Learn how to interact with this file using the Ouro SDK or REST API.
API access requires an API key. Create one in Settings → API Keys, then set OURO_API_KEY in your environment.
Get file metadata including name, visibility, description, file size, and other asset properties.
import os
from ouro import Ouro
# Set OURO_API_KEY in your environment or replace os.environ.get("OURO_API_KEY")
ouro = Ouro(api_key=os.environ.get("OURO_API_KEY"))
file_id = "794239ce-9e87-4de4-96e0-12f4460008ba"
# Retrieve file metadata
file = ouro.files.retrieve(file_id)
print(file.name, file.visibility)
print(file.metadata)Get a URL to download or embed the file. For private assets, the URL is temporary and will expire after 1 hour.
# Get signed URL to download the file
file_data = file.read_data()
print(file_data.url)
# Download the file using requests
import requests
response = requests.get(file_data.url)
with open('downloaded_file', 'wb') as output_file:
output_file.write(response.content)Update file metadata (name, description, visibility, etc.) and optionally replace the file data with a new file. Requires write or admin permission.
# Update file metadata
updated = ouro.files.update(
id=file_id,
name="Updated file name",
description="Updated description",
visibility="private"
)
# Update file data with a new file
updated = ouro.files.update(
id=file_id,
file_path="./new_file.txt"
)Permanently delete a file from the platform. Requires admin permission. This action cannot be undone.
# Delete a file (requires admin permission)
ouro.files.delete(id=file_id)~1900 materials collected from NovoMag and Novamag datasets, cleaned CSV with CIF file and MAE value.
ZIP file includes:
folder of CIFs
a CSV file mapping CIF file names to:
chemical_formula
cif_file (file name to be matched with cifs/ folder)
source (novomag, novamag)
magnetic_anisotropy_energy
There are only 1900 materials here is because NovoMag doesn't all include MAE predictions for all ~3800 materials.
Like our work on Curie temperature, the effort here is to build a machine learning model that can take a crystal structure and predict its magnetocrystalline anisotropy energy. Relevant for permanent