​
Pipeline object

{
  "blocks": [
    {
      "all_upstream_blocks_executed": true,
      "color": null,
      "configuration": {},
      "downstream_blocks": [],
      "executor_config": null,
      "executor_type": "local_python",
      "has_callback": null,
      "name": "load_titanic",
      "language": "python",
      "status": "executed",
      "type": "data_loader",
      "upstream_blocks": [],
      "uuid": "load_titanic",
      "content": "...",
      "metadata": {}
    }
  ],
  "description": null,
  "extensions": {},
  "name": "example_pipeline",
  "schedules": [
    {
      "created_at": "2023-03-14T23:24:17.814478+00:00",
      "id": 59,
      "name": "dry haze",
      "pipeline_uuid": "aged_night",
      "schedule_interval": null,
      "schedule_type": "api",
      "start_time": "2023-03-14T23:25:00+00:00",
      "status": "inactive",
      "updated_at": "2023-03-14T23:25:27.351528+00:00"
    }
  ],
  "type": "python",
  "uuid": "example_pipeline",
  "variables": {
    "env": "prod"
  },
  "widgets": []
}
blocks
array of objects

Array of block objects. See the blocks section for more details.

description
string

Description for the pipeline.

extensions
array of objects

Array of extension block objects. Same shape as blocks.

namerequired
string

Human friendly name of the pipeline.

schedulesrequired
array of objects

Array of trigger objects.

typerequired
string

The type of the pipeline: integration, pyspark, python, streaming Note that python is a standard (batch) pipeline with a python backend, while pyspark is a batch pipeline with a spark backend.

uuidrequired
string

Unique identifier for the pipeline.

variables
object

Object containing variables for the pipeline.

[key]
string

The property name is user defined.

widgets
array of objects

Array of widget block objects. Same shape as blocks.