用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/vamseeachanta/workspace-hub --skill parallel-file-processor-core-components命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
基于 SOC 职业分类
正在显示 SKILL.md
| name | parallel-file-processor-core-components |
| description | Sub-skill of parallel-file-processor: Core Components (+5). |
| version | 1.1.0 |
| category | development |
| type | reference |
| scripts_exempt | true |
from dataclasses import dataclass, field
from pathlib import Path
from typing import (
List, Dict, Any, Callable, Optional, Generator, TypeVar, Generic
)
from enum import Enum
import logging
logger = logging.getLogger(__name__)
*See sub-skills for full details.*
## File Scanner
```python
import fnmatch
from typing import List, Optional, Set, Generator
from pathlib import Path
class FileScanner:
"""
Scan directories for files matching patterns.
Supports glob patterns, extension filtering, and size limits.
*See sub-skills for full details.*
## Parallel Processor
```python
import time
from concurrent.futures import (
ThreadPoolExecutor, ProcessPoolExecutor,
as_completed, Future
)
from typing import Callable, TypeVar, Generic, List
import asyncio
from functools import partial
*See sub-skills for full details.*
## File Processor
```python
class FileProcessor:
"""
High-level file processing with parallel execution.
Combines scanning, filtering, and parallel processing.
"""
def __init__(self,
scanner: FileScanner = None,
*See sub-skills for full details.*
## Progress Tracking
```python
from datetime import datetime, timedelta
import sys
class ProgressTracker:
"""Track and display processing progress."""
def __init__(self,
total: int,
description: str = "Processing",
*See sub-skills for full details.*
## Result Aggregator
```python
import json
class ResultAggregator:
"""Aggregate and export batch processing results."""
def __init__(self, batch_result: BatchResult):
self.batch_result = batch_result
def to_dataframe(self) -> pd.DataFrame:
*See sub-skills for full details.*