ABOUTME: Complete Python development with uv package manager, quality tools, and Docker

ABOUTME: Modern workflow with uv, ruff, ty, pytest, Pydantic, and containerization

Python Development

What's New (2025-2026)

Python 3.14 (Oct 2025)

• Template strings (PEP 750): t"Hello {name}" - safe SQL/HTML interpolation
• Incremental GC: 10ms pauses (was 100ms)
• uuid7: Time-ordered UUIDs (better for DBs)
• Remote pdb: python -p PID

Tooling

Tool	Notes
ty	Astral's type checker, 10-60x faster than mypy
Ruff 0.8+	Type-aware linting, 800+ rules
uv 0.5+	Stable, production-ready

Quick Reference

uv init myproject && cd myproject              # New project
uv add requests pydantic httpx                 # Add deps
uv add --dev pytest ruff                       # Dev deps
uv sync --locked                               # CI-safe sync
uv run python main.py                          # Run code
uv run ruff check . && uv run ruff format --check . && uvx ty check && uv run pytest  # Quality

Target: Python 3.13 | See also: _AST_GREP.md, _PATTERNS.md, source-control

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Package Management (uv)

UV is the ONLY way. Do NOT use pip/poetry/pipenv. 10-100x faster, universal lockfile.

pyproject.toml

[project]
name = "myproject"
version = "0.1.0"
requires-python = ">=3.13"
dependencies = ["httpx>=0.27.0", "pydantic>=2.10.0"]

[dependency-groups]
dev = ["pytest>=8.0.0", "ruff>=0.8.0"]

[tool.pytest.ini_options]
testpaths = ["tests"]
asyncio_mode = "auto"

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Code Quality

Type checking: uvx ty check

Linting (Ruff): uv run ruff check . && uv run ruff format --check .

[tool.ruff]
line-length = 100
target-version = "py313"

[tool.ruff.lint]
select = ["E", "F", "I", "N", "W", "UP", "B", "C4", "SIM", "TCH", "RUF", "PERF"]

Testing: uv run pytest --cov=myproject --cov-report=html. Fixtures, AAA pattern, parametrize.

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Pydantic v2

from pydantic import BaseModel, Field, field_validator

class User(BaseModel):
    id: int
    name: str = Field(min_length=1, max_length=100)
    email: str

    @field_validator("email")
    @classmethod
    def validate_email(cls, v): return v.lower() if "@" in v else raise ValueError("Invalid")

# Performance
user = User.model_validate_json('{"id":1,"name":"Max","email":"m@x.com"}')  # Fast JSON

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Code Review Checklist

• Public functions have type hints, no unjustified Any
• Pydantic for external data, X | None not Optional[X]
• Ruff/type checker pass, no bare except:
• Context managers, asyncio.gather() for concurrency
• AAA tests, parametrized

For Docker, CI/CD, async patterns, and detailed testing examples, see references/python-patterns.md.

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Resources

Astral: uv, Ruff, ty Python: pytest, Pydantic