diff --git a/examples/pipeline/pipeline_from_tasks.py b/examples/pipeline/pipeline_from_tasks.py
index df55f061..bf1f590b 100644
--- a/examples/pipeline/pipeline_from_tasks.py
+++ b/examples/pipeline/pipeline_from_tasks.py
@@ -4,7 +4,11 @@ from clearml.automation import PipelineController
 
 def pre_execute_callback_example(a_pipeline, a_node, current_param_override):
     # type (PipelineController, PipelineController.Node, dict) -> bool
-    print('Cloning Task id={} with parameters: {}'.format(a_node.base_task_id, current_param_override))
+    print(
+        "Cloning Task id={} with parameters: {}".format(
+            a_node.base_task_id, current_param_override
+        )
+    )
     # if we want to skip this node (and subtree of this node) we return False
     # return True to continue DAG execution
     return True
@@ -12,7 +16,7 @@ def pre_execute_callback_example(a_pipeline, a_node, current_param_override):
 
 def post_execute_callback_example(a_pipeline, a_node):
     # type (PipelineController, PipelineController.Node) -> None
-    print('Completed Task id={}'.format(a_node.executed))
+    print("Completed Task id={}".format(a_node.executed))
     # if we need the actual executed Task: Task.get_task(task_id=a_node.executed)
     return
 
@@ -20,25 +24,43 @@ def post_execute_callback_example(a_pipeline, a_node):
 # Connecting ClearML with the current pipeline,
 # from here on everything is logged automatically
 pipe = PipelineController(
-    name='Pipeline demo',
-    project='examples',
-    version='0.0.1',
-    add_pipeline_tags=False,
+    name="Pipeline demo", project="examples", version="0.0.1", add_pipeline_tags=False
 )
 
-pipe.set_default_execution_queue('default')
+pipe.add_parameter(
+    "url",
+    "https://files.community.clear.ml/examples%252F.pipelines%252FPipeline%20demo/stage_data.8f17b6316ce442ce8904f6fccb1763de/artifacts/dataset/f6d08388e9bc44c86cab497ad31403c4.iris_dataset.pkl",
+    "dataset_url",
+)
 
-pipe.add_step(name='stage_data', base_task_project='examples', base_task_name='Pipeline step 1 dataset artifact')
-pipe.add_step(name='stage_process', parents=['stage_data', ],
-              base_task_project='examples', base_task_name='Pipeline step 2 process dataset',
-              parameter_override={'General/dataset_url': '${stage_data.artifacts.dataset.url}',
-                                  'General/test_size': 0.25},
-              pre_execute_callback=pre_execute_callback_example,
-              post_execute_callback=post_execute_callback_example
-              )
-pipe.add_step(name='stage_train', parents=['stage_process', ],
-              base_task_project='examples', base_task_name='Pipeline step 3 train model',
-              parameter_override={'General/dataset_task_id': '${stage_process.id}'})
+pipe.set_default_execution_queue("default")
+
+pipe.add_step(
+    name="stage_data",
+    base_task_project="examples",
+    base_task_name="Pipeline step 1 dataset artifact",
+    parameter_override={"General/dataset_url": "${pipeline.url}"},
+)
+
+pipe.add_step(
+    name="stage_process",
+    parents=["stage_data"],
+    base_task_project="examples",
+    base_task_name="Pipeline step 2 process dataset",
+    parameter_override={
+        "General/dataset_url": "${stage_data.artifacts.dataset.url}",
+        "General/test_size": 0.25,
+    },
+    pre_execute_callback=pre_execute_callback_example,
+    post_execute_callback=post_execute_callback_example,
+)
+pipe.add_step(
+    name="stage_train",
+    parents=["stage_process"],
+    base_task_project="examples",
+    base_task_name="Pipeline step 3 train model",
+    parameter_override={"General/dataset_task_id": "${stage_process.id}"},
+)
 
 # for debugging purposes use local jobs
 # pipe.start_locally()
@@ -46,4 +68,4 @@ pipe.add_step(name='stage_train', parents=['stage_process', ],
 # Starting the pipeline (in the background)
 pipe.start()
 
-print('done')
+print("done")