NCAS-CMS / pyfive
A pure Python HDF5 file reader
AI Architecture Analysis
This repository is indexed by RepoMind. By analyzing NCAS-CMS/pyfive in our AI interface, you can instantly generate complete architecture diagrams, visualize control flows, and perform automated security audits across the entire codebase.
Our Agentic Context Augmented Generation (Agentic CAG) engine loads full source files into context on-demand, avoiding the fragmentation of traditional RAG systems. Ask questions about the architecture, dependencies, or specific features to see it in action.
Embed this Badge
Showcase RepoMind's analysis directly in your repository's README.
Repository Overview (README excerpt)
Crawler viewLatest doc builds on RTD pyfive : A pure Python HDF5 file reader ======================================= pyfive is an open source library for reading HDF5 files written using pure Python (no C extensions). The package is still in development and not all features of HDF5 files are supported. pyfive aims to support the same API as for reading files. Cases where a file uses a feature that is supported by h5py but not pyfive are considered bugs and should be reported in our Issues. Writing HDF5 output is not a goal of pyfive and portions of the API which apply only to writing will not be implemented. Dependencies ============ pyfive is tested against Python versions 3.10 to 3.14. It may also work with other Python versions. The only dependencies to run the software besides Python is numpy . Install ======= pyfive can be installed using pip using the command:: pip install pyfive conda packages are also available from conda-forge:: conda install -c conda-forge pyfive To install from source in your home directory use:: pip install --user ./pyfive The library can also be imported directly from the source directory. Development =========== git --- You can check out the latest pyfive souces with the command:: git clone https://github.com/NCAS-CMS/pyfive.git testing ------- pyfive comes with a test suite in the tests directory. These tests can be exercised using the pytest command from the root directory (requires installation of the pytest package). Conda-forge feedstock ===================== Package repository conda-forge feedstock Codecov ======= Test coverage assessement is done using codecov Documentation ============= Build locally with Sphinx: $ sphinx-build -Ea doc doc/build