Search the Catalogue#

Use atomscale.client.Client.search() to locate uploaded data. The examples below mirror general_use.ipynb and add a few extra filters you can combine.

Basic search#

from atomscale.client import Client

client = Client(api_key="YOUR_API_KEY")

rheed_runs = client.search(keywords=["WSe2"])
print(rheed_runs[["Data ID", "Status", "Sample Name"]])

Tip

Keywords are matched against sample names, file names, and metadata fields. Use specific terms for more precise results.

Limit to your uploads#

personal_only = client.search(
    keywords="demo",
    include_organization_data=False,
)

Filter by IDs or type#

exact = client.search(data_ids=["44fa63b0-74da-4d25-a362-2276c80a670a"])

rotating = client.search(data_type="rheed_rotating")

Available data types#
Type	Description
`rheed_stationary`	Stationary RHEED video
`rheed_rotating`	Rotating RHEED video
`rheed_image`	Single RHEED image
`xps`	XPS spectrum data

Filter by lifecycle state#

status accepts "success", "pending", "running", "error", and the streaming-specific values "stream_active", "stream_interrupted", "stream_finalizing", and "stream_error".

completed = client.search(status="success")

Note

Use status="stream_active" to find live streaming sessions that are currently receiving data.

Apply numeric or datetime bounds#

You can pass (min, max) tuples for growth length (seconds), upload timestamp, or last-accessed timestamp. Use None for an open bound.

from datetime import datetime

recent = client.search(
    upload_datetime=(datetime(2025, 1, 1), None),
    growth_length=(3000, None),
)

Tip

Combine multiple filters in a single call for precise queries:

results = client.search(
    keywords="GaN",
    data_type="rheed_stationary",
    status="success",
    growth_length=(1000, 5000),
)

Next steps#

Pass the Data ID column to atomscale.client.Client.get() to fetch analysis artefacts.