From d63f3b5ca7eb53febf12db5ce4f03f25b67a7c0a Mon Sep 17 00:00:00 2001
From: allegroai <>
Date: Sun, 26 Jun 2022 18:19:50 +0300
Subject: [PATCH] Fix taking artifacts from non-completed tasks might fail

---
 examples/reporting/artifacts.py               | 81 ++++++++++---------
 examples/reporting/artifacts_retrieval.py     |  6 +-
 examples/reporting/using_artifacts_example.py |  4 +-
 3 files changed, 50 insertions(+), 41 deletions(-)

diff --git a/examples/reporting/artifacts.py b/examples/reporting/artifacts.py
index 9cc59185..1c12acd4 100644
--- a/examples/reporting/artifacts.py
+++ b/examples/reporting/artifacts.py
@@ -7,45 +7,50 @@ from PIL import Image
 from clearml import Task
 
 
-# Connecting ClearML with the current process,
-# from here on everything is logged automatically
-task = Task.init(project_name='examples', task_name='Artifacts example')
+def main():
+    # Connecting ClearML with the current process,
+    # from here on everything is logged automatically
+    task = Task.init(project_name='examples', task_name='Artifacts example')
 
-df = pd.DataFrame(
-    {
-        'num_legs': [2, 4, 8, 0],
-        'num_wings': [2, 0, 0, 0],
-        'num_specimen_seen': [10, 2, 1, 8]
-    },
-    index=['falcon', 'dog', 'spider', 'fish']
-)
+    df = pd.DataFrame(
+        {
+            'num_legs': [2, 4, 8, 0],
+            'num_wings': [2, 0, 0, 0],
+            'num_specimen_seen': [10, 2, 1, 8]
+        },
+        index=['falcon', 'dog', 'spider', 'fish']
+    )
 
-# Register Pandas object as artifact to watch
-# (it will be monitored in the background and automatically synced and uploaded)
-task.register_artifact('train', df, metadata={'counting': 'legs', 'max legs': 69})
-# change the artifact object
-df.sample(frac=0.5, replace=True, random_state=1)
-# or access it from anywhere using the Task's get_registered_artifacts()
-Task.current_task().get_registered_artifacts()['train'].sample(frac=0.5, replace=True, random_state=1)
+    # Register Pandas object as artifact to watch
+    # (it will be monitored in the background and automatically synced and uploaded)
+    task.register_artifact('train', df, metadata={'counting': 'legs', 'max legs': 69})
+    # change the artifact object
+    df.sample(frac=0.5, replace=True, random_state=1)
+    # or access it from anywhere using the Task's get_registered_artifacts()
+    Task.current_task().get_registered_artifacts()['train'].sample(frac=0.5, replace=True, random_state=1)
 
-# add and upload pandas.DataFrame (onetime snapshot of the object)
-task.upload_artifact('Pandas', artifact_object=df)
-# add and upload local file artifact
-task.upload_artifact('local file', artifact_object=os.path.join('data_samples', 'dancing.jpg'))
-# add and upload dictionary stored as JSON)
-task.upload_artifact('dictionary', df.to_dict())
-# add and upload Numpy Object (stored as .npz file)
-task.upload_artifact('Numpy Eye', np.eye(100, 100))
-# add and upload Image (stored as .png file)
-im = Image.open(os.path.join('data_samples', 'dancing.jpg'))
-task.upload_artifact('pillow_image', im)
-# add and upload a folder, artifact_object should be the folder path
-task.upload_artifact('local folder', artifact_object=os.path.join('data_samples'))
-# add and upload a wildcard
-task.upload_artifact('wildcard jpegs', artifact_object=os.path.join('data_samples', '*.jpg'))
-# do something here
-sleep(1.)
-print(df)
+    # add and upload pandas.DataFrame (onetime snapshot of the object)
+    task.upload_artifact('Pandas', artifact_object=df)
+    # add and upload local file artifact
+    task.upload_artifact('local file', artifact_object=os.path.join('data_samples', 'dancing.jpg'))
+    # add and upload dictionary stored as JSON)
+    task.upload_artifact('dictionary', df.to_dict())
+    # add and upload Numpy Object (stored as .npz file)
+    task.upload_artifact('Numpy Eye', np.eye(100, 100))
+    # add and upload Image (stored as .png file)
+    im = Image.open(os.path.join('data_samples', 'dancing.jpg'))
+    task.upload_artifact('pillow_image', im)
+    # add and upload a folder, artifact_object should be the folder path
+    task.upload_artifact('local folder', artifact_object=os.path.join('data_samples'))
+    # add and upload a wildcard
+    task.upload_artifact('wildcard jpegs', artifact_object=os.path.join('data_samples', '*.jpg'))
+    # do something here
+    sleep(1.)
+    print(df)
 
-# we are done
-print('Done')
+    # we are done
+    print('Done')
+
+
+if __name__ == '__main__':
+    main()
diff --git a/examples/reporting/artifacts_retrieval.py b/examples/reporting/artifacts_retrieval.py
index 79d34e99..0d21be4e 100644
--- a/examples/reporting/artifacts_retrieval.py
+++ b/examples/reporting/artifacts_retrieval.py
@@ -8,7 +8,11 @@ from clearml import Task
 
 def main():
     # Getting the task we want to get the artifacts from
-    artifacts_task = Task.get_task(project_name='examples', task_name='Artifacts example')
+    artifacts_task = Task.get_task(
+        project_name='examples',
+        task_name='Artifacts example',
+        task_filter={'status': ['completed']}
+    )
 
     # getting the numpy object back
     numpy_artifact = artifacts_task.artifacts['Numpy Eye'].get()
diff --git a/examples/reporting/using_artifacts_example.py b/examples/reporting/using_artifacts_example.py
index d1a7a73c..31fe6050 100644
--- a/examples/reporting/using_artifacts_example.py
+++ b/examples/reporting/using_artifacts_example.py
@@ -5,7 +5,6 @@ Upload artifacts from a Task, and then a different Task can access and utilize t
 from clearml import Task
 from time import sleep
 
-
 task1 = Task.init(project_name='examples', task_name='Create artifact')
 # upload data file to the initialized task, inputting a name and file location
 task1.upload_artifact(name='data file', artifact_object='data_samples/sample.json')
@@ -15,7 +14,8 @@ task1.close()
 # initialize another task to use some other task's artifacts
 task2 = Task.init(project_name='examples', task_name='Use artifact from other task')
 # get instance of Task that created artifact (task1), using Task's project and name. You could also use its ID number.
-preprocess_task = Task.get_task(project_name='examples', task_name='Create artifact')
+preprocess_task = Task.get_task(project_name='examples', task_name='Create artifact',
+                                task_filter={'status': ['completed']})
 # access artifact from task1, using the artifact's name
 # get_local_copy() caches the files for later use and returns a path to the cached file
 local_json = preprocess_task.artifacts['data file'].get_local_copy()