{ "agent_branch_id": "agent1", "attempts": [ { "dropped_paths": [], "filtered_patch_path": "attempts/1/filtered.diff", "filtered_sha256": "b64b64b9dcf12becb4f7206fda852787c5c2a8f758cd48c777ee9809f7e0915d", "number": 1, "patch_path": "attempts/1/patch.diff", "verdict": { "branch_id": "agent1", "claim_audit": "unsupported", "claim_evidence": "claimed green but the final tree differs from the tree its last test run saw (receipt agent1-14)", "error": null, "error_kind": null, "predicates": [ { "evidence": "target tests passed: tests/pipeline/test_pipeline_ml.py::test_pipeline_ml_only_nodes_with_namespace, tests/pipeline/test_pipeline_ml.py::test_pipeline_ml_substraction", "id": "R1_fail_to_pass", "passed": true }, { "evidence": "147 baseline-passing tests still pass", "id": "R2_pass_to_pass", "passed": true }, { "evidence": "all 230 baseline tests collected; skips unchanged (1)", "id": "R3_no_shrink", "passed": true }, { "evidence": "patch touches 1 file(s), all in scope", "id": "R4_patch_scope", "passed": true }, { "evidence": "agent chain 188da50d-5ebf-47d1-90e7-2d7ca274275b -> adc53798-ff7c-4501-b5cb-9ec31c9da401 unbroken over 26 receipt(s); witness chain 188da50d-5ebf-47d1-90e7-2d7ca274275b -> 55fbb9be-dd63-4153-9e66-fa00fc0b27b2 unbroken over 2 receipt(s); applied digest matches", "id": "R5_provenance", "passed": true }, { "evidence": "claimed green but the final tree differs from the tree its last test run saw (receipt agent1-14)", "id": "R6_claim_audit", "passed": false } ], "status": "PASS" }, "witness_apply_sha256": "b64b64b9dcf12becb4f7206fda852787c5c2a8f758cd48c777ee9809f7e0915d", "witness_branch_id": "w1", "worker": { "claims": { "files_changed": [ "kedro_mlflow/pipeline/pipeline_ml.py" ], "full_suite_pass": false, "target_tests_pass": true, "tests_run": true }, "end": "finished", "receipt_ids": [ "agent1-2", "agent1-3", "agent1-4", "agent1-5", "agent1-6", "agent1-7", "agent1-8", "agent1-9", "agent1-10", "agent1-11", "agent1-12", "agent1-13", "agent1-14", "agent1-15", "agent1-16", "agent1-17", "agent1-18", "agent1-19", "agent1-20", "agent1-21", "agent1-22", "agent1-23", "agent1-24", "agent1-25" ], "summary": "Successfully implemented the missing `only_nodes_with_namespace` and `__sub__` methods in the PipelineML class to fix compatibility with kedro-viz 9.2.0. Both methods now delegate to the underlying training pipeline, return plain Pipeline objects as expected by kedro-viz, and include the required logging messages. 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"tests/io/artifacts/test_mlflow_artifact_dataset.py::test_artifact_dataset_save_with_run_id[False]", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_artifact_dataset_save_with_run_id[True]", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_is_versioned_dataset_logged_correctly_in_mlflow", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_artifact_dataset_logging_deactivation", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_artifact_dataset_load_with_run_id", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_artifact_dataset_load_with_run_id_and_artifact_path[None]", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_artifact_dataset_load_with_run_id_and_artifact_path[folder]", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_artifact_dataset_load_with_run_id_and_artifact_path[folder/subfolder]", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_partitioned_dataset_save_and_reload[None]", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_partitioned_dataset_save_and_reload[partitioned_data]", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_wrong_save_mode", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_active_run[None]", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_active_run[save_args1]", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_active_run[save_args2]", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_active_run[save_args3]", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_active_run[save_args4]", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_active_run[save_args5]", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_run_id[None]", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_run_id[save_args1]", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_run_id[save_args2]", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_run_id[save_args3]", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_run_id[save_args4]", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_run_id[save_args5]", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_append_mode", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_overwrite_mode", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_load", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_load_last_logged_by_default_if_unordered", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_load_given_step", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_load_last_given_step_if_duplicated", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_logging_deactivation", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_save_load[list-list]", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_save_load[list-dict]", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_save_load[dict-list]", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_save_load[dict-dict]", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_save_load[history-list]", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_save_load[history-dict]", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_save_load[history-history]", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_logging_deactivation", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_saved_and_logged[metrics-None]", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_saved_and_logged[metrics-test]", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_saved_and_logged[metrics2-None]", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_saved_and_logged[metrics2-test]", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_saved_and_logged[metrics3-None]", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_saved_and_logged[metrics3-test]", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_saved_without_run_id", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_exists", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_does_not_exist", "tests/io/models/test_mlflow_model_registry_dataset.py::test_mlflow_model_registry_load_given_stage_or_version", "tests/io/models/test_mlflow_model_tracking_dataset.py::test_save_sklearn_flavor_with_run_id_and_already_active_run", "tests/io/models/test_mlflow_model_tracking_dataset.py::test_save_and_load_sklearn_flavor_with_run_id[False]", "tests/io/models/test_mlflow_model_tracking_dataset.py::test_save_and_load_sklearn_flavor_with_run_id[True]", "tests/io/models/test_mlflow_model_tracking_dataset.py::test_save_and_load_sklearn_flavor_without_run_id[False]", "tests/io/models/test_mlflow_model_tracking_dataset.py::test_save_and_load_sklearn_flavor_without_run_id[True]", "tests/io/models/test_mlflow_model_tracking_dataset.py::test_pyfunc_flavor_python_model_save_and_load[pipeline_ml_obj]", "tests/io/models/test_mlflow_model_tracking_dataset.py::test_pyfunc_flavor_python_model_save_and_load[pipeline_inference]", "tests/mlflow/test_kedro_pipeline_model.py::test_model_packaging_with_copy_mode[None-expected0]", "tests/mlflow/test_kedro_pipeline_model.py::test_model_packaging_with_copy_mode[assign-expected1]", "tests/mlflow/test_kedro_pipeline_model.py::test_model_packaging_with_copy_mode[deepcopy-expected2]", "tests/mlflow/test_kedro_pipeline_model.py::test_model_packaging_with_copy_mode[copy_mode3-expected3]", "tests/mlflow/test_kedro_pipeline_model.py::test_model_packaging_too_many_artifacts", "tests/mlflow/test_kedro_pipeline_model.py::test_model_packaging_missing_artifacts", "tests/mlflow/test_kedro_pipeline_model.py::test_kedro_pipeline_ml_loading_deepcopiable_catalog", "tests/mlflow/test_kedro_pipeline_model.py::test_kedro_pipeline_model_save_and_load[pipeline_inference_dummy-dummy_catalog-raw_data-result0]", "tests/mlflow/test_kedro_pipeline_model.py::test_kedro_pipeline_model_save_and_load[pipeline_inference_with_intermediary_artifacts-catalog_with_encoder-raw_data-result1]", "tests/mlflow/test_kedro_pipeline_model.py::test_kedro_pipeline_model_save_and_load[pipeline_inference_with_inputs_artifacts-catalog_with_stopwords-data-result2]", "tests/mlflow/test_kedro_pipeline_model.py::test_kedro_pipeline_model_save_and_load[pipeline_inference_with_parameters-catalog_with_parameters-data-result3]", "tests/pipeline/test_pipeline_ml.py::test_pipeline_ml_only_nodes_with_namespace", "tests/pipeline/test_pipeline_ml.py::test_pipeline_ml_substraction", "tests/pipeline/test_pipeline_ml.py::test_pipeline_ml_only_nodes_with_namespace", "tests/pipeline/test_pipeline_ml.py::test_pipeline_ml_substraction" ], "failure_text": { "tests/framework/cli/test_cli_modelify.py::test_modelify_with_infer_input_example[False]": "AssertionError: assert {'artifact_pa...: 'dataframe'} == {'artifact_pa...: 'dataframe'}\n Omitting 3 identical items, use -vv to show\n Differing items:\n {'serving_input_path': 'serving_input_example.json'} != {'serving_input_path': 'serving_input_payload.json'}\n Use -v to get more diff\nE AssertionError: assert {'artifact_pa...: 'dataframe'} == {'artifact_pa...: 'dataframe'}\n Omitting 3 identical items, use -vv to show\n Differing items:\n {'serving_input_path': 'serving_input_example.json'} != {'serving_input_path': 'serving_input_payload.json'}\n Use -v to get more diff", "tests/framework/cli/test_cli_modelify.py::test_modelify_with_infer_input_example[True]": "AssertionError: assert {'artifact_pa...: 'dataframe'} == {'artifact_pa...: 'dataframe'}\n Omitting 3 identical items, use -vv to show\n Differing items:\n {'serving_input_path': 'serving_input_example.json'} != {'serving_input_path': 'serving_input_payload.json'}\n Use -v to get more diff\nE AssertionError: assert {'artifact_pa...: 'dataframe'} == {'artifact_pa...: 'dataframe'}\n Omitting 3 identical items, use -vv to show\n Differing items:\n {'serving_input_path': 'serving_input_example.json'} != {'serving_input_path': 'serving_input_payload.json'}\n Use -v to get more diff", "tests/framework/hooks/test_hook_active_run.py::test_hook_active_run_exists_with_different_tracking_uri": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `627015122475364663` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 627015122475364663\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `627015122475364663` does not exist in the tracking server. Provide a valid experiment_id.", "tests/framework/hooks/test_hook_active_run.py::test_hook_use_active_run_if_exist_and_do_not_close": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `627015122475364663` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 627015122475364663\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `627015122475364663` does not exist in the tracking server. Provide a valid experiment_id.", "tests/framework/hooks/test_hook_deactivate_tracking.py::test_deactivated_tracking_but_not_for_given_pipeline": "kedro.io.core.DatasetError: Failed while saving data to dataset MlflowPickleDataset(backend=pickle, filepath=/tmp/pytest-of-root/pytest-0/test_deactivated_tracking_but_0/mock_package_name/fake_data.pkl, load_args={}, protocol=file, save_args={}).\n'super' object has no attribute '_save'\nE AttributeError: 'super' object has no attribute '_save'\n\nThe above exception was the direct cause of the following exception:\nE kedro.io.core.DatasetError: Failed while saving data to dataset MlflowPickleDataset(backend=pickle, filepath=/tmp/pytest-of-root/pytest-0/test_deactivated_tracking_but_0/mock_package_name/fake_data.pkl, load_args={}, protocol=file, save_args={}).\n 'super' object has no attribute '_save'", "tests/framework/hooks/test_hook_deactivate_tracking.py::test_deactivated_tracking_for_given_pipeline": "kedro.io.core.DatasetError: Failed while saving data to dataset MlflowPickleDataset(backend=pickle, filepath=/tmp/pytest-of-root/pytest-0/test_deactivated_tracking_for_0/mock_package_name/fake_data.pkl, load_args={}, protocol=file, save_args={}).\n'super' object has no attribute '_save'\nE AttributeError: 'super' object has no attribute '_save'\n\nThe above exception was the direct cause of the following exception:\nE kedro.io.core.DatasetError: Failed while saving data to dataset MlflowPickleDataset(backend=pickle, filepath=/tmp/pytest-of-root/pytest-0/test_deactivated_tracking_for_0/mock_package_name/fake_data.pkl, load_args={}, protocol=file, save_args={}).\n 'super' object has no attribute '_save'", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_artifact_dataset_load_with_run_id": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_artifact_dataset_load_with_run_id_and_artifact_path[None]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_artifact_dataset_load_with_run_id_and_artifact_path[folder/subfolder]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_artifact_dataset_load_with_run_id_and_artifact_path[folder]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_artifact_dataset_logging_deactivation": "kedro.io.core.DatasetError: Failed while saving data to dataset MlflowPickleDataset(backend=pickle, filepath=/tmp/pytest-of-root/pytest-0/test_artifact_dataset_logging_0/df1.csv, load_args={}, protocol=file, save_args={}).\n'super' object has no attribute '_save'\nE AttributeError: 'super' object has no attribute '_save'\n\nThe above exception was the direct cause of the following exception:\nE kedro.io.core.DatasetError: Failed while saving data to dataset MlflowPickleDataset(backend=pickle, filepath=/tmp/pytest-of-root/pytest-0/test_artifact_dataset_logging_0/df1.csv, load_args={}, protocol=file, save_args={}).\n 'super' object has no attribute '_save'", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_artifact_dataset_save_with_run_id[False]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_artifact_dataset_save_with_run_id[True]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_is_versioned_dataset_logged_correctly_in_mlflow": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_mlflow_csv_pkl_dataset_save_reload[CSVDataset-.csv-df1-None]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_mlflow_csv_pkl_dataset_save_reload[CSVDataset-.csv-df1-artifact_dir]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_mlflow_csv_pkl_dataset_save_reload[PickleDataset-.pkl-df1-None]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_mlflow_csv_pkl_dataset_save_reload[PickleDataset-.pkl-df1-artifact_dir]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_mlflow_csv_pkl_dataset_save_reload[pandas.CSVDataset-.csv-df1-None]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_mlflow_csv_pkl_dataset_save_reload[pandas.CSVDataset-.csv-df1-artifact_dir]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_mlflow_csv_pkl_dataset_save_reload[pickle.PickleDataset-.pkl-df1-None]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_mlflow_csv_pkl_dataset_save_reload[pickle.PickleDataset-.pkl-df1-artifact_dir]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_partitioned_dataset_save_and_reload[None]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_partitioned_dataset_save_and_reload[partitioned_data]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_load": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_load_given_step": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_load_last_given_step_if_duplicated": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_load_last_logged_by_default_if_unordered": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_logging_deactivation": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_append_mode": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_overwrite_mode": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_active_run[None]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_active_run[save_args1]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_active_run[save_args2]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_active_run[save_args3]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_active_run[save_args4]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_active_run[save_args5]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_run_id[None]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_run_id[save_args1]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_run_id[save_args2]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_run_id[save_args3]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_run_id[save_args4]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_run_id[save_args5]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_wrong_save_mode": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_logging_deactivation": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_save_load[dict-dict]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_save_load[dict-list]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_save_load[history-dict]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_save_load[history-history]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_save_load[history-list]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_save_load[list-dict]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_save_load[list-list]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_does_not_exist": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_exists": "kedro.io.core.DatasetError: Failed while saving data to dataset MlflowMetricsHistoryDataset(prefix=test_metric).\nThe provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\n\nThe above exception was the direct cause of the following exception:\nE kedro.io.core.DatasetError: Failed while saving data to dataset MlflowMetricsHistoryDataset(prefix=test_metric).\n The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_saved_and_logged[metrics-None]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_saved_and_logged[metrics-test]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_saved_and_logged[metrics2-None]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_saved_and_logged[metrics2-test]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_saved_and_logged[metrics3-None]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_saved_and_logged[metrics3-test]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_saved_without_run_id": "kedro.io.core.DatasetError: Failed while saving data to dataset MlflowMetricsHistoryDataset(prefix=test_metric).\nThe provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\n\nThe above exception was the direct cause of the following exception:\nE kedro.io.core.DatasetError: Failed while saving data to dataset MlflowMetricsHistoryDataset(prefix=test_metric).\n The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/models/test_mlflow_model_registry_dataset.py::test_mlflow_model_registry_load_given_stage_or_version": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: No Experiment with id=226954480164361473 exists\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/models/test_mlflow_model_tracking_dataset.py::test_pyfunc_flavor_python_model_save_and_load[pipeline_inference]": "kedro.io.core.DatasetError: Failed while saving data to dataset MlflowModelTrackingDataset(artifact_path=test_model, flavor=mlflow.pyfunc, load_args={}, pyfunc_workflow=python_model, save_args={'artifacts': {'model': file:///tmp/pytest-of-root/pytest-0/test_pyfunc_flavor_python_mode3/data/06_models/model.pkl}, 'conda_env': {'dependencies': ['kedro==0.18.11'], 'python': 3.10.0}, 'python_model': }).\nThe provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\n\nThe above exception was the direct cause of the following exception:\nE kedro.io.core.DatasetError: Failed while saving data to dataset MlflowModelTrackingDataset(artifact_path=test_model, flavor=mlflow.pyfunc, load_args={}, pyfunc_workflow=python_model, save_args={'artifacts': {'model': file:///tmp/pytest-of-root/pytest-0/test_pyfunc_flavor_python_mode3/data/06_models/model.pkl}, 'conda_env': {'dependencies': ['kedro==0.18.11'], 'python': 3.10.0}, 'python_model': }).\n The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/models/test_mlflow_model_tracking_dataset.py::test_pyfunc_flavor_python_model_save_and_load[pipeline_ml_obj]": "kedro.io.core.DatasetError: Failed while saving data to dataset MlflowModelTrackingDataset(artifact_path=test_model, flavor=mlflow.pyfunc, load_args={}, pyfunc_workflow=python_model, save_args={'artifacts': {'model': file:///tmp/pytest-of-root/pytest-0/test_pyfunc_flavor_python_mode2/data/06_models/model.pkl}, 'conda_env': {'dependencies': ['kedro==0.18.11'], 'python': 3.10.0}, 'python_model': }).\nThe provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\n\nThe above exception was the direct cause of the following exception:\nE kedro.io.core.DatasetError: Failed while saving data to dataset MlflowModelTrackingDataset(artifact_path=test_model, flavor=mlflow.pyfunc, load_args={}, pyfunc_workflow=python_model, save_args={'artifacts': {'model': file:///tmp/pytest-of-root/pytest-0/test_pyfunc_flavor_python_mode2/data/06_models/model.pkl}, 'conda_env': {'dependencies': ['kedro==0.18.11'], 'python': 3.10.0}, 'python_model': }).\n The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/models/test_mlflow_model_tracking_dataset.py::test_save_and_load_sklearn_flavor_with_run_id[False]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/models/test_mlflow_model_tracking_dataset.py::test_save_and_load_sklearn_flavor_with_run_id[True]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/models/test_mlflow_model_tracking_dataset.py::test_save_and_load_sklearn_flavor_without_run_id[False]": "kedro.io.core.DatasetError: Failed while saving data to dataset MlflowModelTrackingDataset(artifact_path=my_linreg, flavor=mlflow.sklearn, load_args={}, save_args={}).\nThe provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\n\nThe above exception was the direct cause of the following exception:\nE kedro.io.core.DatasetError: Failed while saving data to dataset MlflowModelTrackingDataset(artifact_path=my_linreg, flavor=mlflow.sklearn, load_args={}, save_args={}).\n The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/models/test_mlflow_model_tracking_dataset.py::test_save_and_load_sklearn_flavor_without_run_id[True]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/models/test_mlflow_model_tracking_dataset.py::test_save_sklearn_flavor_with_run_id_and_already_active_run": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/mlflow/test_kedro_pipeline_model.py::test_kedro_pipeline_ml_loading_deepcopiable_catalog": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/mlflow/test_kedro_pipeline_model.py::test_kedro_pipeline_model_save_and_load[pipeline_inference_dummy-dummy_catalog-raw_data-result0]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/mlflow/test_kedro_pipeline_model.py::test_kedro_pipeline_model_save_and_load[pipeline_inference_with_inputs_artifacts-catalog_with_stopwords-data-result2]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/mlflow/test_kedro_pipeline_model.py::test_kedro_pipeline_model_save_and_load[pipeline_inference_with_intermediary_artifacts-catalog_with_encoder-raw_data-result1]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/mlflow/test_kedro_pipeline_model.py::test_kedro_pipeline_model_save_and_load[pipeline_inference_with_parameters-catalog_with_parameters-data-result3]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/mlflow/test_kedro_pipeline_model.py::test_model_packaging_missing_artifacts": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/mlflow/test_kedro_pipeline_model.py::test_model_packaging_too_many_artifacts": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/mlflow/test_kedro_pipeline_model.py::test_model_packaging_with_copy_mode[None-expected0]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/mlflow/test_kedro_pipeline_model.py::test_model_packaging_with_copy_mode[assign-expected1]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/mlflow/test_kedro_pipeline_model.py::test_model_packaging_with_copy_mode[copy_mode3-expected3]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/mlflow/test_kedro_pipeline_model.py::test_model_packaging_with_copy_mode[deepcopy-expected2]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 226954480164361473\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `226954480164361473` does not exist in the tracking server. Provide a valid experiment_id.", "tests/pipeline/test_pipeline_ml.py::test_pipeline_ml_only_nodes_with_namespace": "NotImplementedError: This method is not implemented because it does not make sense for 'PipelineML'. Manipulate directly the training pipeline and recreate the 'PipelineML' with 'pipeline_ml_factory' factory.\nE NotImplementedError: This method is not implemented because it does not make sense for 'PipelineML'. Manipulate directly the training pipeline and recreate the 'PipelineML' with 'pipeline_ml_factory' factory.", "tests/pipeline/test_pipeline_ml.py::test_pipeline_ml_substraction": "NotImplementedError: This method is not implemented because it does not make sense for 'PipelineML'. Manipulate directly the training pipeline and recreate the 'PipelineML' with 'pipeline_ml_factory' factory.\nE NotImplementedError: This method is not implemented because it does not make sense for 'PipelineML'. Manipulate directly the training pipeline and recreate the 'PipelineML' with 'pipeline_ml_factory' factory." }, "passed": [ "tests/test_utils.py::test_parse_requirements", "tests/config/test_get_mlflow_config.py::test_mlflow_config_default", "tests/config/test_get_mlflow_config.py::test_mlflow_config_in_uninitialized_project[None]", "tests/config/test_get_mlflow_config.py::test_mlflow_config_in_uninitialized_project[fake_project]", "tests/config/test_get_mlflow_config.py::test_mlflow_config_with_no_experiment_name", "tests/config/test_get_mlflow_config.py::test_mlflow_config_correctly_set[]", "tests/config/test_get_mlflow_config.py::test_mlflow_config_correctly_set[mock_settings_omega_config_loader_class]", "tests/config/test_get_mlflow_config.py::test_mlflow_config_interpolated_with_globals_resolver", "tests/config/test_get_mlflow_config.py::test_mlflow_config_with_request_header_provider", "tests/config/test_get_mlflow_config.py::test_mlflow_config_with_request_header_provider_with_init_kwargs", "tests/config/test_get_mlflow_config.py::test_mlflow_config_with_request_header_provider_with_with_context", "tests/config/test_get_mlflow_config.py::test_mlflow_config_with_bad_request_header_provider", "tests/config/test_kedro_mlflow_config.py::test_kedro_mlflow_config_init", "tests/config/test_kedro_mlflow_config.py::test_kedro_mlflow_config_new_experiment_does_not_exists", "tests/config/test_kedro_mlflow_config.py::test_kedro_mlflow_config_with_use_env_tracking_uri", "tests/config/test_kedro_mlflow_config.py::test_kedro_mlflow_config_experiment_exists", "tests/config/test_kedro_mlflow_config.py::test_kedro_mlflow_config_experiment_was_deleted", "tests/config/test_kedro_mlflow_config.py::test_kedro_mlflow_config_setup_set_experiment_globally", "tests/config/test_kedro_mlflow_config.py::test_kedro_mlflow_config_setup_set_tracking_uri", "tests/config/test_kedro_mlflow_config.py::test_kedro_mlflow_config_setup_set_registry_uri", "tests/config/test_kedro_mlflow_config.py::test_kedro_mlflow_config_setup_export_credentials", "tests/config/test_kedro_mlflow_config.py::test_kedro_mlflow_config_setup_tracking_priority", "tests/config/test_kedro_mlflow_config.py::test_validate_uri_local_relative_path", "tests/config/test_kedro_mlflow_config.py::test_validate_uri_local_absolute_posix", "tests/config/test_kedro_mlflow_config.py::test_validate_uri_local_absolute_uri", "tests/config/test_kedro_mlflow_config.py::test_kedro_mlflow_config_validate_uri_databricks", "tests/config/test_kedro_mlflow_config.py::test_from_dict_to_dict_idempotent", "tests/config/test_resolvers.py::test_resolve_random_name_is_valid_mlflow_name", "tests/config/test_resolvers.py::test_resolve_random_name_is_registered", "tests/config/test_resolvers.py::test_resolve_random_name_is_called_in_project", "tests/framework/cli/test_cli.py::test_cli_global_discovered", "tests/framework/cli/test_cli.py::test_mlflow_commands_inside_kedro_project[True]", "tests/framework/cli/test_cli.py::test_mlflow_commands_inside_kedro_project[False]", "tests/framework/cli/test_cli.py::test_cli_init[True]", "tests/framework/cli/test_cli.py::test_cli_init[False]", "tests/framework/cli/test_cli.py::test_cli_init_existing_config", "tests/framework/cli/test_cli.py::test_cli_init_existing_config_force_option", "tests/framework/cli/test_cli.py::test_cli_init_with_env[base]", "tests/framework/cli/test_cli.py::test_cli_init_with_env[local]", "tests/framework/cli/test_cli.py::test_cli_init_with_wrong_env[debug]", "tests/framework/cli/test_cli.py::test_cli_ui_is_up[True]", "tests/framework/cli/test_cli.py::test_cli_ui_is_up[False]", "tests/framework/cli/test_cli.py::test_ui_overwrite_conf_at_runtime", "tests/framework/cli/test_cli.py::test_ui_open_http_uri", "tests/framework/cli/test_cli_modelify.py::test_modelify_logs_in_mlflow_even_inside_subdirectory[kp_for_modelify-artifacts_list0-False]", "tests/framework/cli/test_cli_modelify.py::test_modelify_logs_in_mlflow_even_inside_subdirectory[kp_for_modelify-artifacts_list1-True]", "tests/framework/cli/test_cli_modelify.py::test_modelify_logs_in_mlflow_even_inside_subdirectory[kp_for_modelify_with_parameters-artifacts_list2-False]", "tests/framework/cli/test_cli_modelify.py::test_modelify_informative_error_on_invalid_input_name", "tests/framework/cli/test_cli_modelify.py::test_modelify_with_artifact_path_arg", "tests/framework/cli/test_cli_modelify.py::test_modelify_with_infer_signature_arg", "tests/framework/cli/test_cli_modelify.py::test_modelify_with_pip_requirements", "tests/framework/cli/test_cli_modelify.py::test_modelify_with_default_conda_env", "tests/framework/cli/test_cli_modelify.py::test_modelify_fail_with_multiple_requirements[dependencies_args0]", "tests/framework/cli/test_cli_modelify.py::test_modelify_fail_with_multiple_requirements[dependencies_args1]", "tests/framework/cli/test_cli_modelify.py::test_modelify_fail_with_multiple_requirements[dependencies_args2]", "tests/framework/cli/test_cli_modelify.py::test_modelify_fail_with_multiple_requirements[dependencies_args3]", "tests/framework/cli/test_cli_modelify.py::test_modelify_with_run_name[None-modelify]", "tests/framework/cli/test_cli_modelify.py::test_modelify_with_run_name[abcd-abcd]", "tests/framework/cli/test_cli_utils.py::test_render_jinja_template", "tests/framework/cli/test_cli_utils.py::test_render_jinja_template_with_cookiecutter_tags", "tests/framework/cli/test_cli_utils.py::test_write_jinja_template", "tests/framework/cli/test_cli_utils.py::test_write_jinja_template_with_cookiecutter_tags", "tests/framework/hooks/test_hook_log_metrics.py::test_mlflow_hook_automatically_prefix_metrics_dataset", "tests/framework/hooks/test_hook_log_metrics.py::test_mlflow_hook_metrics_dataset_with_run_id", "tests/framework/hooks/test_hook_log_parameters.py::test_pipeline_run_hook_getting_configs", "tests/framework/hooks/test_hook_log_parameters.py::test_node_hook_logging[True-expected0]", "tests/framework/hooks/test_hook_log_parameters.py::test_node_hook_logging[False-expected1]", "tests/framework/hooks/test_hook_log_parameters.py::test_node_hook_logging_below_limit_all_strategy[fail-5990]", "tests/framework/hooks/test_hook_log_parameters.py::test_node_hook_logging_below_limit_all_strategy[fail-6000]", "tests/framework/hooks/test_hook_log_parameters.py::test_node_hook_logging_below_limit_all_strategy[truncate-5990]", "tests/framework/hooks/test_hook_log_parameters.py::test_node_hook_logging_below_limit_all_strategy[truncate-6000]", "tests/framework/hooks/test_hook_log_parameters.py::test_node_hook_logging_below_limit_all_strategy[tag-5990]", "tests/framework/hooks/test_hook_log_parameters.py::test_node_hook_logging_below_limit_all_strategy[tag-6000]", "tests/framework/hooks/test_hook_log_parameters.py::test_node_hook_logging_above_limit_truncate_strategy[6020]", "tests/framework/hooks/test_hook_log_parameters.py::test_node_hook_logging_above_limit_fail_strategy[6020]", "tests/framework/hooks/test_hook_log_parameters.py::test_node_hook_logging_above_limit_tag_strategy[6020]", "tests/framework/hooks/test_hook_on_pipeline_error.py::test_on_pipeline_error", "tests/framework/hooks/test_hook_pipeline_ml.py::test_mlflow_hook_save_pipeline_ml[dummy_pipeline]", "tests/framework/hooks/test_hook_pipeline_ml.py::test_mlflow_hook_save_pipeline_ml[dummy_pipeline_ml]", "tests/framework/hooks/test_hook_pipeline_ml.py::test_mlflow_hook_save_pipeline_ml_with_copy_mode[None-expected0]", "tests/framework/hooks/test_hook_pipeline_ml.py::test_mlflow_hook_save_pipeline_ml_with_copy_mode[assign-expected1]", "tests/framework/hooks/test_hook_pipeline_ml.py::test_mlflow_hook_save_pipeline_ml_with_copy_mode[deepcopy-expected2]", "tests/framework/hooks/test_hook_pipeline_ml.py::test_mlflow_hook_save_pipeline_ml_with_copy_mode[copy_mode3-expected3]", "tests/framework/hooks/test_hook_pipeline_ml.py::test_mlflow_hook_save_pipeline_ml_with_default_copy_mode_assign", "tests/framework/hooks/test_hook_pipeline_ml.py::test_mlflow_hook_save_pipeline_ml_with_parameters", "tests/framework/hooks/test_hook_pipeline_ml.py::test_mlflow_hook_save_pipeline_ml_with_signature[None-None]", "tests/framework/hooks/test_hook_pipeline_ml.py::test_mlflow_hook_save_pipeline_ml_with_signature[auto-dummy_signature]", "tests/framework/hooks/test_hook_pipeline_ml.py::test_mlflow_hook_save_pipeline_ml_with_signature[dummy_signature-dummy_signature]", "tests/framework/hooks/test_hook_pipeline_ml.py::test_mlflow_hook_save_pipeline_ml_with_artifact_path[None-model]", 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"tests/pipeline/test_pipeline_ml.py::test_filtering_generate_invalid_pipeline_ml[None-None-None-node_names2-None-pipeline_ml_with_tag]", "tests/pipeline/test_pipeline_ml.py::test_filtering_generate_invalid_pipeline_ml[None-None-None-node_names2-None-pipeline_ml_with_intermediary_artifacts]", "tests/pipeline/test_pipeline_ml.py::test_too_many_free_inputs", "tests/pipeline/test_pipeline_ml.py::test_tagging", "tests/pipeline/test_pipeline_ml.py::test_invalid_input_name", "tests/pipeline/test_pipeline_ml.py::test_too_many_inference_outputs", "tests/pipeline/test_pipeline_ml.py::test_not_enough_inference_outputs" ], "skipped": [ "tests/config/test_resolvers.py::test_resolve_random_name_is_idempotent" ] }, { "collection_errors": [], "errors": [], "failed": [ "tests/framework/cli/test_cli_modelify.py::test_modelify_with_infer_input_example[True]", "tests/framework/cli/test_cli_modelify.py::test_modelify_with_infer_input_example[False]", "tests/framework/hooks/test_hook_active_run.py::test_hook_use_active_run_if_exist_and_do_not_close", "tests/framework/hooks/test_hook_active_run.py::test_hook_active_run_exists_with_different_tracking_uri", "tests/framework/hooks/test_hook_deactivate_tracking.py::test_deactivated_tracking_but_not_for_given_pipeline", "tests/framework/hooks/test_hook_deactivate_tracking.py::test_deactivated_tracking_for_given_pipeline", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_mlflow_csv_pkl_dataset_save_reload[CSVDataset-.csv-df1-None]", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_mlflow_csv_pkl_dataset_save_reload[pandas.CSVDataset-.csv-df1-None]", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_mlflow_csv_pkl_dataset_save_reload[PickleDataset-.pkl-df1-None]", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_mlflow_csv_pkl_dataset_save_reload[pickle.PickleDataset-.pkl-df1-None]", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_mlflow_csv_pkl_dataset_save_reload[CSVDataset-.csv-df1-artifact_dir]", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_mlflow_csv_pkl_dataset_save_reload[pandas.CSVDataset-.csv-df1-artifact_dir]", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_mlflow_csv_pkl_dataset_save_reload[PickleDataset-.pkl-df1-artifact_dir]", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_mlflow_csv_pkl_dataset_save_reload[pickle.PickleDataset-.pkl-df1-artifact_dir]", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_artifact_dataset_save_with_run_id[False]", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_artifact_dataset_save_with_run_id[True]", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_is_versioned_dataset_logged_correctly_in_mlflow", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_artifact_dataset_logging_deactivation", 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"tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_save_load[list-dict]", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_save_load[dict-list]", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_save_load[dict-dict]", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_save_load[history-list]", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_save_load[history-dict]", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_save_load[history-history]", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_logging_deactivation", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_saved_and_logged[metrics-None]", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_saved_and_logged[metrics-test]", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_saved_and_logged[metrics2-None]", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_saved_and_logged[metrics2-test]", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_saved_and_logged[metrics3-None]", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_saved_and_logged[metrics3-test]", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_saved_without_run_id", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_exists", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_does_not_exist", "tests/io/models/test_mlflow_model_registry_dataset.py::test_mlflow_model_registry_load_given_stage_or_version", "tests/io/models/test_mlflow_model_tracking_dataset.py::test_save_sklearn_flavor_with_run_id_and_already_active_run", "tests/io/models/test_mlflow_model_tracking_dataset.py::test_save_and_load_sklearn_flavor_with_run_id[False]", "tests/io/models/test_mlflow_model_tracking_dataset.py::test_save_and_load_sklearn_flavor_with_run_id[True]", "tests/io/models/test_mlflow_model_tracking_dataset.py::test_save_and_load_sklearn_flavor_without_run_id[False]", "tests/io/models/test_mlflow_model_tracking_dataset.py::test_save_and_load_sklearn_flavor_without_run_id[True]", "tests/io/models/test_mlflow_model_tracking_dataset.py::test_pyfunc_flavor_python_model_save_and_load[pipeline_ml_obj]", "tests/io/models/test_mlflow_model_tracking_dataset.py::test_pyfunc_flavor_python_model_save_and_load[pipeline_inference]", "tests/mlflow/test_kedro_pipeline_model.py::test_model_packaging_with_copy_mode[None-expected0]", "tests/mlflow/test_kedro_pipeline_model.py::test_model_packaging_with_copy_mode[assign-expected1]", "tests/mlflow/test_kedro_pipeline_model.py::test_model_packaging_with_copy_mode[deepcopy-expected2]", "tests/mlflow/test_kedro_pipeline_model.py::test_model_packaging_with_copy_mode[copy_mode3-expected3]", "tests/mlflow/test_kedro_pipeline_model.py::test_model_packaging_too_many_artifacts", "tests/mlflow/test_kedro_pipeline_model.py::test_model_packaging_missing_artifacts", "tests/mlflow/test_kedro_pipeline_model.py::test_kedro_pipeline_ml_loading_deepcopiable_catalog", "tests/mlflow/test_kedro_pipeline_model.py::test_kedro_pipeline_model_save_and_load[pipeline_inference_dummy-dummy_catalog-raw_data-result0]", "tests/mlflow/test_kedro_pipeline_model.py::test_kedro_pipeline_model_save_and_load[pipeline_inference_with_intermediary_artifacts-catalog_with_encoder-raw_data-result1]", "tests/mlflow/test_kedro_pipeline_model.py::test_kedro_pipeline_model_save_and_load[pipeline_inference_with_inputs_artifacts-catalog_with_stopwords-data-result2]", "tests/mlflow/test_kedro_pipeline_model.py::test_kedro_pipeline_model_save_and_load[pipeline_inference_with_parameters-catalog_with_parameters-data-result3]", "tests/pipeline/test_pipeline_ml.py::test_pipeline_ml_only_nodes_with_namespace", "tests/pipeline/test_pipeline_ml.py::test_pipeline_ml_substraction", "tests/pipeline/test_pipeline_ml.py::test_pipeline_ml_only_nodes_with_namespace", "tests/pipeline/test_pipeline_ml.py::test_pipeline_ml_substraction" ], "failure_text": { "tests/framework/cli/test_cli_modelify.py::test_modelify_with_infer_input_example[False]": "AssertionError: assert {'artifact_pa...: 'dataframe'} == {'artifact_pa...: 'dataframe'}\n Omitting 3 identical items, use -vv to show\n Differing items:\n {'serving_input_path': 'serving_input_example.json'} != {'serving_input_path': 'serving_input_payload.json'}\n Use -v to get more diff\nE AssertionError: assert {'artifact_pa...: 'dataframe'} == {'artifact_pa...: 'dataframe'}\n Omitting 3 identical items, use -vv to show\n Differing items:\n {'serving_input_path': 'serving_input_example.json'} != {'serving_input_path': 'serving_input_payload.json'}\n Use -v to get more diff", "tests/framework/cli/test_cli_modelify.py::test_modelify_with_infer_input_example[True]": "AssertionError: assert {'artifact_pa...: 'dataframe'} == {'artifact_pa...: 'dataframe'}\n Omitting 3 identical items, use -vv to show\n Differing items:\n {'serving_input_path': 'serving_input_example.json'} != {'serving_input_path': 'serving_input_payload.json'}\n Use -v to get more diff\nE AssertionError: assert {'artifact_pa...: 'dataframe'} == {'artifact_pa...: 'dataframe'}\n Omitting 3 identical items, use -vv to show\n Differing items:\n {'serving_input_path': 'serving_input_example.json'} != {'serving_input_path': 'serving_input_payload.json'}\n Use -v to get more diff", "tests/framework/hooks/test_hook_active_run.py::test_hook_active_run_exists_with_different_tracking_uri": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `829740221877882377` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 829740221877882377\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `829740221877882377` does not exist in the tracking server. Provide a valid experiment_id.", "tests/framework/hooks/test_hook_active_run.py::test_hook_use_active_run_if_exist_and_do_not_close": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `829740221877882377` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 829740221877882377\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `829740221877882377` does not exist in the tracking server. Provide a valid experiment_id.", "tests/framework/hooks/test_hook_deactivate_tracking.py::test_deactivated_tracking_but_not_for_given_pipeline": "kedro.io.core.DatasetError: Failed while saving data to dataset MlflowPickleDataset(backend=pickle, filepath=/tmp/pytest-of-root/pytest-1/test_deactivated_tracking_but_0/mock_package_name/fake_data.pkl, load_args={}, protocol=file, save_args={}).\n'super' object has no attribute '_save'\nE AttributeError: 'super' object has no attribute '_save'\n\nThe above exception was the direct cause of the following exception:\nE kedro.io.core.DatasetError: Failed while saving data to dataset MlflowPickleDataset(backend=pickle, filepath=/tmp/pytest-of-root/pytest-1/test_deactivated_tracking_but_0/mock_package_name/fake_data.pkl, load_args={}, protocol=file, save_args={}).\n 'super' object has no attribute '_save'", "tests/framework/hooks/test_hook_deactivate_tracking.py::test_deactivated_tracking_for_given_pipeline": "kedro.io.core.DatasetError: Failed while saving data to dataset MlflowPickleDataset(backend=pickle, filepath=/tmp/pytest-of-root/pytest-1/test_deactivated_tracking_for_0/mock_package_name/fake_data.pkl, load_args={}, protocol=file, save_args={}).\n'super' object has no attribute '_save'\nE AttributeError: 'super' object has no attribute '_save'\n\nThe above exception was the direct cause of the following exception:\nE kedro.io.core.DatasetError: Failed while saving data to dataset MlflowPickleDataset(backend=pickle, filepath=/tmp/pytest-of-root/pytest-1/test_deactivated_tracking_for_0/mock_package_name/fake_data.pkl, load_args={}, protocol=file, save_args={}).\n 'super' object has no attribute '_save'", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_artifact_dataset_load_with_run_id": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_artifact_dataset_load_with_run_id_and_artifact_path[None]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_artifact_dataset_load_with_run_id_and_artifact_path[folder/subfolder]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_artifact_dataset_load_with_run_id_and_artifact_path[folder]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_artifact_dataset_logging_deactivation": "kedro.io.core.DatasetError: Failed while saving data to dataset MlflowPickleDataset(backend=pickle, filepath=/tmp/pytest-of-root/pytest-1/test_artifact_dataset_logging_0/df1.csv, load_args={}, protocol=file, save_args={}).\n'super' object has no attribute '_save'\nE AttributeError: 'super' object has no attribute '_save'\n\nThe above exception was the direct cause of the following exception:\nE kedro.io.core.DatasetError: Failed while saving data to dataset MlflowPickleDataset(backend=pickle, filepath=/tmp/pytest-of-root/pytest-1/test_artifact_dataset_logging_0/df1.csv, load_args={}, protocol=file, save_args={}).\n 'super' object has no attribute '_save'", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_artifact_dataset_save_with_run_id[False]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_artifact_dataset_save_with_run_id[True]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_is_versioned_dataset_logged_correctly_in_mlflow": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_mlflow_csv_pkl_dataset_save_reload[CSVDataset-.csv-df1-None]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_mlflow_csv_pkl_dataset_save_reload[CSVDataset-.csv-df1-artifact_dir]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_mlflow_csv_pkl_dataset_save_reload[PickleDataset-.pkl-df1-None]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_mlflow_csv_pkl_dataset_save_reload[PickleDataset-.pkl-df1-artifact_dir]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_mlflow_csv_pkl_dataset_save_reload[pandas.CSVDataset-.csv-df1-None]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_mlflow_csv_pkl_dataset_save_reload[pandas.CSVDataset-.csv-df1-artifact_dir]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_mlflow_csv_pkl_dataset_save_reload[pickle.PickleDataset-.pkl-df1-None]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_mlflow_csv_pkl_dataset_save_reload[pickle.PickleDataset-.pkl-df1-artifact_dir]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_partitioned_dataset_save_and_reload[None]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/artifacts/test_mlflow_artifact_dataset.py::test_partitioned_dataset_save_and_reload[partitioned_data]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_load": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_load_given_step": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_load_last_given_step_if_duplicated": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_load_last_logged_by_default_if_unordered": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_logging_deactivation": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_append_mode": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_overwrite_mode": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_active_run[None]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_active_run[save_args1]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_active_run[save_args2]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_active_run[save_args3]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_active_run[save_args4]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_active_run[save_args5]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_run_id[None]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_run_id[save_args1]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_run_id[save_args2]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_run_id[save_args3]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_run_id[save_args4]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_metric_dataset_save_with_run_id[save_args5]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_dataset.py::test_mlflow_wrong_save_mode": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_logging_deactivation": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_save_load[dict-dict]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_save_load[dict-list]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_save_load[history-dict]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_save_load[history-history]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_save_load[history-list]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_save_load[list-dict]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metric_history_dataset.py::test_mlflow_metric_history_dataset_save_load[list-list]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_does_not_exist": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_exists": "kedro.io.core.DatasetError: Failed while saving data to dataset MlflowMetricsHistoryDataset(prefix=test_metric).\nThe provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\n\nThe above exception was the direct cause of the following exception:\nE kedro.io.core.DatasetError: Failed while saving data to dataset MlflowMetricsHistoryDataset(prefix=test_metric).\n The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_saved_and_logged[metrics-None]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_saved_and_logged[metrics-test]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_saved_and_logged[metrics2-None]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_saved_and_logged[metrics2-test]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_saved_and_logged[metrics3-None]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_saved_and_logged[metrics3-test]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/metrics/test_mlflow_metrics_dataset.py::test_mlflow_metrics_dataset_saved_without_run_id": "kedro.io.core.DatasetError: Failed while saving data to dataset MlflowMetricsHistoryDataset(prefix=test_metric).\nThe provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\n\nThe above exception was the direct cause of the following exception:\nE kedro.io.core.DatasetError: Failed while saving data to dataset MlflowMetricsHistoryDataset(prefix=test_metric).\n The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/models/test_mlflow_model_registry_dataset.py::test_mlflow_model_registry_load_given_stage_or_version": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: No Experiment with id=876034717817533601 exists\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/models/test_mlflow_model_tracking_dataset.py::test_pyfunc_flavor_python_model_save_and_load[pipeline_inference]": "kedro.io.core.DatasetError: Failed while saving data to dataset MlflowModelTrackingDataset(artifact_path=test_model, flavor=mlflow.pyfunc, load_args={}, pyfunc_workflow=python_model, save_args={'artifacts': {'model': file:///tmp/pytest-of-root/pytest-1/test_pyfunc_flavor_python_mode3/data/06_models/model.pkl}, 'conda_env': {'dependencies': ['kedro==0.18.11'], 'python': 3.10.0}, 'python_model': }).\nThe provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\n\nThe above exception was the direct cause of the following exception:\nE kedro.io.core.DatasetError: Failed while saving data to dataset MlflowModelTrackingDataset(artifact_path=test_model, flavor=mlflow.pyfunc, load_args={}, pyfunc_workflow=python_model, save_args={'artifacts': {'model': file:///tmp/pytest-of-root/pytest-1/test_pyfunc_flavor_python_mode3/data/06_models/model.pkl}, 'conda_env': {'dependencies': ['kedro==0.18.11'], 'python': 3.10.0}, 'python_model': }).\n The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/models/test_mlflow_model_tracking_dataset.py::test_pyfunc_flavor_python_model_save_and_load[pipeline_ml_obj]": "kedro.io.core.DatasetError: Failed while saving data to dataset MlflowModelTrackingDataset(artifact_path=test_model, flavor=mlflow.pyfunc, load_args={}, pyfunc_workflow=python_model, save_args={'artifacts': {'model': file:///tmp/pytest-of-root/pytest-1/test_pyfunc_flavor_python_mode2/data/06_models/model.pkl}, 'conda_env': {'dependencies': ['kedro==0.18.11'], 'python': 3.10.0}, 'python_model': }).\nThe provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\n\nThe above exception was the direct cause of the following exception:\nE kedro.io.core.DatasetError: Failed while saving data to dataset MlflowModelTrackingDataset(artifact_path=test_model, flavor=mlflow.pyfunc, load_args={}, pyfunc_workflow=python_model, save_args={'artifacts': {'model': file:///tmp/pytest-of-root/pytest-1/test_pyfunc_flavor_python_mode2/data/06_models/model.pkl}, 'conda_env': {'dependencies': ['kedro==0.18.11'], 'python': 3.10.0}, 'python_model': }).\n The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/models/test_mlflow_model_tracking_dataset.py::test_save_and_load_sklearn_flavor_with_run_id[False]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/models/test_mlflow_model_tracking_dataset.py::test_save_and_load_sklearn_flavor_with_run_id[True]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/models/test_mlflow_model_tracking_dataset.py::test_save_and_load_sklearn_flavor_without_run_id[False]": "kedro.io.core.DatasetError: Failed while saving data to dataset MlflowModelTrackingDataset(artifact_path=my_linreg, flavor=mlflow.sklearn, load_args={}, save_args={}).\nThe provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\n\nThe above exception was the direct cause of the following exception:\nE kedro.io.core.DatasetError: Failed while saving data to dataset MlflowModelTrackingDataset(artifact_path=my_linreg, flavor=mlflow.sklearn, load_args={}, save_args={}).\n The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/models/test_mlflow_model_tracking_dataset.py::test_save_and_load_sklearn_flavor_without_run_id[True]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/io/models/test_mlflow_model_tracking_dataset.py::test_save_sklearn_flavor_with_run_id_and_already_active_run": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/mlflow/test_kedro_pipeline_model.py::test_kedro_pipeline_ml_loading_deepcopiable_catalog": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/mlflow/test_kedro_pipeline_model.py::test_kedro_pipeline_model_save_and_load[pipeline_inference_dummy-dummy_catalog-raw_data-result0]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/mlflow/test_kedro_pipeline_model.py::test_kedro_pipeline_model_save_and_load[pipeline_inference_with_inputs_artifacts-catalog_with_stopwords-data-result2]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/mlflow/test_kedro_pipeline_model.py::test_kedro_pipeline_model_save_and_load[pipeline_inference_with_intermediary_artifacts-catalog_with_encoder-raw_data-result1]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/mlflow/test_kedro_pipeline_model.py::test_kedro_pipeline_model_save_and_load[pipeline_inference_with_parameters-catalog_with_parameters-data-result3]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/mlflow/test_kedro_pipeline_model.py::test_model_packaging_missing_artifacts": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/mlflow/test_kedro_pipeline_model.py::test_model_packaging_too_many_artifacts": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/mlflow/test_kedro_pipeline_model.py::test_model_packaging_with_copy_mode[None-expected0]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/mlflow/test_kedro_pipeline_model.py::test_model_packaging_with_copy_mode[assign-expected1]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/mlflow/test_kedro_pipeline_model.py::test_model_packaging_with_copy_mode[copy_mode3-expected3]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/mlflow/test_kedro_pipeline_model.py::test_model_packaging_with_copy_mode[deepcopy-expected2]": "mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.\nE mlflow.exceptions.MlflowException: Could not find experiment with ID 876034717817533601\n\nThe above exception was the direct cause of the following exception:\nE mlflow.exceptions.MlflowException: The provided MLFLOW_EXPERIMENT_ID environment variable value `876034717817533601` does not exist in the tracking server. Provide a valid experiment_id.", "tests/pipeline/test_pipeline_ml.py::test_pipeline_ml_only_nodes_with_namespace": "NotImplementedError: This method is not implemented because it does not make sense for 'PipelineML'. Manipulate directly the training pipeline and recreate the 'PipelineML' with 'pipeline_ml_factory' factory.\nE NotImplementedError: This method is not implemented because it does not make sense for 'PipelineML'. Manipulate directly the training pipeline and recreate the 'PipelineML' with 'pipeline_ml_factory' factory.", "tests/pipeline/test_pipeline_ml.py::test_pipeline_ml_substraction": "NotImplementedError: This method is not implemented because it does not make sense for 'PipelineML'. Manipulate directly the training pipeline and recreate the 'PipelineML' with 'pipeline_ml_factory' factory.\nE NotImplementedError: This method is not implemented because it does not make sense for 'PipelineML'. Manipulate directly the training pipeline and recreate the 'PipelineML' with 'pipeline_ml_factory' factory." }, "passed": [ "tests/test_utils.py::test_parse_requirements", "tests/config/test_get_mlflow_config.py::test_mlflow_config_default", "tests/config/test_get_mlflow_config.py::test_mlflow_config_in_uninitialized_project[None]", "tests/config/test_get_mlflow_config.py::test_mlflow_config_in_uninitialized_project[fake_project]", "tests/config/test_get_mlflow_config.py::test_mlflow_config_with_no_experiment_name", "tests/config/test_get_mlflow_config.py::test_mlflow_config_correctly_set[]", "tests/config/test_get_mlflow_config.py::test_mlflow_config_correctly_set[mock_settings_omega_config_loader_class]", "tests/config/test_get_mlflow_config.py::test_mlflow_config_interpolated_with_globals_resolver", "tests/config/test_get_mlflow_config.py::test_mlflow_config_with_request_header_provider", 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"numbers", "obstore", "opcode", "openai", "opentelemetry", "operator", "optparse", "os", "ossaudiodev", "packaging", "pathlib", "pdb", "pickle", "pickletools", "pipes", "pkgutil", "platform", "plistlib", "pluggy", "poplib", "posix", "posixpath", "pprint", "profile", "propcache", "pstats", "pty", "pwd", "py", "py_compile", "pyclbr", "pydantic", "pydantic_core", "pydoc", "pydoc_data", "pyexpat", "pygments", "pyproject.toml", "pytest", "pytest_asyncio", "python_multipart", "queue", "quopri", "random", "re", "readline", "reprlib", "requests", "requirements.txt", "resource", "rlcompleter", "runpy", "sched", "secrets", "select", "selectors", "setup", "shelve", "shlex", "shutil", "signal", "simple_websocket", "site", "six", "smtplib", "sndhdr", "sniffio", "socket", "socketio", "socketserver", "spwd", "sqlite3", "sre_compile", "sre_constants", "sre_parse", "ssl", "stat", "statistics", "string", "stringprep", "struct", "subprocess", "sunau", "symtable", "sys", "sysconfig", "syslog", "tabnanny", "tarfile", "telnetlib", "tempfile", "termios", "tests", "textwrap", "this", "threading", "time", "timeit", "tkinter", "token", "tokenize", "toml", "tomllib", "trace", "traceback", "tracemalloc", "truststore", "tty", "turtle", "turtledemo", "types", "typing", "typing_extensions", "typing_inspection", "unicodedata", "unittest", "urllib", "urllib3", "uu", "uuid", "venv", "warnings", "wave", "weakref", "webbrowser", "websocket", "winreg", "winsound", "wrapt", "wrapt-stubs", "wsgiref", "wsproto", "xdrlib", "xml", "xmlrpc", "yarl", "zipapp", "zipfile", "zipimport", "zlib", "zoneinfo" ] }, "skipped_ids": [ "tests/config/test_resolvers.py::test_resolve_random_name_is_idempotent" ], "spec_paths": [ "tests/pipeline/test_pipeline_ml.py" ], "target": [ "tests/pipeline/test_pipeline_ml.py::test_pipeline_ml_only_nodes_with_namespace", "tests/pipeline/test_pipeline_ml.py::test_pipeline_ml_substraction" ], "target_failure_text": { "tests/pipeline/test_pipeline_ml.py::test_pipeline_ml_only_nodes_with_namespace": "NotImplementedError: This method is not implemented because it does not make sense for 'PipelineML'. Manipulate directly the training pipeline and recreate the 'PipelineML' with 'pipeline_ml_factory' factory.\nE NotImplementedError: This method is not implemented because it does not make sense for 'PipelineML'. Manipulate directly the training pipeline and recreate the 'PipelineML' with 'pipeline_ml_factory' factory.", "tests/pipeline/test_pipeline_ml.py::test_pipeline_ml_substraction": "NotImplementedError: This method is not implemented because it does not make sense for 'PipelineML'. Manipulate directly the training pipeline and recreate the 'PipelineML' with 'pipeline_ml_factory' factory.\nE NotImplementedError: This method is not implemented because it does not make sense for 'PipelineML'. Manipulate directly the training pipeline and recreate the 'PipelineML' with 'pipeline_ml_factory' factory." }, "target_map": { "tests/pipeline/test_pipeline_ml.py::test_pipeline_ml_only_nodes_with_namespace": [ "tests/pipeline/test_pipeline_ml.py::test_pipeline_ml_only_nodes_with_namespace" ], "tests/pipeline/test_pipeline_ml.py::test_pipeline_ml_substraction": [ "tests/pipeline/test_pipeline_ml.py::test_pipeline_ml_substraction" ] }, "unstable": [] }, "checkpoint": { "digest": "188da50d-5ebf-47d1-90e7-2d7ca274275b", "id": "188da50d-5ebf-47d1-90e7-2d7ca274275b", "parent": "188da50d-5ebf-47d1-90e7-2d7ca274275b" }, "checkpoint_id": "188da50d-5ebf-47d1-90e7-2d7ca274275b", "cleanup_error": null, "cost": { "estimated_dollars": 0.1277229, "model_retries": {}, "models": { "nvidia/nemotron-3-super-120b-a12b": { "completion_tokens": 6873, "estimated_dollars": 0.1277229, "prompt_tokens": 405124, "reasoning_tokens": 0 } }, "planner_dollars": 0.0028437, "planner_tokens": 9231, "pricing_is_estimate": true, "sandbox_seconds": 550.7825114169326 }, "disclosure": { "executor_kind": "tokenfactory", "lock_sha256": "6ba1b46a6b333b8aa0d998992d24fa3b069d4fba507a7274db2b64abdb75991e", "model": { "base_url": "https://api.tokenfactory.nebius.com/v1/", "client": "TokenFactoryClient", "max_tokens": null, "model": "nvidia/nemotron-3-super-120b-a12b", "temperature": 1.0, "thinking": false, "top_p": 0.95 }, "pytest_config_digests": { "pyproject.toml": "0f4b0534dc08d489a15145982dfd4a6b0c3d0cb9fdc6a324e7a478610a3deb1d", "tests/conftest.py": "20a7038c8ea71a8926234c1cef77be6c4d4d89de294a37ac668eea6a04538567" }, "receipts_version": "0.0.1", "test_digests": { "tests/pipeline/__init__.py": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "tests/pipeline/test_pipeline_ml.py": "7dc6fb34b48abff4bad206aa753f6c794bd6582ba56d0cf3a95e0dfc42fc9400" } }, "final_verdict": { "branch_id": "agent1", "claim_audit": "unsupported", "claim_evidence": "claimed green but the final tree differs from the tree its last test run saw (receipt agent1-14)", "error": null, "error_kind": null, "predicates": [ { "evidence": "target tests passed: tests/pipeline/test_pipeline_ml.py::test_pipeline_ml_only_nodes_with_namespace, tests/pipeline/test_pipeline_ml.py::test_pipeline_ml_substraction", "id": "R1_fail_to_pass", "passed": true }, { "evidence": "147 baseline-passing tests still pass", "id": "R2_pass_to_pass", "passed": true }, { "evidence": "all 230 baseline tests collected; skips unchanged (1)", "id": "R3_no_shrink", "passed": true }, { "evidence": "patch touches 1 file(s), all in scope", "id": "R4_patch_scope", "passed": true }, { "evidence": "agent chain 188da50d-5ebf-47d1-90e7-2d7ca274275b -> adc53798-ff7c-4501-b5cb-9ec31c9da401 unbroken over 26 receipt(s); witness chain 188da50d-5ebf-47d1-90e7-2d7ca274275b -> 55fbb9be-dd63-4153-9e66-fa00fc0b27b2 unbroken over 2 receipt(s); applied digest matches", "id": "R5_provenance", "passed": true }, { "evidence": "claimed green but the final tree differs from the tree its last test run saw (receipt agent1-14)", "id": "R6_claim_audit", "passed": false } ], "status": "PASS" }, "input": { "appeals": 1, "budgets": { "baseline_limit_s": 600, "verification_timeout_s": 600, "worker": { "max_completion_tokens": 96000, "max_turns": 60, "max_wall_seconds": 1500.0, "prompt_token_budget": 160000 } }, "issue": "PipelineML breaks on kedro-viz 9.2.0\n## Description\r\n\r\nPipelineML breaks on kedro-viz 9.2.0\r\n\r\n## Context\r\n\r\nThe new kedro-viz 9.2.0 release heavily refactors graph generation for namespaced pipelines - https://github.com/kedro-org/kedro-viz/pull/1897. It now uses `only_nodes_with_namespace` and `__sub__` pipeline methods, but PipelineML doesn't have them implemented. \r\n\r\n## Steps to Reproduce\r\n\r\n1. Have a PipelineML specified in kedro project (by using `pipeline_ml_factory`)\r\n2. Run kedro viz\r\n\r\n## Expected Result\r\n\r\nKedro viz should run, and pipeline should display training nodes\r\n\r\n## Actual Result\r\n\r\nKedro viz cannot run at all\r\n\r\n```\r\n File \"repo/venv/lib/python3.10/site-packages/kedro_viz/data_access/repositories/modular_pipelines.py\", line 61, in populate_tree\r\n sub_pipeline = pipeline.only_nodes_with_namespace(modular_pipeline_id)\r\n File \"repo/venv/lib/python3.10/site-packages/kedro_mlflow/pipeline/pipeline_ml.py\", line 168, in only_nodes_with_namespace\r\n raise NotImplementedError(MSG_NOT_IMPLEMENTED)\r\nNotImplementedError: This method is not implemented because it does not make sense for 'PipelineML'. Manipulate directly the training pipeline and recreate the 'PipelineML' with 'pipeline_ml_factory' factory.\r\n\r\n```\r\n\r\n```\r\n File \"repo/venv/lib/python3.10/site-packages/kedro_viz/data_access/repositories/modular_pipelines.py\", line 62, in populate_tree\r\n rest_of_the_pipeline = pipeline - sub_pipeline\r\n File \"repo/venv/lib/python3.10/site-packages/kedro_mlflow/pipeline/pipeline_ml.py\", line 239, in __sub__\r\n raise NotImplementedError(MSG_NOT_IMPLEMENTED)\r\nNotImplementedError: This method is not implemented because it does not make sense for 'PipelineML'. Manipulate directly the training pipeline and recreate the 'PipelineML' with 'pipeline_ml_factory' factory.\r\n\r\n```\r\n\r\n\r\n## Workaround\r\n\r\nQuick and dirty implementation in PipelineML class:\r\n\r\n```py\r\ndef only_nodes_with_namespace(\r\n self, node_namespace: str\r\n) -> \"Pipeline\": # pragma: no cover\r\n return self.training.only_nodes_with_namespace(node_namespace)\r\n```\r\n\r\n```py\r\ndef __sub__(self, other): # pragma: no cover\r\n return self.training - other\r\n```\r\n\r\nCan't use `self._turn_pipeline_to_ml(...)` here as the pipelines are not consistent anymore\r\n\r\n## Your Environment\r\n\r\n\r\n\r\n* `kedro` and `kedro-mlflow` : 0.19.6 and 0.12.2\r\n* Python version used (`python -V`): 3.10.11\r\n* Operating system and version: M2 Sonoma 14.5\r\n\r\n## Does the bug also happen with the last version on master?\r\n\r\nProbably yes", "source": { "image": "docker.io/swerebenchv2/galileo-galilei-kedro-mlflow:585-61864f0", "platform": "linux/amd64", "python": "python", "setup": [ "python -c 'import base64; from pathlib import Path; Path('\"'\"'/tmp/receipts-galileo-galilei__kedro-mlflow-585-test.patch'\"'\"').write_bytes(base64.b64decode('\"'\"'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'\"'\"'))'", "git apply /tmp/receipts-galileo-galilei__kedro-mlflow-585-test.patch" ], "workdir": "/kedro-mlflow" }, "spec_paths": [ "tests/pipeline/test_pipeline_ml.py" ], "spec_tests": [ "tests/pipeline/test_pipeline_ml.py::test_pipeline_ml_only_nodes_with_namespace", "tests/pipeline/test_pipeline_ml.py::test_pipeline_ml_substraction" ], "suite_scope": "--no-header -rA --tb=line --color=no -p no:cacheprovider -W ignore::DeprecationWarning tests/pipeline/test_pipeline_ml.py" }, "plan": { "approach": "Add implementations for the two missing methods that delegate calls to the corresponding methods on the `training` pipeline attribute, returning plain `Pipeline` objects as expected by kedro-viz while preserving the original behavior for internal consistency checks via appropriate logging messages per the test expectations.", "files_to_edit": [ "kedro_mlflow/pipeline/pipeline_ml.py" ], "finish_reason": "stop", "hypothesis": "Implement the missing methods `only_nodes_with_namespace` and `__sub__` in the `PipelineML` class by delegating to the underlying `training` pipeline.", "usage": { "completion": 124, "prompt": 9107, "reasoning": 0 } }, "selected_patch_path": "attempts/1/filtered.diff", "snapshot_receipt_id": "base-7", "verdict_history": [ { "branch_id": "agent1", "claim_audit": "unsupported", "claim_evidence": "claimed green but the final tree differs from the tree its last test run saw (receipt agent1-14)", "error": null, "error_kind": null, "predicates": [ { "evidence": "target tests passed: tests/pipeline/test_pipeline_ml.py::test_pipeline_ml_only_nodes_with_namespace, tests/pipeline/test_pipeline_ml.py::test_pipeline_ml_substraction", "id": "R1_fail_to_pass", "passed": true }, { "evidence": "147 baseline-passing tests still pass", "id": "R2_pass_to_pass", "passed": true }, { "evidence": "all 230 baseline tests collected; skips unchanged (1)", "id": "R3_no_shrink", "passed": true }, { "evidence": "patch touches 1 file(s), all in scope", "id": "R4_patch_scope", "passed": true }, { "evidence": "agent chain 188da50d-5ebf-47d1-90e7-2d7ca274275b -> adc53798-ff7c-4501-b5cb-9ec31c9da401 unbroken over 26 receipt(s); witness chain 188da50d-5ebf-47d1-90e7-2d7ca274275b -> 55fbb9be-dd63-4153-9e66-fa00fc0b27b2 unbroken over 2 receipt(s); applied digest matches", "id": "R5_provenance", "passed": true }, { "evidence": "claimed green but the final tree differs from the tree its last test run saw (receipt agent1-14)", "id": "R6_claim_audit", "passed": false } ], "status": "PASS" } ], "verified_fix": true, "wall_time_s": 922.5725497079547 }