benchhub-client 0.1.1

Python client + typed contract for the BenchHub benchmarking platform

BenchHub

BenchHub is an open-source benchmarking platform: pick a dataset, define metrics in Python, upload predictions, and see how your model ranks. Live at https://runbenchhub.com.

Originally built as a private dTOF SPAD pipeline benchmarking tool, then generalized into a public, multi-tenant web app.

Features

• OAuth sign-in (GitHub) — no passwords; one-click account creation.
• Datasets and leaderboards are global — no project namespace.
• Per-row visibility (public / unlisted / private) on datasets, leaderboards, and metric/visualization library entries.
• HuggingFace import: pull a structured HF dataset repo as a one-click alternative to a ZIP upload (see scripts/seed_nyu_v2_curated.py for an example workflow).
• User-defined metrics in Python — bring your own scoring code; the metric engine resolves dependencies and runs them per-sample or aggregated. Sandbox-isolated when BENCHHUB_SANDBOX_METRICS=1.
• Asynchronous processing with Celery (Redis broker).
• Per-user quotas: 50 MB storage, 5 datasets, 50 submissions / 24h by default. Free-tier safe to expose to the open internet.
• API tokens for programmatic uploads (/settings/api_tokens).
• Account deletion (GDPR right-to-be-forgotten) with cascading cleanup.
• Public landing page at /, /leaderboards for browsing the catalog, /u/<id> for public profile pages.

Prerequisites

• Python 3.10+
• Redis (broker + result backend, default port 6379)

Installation

git clone <repository-url>
cd BenchHub
python -m venv venv && source venv/bin/activate
pip install -r requirements.txt

Running

Three terminals:

# 1. Redis
redis-server

# 2. Celery worker
celery -A app.celery worker --loglevel=info

# 3. Flask app
python app.py

Then open http://localhost:6060.

Data lives outside the repo at ~/.dtofbenchmarking/ (database + uploads). Override with BENCHHUB_DATA_DIR=/some/path.

Tests

pytest

429 tests, ~3-4 seconds. Coverage gate is configured in pytest.ini.

Dataset / submission ZIP convention

Folders are auto-detected by prefix:

Prefix	Type	Files
metric_	metric	<sample>.txt containing a float
hist_ / raw_histogram / hist	histogram	<sample>.npz (bins, counts)
raw_	depth/map	<sample>_<W>x<H>.npz
(anything else)	image / scalar / json / text	by file extension

git_info.json (or git.info) at the ZIP root attaches commit metadata to the resulting dataset/submission row.

DLP-safe code uploads

Some networks block .py uploads. The metric editor encodes user code as BASE64:<...> client-side; the server decodes. Standalone helpers:

• scripts/obfuscator.html — portable browser tool
• scripts/obfuscator_gui.py — Tkinter GUI

Deployment

The production app is self-hosted on a home Ubuntu 24.04 box (RTX 5090, 128 GB RAM, 8 TB) reachable at https://runbenchhub.com. gunicorn + celery

• redis run directly under systemd; nginx + certbot terminate TLS; the domain is on Cloudflare in DNS-only mode (no proxy) with ddclient keeping the A record pointed at the home WAN IP.

Operational runbook: docs/SELFHOST_RUNBOOK.md — code-push procedure, .env keys, log tailing, DDNS, TLS renewal, rollback, and the breakages we've already hit.

Fly.io is deprecated: the app was destroyed after the cutover to the home box. The Fly artifacts (fly.toml, Dockerfile, DEPLOY.md, …) are archived under archive/fly/ for the case where a future Fly redeploy needs to be reconstructed.

License

(Choose and add a license file — repository currently has no LICENSE.)