Install
$ agentstack add skill-martinffx-atelier-python-sqlalchemy ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
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Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
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SQLAlchemy ORM Patterns
Modern SQLAlchemy 2.0+ patterns for database access in Python applications.
Model Definition
from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column
from sqlalchemy import String
from uuid import UUID
from decimal import Decimal
class Base(DeclarativeBase):
pass
class ProductModel(Base):
__tablename__ = "products"
id: Mapped[UUID] = mapped_column(primary_key=True)
name: Mapped[str] = mapped_column(String(100))
price: Mapped[Decimal]
in_stock: Mapped[bool] = mapped_column(default=True)
Session Management
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
engine = create_engine("postgresql://user:pass@localhost/db")
SessionLocal = sessionmaker(bind=engine)
def get_db():
db = SessionLocal()
try:
yield db
finally:
db.close()
Query Patterns
# Select
stmt = select(ProductModel).where(ProductModel.price > 100)
products = session.execute(stmt).scalars().all()
# Filter
products = session.query(ProductModel).filter(ProductModel.in_stock == True).all()
# Get by ID
product = session.get(ProductModel, product_id)
# Count
count = session.query(ProductModel).count()
Upsert
from sqlalchemy.dialects.postgresql import insert
stmt = insert(ProductModel).values(
id=product_id,
name="Widget",
price=9.99,
)
# On conflict, update
stmt = stmt.on_conflict_do_update(
index_elements=["id"],
set_={"name": stmt.excluded.name, "price": stmt.excluded.price},
)
session.execute(stmt)
session.commit()
Relationships
from sqlalchemy.orm import relationship
class UserModel(Base):
__tablename__ = "users"
id: Mapped[int] = mapped_column(primary_key=True)
orders: Mapped[list["OrderModel"]] = relationship(back_populates="user")
class OrderModel(Base):
__tablename__ = "orders"
id: Mapped[int] = mapped_column(primary_key=True)
user_id: Mapped[int] = mapped_column(ForeignKey("users.id"))
user: Mapped["UserModel"] = relationship(back_populates="orders")
JSON Columns
from sqlalchemy import JSON
class ConfigModel(Base):
__tablename__ = "configs"
id: Mapped[int] = mapped_column(primary_key=True)
settings: Mapped[dict] = mapped_column(JSON)
# Query JSON field
configs = session.query(ConfigModel).filter(
ConfigModel.settings["theme"] == "dark"
).all()
See references/ for model patterns, query optimization, and async SQLAlchemy.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: martinffx
- Source: martinffx/atelier
- License: MIT
- Homepage: https://github.com/martinffx/atelier
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.