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Backend Models Standards

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Backend Models Standards

Core Rule: Models define data structure and integrity. Keep them focused on data representation, not business logic.

When to use this skill

  • When creating or modifying database model files (models.py, models/, schema.prisma, etc.)
  • When defining ORM classes or ActiveRecord models for database tables
  • When establishing table relationships (one-to-many, many-to-many, has-many, belongs-to)
  • When configuring foreign keys, indexes, and cascade behaviors
  • When implementing model-level validation rules
  • When adding timestamp fields (created_at, updated_at) for auditing
  • When setting database constraints (NOT NULL, UNIQUE, CHECK constraints)
  • When choosing appropriate data types for model fields
  • When balancing normalization with query performance needs
  • When defining model methods or scopes for common queries

This Skill provides Claude Code with specific guidance on how to adhere to coding standards as they relate to how it should handle backend models.

Naming Conventions

Models: Singular, PascalCase (User, OrderItem, PaymentMethod)

Tables: Plural, snake_case (users, order_items, payment_methods)

Relationships: Descriptive and clear

  • user.orders (one-to-many)
  • order.items (one-to-many)
  • product.categories (many-to-many)

Avoid generic names: data, info, record, entity

Required Fields

Timestamps on every model:

created_at = Column(DateTime, nullable=False, default=datetime.utcnow)
updated_at = Column(DateTime, nullable=False, default=datetime.utcnow, onupdate=datetime.utcnow)

Primary keys: Always explicit, prefer UUIDs for distributed systems or auto-incrementing integers for simplicity

Why: Auditing, debugging, data lineage tracking, soft deletes

Data Integrity - Database Level

Use constraints, not just application validation:

# NOT NULL for required fields
email = Column(String(255), nullable=False)

# UNIQUE constraints
email = Column(String(255), unique=True, nullable=False)

# CHECK constraints for business rules
age = Column(Integer, CheckConstraint('age >= 18'))

# Foreign keys with explicit cascade behavior
user_id = Column(Integer, ForeignKey('users.id', ondelete='CASCADE'))

Why: Database enforces rules even if application code bypassed. Defense in depth.

Data Types - Choose Appropriately

DataTypeAvoid
Email, URLVARCHAR(255)TEXT
Short textVARCHAR(n)TEXT
Long textTEXTVARCHAR
MoneyDECIMAL(10,2)FLOAT
BooleanBOOLEANTINYINT
TimestampsTIMESTAMP/DATETIMEVARCHAR
JSON dataJSON/JSONBTEXT
UUIDsUUIDVARCHAR(36)

Why: Correct types enable database optimizations, constraints, and prevent data corruption.

Indexes - Performance Critical

Always index:

  • Primary keys (automatic)
  • Foreign keys (manual in most ORMs)
  • Columns in WHERE clauses
  • Columns in JOIN conditions
  • Columns in ORDER BY clauses

Example:

class Order(Base):
    __tablename__ = 'orders'
    
    id = Column(Integer, primary_key=True)
    user_id = Column(Integer, ForeignKey('users.id'), index=True)
    status = Column(String(50), index=True)  # Frequently filtered
    created_at = Column(DateTime, index=True)  # Frequently sorted

Don't over-index: Each index slows writes. Index only queried columns.

Relationships - Explicit Configuration

Define both sides of relationships:

# One-to-many
class User(Base):
    orders = relationship('Order', back_populates='user', cascade='all, delete-orphan')

class Order(Base):
    user_id = Column(Integer, ForeignKey('users.id'))
    user = relationship('User', back_populates='orders')

Cascade behaviors:

  • CASCADE: Delete related records (user deleted → orders deleted)
  • SET NULL: Nullify foreign key (category deleted → product.category_id = NULL)
  • RESTRICT: Prevent deletion if related records exist
  • NO ACTION: Database default, usually same as RESTRICT

Choose based on business logic, not convenience.

Validation - Two Layers

Model-level validation (application):

@validates('email')
def validate_email(self, key, email):
    if not re.match(r'^[^@]+@[^@]+\.[^@]+$', email):
        raise ValueError('Invalid email format')
    return email

Database-level constraints (see Data Integrity section)

Why both: Model validation provides clear error messages. Database constraints prevent data corruption if application bypassed.

What Belongs in Models

YES:

  • Field definitions and types
  • Relationships to other models
  • Simple property methods (@property def full_name)
  • Data validation rules
  • Database constraints

NO:

  • Business logic (move to service layer)
  • External API calls
  • Complex calculations (move to service methods)
  • Email sending, file uploads, etc.

Models represent data structure, not behavior.

Normalization vs Performance

Normalize when:

  • Data has clear entity boundaries
  • Updates need to propagate (user email changes once)
  • Avoiding data duplication is critical

Denormalize when:

  • Read performance critical (analytics, reporting)
  • Data rarely changes (historical snapshots)
  • Joins become too expensive

Default to normalized. Denormalize only with evidence of performance issues.

Common Patterns

Soft deletes:

deleted_at = Column(DateTime, nullable=True, index=True)

# Query only active records
query = session.query(User).filter(User.deleted_at.is_(None))

Polymorphic associations:

# Avoid if possible - complex and hard to maintain
# Prefer separate relationship fields or inheritance

Enums for fixed values:

from enum import Enum

class OrderStatus(str, Enum):
    PENDING = 'pending'
    PAID = 'paid'
    SHIPPED = 'shipped'
    DELIVERED = 'delivered'

status = Column(Enum(OrderStatus), nullable=False, default=OrderStatus.PENDING)

Testing Models

Test constraints and validation:

def test_user_email_required():
    with pytest.raises(IntegrityError):
        user = User(name='Test')
        session.add(user)
        session.commit()

def test_user_email_unique():
    user1 = User(email='test@example.com')
    user2 = User(email='test@example.com')
    session.add(user1)
    session.commit()
    
    with pytest.raises(IntegrityError):
        session.add(user2)
        session.commit()

Test relationships:

def test_user_orders_cascade_delete():
    user = User(email='test@example.com')
    order = Order(user=user)
    session.add(user)
    session.commit()
    
    session.delete(user)
    session.commit()
    
    assert session.query(Order).count() == 0

Checklist for New Models

  • Singular model name, plural table name
  • Primary key defined
  • created_at and updated_at timestamps
  • NOT NULL on required fields
  • UNIQUE constraints where appropriate
  • Foreign keys with explicit cascade behavior
  • Indexes on foreign keys and queried columns
  • Appropriate data types (not all VARCHAR)
  • Validation at model and database levels
  • Relationships defined on both sides
  • Tests for constraints and validation

Source

git clone https://github.com/Microck/ordinary-claude-skills/blob/main/skills_all/backend-models-standards/SKILL.mdView on GitHub

Overview

Defines database models with clear naming, appropriate data types, constraints, and relationships across ORM classes and schema definitions. It enforces multi-layer validation and database rules (NOT NULL, UNIQUE, CHECK) to safeguard data integrity and support reliable querying, auditing, and evolution.

How This Skill Works

Models use singular PascalCase naming for classes and plural snake_case for tables, with explicit primary keys (UUIDs or auto-incrementing IDs). They declare foreign keys, cascade behaviors, and constraints at the database level, plus model-level validations to complement application checks. They also standardize timestamps (created_at, updated_at) and appropriate data types to balance normalization with performance.

When to Use It

  • When creating or modifying database model files (models.py, Prisma schema, etc.).
  • When defining ORM/ActiveRecord classes for tables and relationships.
  • When establishing table relationships (one-to-many, many-to-many) and foreign keys.
  • When configuring cascade behaviors, indexes, and constraints like NOT NULL, UNIQUE, and CHECK.
  • When you need multi-layer data validation and auditable timestamps for data integrity.

Quick Start

  1. Step 1: Define model class with a clear name and primary key.
  2. Step 2: Add fields with appropriate data types, NOT NULL, and unique constraints.
  3. Step 3: Add timestamps, foreign keys, and indexes, then run migrations to apply them.

Best Practices

  • Follow singular PascalCase for models and plural snake_case for tables.
  • Include created_at and updated_at on every model.
  • Enforce NOT NULL, UNIQUE, and CHECK constraints at the database level.
  • Declare foreign keys with clear cascade rules and explicit indices.
  • Choose appropriate data types and document relationships with descriptive names.

Example Use Cases

  • User model with id (UUID), email (UNIQUE, NOT NULL), and timestamps.
  • Post model with author_id FK to users and ON DELETE CASCADE.
  • Many-to-many relation between posts and tags via a join table post_tags.
  • Product model with price as DECIMAL and CHECK price >= 0.
  • Index foreign keys and commonly filtered fields (e.g., user_id, created_at).

Frequently Asked Questions

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