code: def main():
      # Getting the task we want to get the artifacts from
      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()
      print("numpy_artifact is:\n{}\n".format(numpy_artifact))
  
      # download the numpy object as a npz file
      download_numpy_artifact = artifacts_task.artifacts[
          "Numpy Eye"
      ].get_local_copy()
      print(
          "download_numpy_artifact path is:\n{}\n".format(
              download_numpy_artifact
          )
      )
  
      # getting the PIL Image object
      pil_artifact = artifacts_task.artifacts["pillow_image"].get()
      print("pil_artifact is:\n{}\n".format(pil_artifact))
  
      # getting the pandas object
      pandas_artifact = artifacts_task.artifacts["Pandas"].get()
      print("pandas_artifact is:\n{}\n".format(pandas_artifact))
  
      # getting the dictionary object
      dictionary_artifact = artifacts_task.artifacts["dictionary"].get()
      print("dictionary_artifact is:\n")
      pprint(dictionary_artifact)
  
      # getting the train DataFrame
      df_artifact = artifacts_task.artifacts["train"].get()
      print("df_artifact is:\n{}\n".format(df_artifact))
  
      # download the train DataFrame csv in the same format as in the UI (gz file)
      df_artifact_as_gz = artifacts_task.artifacts[
          "train"
      ].get_local_copy()
      print(
          "df_artifact_as_gz path is:\n{}\n".format(df_artifact_as_gz)
      )
  
      # download the wildcard jpegs images (getting the zip file already extracted into a cached folder),
      # the path containing those will be returned
      jpegs_artifact = artifacts_task.artifacts["wildcard jpegs"].get()
      print("jpegs_artifact path is:\n{}\n".format(jpegs_artifact))
  
      # download the local folder that was uploaded (getting the zip file already extracted into a cached folder),
      # the path containing those will be returned
      local_folder_artifact = artifacts_task.artifacts[
          "local folder"
      ].get()
      print(
          "local_folder_artifact path is:\n{}\n".format(
              local_folder_artifact
          )
      )
  
      # download the local folder that was uploaded (getting the zip file without extracting it),
      # the path containing the zip file will be returned
      local_folder_artifact_as_zip = artifacts_task.artifacts[
          "local folder"
      ].get_local_copy(extract_archive=False)
      print(
          "local_folder_artifact_as_zip path is:\n{}\n".format(
              local_folder_artifact_as_zip
          )
      )
  
      # download the local file that was uploaded (getting the zip file already extracted into a cached folder),
      # the path containing this file will be returned
      local_file_artifact = artifacts_task.artifacts["local file"].get()
      print(
          "local_file_artifact path is:\n{}\n".format(
              local_file_artifact
          )
      )
  
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types