A DataLad extension that simplifies access to PublicnEUro datasets
Project description
DataLad PublicnEUro extension
This repository contains a datalad extension that simplifies data download from PublicnEUro collections.
Installation
Install the extension via pip (a virtual environment is recommended):
> pip install datalad-publicneuro
Usage
The extension provides the new git annex special remote uncurl-publicneuro. To use it, activate the special remote in your DataLad dataset:
git annex initremote uncurl-publicneuro type=external externaltype=uncurl-publicneuro encryption=none
The uncurl-publicneuro special remote handles URLs with the following structure (where <dataset-id> is the PublicnEUro ID of the dataset, e.g., PN000001, and path is the absolute path of a file within the dataset, e.g., /README.txt):
publicneuro+https://<dataset-id><path>
The following command adds a reference to a file in a PublicnEUro dataset and downloads the file content (here the file /README.txt of dataset PN000001 is added with the local name README.txt):
> git annex addurl --file README.txt publicneuro+https://PN000001/README.txt
The command will prompt for credentials if no credentials are available yet.
After successful authentication, the file will be downloaded and added to the annex.
Valid credentials will be stored in DataLad's credential store and automatically used for subsequent addurl-commands.
Contributing
PRs are welcome! Please open an issue or a pull request if you find a bug or have a feature request.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file datalad_publicneuro-0.0.3-py3-none-any.whl.
File metadata
- Download URL: datalad_publicneuro-0.0.3-py3-none-any.whl
- Upload date:
- Size: 9.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: python-httpx/0.28.1
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
3503a5d36a974f5245cd4949dcedf38f471c10944ea48c1afcf92d0b16ff3eb3
|
|
| MD5 |
9b9d3f4920c1f7ea4fec557f83795e90
|
|
| BLAKE2b-256 |
da61e18bc11a5572cf81353c6cbce3cc756c1bf2dda0411eaebe988088b929cd
|