Generation'

Introduction'

The generate module provides a way of generating metadata files that follow the FAIR guidelines adopted by the AI-READI project.

Warning

The generate module is still under development.

Note

The generate module of this package uses the validate module internally to verify that the input data follows the required schema.

Methods'

The following methods are available in the generate module. Each method is described in detail below.

Generate Dataset Description'

You can call the generate_dataset_description method to generate a dataset_description file.

Parameters'

data'

Provide the data required for your dataset_description file in this paramater.

Type	Default value	Required	Accepted values
Object	{}	yes	Data object following the required schemas

More information about the required data can be found in the dataset_description schema.

file_path'

Provide the path to the file where you want to save the generated dataset_description file.

Type	Default value	Required	Accepted values
String	None	yes	Any string

file_type'

Provide the file type of the file where you want to save the generated dataset_description file.

Type	Default value	Required	Accepted values
String	None	yes	`json`, `xml`, `xlsx`, `csv`

Returns'

Type	Description
String	Returns the path to the generated dataset_description file as a string.

How to use'

from pyfairdatatools import generate

data  = {
    "Title": "My Dataset",
    "Identifier": "10.5281/zenodo.1234567",
    "IdentifierType": "DOI"
}

output = generate.generate_dataset_description(data = data, file_path = "dataset_description.json", file_type = "json")

print(output)  # dataset_description.json

Generate Study Description'

You can call the generate_study_description method to generate a study_description file.

Parameters'

data'

Provide the data required for your study_description file in this paramater.

Type	Default value	Required	Accepted values
Object	{}	yes	Data object following the required schemas

More information about the required data can be found in the study_description schema.

file_path'

Provide the path to the file where you want to save the generated study_description file.

Type	Default value	Required	Accepted values
String	None	yes	Any string

file_type'

Provide the file type of the file where you want to save the generated study_description file.

Type	Default value	Required	Accepted values
String	None	yes	`json`, `xml`, `xlsx`, `csv`

Returns'

Type	Description
String	Returns the path to the generated study_description file as a string.

How to use'

from pyfairdatatools import generate

data  = {
    "Title": "My Dataset",
    "Identifier": "10.5281/zenodo.1234567",
    "IdentifierType": "DOI"
}

output = generate.generate_study_description(data = data, file_path = "study_description.json", file_type = "json")

print(output)  # study_description.json

Generate Readme'

You can call the generate_readme method to generate a readme file.

Parameters'

data'

Provide the data required for your readme file in this paramater.

Type	Default value	Required	Accepted values
Object	{}	yes	Data object following the required schemas

More information about the required data can be found in the readme schema.

file_path'

Provide the path to the file where you want to save the generated readme file.

Type	Default value	Required	Accepted values
String	None	yes	Any string

file_type'

Provide the file type of the file where you want to save the generated readme file.

Type	Default value	Required	Accepted values
String	None	yes	`md`, `txt`

Returns'

Type	Description
String	Returns the path to the generated readme file as a string.

How to use'

from pyfairdatatools import generate

data  = {
    "Title": "My Dataset",
    "Identifier": "10.5281/zenodo.1234567",
    "Version": "1.0.0",
}

output = generate.generate_readme(data = data, file_path = "readme.md", file_type = "md")

print(output)  # readme.md

Generate Changelog'

You can call the generate_changelog method to generate a changelog file.

Parameters'

data'

Provide the content of the changelog file in this paramater.

Type	Default value	Required	Accepted values
String	None	yes	Any string

file_path'

Provide the path to the file where you want to save the generated changelog file.

Type	Default value	Required	Accepted values
String	None	yes	Any string

file_type'

Provide the file type of the file where you want to save the generated changelog file.

Type	Default value	Required	Accepted values
String	None	yes	`md`, `txt`

Returns'

Type	Description
String	Returns the path to the generated changelog file as a string.

How to use'

from pyfairdatatools import generate

data  = """
# Changelog

## 1.0.0

- Initial release
"""

output = generate.generate_changelog(data = data, file_path = "changelog.md", file_type = "md")

print(output)  # changelog.md

Generate License'

You can call the generate_license method to generate a license file.

Parameters'

identifier'

Provide the identifier of the license you want to use in this paramater.

Type	Default value	Required	Accepted values
String	""	yes	SPDX license identifier

For a list of all SPDX license identifiers, see here.

Warning

If you provide an invalid identifier, the method will raise an error. If you want to use a custom license, use the data parameter instead and provide the content of the license file. Leave this parameter empty if you are using custom license text.

data'

Provide the content of the license file in this paramater.

Type	Default value	Required	Accepted values
String	None	yes	Any string

Warning

Use this parameter if you want to use a custom license. Leave this parameter empty if you are using a SPDX license identifier. If you provide a SPDX license identifier, the method will prioritize this parameter over the identifier parameter.

file_path'

Provide the path to the file where you want to save the generated license file.

Type	Default value	Required	Accepted values
String	None	yes	Any string

file_type'

Provide the file type of the file where you want to save the generated license file.

Type	Default value	Required	Accepted values
String	None	yes	`md`, `txt`

Returns'

Type	Description
String	Returns the path to the generated license file as a string.

How to use'

from pyfairdatatools import generate

data  = """
MIT License

SPDX short identifier: MIT

Further resources on the MIT License

- [Text](https://spdx.org/licenses/MIT.html)
- [JSON](https://spdx.org/licenses/MIT.json)
- [RDF](https://spdx.org/licenses/MIT.rdf)
- [HTML](https://spdx.org/licenses/MIT.html)
"""

output = generate.generate_license(identifier = "MIT", data = data, file_path = "LICENSE.md", file_type = "md")

print(output)  # LICENSE.md

To create a license file using a SPDX license identifier:

from pyfairdatatools import generate

identifier = "MIT"

output = generate.generate_license(identifier = identifier, file_path = "LICENSE.md", file_type = "md")

print(output)  # LICENSE.md