removed all tracy related code (#524)

* removed all tracy related code Signed-off-by: Jonita Ruiter <[email protected]> * removed the left over tracy things Signed-off-by: Jonita Ruiter <[email protected]> * fixed black format code error Signed-off-by: Jonita Ruiter <[email protected]> * lint fail fix unused local variable Signed-off-by: Jonita Ruiter <[email protected]> * lint fail fix unused local variable and isorted all files Signed-off-by: Jonita Ruiter <[email protected]> --------- Signed-off-by: Jonita Ruiter <[email protected]>
OpenSTEF · Mar 27, 2024 · 5f668dd · 5f668dd
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diff --git a/docs/sql_database_diagram.rst b/docs/sql_database_diagram.rst
@@ -299,27 +299,6 @@ API key to retrieve systems measurements.
 | apiKey         | chr            | API key value   | uuid-Measurements |
 +----------------+----------------+-----------------+-------------------+
 
-todolist
-^^^^^^^^
-
-+----------------------+-------------+----------------+----------------+
-| **Name**             | **Type**    | **Comment**    | **Example**    |
-+======================+=============+================+================+
-| id                   | int         | id of the job  |                |
-+----------------------+-------------+----------------+----------------+
-| created              | datetime    |                |                |
-+----------------------+-------------+----------------+----------------+
-| function             | chr         | functions to   |                |
-|                      |             | execute        |                |
-+----------------------+-------------+----------------+----------------+
-| args                 | chr         | arguments of   |                |
-|                      |             | the functions  |                |
-+----------------------+-------------+----------------+----------------+
-| inprogress           | int         |                |                |
-+----------------------+-------------+----------------+----------------+
-
-The todolist table stores jobs that are picked up by the tracy procces that is run every 5 minutes via a CRON job. This makes it possible to run pipelines manually by adding the respective job to the todo list.
-
 weatherforecastlocations
 ^^^^^^^^^^^^^^^^^^^^^^^^
 Contains the locations of the weather stations. These are used when retrieving weather data for a prediction.

diff --git a/openstef/data_classes/data_prep.py b/openstef/data_classes/data_prep.py
@@ -5,7 +5,7 @@
 import inspect
 import json
 from importlib import import_module
-from typing import Any, Sequence, Union, TypeVar
+from typing import Any, Sequence, TypeVar, Union
 
 from pydantic.v1 import BaseModel
 

diff --git a/openstef/data_classes/prediction_job.py b/openstef/data_classes/prediction_job.py
@@ -6,9 +6,9 @@
 
 from pydantic.v1 import BaseModel
 
+from openstef.data_classes.data_prep import DataPrepDataClass
 from openstef.data_classes.model_specifications import ModelSpecificationDataClass
 from openstef.data_classes.split_function import SplitFuncDataClass
-from openstef.data_classes.data_prep import DataPrepDataClass
 from openstef.enums import PipelineType
 
 

diff --git a/openstef/enums.py b/openstef/enums.py
@@ -20,12 +20,6 @@ class ForecastType(Enum):
     BASECASE = "basecase"
 
 
-class TracyJobResult(Enum):
-    SUCCESS = "success"
-    FAILED = "failed"
-    UNKNOWN = "unknown"
-
-
 class PipelineType(Enum):
     FORECAST = "forecast"
     TRAIN = "train"

diff --git a/openstef/feature_engineering/data_preparation.py b/openstef/feature_engineering/data_preparation.py
@@ -1,24 +1,24 @@
 # SPDX-FileCopyrightText: 2017-2023 Alliander N.V. <[email protected]> # noqa E501>
 #
 # SPDX-License-Identifier: MPL-2.0
-import structlog
-
 from abc import ABC, abstractmethod
+from datetime import timedelta
 from typing import Optional
 
 import pandas as pd
-from datetime import timedelta
+import structlog
+
 from openstef.data_classes.model_specifications import ModelSpecificationDataClass
 from openstef.data_classes.prediction_job import PredictionJobDataClass
-from openstef.model.regressors.regressor import OpenstfRegressor
 from openstef.feature_engineering.feature_applicator import (
-    TrainFeatureApplicator,
     OperationalPredictFeatureApplicator,
+    TrainFeatureApplicator,
 )
 from openstef.feature_engineering.general import (
     enforce_feature_order,
     remove_non_requested_feature_columns,
 )
+from openstef.model.regressors.regressor import OpenstfRegressor
 from openstef.pipeline.utils import generate_forecast_datetime_range
 
 

diff --git a/openstef/model/model_creator.py b/openstef/model/model_creator.py
@@ -6,13 +6,13 @@
 import structlog
 
 from openstef.enums import MLModelType
+from openstef.model.regressors.arima import ARIMAOpenstfRegressor
 from openstef.model.regressors.custom_regressor import is_custom_type, load_custom_model
 from openstef.model.regressors.lgbm import LGBMOpenstfRegressor
 from openstef.model.regressors.linear import LinearOpenstfRegressor
 from openstef.model.regressors.regressor import OpenstfRegressor
 from openstef.model.regressors.xgb import XGBOpenstfRegressor
 from openstef.model.regressors.xgb_quantile import XGBQuantileOpenstfRegressor
-from openstef.model.regressors.arima import ARIMAOpenstfRegressor
 
 logger = structlog.get_logger(__name__)
 

diff --git a/openstef/model/objective_creator.py b/openstef/model/objective_creator.py
@@ -6,12 +6,12 @@
 
 from openstef.enums import MLModelType
 from openstef.model.objective import (
+    ARIMARegressorObjective,
     LGBRegressorObjective,
     LinearRegressorObjective,
     RegressorObjective,
     XGBQuantileRegressorObjective,
     XGBRegressorObjective,
-    ARIMARegressorObjective,
 )
 from openstef.model.regressors.custom_regressor import (
     create_custom_objective,

diff --git a/openstef/model/regressors/arima.py b/openstef/model/regressors/arima.py
@@ -5,9 +5,9 @@
 import numpy as np
 import pandas as pd
 import statsmodels.api as sm
-
 from sklearn.metrics import r2_score
 from sklearn.model_selection import TimeSeriesSplit
+
 from openstef.model.regressors.regressor import OpenstfRegressor
 
 

diff --git a/openstef/monitoring/performance_meter.py b/openstef/monitoring/performance_meter.py
@@ -20,8 +20,7 @@ def start_level(self, level_label: str, level_name: str, **kwargs):
 
         Args:
             level_label: The label of the new level. This could i.e. be 'task'
-            level_name: The name of the specified level. This could i.e. be
-                'tracy_todo'
+            level_name: The name of the specified level.
             **kwargs: Any other kwargs are appended to the logging.
 
         Returns:

diff --git a/openstef/pipeline/create_basecase_forecast.py b/openstef/pipeline/create_basecase_forecast.py
@@ -7,7 +7,7 @@
 import structlog
 
 from openstef.data_classes.prediction_job import PredictionJobDataClass
-from openstef.exceptions import NoRealisedLoadError, InputDataOngoingZeroFlatlinerError
+from openstef.exceptions import InputDataOngoingZeroFlatlinerError, NoRealisedLoadError
 from openstef.feature_engineering.feature_applicator import (
     OperationalPredictFeatureApplicator,
 )

diff --git a/openstef/pipeline/create_component_forecast.py b/openstef/pipeline/create_component_forecast.py
@@ -3,6 +3,7 @@
 # SPDX-License-Identifier: MPL-2.0
 
 import joblib
+import numpy as np
 import pandas as pd
 import structlog
 
@@ -12,8 +13,6 @@
 from openstef.enums import ForecastType
 from openstef.model.regressors.dazls import Dazls
 
-import numpy as np
-
 # Set the path for the Dazls stored model
 DAZLS_STORED = str(
     PROJECT_ROOT / "openstef" / "data" / "dazls_model_3.4.7" / "dazls_stored_3.4.7_"

diff --git a/openstef/pipeline/optimize_hyperparameters.py b/openstef/pipeline/optimize_hyperparameters.py
@@ -21,12 +21,12 @@
 from openstef.model.objective_creator import ObjectiveCreator
 from openstef.model.regressors.regressor import OpenstfRegressor
 from openstef.model.serializer import MLflowSerializer
+from openstef.model_selection.model_selection import split_data_train_validation_test
 from openstef.pipeline.train_model import (
     DEFAULT_TRAIN_HORIZONS_HOURS,
     train_model_pipeline_core,
 )
 from openstef.validation import validation
-from openstef.model_selection.model_selection import split_data_train_validation_test
 
 optuna.logging.enable_propagation()  # Propagate logs to the root logger.
 optuna.logging.disable_default_handler()  # Stop showing logs in sys.stderr.

diff --git a/openstef/tasks/calculate_kpi.py b/openstef/tasks/calculate_kpi.py
@@ -106,10 +106,6 @@ def check_kpi_task(
             rMAE=kpis["47.0h"]["rMAE"],
             retraining_threshold=THRESHOLD_RETRAINING,
         )
-        function_name = "train_model"
-
-        context.logger.info("Adding tracy job", function=function_name)
-        context.database.ktp_api.add_tracy_job(pj["id"], function=function_name)
 
     if kpis["47.0h"]["rMAE"] > THRESHOLD_OPTIMIZING:
         context.logger.warning(
@@ -118,9 +114,6 @@ def check_kpi_task(
             rMAE=kpis["47.0h"]["rMAE"],
             optimizing_threshold=THRESHOLD_OPTIMIZING,
         )
-        function_name = "optimize_hyperparameters"
-        context.logger.info("Adding tracy job", function=function_name)
-        context.database.ktp_api.add_tracy_job(pj["id"], function=function_name)
 
 
 def calc_kpi_for_specific_pid(

diff --git a/openstef/tasks/create_components_forecast.py b/openstef/tasks/create_components_forecast.py
@@ -24,8 +24,8 @@
 from datetime import datetime, timedelta, timezone
 from pathlib import Path
 
-import structlog
 import pandas as pd
+import structlog
 
 from openstef.data_classes.prediction_job import PredictionJobDataClass
 from openstef.enums import MLModelType

diff --git a/openstef/tasks/run_tracy.py b/openstef/tasks/run_tracy.py
diff --git a/openstef/tasks/train_model.py b/openstef/tasks/train_model.py
@@ -23,22 +23,20 @@
 from pathlib import Path
 
 from openstef.data_classes.prediction_job import PredictionJobDataClass
-
 from openstef.enums import MLModelType, PipelineType
 from openstef.exceptions import (
-    SkipSaveTrainingForecasts,
     InputDataOngoingZeroFlatlinerError,
+    SkipSaveTrainingForecasts,
 )
+from openstef.model.serializer import MLflowSerializer
 from openstef.pipeline.train_model import (
+    MAXIMUM_MODEL_AGE,
     train_model_pipeline,
     train_pipeline_step_load_model,
-    MAXIMUM_MODEL_AGE,
 )
 from openstef.tasks.utils.predictionjobloop import PredictionJobLoop
 from openstef.tasks.utils.taskcontext import TaskContext
 
-from openstef.model.serializer import MLflowSerializer
-
 TRAINING_PERIOD_DAYS: int = 120
 DEFAULT_CHECK_MODEL_AGE: bool = True