NiReports: the NiPreps’ reporting and visualization tools
NiReports contains the two main components of the visual reporting system of NiPreps:
Reportlets: visualizations for assessing the quality of a particular processing step within the neuroimaging pipeline. Typically, reportlets show brain mosaics perhaps with contours and/or segmentations. They can be dynamic and flicker between two different states to help assess the accuracy of image registrations. However, the reportlets are not limited to brain mosaics, and can contain correlation plots, BOLD fMRI carpetplots, etc.
Assembler: end-user NiPreps write out reportlets to a predetermined folder, which is then queried by the assembler using PyBIDS. The assembler follows a report specification in YAML format, which states the query to find specific reportlets and their corresponding metadata and text annotations. As a result, one HTML file with a concatenation of reportlets is produced.
Release files for nireports 26.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| nireports-26.0.0.tar.gz | 77.4 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| nireports-26.0.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 77.6 MB
Release files / nireports-26.0.0.tar.gz
| Download URL | nireports-26.0.0.tar.gz |
|---|---|
| Size | 77.4 MB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
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Transparency logRelease files / nireports-26.0.0-py3-none-any.whl
| Download URL | nireports-26.0.0-py3-none-any.whl |
|---|---|
| Size | 144.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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|
BLAKE2b-256 checksum How to use checksums |
3d0a8b826188ba64e9379a1d18b5df85d8b24ae4c6e4beaf59bd6a46ceef2840
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
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 Sep 2, 2026.
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