juniper-data-client

Python HTTP client for the juniper-data dataset-generation service.

juniper-data-client is a thin, synchronous HTTP client for fetching datasets from a juniper-data instance. It exposes a single JuniperDataClient class whose methods correspond to the REST surface: generator schemas, dataset creation, tag-based filtering, batch operations, the named-version registry, and download of the resulting NPZ artifacts as ready-to-train numpy arrays. It is the canonical dataset-fetch interface used by juniper-cascor (training) and juniper-canopy (visualisation), and it reads the platform's shared X_train / y_train / X_val / y_val / X_test / y_test NPZ schema (all float32). val is presence-conditional: validate_npz_contract skips a split the artifact does not carry. Fake producers emit it (#187); live artifacts may omit it.

Part of the Juniper platform. juniper-data-client is the Python HTTP client for the juniper-data dataset service in Juniper — a multi-package ML research platform built around constructive (Cascade-Correlation) and recurrent neural networks. Point it at any running juniper-data instance.

Install

pip install juniper-data-client

Optional extras: [observability] adds X-Request-ID propagation via juniper-observability; [test] and [dev] install the test and lint/type-check toolchains.

Quick start

from juniper_data_client import JuniperDataClient

with JuniperDataClient("http://localhost:8100") as client:
    print(client.health_check()["status"])

    result = client.create_spiral_dataset(n_spirals=2, n_points_per_spiral=100, noise=0.1, seed=42)
    arrays = client.download_artifact_npz(result["dataset_id"])

    print("train:", len(arrays["X_train"]), "test:", len(arrays["X_test"]))

The artifacts come back as a dict of float32 numpy arrays, ready for torch.from_numpy(...).

API

Status

Beta on PyPI. The current version is shown by the badge above; see CHANGELOG.md.

Documentation

• docs/QUICK_START.md — installation and verification guide
• docs/REFERENCE.md — full API reference, configuration, and error model

License

MIT — see LICENSE.