Metadata-Version: 2.1
Name: fairly
Version: 0.2.3
Summary: A package to create, publish, and download research datasets
Author-email: Serkan Girgin <s.girgin@utwente.nl>, Manuel Garcia Alvarez <m.g.garciaalvarez@tudelft.nl>, Jose Urra Llanusa <j.c.urrallanusa@tudelft.nl>
License: MIT License
        
        Copyright (c) 2022 JupyterFAIR Team
        
        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.
        
Project-URL: Homepage, https://github.com/ITC-CRIB/fairly
Project-URL: Bug Tracker, https://github.com/ITC-CRIB/fairly/issues
Project-URL: Documentation, https://jupyterfair.readthedocs.io/en/latest/
Project-URL: Funding, https://nwo.nl/en/researchprogrammes/open-science/open-science-fund
Keywords: fairly,open science,research data,data management
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: python-dateutil
Requires-Dist: requests
Requires-Dist: requests-toolbelt
Requires-Dist: ruamel.yaml
Requires-Dist: typer (>=0.6.1)
Requires-Dist: rich
Provides-Extra: dev
Requires-Dist: pytest ; extra == 'dev'
Requires-Dist: pytest-cov ; extra == 'dev'
Requires-Dist: pytest-recording ; extra == 'dev'
Requires-Dist: python-dotenv ; extra == 'dev'
Requires-Dist: vcrpy ; extra == 'dev'

# fairly
A package to create, publish and clone research datasets.

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)


## Installation

*fairly* requires Python 3.8 or later, and it can be installed directly using PIP.

```shell
pip install fairly
```

### Installing from source

1. Clone or download the [source code](https://github.com/ITC-CRIB/fairly):

    ```shell
    git clone https://github.com/ITC-CRIB/fairly.git
    ```

2. Go to the root directory:

    ```shell
    cd fairly/
    ```

3. Compile and install using PIP:

    ```shell
    pip install .
    ```

## Usage

Basic example to create a local research dataset and deposit it to a repository:

```python
import fairly

# Initialize a local dataset
dataset = fairly.init_dataset('/path/dataset')

# Set metadata
dataset.metadata['license'] = 'MIT'
dataset.set_metadata(
	title='My dataset',
	keywords=['FAIR', 'research', 'data'],
	authors=[
		'0000-0002-0156-185X',
		{'name': 'John', 'surname': 'Doe'}
	]
)

# Add data files
dataset.includes.extend([
	'README.txt',
	'*.csv',
	'train/*.jpg'
])

# Save dataset
dataset.save()

# Upload to a data repository
remote_dataset = dataset.upload('zenodo')
```

Basic example to access a remote dataset and store it locally:

```python
import fairly

# Open a remote dataset
dataset = fairly.dataset('doi:10.4121/21588096.v1')

# Get dataset information
dataset.id
>>> {'id': '21588096', 'version': '1'}

dataset.url
>>> 'https://data.4tu.nl/articles/dataset/.../21588096/1'

dataset.size
>>> 33339

len(dataset.files)
>>> 6

dataset.metadata
>>> Metadata({'keywords': ['Earthquakes', 'precursor', ...], ...})

# Update metadata
dataset.metadata['keywords'] = ['Landslides', 'precursor']
dataset.save()

# Store dataset to a local directory (i.e. clone dataset)
local_dataset = dataset.store('/path/dataset')
```

Currently, the package supports the following research data management platforms:

- [Zenodo](https://zenodo.org/)
- [Figshare](https://figshare.com/)
- [Djehuty](https://github.com/4TUResearchData/djehuty/)

All research data repositories based on the listed platforms are supported.

For more details and examples, consult the [package documentation](https://jupyterfair.readthedocs.io/en/latest/package/installation.html).


## Testing

Unit tests can be run by using `pytest` command in the root directory.


## Contributions

Read the [guidelines](CONTRIBUTING.md) to know how you can be part of this open source project.

## JupyterLab Extension

An extension for JupyerLab is being developed in a [different repository.](https://github.com/ITC-CRIB/JupyterFAIR)

## Citation

Please cite this software using as follows:

*Girgin, S., Garcia Alvarez, M., & Urra Llanusa, J., fairly: a package to create, publish and clone research datasets [Computer software]*


## Acknowledgements

This research is funded by the [Dutch Research Council (NWO) Open Science Fund](https://www.nwo.nl/en/researchprogrammes/open-science/open-science-fund/), File No. 203.001.114.

Project members:

- [Center of Expertise in Big Geodata Science, University of Twente, Faculty ITC](https://itc.nl/big-geodata/)
- [Digital Competence Centre, TU Delft](https://dcc.tudelft.nl/)
- [4TU.ResearchData](https://data.4tu.nl/)
