Lightning-fast bulk file downloader for datanodes.to & fuckingfast.co
Built with Python · Playwright · aiohttp
Best tested:
~250 MB/son a 2.5 Gbps fiber — 23.5 GB across 47 files in ~3 minutes
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- Install Python 3.10+ — check ✅ "Add Python to PATH"
- Double-click
avvia.bat - Done. First run auto-installs everything.
pip install -r requirements.txt
playwright install chromium
python gen_1.pypython gen_cli.py <url1> <url2> ... -o <output_folder>| Setting | Range | Default | Description |
|---|---|---|---|
| Browsers | 8 – 32 | 16 | Parallel browser workers for link extraction |
| DL Streams | 16 – 64 | 48 | Concurrent download connections |
| Retries | 0 – 5 | 3 | Retry attempts per failed URL |
Tip: For 40+ file sessions, 16 browsers / 48 streams is the sweet spot. For 200+ files, push browsers toward 32.
| File | Description |
|---|---|
moontech_*.log |
Human-readable performance report |
moontech_*.json |
Per-file metrics (machine-readable) |
output_links.txt |
Extracted direct links (Links-only mode) |
failed_links.txt |
URLs that failed all retries |
Place in the same folder as gen_1.py:
| File | Purpose |
|---|---|
proxies.txt |
Proxy list — ip:port:user:pass or http://user:pass@ip:port |
logo.png |
Custom header logo (auto-scaled to 44×44) |
Single-file application (~1500 lines), structured in layers:
gen_1.py
├── Global config — theme, tuning constants, user agents
├── Resource singletons — aiohttp session pool, proxy rotation
├── Extraction layer — fuckingfast (regex) + datanodes (Playwright)
├── Download engine — Range resume, stall detection, lane kills
├── Telemetry — 1 Hz snapshots, .log + .json output
├── GUI (tkinter) — live stats, dual progress bars, color log
└── Async orchestration — queue-based workers, semaphore concurrency
- OS: Windows 10 / 11
- Python: 3.10+
- Disk: ~150 MB for Chromium browser
- Packages:
aiohttp,playwright,pillow
Made with 🖤 and cold coffee


