h5grove

What it is and what it does

h5grove is a Python library for building backends that expose HDF5 file contents over the network. Rather than being a complete server, it provides reusable utilities that solve recurring problems in HDF5 serving: resolving external links, handling dataset compression and slicing, and encoding data consistently for JSON transport (including special handling for NaN and Infinity). It wraps h5py for file access and depends on numpy, orjson, tifffile, and typing-extensions.

The package is designed for developers building custom HDF5 backends, with optional integrations for FastAPI, Flask, and Tornado. You install the core package and add framework-specific extras only when needed. It's actively maintained, supports current Python versions (3.10+), and carries no known security vulnerabilities.

Use it for:

• Build a REST API to query and download slices of large HDF5 datasets stored on disk.
• Serve scientific instrument data (common in synchrotron facilities) to web clients without reimplementing link resolution and compression logic.
• Create a custom HDF5 viewer backend that handles external file references and encodes numeric data safely for JSON.
• Integrate HDF5 file access into an existing FastAPI or Flask application with minimal boilerplate.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

h5grove provides building blocks for serving HDF5 file contents—attributes, metadata, and data—via web backends, handling common problems like external link resolution, dataset compression/slicing, and JSON-safe data encoding.

Yes, if you are building a backend to serve HDF5 files and want to reuse battle-tested utilities for common problems (link resolution, compression, JSON encoding). No, if you only need to read HDF5 files in a local Python script—h5py alone is sufficient. Yes-with-conditions if you plan to use the web framework integrations: verify that the FastAPI/Flask/Tornado extras match your framework version and production readiness expectations.

Install

h5grove on PyPI

pip install h5grove

uv add h5grove

poetry add h5grove

Installing h5grove

Before you install

Low friction: pure-Python wheel with five stable runtime dependencies (h5py, numpy, orjson, tifffile, typing-extensions). Active maintenance with a release 122 days ago and commits through April 2026.

License in practice

MIT License (permissive): you can use, modify, and distribute h5grove freely in commercial and private projects, provided you include the original copyright notice and license text.

Quickstart

pip install h5grove

import h5grove
import h5py

with h5py.File('data.h5', 'r') as f:
    # Use h5grove utilities to access and serve HDF5 content
    pass

Requires Python 3.10 or later; h5py requires HDF5 libraries on the system.

Verify before relying

• Whether the package provides ready-to-use server implementations or only low-level utilities for custom backends.
• Performance characteristics when serving large HDF5 datasets or handling concurrent requests.
• Whether FastAPI, Flask, and Tornado integrations are production-ready or experimental.

Package facts

Evidence: h5grove-4.0.0-py3-none-any.whl

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