Deploy from Python

Publish Python datasets to hypequery cloud with a deployment bundle and the hypequery CLI.

hypequery cloud is not live yet

You can't sign up for or deploy to cloud today. These pages describe the planned service, and details will change before launch. What runs today is the open-source TypeScript and Python SDKs, in your own backend.

Python projects write a deployment bundle with the Python SDK, then release and submit it with the TypeScript hypequery CLI (npx hypequery). The Python CLI scaffolds and serves projects locally; cloud releases go through the Node.js CLI.

1. Write a deployment bundle

# analytics/cloud.py
from hypequery.datasets import create_dataset_registry, write_dataset_bundle

from .orders import orders

write_dataset_bundle(
    "analytics/hypequery-deployment",
    create_dataset_registry(orders),
    endpoints={
        "orders": {
            "access": {"kind": "authenticated", "roles": ["analyst"], "scopes": []},
            "tenant": {"kind": "not-required"},
            "path": "/api/analytics/datasets/orders/query",
        },
    },
)

Each entry in endpoints publishes one dataset with its access policy, tenant requirement, and path.

2. Log in, release, and submit

python -m analytics.cloud
npx hypequery login
npx hypequery deployment:release analytics/hypequery-deployment
npx hypequery deployment:submit analytics/hypequery-deployment \
  --release analytics/hypequery-deployment.release.json

deployment:release binds the bundle to your project and environment and writes the release beside the bundle.
deployment:submit uploads both. Once cloud accepts the release, check where it is served with npx hypequery deployment:status.

A one-step publish_to_cloud helper for Python, matching TypeScript's publishToCloud, is planned.

1. Write a deployment bundle

2. Log in, release, and submit

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