Automated summary
Offers concrete patterns for using SQLAlchemy 2.0+ asynchronously inside a FastAPI application: engine and session factory, dependency injection, model mixins, and Alembic migrations.
Strengths
- Explains the async engine configuration parameter by parameter (pool_size, max_overflow, pool_pre_ping, pool_recycle, pool_timeout).
- Provides a full FastAPI get_db dependency that guarantees commit, rollback, and session cleanup.
- Ships reusable mixins for database-managed timestamps and soft deletes.
- Includes helper scripts (setup-alembic, generate-migration) and config templates to bootstrap a project quickly.
Limitations
- Relationship loading strategies and query optimization are advertised in the description but lack detailed code in the body.
- Assumes a specific stack (FastAPI, SQLAlchemy 2.0+, Alembic) and an app.core.config module exposing a settings object.
- The bundled Bash scripts should be reviewed and adapted before being run.
Use it when building or refactoring the async database layer of a FastAPI service backed by SQLAlchemy and Alembic.
Skip it for synchronous codebases, non-FastAPI frameworks, or projects on a different ORM such as Django ORM or Tortoise.
Security analysis
CautionThe skill is primarily documentation with code patterns, but it explicitly permits Bash execution and references shell scripts. This introduces execution risk, though the described purpose is standard database tooling. Without reviewing the actual script contents, caution is warranted.
- •Skill allows Bash tool and includes shell scripts for Alembic setup and migration generation, which the agent will execute. While intended for legitimate database operations, the script contents are not shown and could potentially be modified to include unsafe commands.
Examples
Set up an async SQLAlchemy 2.0 engine and session factory for my FastAPI app, with a get_db dependency that commits on success and rolls back on errors.Create a base SQLAlchemy model with UUID primary keys, created_at/updated_at timestamps, and soft delete support that I can reuse across my models.Initialize Alembic for an async SQLAlchemy project and generate the first migration for my new User model with relationships.name: async-sqlalchemy-patterns description: Async SQLAlchemy 2.0+ database patterns for FastAPI including session management, connection pooling, Alembic migrations, relationship loading strategies, and query optimization. Use when implementing database models, configuring async sessions, setting up migrations, optimizing queries, managing relationships, or when user mentions SQLAlchemy, async database, ORM, Alembic, database performance, or connection pooling. allowed-tools: Read, Write, Edit, Grep, Glob, Bash
Async SQLAlchemy Patterns
Purpose: Implement production-ready async SQLAlchemy 2.0+ patterns in FastAPI with proper session management, migrations, and performance optimization.
Activation Triggers:
- Database model implementation
- Async session configuration
- Alembic migration setup
- Query performance optimization
- Relationship loading issues
- Connection pool configuration
- Transaction management
- Database schema migrations
Key Resources:
scripts/setup-alembic.sh- Initialize Alembic with async supportscripts/generate-migration.sh- Create migrations from model changestemplates/base_model.py- Base model with common patternstemplates/session_manager.py- Async session factory and dependencytemplates/alembic.ini- Alembic configuration for asyncexamples/user_model.py- Complete model with relationshipsexamples/async_context_examples.py- Session usage patterns
Core Patterns
1. Async Engine and Session Setup
Database Configuration:
# app/core/database.py
from sqlalchemy.ext.asyncio import (
AsyncSession,
create_async_engine,
async_sessionmaker
)
from sqlalchemy.orm import declarative_base
from app.core.config import settings
# Create async engine
engine = create_async_engine(
settings.DATABASE_URL,
echo=settings.DEBUG,
pool_pre_ping=True, # Verify connections before using
pool_size=5, # Base number of connections
max_overflow=10, # Additional connections when pool is full
pool_recycle=3600, # Recycle connections after 1 hour
pool_timeout=30, # Wait 30s for available connection
)
# Create async session factory
AsyncSessionLocal = async_sessionmaker(
engine,
class_=AsyncSession,
expire_on_commit=False, # Keep objects usable after commit
autoflush=False, # Manual flush control
autocommit=False, # Explicit commits only
)
Base = declarative_base()
Dependency Injection Pattern:
# app/core/deps.py
from typing import AsyncGenerator
from sqlalchemy.ext.asyncio import AsyncSession
from app.core.database import AsyncSessionLocal
async def get_db() -> AsyncGenerator[AsyncSession, None]:
"""
FastAPI dependency for database sessions.
Automatically handles cleanup.
"""
async with AsyncSessionLocal() as session:
try:
yield session
await session.commit()
except Exception:
await session.rollback()
raise
finally:
await session.close()
2. Base Model Pattern
Use template from templates/base_model.py with:
- UUID primary keys by default
- Automatic created_at/updated_at timestamps
- Soft delete support
- Common query methods
Essential Mixins:
from datetime import datetime
from sqlalchemy import DateTime, Boolean, func
from sqlalchemy.orm import Mapped, mapped_column
class TimestampMixin:
"""Auto-managed timestamps"""
created_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True),
server_default=func.now(),
nullable=False
)
updated_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True),
server_default=func.now(),
onupdate=func.now(),
nullable=False
)
class SoftDeleteMixin:
"""Soft delete support"""
is_deleted: Mapped[bool] = mapped_column(
Boolean,
default=False,
nullable=False
)
deleted_at: Mapped[datetime | None] = mapped_column(
DateTime(timezone=True),
nullable=True
)
3. Relationship Loading Strategies
Lazy Loading (Default - N+1 Problem Risk):
# Bad: Causes N+1 queries
users = await session.execute(select(User))
for user in users.scalars():
print(user.posts) # Separate query per user!
Eager Loading (Recommended):
from sqlalchemy.orm import selectinload, joinedload
# selectinload: Separate query, good for one-to-many
stmt = select(User).options(selectinload(User.posts))
result = await session.execute(stmt)
users = result.scalars().all()
# joinedload: SQL JOIN, good for many-to-one
stmt = select(Post).options(joinedload(Post.author))
result = await session.execute(stmt)
posts = result.scalars().unique().all() # unique() required with joins!
# subqueryload: Subquery loading
stmt = select(User).options(subqueryload(User.posts))
Relationship Configuration:
from sqlalchemy.orm import relationship
class User(Base):
__tablename__ = "users"
# One-to-many with cascade
posts: Mapped[list["Post"]] = relationship(
back_populates="author",
cascade="all, delete-orphan",
lazy="selectin" # Default eager loading
)
# Many-to-many
roles: Mapped[list["Role"]] = relationship(
secondary="user_roles",
back_populates="users",
lazy="selectin"
)
4. Query Patterns
Basic CRUD:
from sqlalchemy import select, update, delete
from sqlalchemy.ext.asyncio import AsyncSession
# Create
async def create_user(session: AsyncSession, user_data: dict):
user = User(**user_data)
session.add(user)
await session.commit()
await session.refresh(user)
return user
# Read with filters
async def get_users(session: AsyncSession, skip: int = 0, limit: int = 100):
stmt = (
select(User)
.where(User.is_deleted == False)
.offset(skip)
.limit(limit)
.order_by(User.created_at.desc())
)
result = await session.execute(stmt)
return result.scalars().all()
# Update
async def update_user(session: AsyncSession, user_id: int, updates: dict):
stmt = (
update(User)
.where(User.id == user_id)
.values(**updates)
.returning(User)
)
result = await session.execute(stmt)
await session.commit()
return result.scalar_one()
# Delete
async def delete_user(session: AsyncSession, user_id: int):
stmt = delete(User).where(User.id == user_id)
await session.execute(stmt)
await session.commit()
Complex Queries:
from sqlalchemy import func, and_, or_
# Aggregations
stmt = (
select(User.id, func.count(Post.id))
.join(Post)
.group_by(User.id)
.having(func.count(Post.id) > 5)
)
# Subqueries
subq = (
select(func.avg(Post.views))
.where(Post.user_id == User.id)
.scalar_subquery()
)
stmt = select(User).where(User.id.in_(
select(Post.user_id).where(Post.views > subq)
))
# Window functions
from sqlalchemy import over
stmt = select(
Post,
func.row_number().over(
partition_by=Post.user_id,
order_by=Post.created_at.desc()
).label('row_num')
).where(over.row_num <= 10)
5. Transaction Management
Nested Transactions:
async def transfer_funds(
session: AsyncSession,
from_account: int,
to_account: int,
amount: float
):
async with session.begin_nested(): # Savepoint
# Debit
stmt = (
update(Account)
.where(Account.id == from_account)
.where(Account.balance >= amount)
.values(balance=Account.balance - amount)
)
result = await session.execute(stmt)
if result.rowcount == 0:
raise ValueError("Insufficient funds")
# Credit
stmt = (
update(Account)
.where(Account.id == to_account)
.values(balance=Account.balance + amount)
)
await session.execute(stmt)
await session.commit()
Manual Transaction Control:
async def batch_operation(session: AsyncSession, items: list):
try:
for item in items:
session.add(item)
if len(session.new) >= 100:
await session.flush() # Flush but don't commit
await session.commit()
except Exception as e:
await session.rollback()
raise
6. Alembic Migration Setup
# Initialize Alembic with async template
./scripts/setup-alembic.sh
# Creates:
# - alembic/ directory
# - alembic.ini configured for async
# - env.py with async support
Generate Migrations:
# Auto-generate from model changes
./scripts/generate-migration.sh "add user table"
# Review generated migration in alembic/versions/
# Always review auto-generated migrations!
Migration Best Practices:
- Always review auto-generated migrations
- Use batch operations for large tables
- Add indexes in separate migrations
- Include both upgrade and downgrade
- Test migrations on staging first
Manual Migration Template:
# alembic/versions/xxx_add_index.py
from alembic import op
import sqlalchemy as sa
def upgrade() -> None:
# Use batch for SQLite compatibility
with op.batch_alter_table('users') as batch_op:
batch_op.create_index(
'ix_users_email',
['email'],
unique=True
)
def downgrade() -> None:
with op.batch_alter_table('users') as batch_op:
batch_op.drop_index('ix_users_email')
7. Connection Pool Configuration
Production Settings:
# For web applications
engine = create_async_engine(
DATABASE_URL,
pool_size=20, # Concurrent requests
max_overflow=40, # Burst capacity
pool_recycle=3600, # 1 hour
pool_pre_ping=True, # Verify connections
pool_timeout=30, # Wait time
echo_pool=False, # Pool debug logging
)
# For background tasks
engine = create_async_engine(
DATABASE_URL,
pool_size=5, # Fewer connections
max_overflow=10,
pool_recycle=7200, # 2 hours
)
Connection Health Check:
from sqlalchemy import text
async def check_database_health(session: AsyncSession) -> bool:
try:
await session.execute(text("SELECT 1"))
return True
except Exception:
return False
8. Performance Optimization
Bulk Operations:
# Bulk insert
async def bulk_create_users(session: AsyncSession, users: list[dict]):
stmt = insert(User).values(users)
await session.execute(stmt)
await session.commit()
# Bulk update
async def bulk_update_status(session: AsyncSession, user_ids: list[int]):
stmt = (
update(User)
.where(User.id.in_(user_ids))
.values(status="active")
)
await session.execute(stmt)
await session.commit()
Query Result Streaming:
async def stream_large_dataset(session: AsyncSession):
stmt = select(User).execution_options(yield_per=100)
result = await session.stream(stmt)
async for partition in result.partitions(100):
users = partition.scalars().all()
# Process batch
yield users
Index Optimization:
from sqlalchemy import Index
class User(Base):
__tablename__ = "users"
email: Mapped[str] = mapped_column(unique=True, index=True)
__table_args__ = (
Index('ix_user_status_created', 'status', 'created_at'),
Index('ix_user_email_active', 'email', postgresql_where=~is_deleted),
)
Troubleshooting
Common Issues
"Object is not bound to session":
# Bad: Object expires after commit
user = await create_user(session, data)
print(user.email) # Error if expire_on_commit=True
# Fix: Refresh or configure session
await session.refresh(user)
# Or: AsyncSessionLocal(expire_on_commit=False)
"N+1 Query Problem":
# Enable SQL logging to detect
engine = create_async_engine(url, echo=True)
# Fix with eager loading
stmt = select(User).options(selectinload(User.posts))
"DetachedInstanceError":
# Bad: Accessing relationship outside session
async with AsyncSessionLocal() as session:
user = await session.get(User, user_id)
print(user.posts) # Error!
# Fix: Load within session or use eager loading
stmt = select(User).options(selectinload(User.posts))
"Connection Pool Exhausted":
# Increase pool size or add timeout
engine = create_async_engine(
url,
pool_size=20,
max_overflow=40,
pool_timeout=30
)
Resources
Scripts: scripts/ directory contains:
setup-alembic.sh- Initialize Alembic with async configurationgenerate-migration.sh- Create migrations from model changestest-connection.sh- Test database connectivityoptimize-queries.sh- Analyze and suggest query optimizations
Templates: templates/ directory includes:
base_model.py- Base model with UUID, timestamps, soft deletesession_manager.py- Complete session factory and dependenciesalembic.ini- Production-ready Alembic configurationenv.py- Alembic async environment template
Examples: examples/ directory provides:
user_model.py- Full model with relationships and indexesasync_context_examples.py- Session patterns and best practicesquery_patterns.py- Common query optimization examplesmigration_examples.py- Manual migration patterns
SQLAlchemy Version: 2.0+ Database Support: PostgreSQL, MySQL, SQLite (async drivers) Async Drivers: asyncpg (PostgreSQL), aiomysql (MySQL), aiosqlite (SQLite) Version: 1.0.0
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