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#Task boundary

1. Implement only what the task names; no extra abstractions or files.
2. English-only comments and identifiers.
3. Stop when the checklist passes.

---

#Purpose

Rules for a Python 3.12+ codebase that a second engineer can pick up without archaeology. Python will let you skip all of these; the cost arrives at the first refactor.

Framework rules are Backend/fastapi, Backend/django, Backend/flask; concurrency is Backend/python-async.

---

#One manifest: pyproject.toml

toml
[project]
name = "orders"
version = "1.4.0"
requires-python = ">=3.12"
dependencies = ["fastapi>=0.110,<1", "sqlalchemy>=2,<3"]

[project.optional-dependencies]
dev = ["pytest", "ruff", "mypy"]

[tool.ruff]
line-length = 100
[tool.ruff.lint]
select = ["E", "F", "I", "B", "UP", "S", "N"]

[tool.mypy]
strict = true

1. requirements.txt, setup.py, setup.cfg, .flake8, .isort.cfg all fold into this one file. Two manifests drift.
2. Pin a lockfile (uv.lock) and commit it; keep dependencies as ranges. A range without a lock is a different build every day; a pin without a range blocks every security patch.
3. uv for installs and venvs (uv sync, uv run pytest); it is an order of magnitude faster than pip and produces the lock. If pip, then pip-compile — never hand-edit a lock.

---

#Layout

graphql
src/orders/          # src layout: tests cannot import the package by accident
  __init__.py
  api/  services/  repos/  models.py  settings.py
tests/
  conftest.py  test_orders.py
pyproject.toml  uv.lock  README.md

1. src/ layout, installed editable (uv pip install -e .). A flat layout lets import orders succeed from the repo root without installing, which hides packaging bugs until CI.
2. No utils.py. A module named for what it does (money.py, dates.py) is findable; utils becomes a junk drawer by the third commit.
3. __init__.py re-exports the public surface and nothing else; no side effects at import time (no connections, no config loading).

---

#Typing

python
def total[T: (int, Decimal)](items: Sequence[LineItem[T]]) -> T: ...      # PEP 695

type OrderId = NewType("OrderId", int)                                    # PEP 695 alias
def load(id: OrderId) -> Order | None: ...                                # not Optional[Order]

def parse(raw: dict[str, Any]) -> Order: ...   # Any only at the untyped edge

1. mypy --strict (or pyright strict) in CI from day one; retrofitting strictness onto an untyped codebase is a month of work.
2. Builtin generics (list[int], dict[str, Any]) and X | None; the typing spellings (List, Optional) are legacy.
3. Any is an admission, not a type. It is acceptable at the boundary where data is genuinely untyped, and nowhere inside.
4. Protocol for structural interfaces you own; ABC only when you need the runtime isinstance.
5. TypedDict for dict-shaped data you cannot change; a dataclass or Pydantic model for data you can.

---

#Dataclass or Pydantic

@dataclass(frozen=True, slots=True) is the default internal record: immutable, memory-light, hashable. Reaching for Pydantic for every internal object taxes every construction with validation you already did. → Backend/pydantic

---

#Exceptions

python
class OrdersError(Exception): """Base for this package."""
class OrderNotFound(OrdersError): ...
class InsufficientStock(OrdersError):
    def __init__(self, sku: str, wanted: int, have: int) -> None:
        super().__init__(f"{sku}: wanted {wanted}, have {have}")
        self.sku, self.wanted, self.have = sku, wanted, have

1. One base exception per package; callers catch the base, tests catch the leaf.
2. Carry data as attributes, not only in the message string.
3. raise ... from err to chain; a bare raise inside except to re-raise. raise NewError(str(err)) throws away the traceback.
4. Never except Exception: pass. Catch what you can handle; let the rest propagate to the one place that logs and converts. → Backend/error-handling

---

#Logging

python
log = logging.getLogger(__name__)
log.info("order created", extra={"order_id": order.id, "tenant": tenant.id})

1. logging.getLogger(__name__) per module; never print in library code.
2. Structured fields via extra, formatted as JSON by one handler configured in the entrypoint (dictConfig), not in every module.
3. log.exception(...) inside except — it attaches the traceback.
4. Log at INFO for business events, WARNING for handled failures, ERROR for unhandled. DEBUG is for you, and off in production.

---

#Environments

1. One virtualenv per project, created by uv venv or python -m venv; never install into the system interpreter.
2. .python-version pins the interpreter; CI uses the same one.
3. Secrets from the environment, never from a committed file. .env is for local development and is gitignored. → Security/secret-management

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#Tooling in CI

bash
uv sync --frozen            # fails if the lock is stale
ruff check . && ruff format --check .
mypy src
pytest -q

ruff replaces flake8, isort, pyupgrade and black; one tool, one config, sub-second. Enable the S (bandit) and B (bugbear) rule sets — they catch real bugs, not style. → Testing/pytest

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#Anti-patterns

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#Checklist

• pyproject.toml is the only manifest; requires-python set
• Lockfile committed; CI installs with --frozen
• src/ layout, package installed editable
• No utils.py; no I/O at import time
• mypy --strict (or pyright strict) passes in CI
• Builtin generics and X | None throughout
• Any appears only at untyped boundaries
• Internal records are frozen, slotted dataclasses; boundaries use Pydantic
• One base exception per package; leaves carry data as attributes
• Exceptions chained with from; no silent except
• logging.getLogger(__name__) with structured extra; no print
• ruff with S and B rule sets enabled
• .python-version pinned; secrets come from the environment