Generation

Introduction

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

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.

Generate Study Description from Clinical Trial integration

You can call the generate_study_description_from_clinical_trials method to generate an initial 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.

data

Provide the content of the license 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 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