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Generate json-ld format file based on FAIRification standard

Project description

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Fairmaterials

Fairmaterials is a tool for fairing data. It reads a template JSON file to get the preset data. The user can edit the data by manually inputting or by importing a csv file. The final output will be a new JSON file with the same structure.

Features

  • Importing JSON template as JSON-LD.
  • Display fair data in dataframe format.
  • Automatically notify duplicate names.
  • Modify JSON data.
    • Based on CSV file.
    • Based on keyboard input.
  • Output as standard JSON-LD.

Setup

  1. Install it at bash
$ pip install fairmaterials
  1. Import it in python
from fairmaterials.fairify import *

A quick example

Select a domain

fairify_data("XRD")

Output will be series of json-ld format file

Versions

All notable changes to this project will be documented in this file.

[0.1.0] - 2022-12-10

Added

  • Add fairy_data function,user can select domains to fairy data

Domains

  • XRD
  • CapillaryElectrophoresis
  • PolymerAM
  • PVModule
  • PolymerBacksheets
  • OpticalSpectroscopy
  • Buildings
  • GeospatialWell
  • MetalAM
  • OpticalProfilometry
  • PVSystem
  • XCT

[0.0.213] - 2022-10-8

Added

  • Add template csv file.

[0.0.212] - 2021-10-7

Added

  • Add group input CSV file generation function.
  • Add directly convert a group input CSV file to multiple json file function.
  • Add Version part in Readme.md file.

Funding Acknowledgements:

This work was supported by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) under Solar Energy Technologies Office (SETO) Agreement Numbers DE-EE0009353 and DE-EE0009347, Department of Energy (National Nuclear Security Administration) under Award Number DE-NA0004104 and Contract number B647887, and U.S. National Science Foundation Award under Award Number 2133576.

Download files

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Source Distribution

fairmaterials-0.1.1.tar.gz (4.9 kB view hashes)

Uploaded Source

Built Distribution

fairmaterials-0.1.1-py3-none-any.whl (8.6 kB view hashes)

Uploaded Python 3

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