Dignified Python Reference Documentation

Opinionated Python standards for writing clean, maintainable, modern Python code.

Table of Contents

Core Standards

• dignified-python-core.md - Essential Python standards (always apply)

  • Modern type syntax (list[str], str | None)
  • LBYL exception handling patterns
  • Pathlib operations
  • Absolute imports
  • Error boundaries

• cli-patterns.md - Command-line interface patterns

  • Click usage patterns
  • Argparse best practices
  • CLI error handling
  • Configuration management

Version-Specific Features (versions/)

• python-3.10.md - Python 3.10+ features

  • Structural pattern matching (match/case)
  • Parenthesized context managers
  • Better error messages
  • Type union operator (X | Y)

• python-3.11.md - Python 3.11+ features

  • Exception groups (ExceptionGroup)
  • except* syntax
  • Self type
  • Variadic generics

• python-3.12.md - Python 3.12+ features

  • Type parameter syntax (Generic[T])
  • Override decorator
  • Per-interpreter GIL
  • f-string improvements

• python-3.13.md - Python 3.13+ features

  • Experimental free-threading
  • JIT compilation
  • Improved error messages
  • Performance improvements

Advanced Topics (advanced/)

• exception-handling.md - Exception patterns

  • LBYL (Look Before You Leap) patterns
  • Error boundaries
  • Exception chaining
  • Custom exceptions

• interfaces.md - Interface design

  • ABC (Abstract Base Class) patterns
  • Protocol types
  • Gateway layer interfaces
  • Type narrowing

• typing-advanced.md - Advanced typing

  • Generic types
  • Type narrowing
  • Literal types
  • TypedDict and dataclasses

• api-design.md - API design principles

  • Function signatures
  • Parameter complexity
  • Code organization
  • Production application code examples

Philosophy

Core Principles

Modern Type Syntax: Use Python 3.10+ type syntax everywhere

# Good (modern)
def process(items: list[str]) -> str | None:
    pass

# Avoid (legacy)
from typing import List, Optional
def process(items: List[str]) -> Optional[str]:
    pass

Prefer LBYL When It Is Cheap and Precise: This skill leans toward explicit precondition checks for routine branching, while still using targeted try/except blocks when parsing or API calls are the authoritative test.

# Good (LBYL)
if path.exists():
    content = path.read_text()

# Avoid (EAFP)
try:
    content = path.read_text()
except FileNotFoundError:
    pass

Pathlib Over os.path: Use pathlib for all file operations

# Good
from pathlib import Path
config_path = Path("config.yaml")
if config_path.exists():
    content = config_path.read_text()

# Avoid
import os
if os.path.exists("config.yaml"):
    with open("config.yaml") as f:
        content = f.read()

Absolute Imports: Never use relative imports

# Good
from myproject.utils import helper

# Avoid
from .utils import helper
from ..shared import helper

Error Boundaries at CLI Level: Handle errors at the CLI entry point, not deep in the stack

Quick Reference

Type Annotations

# Basic types
def greet(name: str) -> str:
    return f"Hello, {name}"

# Collections (modern syntax)
def process(items: list[str], mapping: dict[str, int]) -> tuple[str, int]:
    pass

# Optional/Union (modern syntax)
def find(query: str) -> str | None:
    pass

# Multiple types
def parse(value: str | int | float) -> float:
    pass

LBYL Patterns

# File operations
if path.exists():
    content = path.read_text()

# Dictionary access
if "key" in data:
    value = data["key"]

# Attribute access
if hasattr(obj, "method"):
    obj.method()

# Type checking
if isinstance(value, str):
    result = value.upper()

Pathlib Operations

from pathlib import Path

# Create path
config = Path("config.yaml")
data_dir = Path("/data")

# Check existence
if config.exists():
    pass

# Read/write
content = config.read_text()
config.write_text("data")

# Directory operations
for file in data_dir.glob("*.txt"):
    print(file.name)

# Path manipulation
full_path = data_dir / "subdir" / "file.txt"
parent = full_path.parent
name = full_path.name

CLI Patterns (Click)

import click

@click.command()
@click.option("--name", required=True, help="User name")
@click.option("--count", default=1, help="Number of times")
def greet(name: str, count: int) -> None:
    """Greet a user multiple times."""
    for _ in range(count):
        click.echo(f"Hello, {name}!")

if __name__ == "__main__":
    greet()

Version Detection

Automatic version detection determines which Python version features are available:

1. Check pyproject.toml for requires-python field
2. Check setup.py/setup.cfg for python_requires
3. Check .python-version file
4. Default to Python 3.12 if not specified

Based on detected version, appropriate version-specific features are recommended.

Navigation Tips

• Start with dignified-python-core.md for essential patterns that apply to all code
• Check version-specific docs based on your project's Python version
• Reference advanced topics when dealing with specialized patterns
• Use cli-patterns.md when building command-line tools

When to Read Each Reference

Related Skills

• /dagster-best-practices - Dagster-specific patterns (not general Python)
• /dg - Dagster CLI operations
• /dagster-expert - Dagster expertise including integrations

Important: /dignified-python is for general-purpose Python style guidance, not Dagster-specific patterns. It is intentionally opinionated rather than universal. For Dagster patterns, use /dagster-best-practices.

Cross-Skill Usage

Users invoke /dignified-python when they need Python code quality guidance, regardless of whether it's for a Dagster project or any other Python project.

Workflow:

User: "Is this good Python code?"
→ /dignified-python (check dignified-python-core.md)
→ Apply modern type syntax, LBYL, pathlib patterns
→ Check version-specific features based on project

User: "How should I structure my Dagster assets?"
→ /dagster-best-practices (NOT dignified-python)
→ Learn asset patterns, dependencies, partitions

Production Patterns

These standards reflect production-tested conventions:

• ✅ Modern type syntax - Improves IDE support and type checking
• ✅ LBYL patterns - More explicit and easier to debug than EAFP
• ✅ Pathlib - More readable and cross-platform than os.path
• ✅ Absolute imports - Avoid import confusion and relative import issues
• ✅ Error boundaries at CLI - Clean error messages for end users

Documentation Structure

Each reference document follows a consistent structure:

1. Overview - High-level concepts
2. Patterns - Common code patterns with examples
3. Best Practices - Recommended approaches
4. Anti-Patterns - What to avoid
5. Real-World Examples - Production code samples
6. Related Topics - Cross-references

Self-Selecting Usage

Users only invoke /dignified-python when they want Python standards guidance. The skill description makes it clear it's for general Python quality, not Dagster-specific patterns, so users naturally select it when appropriate.

Users will invoke this when they want:

• Code review and quality improvements
• Modern Python patterns
• Type annotation guidance
• Exception handling best practices
• CLI implementation patterns

Users will NOT invoke this when they want:

• Dagster-specific patterns (they'll use /dagster-best-practices)
• Creating Dagster projects (they'll use /dg)
• Finding integrations (they'll use /dagster-expert)