Skip to main content

DataLad-OSF: Opening up the Open Science Framework for DataLad

All Contributors

GitHub release PyPI version fury.io Build status codecov.io docs Documentation Status DOI

Welcome! This repository contains a DataLad extension that enables DataLad to work with the Open Science Framework (OSF). Use it to share, retrieve and collaborate on DataLad datasets via the OSF.

The development of this tool started at OHBM Brainhack 2020 in June 2020, coordinated in this repository. See our documentation for more extensive information.

Requirements

Installation

# create and enter a new virtual environment (optional)
$ virtualenv --python=python3 ~/env/dl-osf
$ . ~/env/dl-osf/bin/activate
# install from PyPi
$ pip install datalad-osf

How to use

See our documentation for more info on how to use this tool and a tutorial on major use cases.

How to contribute

You are very welcome to help out developing this tool further. You can contribute by:

  • Creating an issue for bugs or tips for further development
  • Making a pull request for any changes suggested by yourself
  • Testing out the software and communicating your feedback to us

Please see our contributing guidelines for more information.

Contributors ✨

Thanks goes to these wonderful people (emoji key):


Michael Hanke

🚧 💻 🐛 🤔

Dorien Huijser

📖 📆 🤔 📓

Ashish Sahoo

📖 🚧

Simon Steinkamp

⚠️ 📖 📆 🤔 📓 🚧

Benjamin Poldrack

📆 🤔 💻 🚧

Nick

📆 🤔 💻 🚧

Nikita Beliy

🤔 📓

Moritz J. Boos

💻 📓 🤔 🚧

Adina Wagner

📆 🤔 💻 📖 🚧

Stefan Appelhoff

📖 📓

Tom Hu

🚇

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

Acknowledgements

This DataLad extension was developed with support from the German Federal Ministry of Education and Research (BMBF 01GQ1905), and the US National Science Foundation (NSF 1912266).

Metadata

Release files for datalad-osf 0.3.0

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-osf 0.3.0
File Size Uploaded
datalad_osf-0.3.0.tar.gz 41.6 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for datalad-osf 0.3.0
File Interpreter ABI Platform
datalad_osf-0.3.0-py2.py3-none-any.whl Python 2, Python 3 none any Details

Total release size: 67.9 kB

Release files / datalad_osf-0.3.0.tar.gz

Download URL datalad_osf-0.3.0.tar.gz
Size 41.6 kB
Tags Source
SHA-256 checksum
How to use checksums
ce2690a2db78661a3ee5d1f6de30df608ba40f9a35158a436de358c443c0605c
BLAKE2b-256 checksum
How to use checksums
e3b3d31c80c7e845ffaaf34c207482e95bec0258a097f4836f974bc075d526fd
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.11.2

Release files / datalad_osf-0.3.0-py2.py3-none-any.whl

Download URL datalad_osf-0.3.0-py2.py3-none-any.whl
Size 26.4 kB
Tags Python 2 Python 3
SHA-256 checksum
How to use checksums
2cdc42ac3015d0734ac1f386a2f09fe2bfd2bad56e2035ebcce87a378b0ec209
BLAKE2b-256 checksum
How to use checksums
53eee97f37023938022e38d3abb28058191025c7a2cb240210e7e016f21fee72
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.11.2

Release history Release notifications | RSS feed

This release

0.3.0 This release

2 release files

0.2.3

2 release files

0.2.2

2 release files

0.2.1

2 release files

0.2.0

2 release files

0.1.0

2 release files

0.0.1

2 release files

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