LearnML Python SDK 0.1.3

HTTP(S) URLs select the website API; bare host:port addresses retain direct gRPC.

from getpass import getpass
from learnml import LearnMLClient

with LearnMLClient("https://your-learnml-server.example") as client:
    client.login("you@example.com", getpass("LearnML password: "))
    universe = next(u for u in client.list_universes() if u["name"] == "My experiments")
    uid = universe["id"]
    run = client.create_training_run(uid, "my-experiment", model_name="my-model")
    client.log_metrics(uid, run["id"], step=1, loss=0.42, accuracy=0.91)
    client.upload_data(uid, "experiment-data", "CUSTOM", "experiment.csv")
    client.end_training_run(uid, run["id"])

Install with python -m pip install --upgrade learnml-sdk, or install a local checkout with python -m pip install ./sdk. Restart a notebook kernel after upgrading an already-imported package. HTTP support requires version 0.1.3 or later.

HTTP mode preserves the existing public methods and camelCase response dictionaries. token and refresh state work in both modes. Requests have connection/read timeouts; API and network errors use the SDK exception classes. HTTP multipart uploads stream from the client file; the current gateway still buffers uploads in server memory. chunk_size controls gRPC chunks; the HTTP transport controls its own multipart read sizes. HTTP collection batching uses paginated API calls.

The existing gateway cannot accept custom checkpoint metadata; HTTP save_checkpoint(metadata=...) raises an explicit error if nonempty metadata is supplied. Empty metadata and the normal checkpoint upload/download flow are supported.

Run regression tests with python -m unittest discover -s sdk/tests from the repository root after installing the SDK.