Skip to content
Back to skills

Parallel File Processor

ASecurity

Process multiple files in parallel with aggregation and progress tracking.

  • 17 stars
  • 0 votes
  • 0 copies
  • 3 views
  • Added September 9, 2026
toolspythongoperformance

Security analysis

A100/100

Scanned September 9, 2026

npx -y skills add vamseeachanta/workspace-hub --skill parallel-file-processor --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Parallel File Processor?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Parallel File Processor
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/vamseeachanta-parallel-file-processor/badge)](https://www.skillsdirectory.com/skills/vamseeachanta-parallel-file-processor)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: parallel-file-processor
description: Process multiple files in parallel with aggregation and progress tracking.
  Use for batch file operations, directory scanning, ZIP handling, and parallel data
  processing with 2-3x performance improvement.
type: reference
version: 1.1.0
category: development
related_skills:
- data-pipeline-processor
- yaml-workflow-executor
- engineering-report-generator
capabilities: []
requires: []
tags: []
---

# Parallel File Processor

## Quick Start

```python
from concurrent.futures import ThreadPoolExecutor, as_completed
from pathlib import Path
import pandas as pd

def process_csv(file_path: Path) -> dict:
    """Process a single CSV file."""
    df = pd.read_csv(file_path)
    return {'file': file_path.name, 'rows': len(df), 'columns': len(df.columns)}

# Get all CSV files
files = list(Path('data/raw/').glob('*.csv'))

# Process in parallel
results = []
with ThreadPoolExecutor(max_workers=8) as executor:
    futures = {executor.submit(process_csv, f): f for f in files}
    for future in as_completed(futures):
        results.append(future.result())

print(f"Processed {len(results)} files")
```

## When to Use

- Processing large numbers of files (100+ files)
- Batch operations on directory contents
- Extracting data from multiple ZIP archives
- Aggregating results from parallel operations
- CPU-bound file transformations
- IO-bound file operations with proper concurrency

## Related Skills

- [data-pipeline-processor](../data-pipeline-processor/SKILL.md) - Data transformation
- [yaml-workflow-executor](../yaml-workflow-executor/SKILL.md) - Workflow automation
- [engineering-report-generator](../engineering-report-generator/SKILL.md) - Report generation

---

## Version History

- **1.1.0** (2026-01-02): Upgraded to SKILL_TEMPLATE_v2 format with Quick Start, Error Handling, Metrics, Execution Checklist, additional examples
- **1.0.0** (2024-10-15): Initial release with FileScanner, ParallelProcessor, progress tracking, result aggregation

## Sub-Skills

- [Example 1: Process CSV Files (+3)](example-1-process-csv-files/SKILL.md)
- [Do (+1)](do/SKILL.md)

## Sub-Skills

- [Error Handling](error-handling/SKILL.md)
- [Execution Checklist](execution-checklist/SKILL.md)
- [Metrics](metrics/SKILL.md)

## Sub-Skills

- [Core Pattern](core-pattern/SKILL.md)
- [Core Components (+5)](core-components/SKILL.md)
- [Basic Configuration](basic-configuration/SKILL.md)
- [Mode Selection (+2)](mode-selection/SKILL.md)

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…

Newsletter

Get the weekly list of safe new skills, and the ones we pulled.