---
id: silx
version: "3.1.0"
license: Format: http://www.debian.org/doc/packaging-manuals/copyright-format/1.0/ Upstream-Name: silx Source: https://github.com/silx-kit/silx Files: * Copyright: 2004-2023 European Synchrotron Radiation… (full text in the JSON record)
license_treatment: permissive
maintenance: active
---

# silx — Silx tool-kit: collection of Python packages to support the development of data assessment, reduction and analysis applications at synchrotron radiation facilities

License: permissive · Maintenance: active · Downloads: 84.3K/mo

## What it is and 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.

The 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.

Use it for:

- 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.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

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.

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.

## Install

pip install silx
uv add silx
poetry add silx

## Installing silx

Before you install: Medium install friction due to compiled extensions (Cython) and multiple platform wheels. Active maintenance with a recent release (4 days old) and ongoing repository activity. Requires Python 3.10 or later.

License in practice: MIT-licensed core with permissive treatment. Some components use BSD-3 and CC0 (colormaps); all are compatible with commercial and proprietary use without restriction.

Quickstart:

pip install silx
import silx.io
data = silx.io.open('file.h5')

Requires Python 3.10+; compiled extensions may require a C compiler or pre-built wheels for your platform.

Verify before relying:

- Whether Qt widgets require a display server or can run headless in production environments.
- Performance characteristics for large HDF5 files or streaming data scenarios.
- OpenCL acceleration availability and fallback behavior on systems without OpenCL support.

## Package facts

- License: Format: http://www.debian.org/doc/packaging-manuals/copyright-format/1.0/ Upstream-Name: silx Source: https://github.com/silx-kit/silx Files: * Copyright: 2004-2023 European Synchrotron Radiation… (full text in the JSON record) (permissive)
- Python support: supports_current
- Install friction: medium
- Maintenance: active
- Downloads: 84.3K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

HDF5 data visualization, synchrotron data analysis, scientific data reduction, Qt data browser, image file format reader, tomography reconstruction, spectroscopy data tools, synchrotron-data, hdf5-io, scientific-visualization

[View on SkillFed](https://skillfed.io/packages/silx) · [View on PyPI](https://pypi.org/project/silx/)