Skip to main content

DataLad extension tracking data in an XNAT server

All Contributors

GitHub release PyPI version fury.io Build status codecov.io crippled-filesystems Documentation Status DOI

This software is a DataLad extension that equips DataLad with a set of commands to track XNAT projects.

XNAT is an open source imaging informatics platform developed by the Neuroinformatics Research Group at Washington University. It facilitates common management, productivity, and quality assurance tasks for imaging and associated data. XNAT can be used to support a wide range of neuro/medical imaging-based projects.

Command(s) provided by this extension

  • xnat-init -- Initialize an existing dataset to track an XNAT project
  • xnat-update -- Update an existing dataset of an XNAT project; retrieve data from the tracked project
  • xnat-query-files -- Query available files on an XNAT instance or project

Installation

Before you install this package, please make sure that you install a recent version of git-annex. Afterwards, install the latest version of datalad-xnat from PyPi. It is recommended to use a dedicated virtualenv:

# create and enter a new virtual environment (optional)
virtualenv --system-site-packages --python=python3 ~/env/datalad
. ~/env/datalad/bin/activate

# install from PyPi
pip install datalad_xnat

Support

For general information on how to use or contribute to DataLad (and this extension), please see the DataLad website or the main GitHub project page.

All bugs, concerns and enhancement requests for this software can be submitted here: https://github.com/datalad/datalad-xnat/issues

If you have a problem or would like to ask a question about how to use DataLad, please submit a question to NeuroStars.org with a datalad tag. NeuroStars.org is a platform similar to StackOverflow but dedicated to neuroinformatics.

All previous DataLad questions are available here: http://neurostars.org/tags/datalad/

Acknowledgements

This development was supported by European Union’s Horizon 2020 research and innovation programme under grant agreement VirtualBrainCloud (H2020-EU.3.1.5.3, grant no. 826421).

Contributors ✨

Thanks goes to these wonderful people (emoji key):

Michael Hanke
Michael Hanke

💻 🐛 📖 🤔 🚧
Laura Waite
Laura Waite

💻 🐛 🤔 🚧
Adina Wagner
Adina Wagner

💻 🐛 📖 🤔 🚧
John T. Wodder II
John T. Wodder II

💻 🤔 🚧
Yaroslav Halchenko
Yaroslav Halchenko

💻
Janvi Raina
Janvi Raina

📖
Stephan Heunis
Stephan Heunis

🚇 🎨 🧑‍🏫
tsankeuodelfa
tsankeuodelfa

📖
Michał Szczepanik
Michał Szczepanik

📖 💻
Benjamin Poldrack
Benjamin Poldrack

💻
Alex Waite
Alex Waite

💬 📖 ✅
oportoles
oportoles

📓 📖 🐛 ✅

This project follows the all-contributors specification. Contributions of any kind welcome!

Metadata

Release files for datalad-xnat 0.2.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for datalad-xnat 0.2.1
File Size Uploaded Provenance Actions
datalad_xnat-0.2.1.tar.gz 225.3 kB Without provenance Details for datalad_xnat-0.2.1.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for datalad-xnat 0.2.1
File Interpreter ABI Platform Actions
datalad_xnat-0.2.1-py3-none-any.whl Python 3 none any Details for datalad_xnat-0.2.1-py3-none-any.whl

Total release size: 250.1 kB

Release files / datalad_xnat-0.2.1.tar.gz

Download URL datalad_xnat-0.2.1.tar.gz
Size 225.3 kB
Tags Source
SHA-256 checksum
How to use checksums
9260e44054a5e71e24990cdbf4a27c70708e80a68d26d7567995be0a208a67c5
BLAKE2b-256 checksum
How to use checksums
7b52db8f113adb7ff631bba4ad85d2bfed0c91a42064c5b5cbd4e310f83ff107
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.11.2

Release files / datalad_xnat-0.2.1-py3-none-any.whl

Download URL datalad_xnat-0.2.1-py3-none-any.whl
Size 24.8 kB
Tags Python 3
SHA-256 checksum
How to use checksums
d1b652a8b8b40c04f69dd8847b25d898c21726629dd9267abb8745209ef8c7e3
BLAKE2b-256 checksum
How to use checksums
523e08cd07311f442f2d25339729d22779e4ca209b9ad72e28202dfab3fdf01d
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.11.2

Security for datalad-xnat 0.2.1

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.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page