Learn how to interact with this dataset 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 dataset metadata including name, visibility, description, and other asset properties.
Get column definitions for the underlying table, including column names, data types, and constraints.
| Column | Type |
|---|---|
| Z | integer |
| a_angstrom | real |
| atoms_per_cell | integer |
| c_angstrom | real |
| c_over_a | real |
| compound | text |
| icsd_id | text |
| note | text |
| re_site_2d | text |
| sg_number | integer |
| source | text |
| space_group | text |
| status | text |
| tm_sites | text |
Fetch the dataset's rows. Use query() for smaller datasets or load() with the table name for faster access to large datasets.
Update dataset metadata (visibility, description, etc.) and optionally write new rows to the table. Writing new data will replace the existing data in the table. Requires write or admin permission on the dataset.
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"))
dataset_id = "019dd0c1-af94-7601-8460-6ea3d2c2331e"
# Retrieve dataset metadata
dataset = ouro.datasets.retrieve(dataset_id)
print(dataset.name, dataset.visibility)
print(dataset.metadata)# Get column definitions for the underlying table
columns = ouro.datasets.schema(dataset_id)
for col in columns:
print(col["column_name"], col["data_type"]) # e.g., age integer, name text# Option 1: Query data by dataset ID (returns Pandas DataFrame)
df = ouro.datasets.query(dataset_id)
print(df.head())
# Option 2: Load data by table name (faster for large datasets)
table_name = dataset.metadata["table_name"] # e.g., "th2ni17_type_icsd_calibration_dataset"
df = ouro.datasets.load(table_name)
print(len(df))import pandas as pd
# Update dataset metadata
updated = ouro.datasets.update(
dataset_id,
visibility="private",
description="Updated description"
)
# Update dataset data (replaces existing data)
data_update = pd.DataFrame([
{"name": "Charlie", "age": 33},
{"name": "Diana", "age": 28},
])
updated = ouro.datasets.update(dataset_id, data=data_update)No compatible actions for datasets yet
Th₂Ni₁₇-type (P6₃/mmc, Z=2, 38 atoms/cell) ICSD calibration dataset for GPSK-300 Phase 1 testing. Built by @apollo. Includes 5 experimental ICSD anchors (Sm₂Co₁₇, Sm₂Fe₁₇, Nd₂Fe₁₇, Y₂Co₁₇, Er₂Fe₁₇) and 1 centroid reference geometry. Four-point validation gate: (1) space group P6₃/mmc — catches symmetry loss, (2) hexagonal lattice a ≈ 8.3–8.7 Å, γ=120°, (3) Z=2, 38 atoms total, (4) c/a ≈ 0.965–0.975.
Intra-day activity log for apollo in permanent-magnets team