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GET
/
api
/
notebooks
/
{s3_key}
/
metadata
Get parsed metadata for a notebook
curl --request GET \
  --url https://api.example.com/api/notebooks/{s3_key}/metadata \
  --header 'Authorization: Bearer <token>'
{
  "s3_key": "<string>",
  "owner": "<string>",
  "size_bytes": 123,
  "last_modified": "2023-11-07T05:31:56Z",
  "config": {
    "name": "<string>",
    "compute": "<string>",
    "approval_required": false,
    "schedule": "<string>"
  },
  "tasks": [
    {
      "name": "<string>",
      "cell_indices": [
        123
      ]
    }
  ],
  "inputs": [
    {
      "cell_index": 123,
      "table": "<string>",
      "format": "<string>"
    }
  ],
  "outputs": [
    {
      "cell_index": 123,
      "table": "<string>",
      "mlflow_experiment": "<string>"
    }
  ],
  "framework": "<string>",
  "warnings": [
    "<string>"
  ]
}

Authorizations

Authorization
string
header
required

The access token received from the authorization server in the OAuth 2.0 flow.

Path Parameters

s3_key
string
required

Response

Metadata returned successfully

Parsed notebook structure, detected I/O, and inferred pipeline config.

s3_key
string
required

Object key under the notebooks bucket.

owner
string
required

Owner username extracted from the S3 path prefix.

size_bytes
integer
required

Size of the notebook in bytes.

last_modified
string<date-time>
required

S3 LastModified timestamp.

config
NotebookConfig · object
required

Config parsed from the nx1:config cell (defaults if absent).

tasks
NotebookTask · object[]

Tasks detected from nx1:task:* tags. Empty list means single-task pipeline.

inputs
NotebookInput · object[]

Detected inputs.

outputs
NotebookOutput · object[]

Detected outputs.

framework
string | null

Detected primary framework: spark | pandas | pytorch | sklearn | ... (None if not detected).

warnings
string[]

Static-analysis gaps or unresolved patterns to surface to the user.