fourtheorem-tempo-client
Python client for the public API of Tempo, fourTheorem's high-throughput compute platform for massive-scale modelling workloads. Generated from the platform's OpenAPI specification.
Status: early development. The API surface is small and evolving, and authentication is not implemented yet — use
Client; the generatedAuthenticatedClientis boilerplate for a Bearer scheme the API does not support yet. Expect breaking changes until 1.0.
Install
pip install fourtheorem-tempo-client
# or
uv add fourtheorem-tempo-client
Requires Python 3.11+. Fully typed (py.typed); httpx-based, with sync and async variants for every operation.
Quickstart
from tempo_client import Client
from tempo_client.api.public import get_workload_status, health_check, submit_workload
from tempo_client.models import WorkloadSubmission
client = Client(base_url="https://your-tempo-host/api")
health_check.sync(client=client)
submitted = submit_workload.sync(
client=client,
body=WorkloadSubmission.from_dict(
{
"name": "demo",
"jobs": [{"id": "j-1", "name": "Job 1", "work_type": "default", "predecessors": []}],
}
),
)
status = get_workload_status.sync(client=client, workload_id=submitted.workload_id)
print(status.state)
Every operation also has an async variant:
status = await get_workload_status.asyncio(client=client, workload_id=submitted.workload_id)
What's covered
Workload submission (inline or via presigned uploads for large job graphs), workload lifecycle (status, cancel, delete, audit trail), job and attempt inspection, the resource-class catalog, and worker-artifact registry uploads — the full public API surface.
Documentation
The API reference (Scalar, with try-it-out) and narrative guides are served by your Tempo deployment at /docs/. The client is regenerated from the platform's OpenAPI specification on every API change, so it always matches the deployed contract.
Learn more about Tempo at fourtheorem.com/high-performance-compute, or about fourTheorem at fourtheorem.com.
License
Metadata
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Total release size: 81.7 kB
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