| Name | fsl-pipe JSON |
| Version |
1.2.1
JSON |
| download |
| home_page | None |
| Summary | Declarative pipelines based on Filetrees |
| upload_time | 2025-01-22 11:31:19 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.10 |
| license | MIT License Copyright (c) 2022 Michiel Cottaar, University of Oxford Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
neuroimage
pipeline
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
[](https://open.win.ox.ac.uk/pages/fsl/fsl-pipe)
[](https://open.win.ox.ac.uk/pages/fsl/file-tree)
[](https://doi.org/10.5281/zenodo.6577069)
[](https://git.fmrib.ox.ac.uk/fsl/fsl-pipe/-/pipelines/latest)
[](https://open.win.ox.ac.uk/pages/fsl/fsl-pipe/htmlcov)
Declarative pipelines based on Filetrees. A pipeline is defined by:
- A file-tree, which defines the directory structure of the inputs and outputs of the pipeline. A tutorial on these file-trees is available [here](https://open.win.ox.ac.uk/pages/fsl/file-tree).
- A set of recipes describing how all the pipeline outputs are produced. A tutorial on writing these recipes is available [here](https://open.win.ox.ac.uk/pages/fsl/fsl-pipe).
Fsl-pipe will stitch these recipes together to produce any user-selected output files.
Resulting jobs will either run locally, run distributed using [dask](https://www.dask.org), or be submitted to a cluster using [fsl-sub](https://git.fmrib.ox.ac.uk/fsl/fsl_sub).
An example diffusion MRI pipeline using fsl-pipe with detailed comments is available [here](https://git.fmrib.ox.ac.uk/ndcn0236/fsl-pipe-example).
# Installation
```shell
pip install fsl-pipe
```
Any bug reports and feature requests are very welcome (see [issue tracker](https://git.fmrib.ox.ac.uk/fsl/fsl-pipe/-/issues)).
# Setting up local test environment
This package uses [uv](https://docs.astral.sh/uv/) for project management.
You will need to install uv to develop this package.
First clone the repository:
```shell
git clone https://git.fmrib.ox.ac.uk/fsl/fsl-pipe.git
```
Then we can ask uv to set up the local envoriment.
```shell
cd fsl-pipe
uv sync
```
## Running tests
Tests are run using the [pytest](https://docs.pytest.org) framework.
This will already be available in the `uv` virtual environment.
```shell
uv run pytest src/tests
```
## Compiling documentation
The documentation is build using [sphinx](https://www.sphinx-doc.org/en/master/).
```shell
cd doc
uv run sphinx-build source build
open build/index.html
```
## Contributing
[Merge requests](https://git.fmrib.ox.ac.uk/fsl/fsl-pipe/-/merge_requests) with any bug fixes or documentation updates are always welcome.
For new features, please raise an [issue](https://git.fmrib.ox.ac.uk/fsl/fsl-pipe/-/issues) to allow for discussion before you spend the time implementing them.
## Releasing new versions
- Ensure CHANGELOG.md is up to date.
- Edit the version number on `pyproject.toml`
- Create a new tag for the version number
- Push to gitlab (including tags).
- The pipeline from the tag will automatically publish fsl-pipe to [pypi](https://pypi.org/project/fsl-pipe/).
- Upload code on conda-forge using their automated release detection.
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