silx
Silx tool-kit: collection of Python packages to support the development of data assessment, reduction and analysis applications at synchrotron radiation facilities
Decision gist · record as of 2026-08-14
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.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10+; compiled extensions may require a C compiler or pre-built wheels for your platform.
- 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.
License · maintenance · safety
permissive license (permissive) — MIT-licensed core with permissive treatment. Some components use BSD-3 and CC0 (colormaps); all are compatible with commercial and proprietary use without restriction.
last release 2026-08-10 (4 days) · last repo commit 2026-08-12 · 166 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 84,303 downloads/mo, #14,009 on PyPI
Alternatives
Verify before relying
pip install silx
import silx.io
data = silx.io.open('file.h5')- 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.
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 on this page. Verify before relying on it.
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
silx on PyPI
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.
Requires Python 3.10+; compiled extensions may require a C compiler or pre-built wheels for your platform.
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')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 | permissive license permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | 6 packagesnumpypackagingh5pyfabiopydanticfilelock |
| Maintenance | Actively maintained 4 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 84,303 / month, #14,009 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableEnvironment :: ConsoleEnvironment :: MacOS XEnvironment :: Win32 (MS Windows)Environment :: X11 Applications :: QtIntended Audience :: EducationIntended Audience :: Science/ResearchLicense :: OSI Approved :: MIT LicenseNatural Language :: EnglishOperating System :: MacOSOperating System :: Microsoft :: WindowsOperating System :: POSIXProgramming Language :: CythonProgramming Language :: Python :: 3Programming Language :: Python :: Implementation :: CPythonTopic :: Scientific/Engineering :: PhysicsTopic :: Software Development :: Libraries :: Python Modules |
Evidence: silx-3.1.0-cp310-cp310-macosx_10_9_x86_64.whl; silx-3.1.0-cp310-cp310-macosx_11_0_arm64.whl; silx-3.1.0-cp310-cp310-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl; silx-3.1.0-cp310-cp310-manylinux_2_24_ppc64le.manylinux_2_28_ppc64le.whl; silx-3.1.0-cp310-cp310-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl; silx-3.1.0-cp310-cp310-win_amd64.whl; silx-3.1.0-cp311-cp311-macosx_10_9_x86_64.whl; silx-3.1.0-cp311-cp311-macosx_11_0_arm64.whl; silx-3.1.0-cp311-cp311-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl; silx-3.1.0-cp311-cp311-manylinux_2_24_ppc64le.manylinux_2_28_ppc64le.whl; silx-3.1.0-cp311-cp311-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl; silx-3.1.0-cp311-cp311-win_amd64.whl; silx-3.1.0-cp311-cp311-win_arm64.whl; silx-3.1.0-cp312-cp312-macosx_10_13_x86_64.whl; silx-3.1.0-cp312-cp312-macosx_11_0_arm64.whl; silx-3.1.0-cp312-cp312-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl; silx-3.1.0-cp312-cp312-manylinux_2_24_ppc64le.manylinux_2_28_ppc64le.whl; silx-3.1.0-cp312-cp312-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl; silx-3.1.0-cp312-cp312-win_amd64.whl; silx-3.1.0-cp312-cp312-win_arm64.whl
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