{"categories":[{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/21"},{"label":"Physics","url":"https://skillfed.io/packages/category/scientific-engineering-physics"}],"enrichment":{"capability":"silx provides Python tools for reading, processing, and visualizing scientific data from synchrotron facilities, with support for HDF5, SPEC, and image formats plus Qt-based visualization widgets.","skillfed_tags":["synchrotron-data","hdf5-io","scientific-visualization"],"use_cases":["Browse and inspect HDF5 datasets and SPEC files from beamline experiments using the unified viewer.","Convert experimental data from multiple formats into HDF5 for standardized archival and sharing.","Perform data reduction tasks like histogram binning, curve fitting, and median filtering on detector images.","Visualize 1D and 2D scientific data with interactive Qt widgets supporting zoom, pan, and multiple backends.","Reconstruct tomographic volumes from detector images using filtered backprojection.","Integrate data I/O and visualization into custom analysis applications via the Python API."],"what_it_does":"silx is a toolkit for scientists and engineers working with data from synchrotron radiation facilities. It provides file I/O for HDF5, SPEC, and image formats via fabio, data reduction routines (histogramming, fitting, filtering), and a set of Qt-based visualization widgets for 1D/2D plots and 3D scalar fields. The package includes command-line utilities for viewing and converting data to HDF5, making it useful both as a library for analysis pipelines and as a standalone data browser.\n\nThe toolkit depends on numpy, h5py, fabio, pydantic, packaging, and filelock. It includes Cython-accelerated code paths and optional OpenCL support for image processing tasks like SIFT alignment, median filtering, and tomographic reconstruction. Installation is straightforward on common platforms via pre-built wheels, though compilation may be needed on less common architectures.","worth_installing":"Yes. silx is actively maintained, MIT-licensed, and well-suited for scientists working with synchrotron data. Medium install friction is offset by broad platform support and pre-built wheels. No known vulnerabilities. Install with `pip install silx` for core functionality or `pip install silx[full]` for all optional dependencies."},"id":"silx","links":{"html":"https://skillfed.io/packages/silx","md":"https://skillfed.io/packages/silx.md","pypi":"https://pypi.org/project/silx/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-10","license_spdx":null,"license_treatment":"permissive","name":"silx","python_support":"supports_current","summary":"Silx tool-kit: collection of Python packages to support the development of data assessment, reduction and analysis applications at synchrotron radiation facilities"},"popularity":{"monthly_downloads":84303,"position":14009,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"3.1.0"}