import os
from dataframer import Dataframer

client = Dataframer(
    api_key=os.environ.get("DATAFRAMER_API_KEY"),  # This is the default and can be omitted
)
specs = client.dataframer.specs.list()
print(specs)

curl https://df-api.dataframer.ai/api/dataframer/specs/ \
    -H "Authorization: Bearer $DATAFRAMER_API_KEY"

[
  {
    "id": "550e8400-e29b-41d4-a716-446655440000",
    "name": "Customer Support Conversations Spec",
    "description": "Spec for generating synthetic customer support conversations",
    "status": "SUCCEEDED",
    "created_at": "2025-01-15T10:30:00Z",
    "dataset_id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
    "dataset_name": "Customer Support Dataset",
    "dataset_type": "SINGLE_FILE"
  },
  {
    "id": "661f9511-f30c-52e5-b827-557766551111",
    "name": "Product Reviews Spec",
    "description": "Spec for synthetic product review generation",
    "status": "PROCESSING",
    "created_at": "2025-01-15T11:00:00Z",
    "dataset_id": "b2c3d4e5-f6a7-8901-bcde-f12345678901",
    "dataset_name": "Product Reviews Dataset",
    "dataset_type": "MULTI_FILE"
  },
  {
    "id": "772f0622-g41d-63f6-c938-668877662222",
    "name": "Seedless QA Pairs Spec",
    "description": "Generate QA pairs without seed data",
    "status": "SUCCEEDED",
    "created_at": "2025-01-15T12:00:00Z",
    "dataset_id": null,
    "dataset_name": null,
    "dataset_type": "MULTI_FILE"
  }
]