PSyclone is a source-to-source Fortran compiler designed to programmatically optimise, parallelise and instrument HPC applications via user-provided transformation scripts. By encapsulating the performance-portability aspects (e.g. whether to parallelise with OpenMP or OpenACC), these scripts enable a separation of concerns between the scientific implementation and the optimisation choices. This allows each aspect to be explored and developed largely independently. Additionally, PSyclone supports the development of kernel-based Fortran-embedded DSLs following the PSyKAl model developed in the GungHo project.
PSyclone is currently used to support the LFRic mixed finite-element PSyKAl DSL for the UK MetOffice's next generation modelling system and the GOcean finite-difference PSyKAl DSL for a prototype 2D ocean modelling system. It is also used to insert GPU offloading directives into existing directly-addressed MPI applications such as the NEMO ocean model.
For more detailed information see the PSyclone Documentation.
Installation
You can install the latest release of psyclone from PyPI by using:
$ pip install psyclone
or, if you want an isolated installation in a python virtual environment:
$ python -m venv <virtual_env_name>
$ source <virtual_env_name>/bin/activate
$ pip install psyclone
Alternatively, you can install the latest upstream version of psyclone by cloning this repository and using:
$ pip install .
or in developer (editable) mode using
$ pip install -e .
PSyclone is also available in the Conda and Spack package managers.
For more information about the installation process see the Getting Going. section of the User Guide.
Structure
| Path | Description |
|---|---|
| bin/ | Top-level driver scripts for PSyclone and the PSyclone kernel tool |
| changelog | Information on changes between releases |
| doc/ | Documentation source using Sphinx |
| examples/ | Simple examples |
| README.md | This file |
| src/psyclone | The Python source code |
| src/psyclone/tests/ | Unit and functional tests using pytest |
| tutorial/practicals | Hands-on exercises using a local installation of PSyclone |
Metadata
Release files for PSyclone 3.3.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| psyclone-3.3.1.tar.gz | 1.5 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| psyclone-3.3.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 4.0 MB
Release files / psyclone-3.3.1.tar.gz
| Download URL | psyclone-3.3.1.tar.gz |
|---|---|
| Size | 1.5 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.12
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Transparency logRelease files / psyclone-3.3.1-py3-none-any.whl
| Download URL | psyclone-3.3.1-py3-none-any.whl |
|---|---|
| Size | 2.5 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.12
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jul 7, 2026.
Transparency log