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Use when writing new code, reviewing style, configuring linters, writing docstrings, or establishing project standards.","cercova-studios\u002F10x-swe","cercova-studios","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F217108198?v=4","01M6CCYGHXTH80N3BXRW6KESTE","Cercova Studios","01M6CCYGPADH5MJDR0VNNR775C",1,"MIT","https:\u002F\u002Fgithub.com\u002Fcercova-studios\u002F10x-swe\u002Fblob\u002Fmain\u002Fplugins\u002F10x-swe\u002Fskills\u002Fpython-code-style\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43],"python","code style","code","python code style","python code","style","new","writing","when","docstrings","naming conventions","naming","Documentation Standards","linting","formatting","project","conventions","standards","use","documentation","2026-11-10 10:12:30",false,"---\nname: python-code-style\ndescription: Python code style, linting, formatting, naming conventions, and documentation standards. Use when writing new code, reviewing style, configuring linters, writing docstrings, or establishing project standards.\n---\n\n# Python Code Style & Documentation\n\nConsistent code style and clear documentation make codebases maintainable and collaborative. This skill covers modern Python tooling, naming conventions, and documentation standards.\n\n## When to Use This Skill\n\n- Setting up linting and formatting for a new project\n- Writing or reviewing docstrings\n- Establishing team coding standards\n- Configuring ruff, mypy, or pyright\n- Reviewing code for style consistency\n- Creating project documentation\n\n## Core Concepts\n\n### 1. Automated Formatting\n\nLet tools handle formatting debates. Configure once, enforce automatically.\n\n### 2. Consistent Naming\n\nFollow PEP 8 conventions with meaningful, descriptive names.\n\n### 3. Documentation as Code\n\nDocstrings should be maintained alongside the code they describe.\n\n### 4. Type Annotations\n\nModern Python code should include type hints for all public APIs.\n\n## Quick Start\n\n```bash\n# Install modern tooling\npip install ruff mypy\n\n# Configure in pyproject.toml\n[tool.ruff]\nline-length = 120\ntarget-version = \"py312\"  # Adjust based on your project's minimum Python version\n\n[tool.mypy]\nstrict = true\n```\n\n## Fundamental Patterns\n\n### Pattern 1: Modern Python Tooling\n\nUse `ruff` as an all-in-one linter and formatter. It replaces flake8, isort, and black with a single fast tool.\n\n```toml\n# pyproject.toml\n[tool.ruff]\nline-length = 120\ntarget-version = \"py312\"  # Adjust based on your project's minimum Python version\n\n[tool.ruff.lint]\nselect = [\n    \"E\",    # pycodestyle errors\n    \"W\",    # pycodestyle warnings\n    \"F\",    # pyflakes\n    \"I\",    # isort\n    \"B\",    # flake8-bugbear\n    \"C4\",   # flake8-comprehensions\n    \"UP\",   # pyupgrade\n    \"SIM\",  # flake8-simplify\n]\nignore = [\"E501\"]  # Line length handled by formatter\n\n[tool.ruff.format]\nquote-style = \"double\"\nindent-style = \"space\"\n```\n\nRun with:\n\n```bash\nruff check --fix .  # Lint and auto-fix\nruff format .       # Format code\n```\n\n### Pattern 2: Type Checking Configuration\n\nConfigure strict type checking for production code.\n\n```toml\n# pyproject.toml\n[tool.mypy]\npython_version = \"3.12\"\nstrict = true\nwarn_return_any = true\nwarn_unused_ignores = true\ndisallow_untyped_defs = true\ndisallow_incomplete_defs = true\n\n[[tool.mypy.overrides]]\nmodule = \"tests.*\"\ndisallow_untyped_defs = false\n```\n\nAlternative: Use `pyright` for faster checking.\n\n```toml\n[tool.pyright]\npythonVersion = \"3.12\"\ntypeCheckingMode = \"strict\"\n```\n\n### Pattern 3: Naming Conventions\n\nFollow PEP 8 with emphasis on clarity over brevity.\n\n**Files and Modules:**\n\n```python\n# Good: Descriptive snake_case\nuser_repository.py\norder_processing.py\nhttp_client.py\n\n# Avoid: Abbreviations\nusr_repo.py\nord_proc.py\nhttp_cli.py\n```\n\n**Classes and Functions:**\n\n```python\n# Classes: PascalCase\nclass UserRepository:\n    pass\n\nclass HTTPClientFactory:  # Acronyms stay uppercase\n    pass\n\n# Functions and variables: snake_case\ndef get_user_by_email(email: str) -> User | None:\n    retry_count = 3\n    max_connections = 100\n```\n\n**Constants:**\n\n```python\n# Module-level constants: SCREAMING_SNAKE_CASE\nMAX_RETRY_ATTEMPTS = 3\nDEFAULT_TIMEOUT_SECONDS = 30\nAPI_BASE_URL = \"https:\u002F\u002Fapi.example.com\"\n```\n\n### Pattern 4: Import Organization\n\nGroup imports in a consistent order: standard library, third-party, local.\n\n```python\n# Standard library\nimport os\nfrom collections.abc import Callable\nfrom typing import Any\n\n# Third-party packages\nimport httpx\nfrom pydantic import BaseModel\nfrom sqlalchemy import Column\n\n# Local imports\nfrom myproject.models import User\nfrom myproject.services import UserService\n```\n\nUse absolute imports exclusively:\n\n```python\n# Preferred\nfrom myproject.utils import retry_decorator\n\n# Avoid relative imports\nfrom ..utils import retry_decorator\n```\n\n## Advanced Patterns\n\n### Pattern 5: Google-Style Docstrings\n\nWrite docstrings for all public classes, methods, and functions.\n\n**Simple Function:**\n\n```python\ndef get_user(user_id: str) -> User:\n    \"\"\"Retrieve a user by their unique identifier.\"\"\"\n    ...\n```\n\n**Complex Function:**\n\n```python\ndef process_batch(\n    items: list[Item],\n    max_workers: int = 4,\n    on_progress: Callable[[int, int], None] | None = None,\n) -> BatchResult:\n    \"\"\"Process items concurrently using a worker pool.\n\n    Processes each item in the batch using the configured number of\n    workers. Progress can be monitored via the optional callback.\n\n    Args:\n        items: The items to process. Must not be empty.\n        max_workers: Maximum concurrent workers. Defaults to 4.\n        on_progress: Optional callback receiving (completed, total) counts.\n\n    Returns:\n        BatchResult containing succeeded items and any failures with\n        their associated exceptions.\n\n    Raises:\n        ValueError: If items is empty.\n        ProcessingError: If the batch cannot be processed.\n\n    Example:\n        >>> result = process_batch(items, max_workers=8)\n        >>> print(f\"Processed {len(result.succeeded)} items\")\n    \"\"\"\n    ...\n```\n\n**Class Docstring:**\n\n```python\nclass UserService:\n    \"\"\"Service for managing user operations.\n\n    Provides methods for creating, retrieving, updating, and\n    deleting users with proper validation and error handling.\n\n    Attributes:\n        repository: The data access layer for user persistence.\n        logger: Logger instance for operation tracking.\n\n    Example:\n        >>> service = UserService(repository, logger)\n        >>> user = service.create_user(CreateUserInput(...))\n    \"\"\"\n\n    def __init__(self, repository: UserRepository, logger: Logger) -> None:\n        \"\"\"Initialize the user service.\n\n        Args:\n            repository: Data access layer for users.\n            logger: Logger for tracking operations.\n        \"\"\"\n        self.repository = repository\n        self.logger = logger\n```\n\n### Pattern 6: Line Length and Formatting\n\nSet line length to 120 characters for modern displays while maintaining readability.\n\n```python\n# Good: Readable line breaks\ndef create_user(\n    email: str,\n    name: str,\n    role: UserRole = UserRole.MEMBER,\n    notify: bool = True,\n) -> User:\n    ...\n\n# Good: Chain method calls clearly\nresult = (\n    db.query(User)\n    .filter(User.active == True)\n    .order_by(User.created_at.desc())\n    .limit(10)\n    .all()\n)\n\n# Good: Format long strings\nerror_message = (\n    f\"Failed to process user {user_id}: \"\n    f\"received status {response.status_code} \"\n    f\"with body {response.text[:100]}\"\n)\n```\n\n### Pattern 7: Project Documentation\n\n**README Structure:**\n\n```markdown\n# Project Name\n\nBrief description of what the project does.\n\n## Installation\n\n\\`\\`\\`bash\npip install myproject\n\\`\\`\\`\n\n## Quick Start\n\n\\`\\`\\`python\nfrom myproject import Client\n\nclient = Client(api_key=\"...\")\nresult = client.process(data)\n\\`\\`\\`\n\n## Configuration\n\nDocument environment variables and configuration options.\n\n## Development\n\n\\`\\`\\`bash\npip install -e \".[dev]\"\npytest\n\\`\\`\\`\n```\n\n**CHANGELOG Format (Keep a Changelog):**\n\n```markdown\n# Changelog\n\n## [Unreleased]\n\n### Added\n- New feature X\n\n### Changed\n- Modified behavior of Y\n\n### Fixed\n- Bug in Z\n```\n\n## Best Practices Summary\n\n1. **Use ruff** - Single tool for linting and formatting\n2. **Enable strict mypy** - Catch type errors before runtime\n3. **120 character lines** - Modern standard for readability\n4. **Descriptive names** - Clarity over brevity\n5. **Absolute imports** - More maintainable than relative\n6. **Google-style docstrings** - Consistent, readable documentation\n7. **Document public APIs** - Every public function needs a docstring\n8. **Keep docs updated** - Treat documentation as code\n9. **Automate in CI** - Run linters on every commit\n10. **Target Python 3.10+** - For new projects, Python 3.12+ is recommended for modern language features\n","# Python Code Style & Documentation\n\nConsistent code style and clear documentation make codebases maintainable and collaborative. This skill covers modern Python tooling, naming conventions, and documentation standards.\n\n## When to Use This Skill\n\n- Setting up linting and formatting for a new project\n- Writing or reviewing docstrings\n- Establishing team coding standards\n- Configuring ruff, mypy, or pyright\n- Reviewing code for style consistency\n- Creating project documentation\n\n## Core Concepts\n\n### 1. Automated Formatting\n\nLet tools handle formatting debates. Configure once, enforce automatically.\n\n### 2. Consistent Naming\n\nFollow PEP 8 conventions with meaningful, descriptive names.\n\n### 3. Documentation as Code\n\nDocstrings should be maintained alongside the code they describe.\n\n### 4. Type Annotations\n\nModern Python code should include type hints for all public APIs.\n\n## Quick Start\n\n```bash\n# Install modern tooling\npip install ruff mypy\n\n# Configure in pyproject.toml\n[tool.ruff]\nline-length = 120\ntarget-version = \"py312\"  # Adjust based on your project's minimum Python version\n\n[tool.mypy]\nstrict = true\n```\n\n## Fundamental Patterns\n\n### Pattern 1: Modern Python Tooling\n\nUse `ruff` as an all-in-one linter and formatter. It replaces flake8, isort, and black with a single fast tool.\n\n```toml\n# pyproject.toml\n[tool.ruff]\nline-length = 120\ntarget-version = \"py312\"  # Adjust based on your project's minimum Python version\n\n[tool.ruff.lint]\nselect = [\n    \"E\",    # pycodestyle errors\n    \"W\",    # pycodestyle warnings\n    \"F\",    # pyflakes\n    \"I\",    # isort\n    \"B\",    # flake8-bugbear\n    \"C4\",   # flake8-comprehensions\n    \"UP\",   # pyupgrade\n    \"SIM\",  # flake8-simplify\n]\nignore = [\"E501\"]  # Line length handled by formatter\n\n[tool.ruff.format]\nquote-style = \"double\"\nindent-style = \"space\"\n```\n\nRun with:\n\n```bash\nruff check --fix .  # Lint and auto-fix\nruff format .       # Format code\n```\n\n### Pattern 2: Type Checking Configuration\n\nConfigure strict type checking for production code.\n\n```toml\n# pyproject.toml\n[tool.mypy]\npython_version = \"3.12\"\nstrict = true\nwarn_return_any = true\nwarn_unused_ignores = true\ndisallow_untyped_defs = true\ndisallow_incomplete_defs = true\n\n[[tool.mypy.overrides]]\nmodule = \"tests.*\"\ndisallow_untyped_defs = false\n```\n\nAlternative: Use `pyright` for faster checking.\n\n```toml\n[tool.pyright]\npythonVersion = \"3.12\"\ntypeCheckingMode = \"strict\"\n```\n\n### Pattern 3: Naming Conventions\n\nFollow PEP 8 with emphasis on clarity over brevity.\n\n**Files and Modules:**\n\n```python\n# Good: Descriptive snake_case\nuser_repository.py\norder_processing.py\nhttp_client.py\n\n# Avoid: Abbreviations\nusr_repo.py\nord_proc.py\nhttp_cli.py\n```\n\n**Classes and Functions:**\n\n```python\n# Classes: PascalCase\nclass UserRepository:\n    pass\n\nclass HTTPClientFactory:  # Acronyms stay uppercase\n    pass\n\n# Functions and variables: snake_case\ndef get_user_by_email(email: str) -> User | None:\n    retry_count = 3\n    max_connections = 100\n```\n\n**Constants:**\n\n```python\n# Module-level constants: SCREAMING_SNAKE_CASE\nMAX_RETRY_ATTEMPTS = 3\nDEFAULT_TIMEOUT_SECONDS = 30\nAPI_BASE_URL = \"https:\u002F\u002Fapi.example.com\"\n```\n\n### Pattern 4: Import Organization\n\nGroup imports in a consistent order: standard library, third-party, local.\n\n```python\n# Standard library\nimport os\nfrom collections.abc import Callable\nfrom typing import Any\n\n# Third-party packages\nimport httpx\nfrom pydantic import BaseModel\nfrom sqlalchemy import Column\n\n# Local imports\nfrom myproject.models import User\nfrom myproject.services import UserService\n```\n\nUse absolute imports exclusively:\n\n```python\n# Preferred\nfrom myproject.utils import retry_decorator\n\n# Avoid relative imports\nfrom ..utils import retry_decorator\n```\n\n## Advanced Patterns\n\n### Pattern 5: Google-Style Docstrings\n\nWrite docstrings for all public classes, methods, and functions.\n\n**Simple Function:**\n\n```python\ndef get_user(user_id: str) -> User:\n    \"\"\"Retrieve a user by their unique identifier.\"\"\"\n    ...\n```\n\n**Complex Function:**\n\n```python\ndef process_batch(\n    items: list[Item],\n    max_workers: int = 4,\n    on_progress: Callable[[int, int], None] | None = None,\n) -> BatchResult:\n    \"\"\"Process items concurrently using a worker pool.\n\n    Processes each item in the batch using the configured number of\n    workers. Progress can be monitored via the optional callback.\n\n    Args:\n        items: The items to process. Must not be empty.\n        max_workers: Maximum concurrent workers. Defaults to 4.\n        on_progress: Optional callback receiving (completed, total) counts.\n\n    Returns:\n        BatchResult containing succeeded items and any failures with\n        their associated exceptions.\n\n    Raises:\n        ValueError: If items is empty.\n        ProcessingError: If the batch cannot be processed.\n\n    Example:\n        >>> result = process_batch(items, max_workers=8)\n        >>> print(f\"Processed {len(result.succeeded)} items\")\n    \"\"\"\n    ...\n```\n\n**Class Docstring:**\n\n```python\nclass UserService:\n    \"\"\"Service for managing user operations.\n\n    Provides methods for creating, retrieving, updating, and\n    deleting users with proper validation and error handling.\n\n    Attributes:\n        repository: The data access layer for user persistence.\n        logger: Logger instance for operation tracking.\n\n    Example:\n        >>> service = UserService(repository, logger)\n        >>> user = service.create_user(CreateUserInput(...))\n    \"\"\"\n\n    def __init__(self, repository: UserRepository, logger: Logger) -> None:\n        \"\"\"Initialize the user service.\n\n        Args:\n            repository: Data access layer for users.\n            logger: Logger for tracking operations.\n        \"\"\"\n        self.repository = repository\n        self.logger = logger\n```\n\n### Pattern 6: Line Length and Formatting\n\nSet line length to 120 characters for modern displays while maintaining readability.\n\n```python\n# Good: Readable line breaks\ndef create_user(\n    email: str,\n    name: str,\n    role: UserRole = UserRole.MEMBER,\n    notify: bool = True,\n) -> User:\n    ...\n\n# Good: Chain method calls clearly\nresult = (\n    db.query(User)\n    .filter(User.active == True)\n    .order_by(User.created_at.desc())\n    .limit(10)\n    .all()\n)\n\n# Good: Format long strings\nerror_message = (\n    f\"Failed to process user {user_id}: \"\n    f\"received status {response.status_code} \"\n    f\"with body {response.text[:100]}\"\n)\n```\n\n### Pattern 7: Project Documentation\n\n**README Structure:**\n\n```markdown\n# Project Name\n\nBrief description of what the project does.\n\n## Installation\n\n\\`\\`\\`bash\npip install myproject\n\\`\\`\\`\n\n## Quick Start\n\n\\`\\`\\`python\nfrom myproject import Client\n\nclient = Client(api_key=\"...\")\nresult = client.process(data)\n\\`\\`\\`\n\n## Configuration\n\nDocument environment variables and configuration options.\n\n## Development\n\n\\`\\`\\`bash\npip install -e \".[dev]\"\npytest\n\\`\\`\\`\n```\n\n**CHANGELOG Format (Keep a Changelog):**\n\n```markdown\n# Changelog\n\n## [Unreleased]\n\n### Added\n- New feature X\n\n### Changed\n- Modified behavior of Y\n\n### Fixed\n- Bug in Z\n```\n\n## Best Practices Summary\n\n1. **Use ruff** - Single tool for linting and formatting\n2. **Enable strict mypy** - Catch type errors before runtime\n3. **120 character lines** - Modern standard for readability\n4. **Descriptive names** - Clarity over brevity\n5. **Absolute imports** - More maintainable than relative\n6. **Google-style docstrings** - Consistent, readable documentation\n7. **Document public APIs** - Every public function needs a docstring\n8. **Keep docs updated** - Treat documentation as code\n9. **Automate in CI** - Run linters on every commit\n10. **Target Python 3.10+** - For new projects, Python 3.12+ is recommended for modern language features\n",{"name":5,"description":7},"main","12441d84a8a292fcc94f47bc98877cbefd9b52e2","plugins\u002F10x-swe\u002Fskills\u002Fpython-code-style",0,"https:\u002F\u002Fgithub.com\u002Fcercova-studios\u002F10x-swe","https:\u002F\u002Fgithub.com\u002Fcercova-studios","2026-11-12 00:33:06",{"source":8,"skillName":5,"commands":57,"prompt":67,"zipAvailable":68},[58,61,64],{"tool":59,"command":60},"npx","npx skills add cercova-studios\u002F10x-swe --skill python-code-style",{"tool":62,"command":63},"bunx","bunx skills add cercova-studios\u002F10x-swe --skill python-code-style",{"tool":65,"command":66},"pnpm","pnpm dlx skills add cercova-studios\u002F10x-swe --skill python-code-style","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fcercova-studios\u002F10x-swe\u002Fblob\u002Fmain\u002Fplugins\u002F10x-swe\u002Fskills\u002Fpython-code-style\u002FSKILL.md",true,[],[71,110,144,164,183,195],{"skillNo":72,"name":73,"nameZh":6,"description":74,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":75,"licenseFileUrl":76,"sourceHtmlUrl":77,"categories":78,"keywords":84,"publishedAt":44},"01M6CD3T6EQ9N5KPNXCM6ABHVA","turnstile-spin","Set up Cloudflare Turnstile end-to-end in a project. Scan the codebase, create the widget via the Cloudflare API, embed it where user requests need bot verification (form submissions, SPA actions, API endpoints, download links, comment or vote submissions, etc.), wire canonical server-side siteverify in the customer's existing backend, validate, and persist the skill. Load this when a user asks to add Turnstile, set up CAPTCHA, protect a form or endpoint from bots, or fix a Turnstile integration. 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