Skip to main content

juniper-data

PyPI Python 3.12+ License: MIT

A FastAPI service that generates, versions, and serves ML datasets as NPZ artifacts.

juniper-data turns a catalogue of dataset generators into a REST service: you ask it for a dataset by name and parameters, and it returns a versioned, NPZ-formatted train/test/full split. The catalogue spans synthetic classification problems (two-spiral, concentric circles, XOR, Gaussian mixtures, moons, checkerboard), image sets (MNIST), the ARC-AGI visual-reasoning families, a CSV/JSON import path, and a family of time-series and irregularly-sampled sequence generators (autoregressive, Mackey-Glass, multi-sine, delay-product, equities, and the irregular-Δt equities_seq contract). A named-version registry, tag filtering, batch creation, and per-dataset preview round out the surface. Call GET /v1/generators for the live catalogue.

It is the foundational data layer of the platform: the dataset identifiers it returns are the substrate juniper-cascor trains on and juniper-canopy visualises.

Part of the Juniper platform. juniper-data is the dataset-generation service of Juniper — a multi-package ML research platform built around constructive (Cascade-Correlation) and recurrent neural networks. It runs standalone; the rest of the platform consumes it over HTTP (see juniper-data-client).

Install

pip install juniper-data            # from PyPI

For development from a clone (the optional extras are api, arc-agi, equities, mnist, observability, test, dev, all):

git clone https://github.com/pcalnon/juniper-data.git && cd juniper-data
pip install -e ".[all]"

MNIST / Fashion-MNIST (optional extra)

The mnist generator loads the real MNIST / Fashion-MNIST datasets from the Hugging Face Hub and needs the (heavy) datasets chain, shipped behind an explicit extra — it is never part of the base install:

pip install "juniper-data[mnist]"
  • First call downloads from the Hub into the Hugging Face cache (HF_HOME, default ~/.cache/huggingface; the Docker image pins it to /app/data/hf-cache so a mounted data volume persists it). Later calls are served from the cache.
  • Offline deployments must seed that cache ahead of time (run one generation for each dataset while online, or copy a populated HF_HOME in); with HF_HUB_OFFLINE=1 the generator then works entirely from the cache.
  • Without the extra installed, the generator is unavailable: the registry reports available: false and POST /v1/datasets returns 501 with the install hint instead of a masked 500.
  • The service Docker image ships the extra (it is compiled into requirements.lock), so MNIST generation works in containers out of the box.

Run

uvicorn --factory juniper_data.api.app:get_app --reload    # binds 127.0.0.1:8100
curl http://localhost:8100/v1/health/ready
curl http://localhost:8100/v1/generators                   # the live generator catalogue

Create a dataset over the REST API:

curl -sX POST localhost:8100/v1/datasets \
  -H 'Content-Type: application/json' \
  -d '{"generator": "spiral", "name": "demo", "params": {"n_spirals": 2, "noise": 0.1}}'

Or generate one in-process, without the service:

from juniper_data.generators import SpiralGenerator, SpiralParams

dataset = SpiralGenerator.generate(SpiralParams(n_spirals=2, n_points_per_spiral=100, noise=0.1))
# dataset: dict of float32 arrays — X_train, y_train, X_test, y_test, X_full, y_full

Data contract

Datasets are NPZ archives with the keys X_train, y_train, X_test, y_test, X_full, y_full, all float32. This is the contract every Juniper consumer reads.

Configuration

Settings load from the JUNIPER_DATA_ environment namespace (juniper_data/api/settings.py) and honor the Docker _FILE secret convention. The most common knobs (full surface in docs/REFERENCE.md):

Variable Default Purpose
JUNIPER_DATA_HOST / JUNIPER_DATA_PORT 127.0.0.1 / 8100 Bind address / port (0.0.0.0 under Docker).
JUNIPER_DATA_STORAGE_PATH ./data/datasets Where persisted dataset artifacts live.
JUNIPER_DATA_API_KEYS (unset) CSV / JSON-array of X-API-Key values; auth is disabled when unset.
JUNIPER_DATA_LOG_LEVEL / _LOG_FORMAT INFO / text Verbosity / text or json.
JUNIPER_DATA_METRICS_ENABLED false Expose /metrics for Prometheus (IP-gated).

Docker

docker build -t juniper-data:latest .
docker run --rm -p 8100:8100 -e JUNIPER_DATA_HOST=0.0.0.0 juniper-data:latest

Multi-stage build (Python 3.14-slim); health is probed at /v1/health/ready. For the full stack, see juniper-deploy.

Status

Live on PyPI. The current version is shown by the badge above; see CHANGELOG.md. Consumed by juniper-cascor and juniper-canopy via JUNIPER_DATA_URL, and by juniper-data-client programmatically.

Documentation

License

MIT — see LICENSE.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

juniper_data-0.10.0.tar.gz (269.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

juniper_data-0.10.0-py3-none-any.whl (344.2 kB view details)

Uploaded Python 3

File details

Details for the file juniper_data-0.10.0.tar.gz.

File metadata

  • Download URL: juniper_data-0.10.0.tar.gz
  • Upload date:
  • Size: 269.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.13

File hashes

Hashes for juniper_data-0.10.0.tar.gz
Algorithm Hash digest
SHA256 5b0c8ebb9d8909021703af13f144486366178b9decc73d9a04dce8e43c63e1aa
MD5 9aecd66b8238646f68b1d58c4acdc3a5
BLAKE2b-256 acdda9cd4aee92fc57dcce4db6ae1812171781d5cef797a18f8e90629c47678f

See more details on using hashes here.

Provenance

The following attestation bundles were made for juniper_data-0.10.0.tar.gz:

Publisher: publish.yml on pcalnon/juniper-data

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file juniper_data-0.10.0-py3-none-any.whl.

File metadata

  • Download URL: juniper_data-0.10.0-py3-none-any.whl
  • Upload date:
  • Size: 344.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.13

File hashes

Hashes for juniper_data-0.10.0-py3-none-any.whl
Algorithm Hash digest
SHA256 0003245e62e0ff8a111dc9087fe74ec732e82de7f36b277b6a32d3b0dcd75ff7
MD5 0b07720031705ed7212f2d8c982814bf
BLAKE2b-256 14bd9d0d70a718b5bf90e6df49f669ba462d6705a1873cd39fdcd440b1d087e1

See more details on using hashes here.

Provenance

The following attestation bundles were made for juniper_data-0.10.0-py3-none-any.whl:

Publisher: publish.yml on pcalnon/juniper-data

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page