(Base):\n    __tablename__ = \"user\"\n\n    id: Mapped[int] = mapped_column(primary_key=True)\n    profile: Mapped[\"Profile\"] = relationship(back_populates=\"user\", uselist=False)\n\n\nclass Profile(Base):\n    __tablename__ = \"profile\"\n\n    id: Mapped[int] = mapped_column(primary_key=True)\n    user_id: Mapped[int] = mapped_column(ForeignKey(\"user.id\"), unique=True)\n    user: Mapped[\"User\"] = relationship(back_populates=\"profile\")\n```\n\n### Many-to-Many\n\n```python\nfrom sqlalchemy import Column, Table\n\n# Association table (no ORM class needed)\nassociation_table = Table(\n    \"association\",\n    Base.metadata,\n    Column(\"left_id\", ForeignKey(\"left.id\"), primary_key=True),\n    Column(\"right_id\", ForeignKey(\"right.id\"), primary_key=True),\n)\n\n\nclass Left(Base):\n    __tablename__ = \"left\"\n\n    id: Mapped[int] = mapped_column(primary_key=True)\n    rights: Mapped[List[\"Right\"]] = relationship(\n        secondary=association_table,\n        back_populates=\"lefts\"\n    )\n\n\nclass Right(Base):\n    __tablename__ = \"right\"\n\n    id: Mapped[int] = mapped_column(primary_key=True)\n    lefts: Mapped[List[\"Left\"]] = relationship(\n        secondary=association_table,\n        back_populates=\"rights\"\n    )\n```\n\n### Association Object (Many-to-Many with extra data)\n\n```python\nclass Association(Base):\n    __tablename__ = \"association\"\n\n    left_id: Mapped[int] = mapped_column(ForeignKey(\"left.id\"), primary_key=True)\n    right_id: Mapped[int] = mapped_column(ForeignKey(\"right.id\"), primary_key=True)\n    extra_data: Mapped[Optional[str]]\n\n    left: Mapped[\"Left\"] = relationship(back_populates=\"right_associations\")\n    right: Mapped[\"Right\"] = relationship(back_populates=\"left_associations\")\n\n\nclass Left(Base):\n    __tablename__ = \"left\"\n\n    id: Mapped[int] = mapped_column(primary_key=True)\n    right_associations: Mapped[List[\"Association\"]] = relationship(back_populates=\"left\")\n\n\nclass Right(Base):\n    __tablename__ = \"right\"\n\n    id: Mapped[int] = mapped_column(primary_key=True)\n    left_associations: Mapped[List[\"Association\"]] = relationship(back_populates=\"right\")\n```\n\n## Loading Strategies\n\n### Lazy Loading (Default)\n\n```python\n# Lazy loading - queries database when attribute is accessed\nuser = session.get(User, 1)\n# SELECT ... FROM user WHERE id = 1\n\naddresses = user.addresses  # N+1 query problem!\n# SELECT ... FROM address WHERE user_id = 1\n```\n\n### Eager Loading with joinedload\n\n```python\nfrom sqlalchemy.orm import joinedload\n\n# Load user and addresses in single query using JOIN\nstmt = select(User).options(joinedload(User.addresses)).where(User.id == 1)\nuser = session.scalars(stmt).unique().first()\n# SELECT ... FROM user LEFT OUTER JOIN address ON ...\n```\n\n### Eager Loading with selectinload (Recommended)\n\n```python\nfrom sqlalchemy.orm import selectinload\n\n# Load users, then load all addresses with IN clause\nstmt = select(User).options(selectinload(User.addresses))\nusers = session.scalars(stmt).all()\n# SELECT ... FROM user\n# SELECT ... FROM address WHERE user_id IN (1, 2, 3, ...)\n```\n\n### Raise on Lazy Load (Prevent N+1)\n\n```python\nfrom sqlalchemy.orm import raiseload\n\n# Raise error if lazy loading is attempted\nstmt = select(User).options(raiseload(User.addresses))\nuser = session.scalars(stmt).first()\nuser.addresses  # Raises InvalidRequestError\n```\n\n### Setting Default Loading Strategy\n\n```python\nclass User(Base):\n    __tablename__ = \"user\"\n\n    id: Mapped[int] = mapped_column(primary_key=True)\n    # Always eager load addresses\n    addresses: Mapped[List[\"Address\"]] = relationship(lazy=\"selection\")\n```\n\n## Joins and Complex Queries\n\n```python\nfrom sqlalchemy import select, and_, or_, func\n\n# Explicit JOIN\nstmt = (\n    select(User, Address)\n    .join(Address, User.id == Address.user_id)\n    .where(User.name == \"alice\")\n)\n\n# JOIN using relationship\nstmt = (\n    select(","tagline":"Python SQL toolkit and Object Relational Mapper (ORM). 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Creators can claim the listing to update ownership signals."},"stats":{"stars":24,"forks":10,"verified_installs":0,"successful_runs":0,"total_outcomes":0,"rating":0,"review_count":0,"quality_score":27.79},"quality":{"score":55,"tier":"promising","label":"Promising","summary":"Useful candidate, but compare it with alternatives before adopting.","signals":[{"label":"GitHub stars","value":"24","tone":"neutral"},{"label":"Freshness","value":"5d ago","tone":"positive"},{"label":"Install ready","value":"Yes","tone":"positive"},{"label":"License","value":"MIT","tone":"neutral"}],"warnings":["Low GitHub adoption signal"]},"trust":{"version":"trust-score-v5","score":57,"base_score":65,"outcome_confidence":0,"tier":"risk","label":"Do not auto-install","summary":"Trust Score v5 found insufficient evidence for agent installation. 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require human review before any live investment decision.","Low GitHub adoption signal","Quality score needs review","Permission surface needs review: secrets or environment access, shell or command execution"]},"outcomeEvidence":{"total":0,"successes":0,"failures":0,"notRelevant":0,"successRate":null,"installAttempts":0,"riskBlocked":0,"setupRequired":0,"installSuccessRate":null,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"recentSuccessRate":null,"recentFailureRate":null,"uniqueAgents":0,"agentProvenScore":0,"agentProvenLabel":"Needs first agent run","lastOutcomeAt":null,"label":"No agent outcome data yet"},"autoInstall":{"allowed":false,"sandboxRequired":true,"policy":"human_review_before_install","reason":"Compare alternatives before installing."},"outcome_loop":{"version":"openagentskill-agent-outcome-v4","required_after_install":true,"endpoint":"/api/agent/outcome","method":"POST","event_id_source":"feedback.event_id, install_receipt.resolve_event_id, or decision_packet.outcome_feedback.event_id","expected_outcomes":["success","failed","not_relevant","blocked_by_risk","setup_required"],"required_fields":["event_id","skill_slug","task"],"quality_fields":["task_success","output_quality","error_type","human_review_required","used_in_production","workspace","evidence_url","time_to_useful_ms","source_version"],"ranking_inputs_updated":["Trust Score v5 outcome confidence","Agent Proven Score","Resolve ranking task-fit evidence","Skill detail machine-readable metadata","Outcome leaderboard"]},"agent_contract":{"suited_tasks":["design-creative","agent-skill"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI"],"install_command":"npx skills add pavelzw/skill-forge --skill sqlalchemy","trust_score":57,"trust_version":"trust-score-v5","risk_level":"medium","do_not_use_when":["Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface","Automatic installation in a production workspace","Autonomous investment, trading, tax, or suitability decisions without a qualified human review"],"before_install":["Read the audit page and machine-readable metadata.","Confirm the install command, license, and permission surface fit the workspace.","Get explicit human approval or choose an alternative before installing."],"after_run":["Report the outcome to /api/agent/outcome using the resolve event id.","Include output_quality, workspace, human_review_required, and evidence_url when available.","Re-resolve before broad production rollout."]},"bestFor":["design-creative","agent-skill"],"doNotUseFor":["Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface","Automatic installation in a production workspace","Autonomous investment, trading, tax, or suitability decisions without a qualified human review"],"knownRisks":["AI review approval is missing","Financial research output is not financial advice; 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