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GET
/
data_entries
from atomscale import Client

client = Client(api_key="YOUR_API_KEY")
results = client.search(data_type="rheed_video", status="success")

[
  {
    "data_id": "d290f1ee-6c54-4b01-90e6-d701748f0851",
    "raw_name": "rheed_video_2024_01_15.mp4",
    "char_source_type": "rheed_video",
    "pipeline_status": "success",
    "upload_datetime": "2024-01-15T10:30:00Z",
    "last_accessed_datetime": "2024-01-15T14:00:00Z",
    "physical_sample_id": "a1b2c3d4-5678-90ab-cdef-1234567890ab",
    "physical_sample_name": "GaAs-001",
    "tags": [],
    "projects": []
  }
]
Returns data catalogue items for your organization with advanced filtering options.
​
data_ids
array
Filter by specific data entry UUIDs
​
physical_sample_ids
array
Filter by physical sample UUIDs
​
data_type
string
Filter by characterization source type (e.g., rheed_video, xps, sem, optical, raman, photoluminescence, metrology)
​
status
string
default:"all"
Filter by pipeline status: success, pending, error, running, all
​
keywords
array
Search keywords to filter results
​
include_organization_data
boolean
default:"true"
Include data from the entire organization (not just your own)
​
limit
integer
default:"10000"
Maximum number of results to return (max 10000)
​
offset
integer
default:"0"
Number of results to skip for pagination

​
Response

Returns an array of data catalogue objects. Key fields shown below (the full response includes additional metadata fields).
​
data_id
string
Data entry UUID
​
raw_name
string
Original filename of the uploaded data
​
char_source_type
string
Characterization source type (e.g., rheed_video, xps, sem)
​
pipeline_status
string
Processing pipeline status
​
upload_datetime
string
ISO 8601 timestamp of upload
​
physical_sample_id
string
Associated physical sample UUID
​
physical_sample_name
string
Name of the associated physical sample
​
tags
array
Tags associated with this data entry
​
projects
array
Projects this data entry belongs to
from atomscale import Client

client = Client(api_key="YOUR_API_KEY")
results = client.search(data_type="rheed_video", status="success")

[
  {
    "data_id": "d290f1ee-6c54-4b01-90e6-d701748f0851",
    "raw_name": "rheed_video_2024_01_15.mp4",
    "char_source_type": "rheed_video",
    "pipeline_status": "success",
    "upload_datetime": "2024-01-15T10:30:00Z",
    "last_accessed_datetime": "2024-01-15T14:00:00Z",
    "physical_sample_id": "a1b2c3d4-5678-90ab-cdef-1234567890ab",
    "physical_sample_name": "GaAs-001",
    "tags": [],
    "projects": []
  }
]