Skill: adarshdigievo/python (version 1.0.0)

--- name: python description: Python coding guidelines and best practices. Use when writing, reviewing, or refactoring Python code. Enforces PEP 8 style, syntax validation via py_compile, unit test execution, modern Python versions only (no EOL), uv for dependency management when available, and idiomatic Pythonic patterns. --- # Python Coding Guidelines ## Code Style (PEP 8) - 4 spaces for indentation (never tabs) - Max line length: 88 chars (Black default) or 79 (strict PEP 8) - Two blank lines before top-level definitions, one within classes - Imports: stdlib → third-party → local, alphabetized within groups - Snake_case for functions/variables, PascalCase for classes, UPPER_CASE for constants ## Before Committing ```bash # Syntax check (always) python -m py_compile *.py # Run tests if present python -m pytest tests/ -v 2>/dev/null || python -m unittest discover -v 2>/dev/null || echo "No tests found" # Format check (if available) ruff check . --fix 2>/dev/null || python -m black --check . 2>/dev/null ``` ## Python Version - **Minimum:** Python 3.10+ (3.9 EOL Oct 2025) - **Target:** Python 3.11-3.13 for new projects - Never use Python 2 syntax or patterns - Use modern features: match statements, walrus operator, type hints ## Dependency Management Check for uv first, fall back to pip: ```bash # Prefer uv if available if command -v uv &>/dev/null; then uv pip install <package> uv pip compile requirements.in -o requirements.txt else pip install <package> fi ``` For new projects with uv: `uv init` or `uv venv && source .venv/bin/activate` ## Pythonic Patterns ```python # ✅ List/dict comprehensions over loops squares = [x**2 for x in range(10)] lookup = {item.id: item for item in items} # ✅ Context managers for resources with open("file.txt") as f: data = f.read() # ✅ Unpacking first, *rest = items a, b = b, a # swap # ✅ EAFP over LBYL try: value = d[key] except KeyError: value = default # ✅ f-strings for formatting msg = f"Hello {name}, you have {count} items" # ✅ Type hints def process(items: list[str]) -> dict[str, int]: ... # ✅ dataclasses/attrs for data containers from dataclasses import dataclass @dataclass class User: name: str email: str active: bool = True # ✅ pathlib over os.path from pathlib import Path config = Path.home() / ".config" / "app.json" # ✅ enumerate, zip, itertools for i, item in enumerate(items): ... for a, b in zip(list1, list2, strict=True): ... ``` ## Anti-patterns to Avoid ```python # ❌ Mutable default arguments def bad(items=[]): # Bug: shared across calls ... def good(items=None): items = items or [] # ❌ Bare except try: ... except: # Catches SystemExit, KeyboardInterrupt ... except Exception: # Better ... # ❌ Global state # ❌ from module import * # ❌ String concatenation in loops (use join) # ❌ == None (use `is None`) # ❌ len(x) == 0 (use `not x`) ``` ## Testing - Use pytest (preferred) or unittest - Name test files `test_*.py`, test functions `test_*` - Aim for focused unit tests, mock external dependencies - Run before every commit: `python -m pytest -v` ## Docstrings ```python def fetch_user(user_id: int, include_deleted: bool = False) -> User | None: """Fetch a user by ID from the database. Args: user_id: The unique user identifier. include_deleted: If True, include soft-deleted users. Returns: User object if found, None otherwise. Raises: DatabaseError: If connection fails. """ ``` ## Quick Checklist - [ ] Syntax valid (`py_compile`) - [ ] Tests pass (`pytest`) - [ ] Type hints on public functions - [ ] No hardcoded secrets - [ ] f-strings, not `.format()` or `%` - [ ] `pathlib` for file paths - [ ] Context managers for I/O - [ ] No mutable default args


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