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Kurt Warner
Kurt Warner

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I built a Professional Automation Toolkit - 6 tools + FastAPI orchestrator (6,877 LOC)

#python #automation #fastapi #opensource

Hey Dev.to! 👋

Just launched my automation toolkit after 6 months of development. Wanted to share with this awesome community!

The Problem

I had 30+ automation scripts scattered across folders with:

  • Inconsistent CLI patterns
  • No error handling
  • Zero documentation
  • Impossible to chain together

The Solution

Built a professional toolkit with 6 production-ready tools + FastAPI orchestrator:

🔧 The 6 Tools

  1. Cookie Analysis Suite (466 lines)

    • Forensic browser cookie analysis
    • 4-stage pipeline: parse → enrich → scan → report
    • Privacy tracking detection

  2. Video Enhancement Suite (1,112 lines)

    • Multi-backend support (Topaz/FFmpeg/HandBrake)
    • Priority-based job queue
    • Concurrent processing

  3. PathPulse (1,205 lines)

    • Real-time file system threat detection
    • 6 threat pattern detectors
    • Ransomware detection

  4. Windows Feature Manager (1,418 lines)

    • Enable/disable Windows features
    • PowerShell/DISM integration
    • Backup/restore with rollback

  5. Web Automation Framework (1,121 lines)

    • Multi-browser Selenium automation
    • 8 action types
    • Headless mode + proxy support

  6. ADB Automation Framework (1,555 lines)

    • Android device management
    • App control + input simulation
    • Screen capture + file transfer

🎛️ The Orchestrator

Built with FastAPI to tie everything together:

  • REST API - Execute any tool programmatically
  • Web Dashboard - Visual monitoring
  • Pipeline Builder - Chain tools together
  • Audit Trail - Complete logging
  • CI/CD Ready - GitHub Actions included

Tech Stack

  • Python 3.11
  • FastAPI + Pydantic
  • Selenium, watchdog, subprocess
  • 6,877 lines of production code
  • Cross-platform (Win/Mac/Linux)

Architecture Pattern

Every tool follows the same pattern:

Models → Business Logic → CLI → API → Dashboard
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This makes them easy to maintain, extend, and integrate.

Quick Start 

git clone https://github.com/dopamin3fiends/ml-systems-portfolio.git
cd ml-systems-portfolio
pip install -r requirements.txt

# Test a tool
cd tools/cookie_analysis
python cli.py demo

# Start orchestrator
cd ../../
python src/backend/orchestrator_api.py
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Open browser: http://localhost:8000

Lessons Learned

  1. Architecture matters - Even for "just scripts"
  2. Documentation is not optional - Future you will thank present you
  3. Demo modes are essential - Safe testing without real data
  4. Integration is hard - REST API makes it manageable
  5. Professional != complicated - Clear patterns beat clever code

Open Source + Support Model

The code is fully open source (MIT license) on GitHub. I'm also offering a packaged version on Gumroad with:

  • Pre-configured setup
  • Professional support
  • Lifetime updates
  • Commercial license clarity

Think: Linux is free, Red Hat makes billions. You're paying for packaging and peace of mind.

🎁 Launch special: Use code LAUNCH20 for 20% off

Links

Questions?

Happy to answer anything about:

  • The architecture decisions
  • FastAPI integration patterns
  • Building production-grade automation tools
  • Open source + paid model

Thanks for reading! 🙏

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