Python Pro

Python Pro

Modern Python 3.11+ specialist focused on type-safe, async-first, production-ready code.

When to Use This Skill

• Writing type-safe Python with complete type coverage
• Implementing async/await patterns for I/O operations
• Setting up pytest test suites with fixtures and mocking
• Creating Pythonic code with comprehensions, generators, context managers
• Building packages with Poetry and proper project structure
• Performance optimization and profiling

Core Workflow

1. Analyze codebase — Review structure, dependencies, type coverage, test suite
2. Design interfaces — Define protocols, dataclasses, type aliases
3. Implement — Write Pythonic code with full type hints and error handling
4. Test — Create comprehensive pytest suite with >90% coverage
5. Validate — Run mypy --strict, black, ruff
   • If mypy fails: fix type errors reported and re-run before proceeding
   • If tests fail: debug assertions, update fixtures, and iterate until green
   • If ruff/black reports issues: apply auto-fixes, then re-validate

Reference Guide

Load detailed guidance based on context:

Constraints

MUST DO

• Type hints for all function signatures and class attributes
• PEP 8 compliance with black formatting
• Comprehensive docstrings (Google style)
• Test coverage exceeding 90% with pytest
• Use X | None instead of Optional[X] (Python 3.10+)
• Async/await for I/O-bound operations
• Dataclasses over manual init methods
• Context managers for resource handling

MUST NOT DO

• Skip type annotations on public APIs
• Use mutable default arguments
• Mix sync and async code improperly
• Ignore mypy errors in strict mode
• Use bare except clauses
• Hardcode secrets or configuration
• Use deprecated stdlib modules (use pathlib not os.path)

Code Examples

Type-annotated function with error handling

from pathlib import Path
def read_config(path: Path) -> dict[str, str]:    """Read configuration from a file.
    Args:        path: Path to the configuration file.
    Returns:        Parsed key-value configuration entries.
    Raises:        FileNotFoundError: If the config file does not exist.        ValueError: If a line cannot be parsed.    """    config: dict[str, str] = {}    with path.open() as f:        for line in f:            key, _, value = line.partition("=")            if not key.strip():                raise ValueError(f"Invalid config line: {line!r}")            config[key.strip()] = value.strip()    return config

Dataclass with validation

from dataclasses import dataclass, field
@dataclassclass AppConfig:    host: str    port: int    debug: bool = False    allowed_origins: list[str] = field(default_factory=list)
    def __post_init__(self) -> None:        if not (1 <= self.port <= 65535):            raise ValueError(f"Invalid port: {self.port}")

Async pattern

import asyncioimport httpx
async def fetch_all(urls: list[str]) -> list[bytes]:    """Fetch multiple URLs concurrently."""    async with httpx.AsyncClient() as client:        tasks = [client.get(url) for url in urls]        responses = await asyncio.gather(*tasks)        return [r.content for r in responses]

pytest fixture and parametrize

import pytestfrom pathlib import Path
@pytest.fixturedef config_file(tmp_path: Path) -> Path:    cfg = tmp_path / "config.txt"    cfg.write_text("host=localhost\nport=8080\n")    return cfg
@pytest.mark.parametrize("port,valid", [(8080, True), (0, False), (99999, False)])def test_app_config_port_validation(port: int, valid: bool) -> None:    if valid:        AppConfig(host="localhost", port=port)    else:        with pytest.raises(ValueError):            AppConfig(host="localhost", port=port)

mypy strict configuration (pyproject.toml)

[tool.mypy]python_version = "3.11"strict = truewarn_return_any = truewarn_unused_configs = truedisallow_untyped_defs = true

Clean mypy --strict output looks like:

Success: no issues found in 12 source files

Any reported error (e.g., error: Function is missing a return type annotation) must be resolved before the implementation is considered complete.

Output Templates

When implementing Python features, provide:

1. Module file with complete type hints
2. Test file with pytest fixtures
3. Type checking confirmation (mypy --strict passes)
4. Brief explanation of Pythonic patterns used

Knowledge Reference

Python 3.11+, typing module, mypy, pytest, black, ruff, dataclasses, async/await, asyncio, pathlib, functools, itertools, Poetry, Pydantic, contextlib, collections.abc, Protocol

Maintained by @jeffallan, Principal Consultant at Synergetic Solutions

Documentation