feat: enhance test scenarios and configuration for regression models

- Updated `pyproject.toml` to include new linting rules for end-to-end tests.
- Modified `requirements-dev.txt` to add dependencies for E2E testing with `testcontainers` and `requests`.
- Refactored multiple JSON test scenario files to standardize structure, including new fields for `experiment_run_id`, `bucket_name`, and `file_name`.
- Improved model training parameters in `train_model_params.py` to use `experiment_name` directly.
- Adjusted `data_manager_repository.py` to utilize the updated `experiment_name` for logging.

These changes improve the organization and clarity of regression model tests and enhance the overall testing framework.

docs/test-scenarios/10-linear-regression-with-ar.json

@@ -1,30 +1,40 @@
 {
   "_description": "Regressão linear com variável autoregressiva (AR)",
-  "experimentName": "test-linear-with-ar",
-  "username": "bruno.domingues@aignosi.com.br",
-  "modelName": "Linear Regression",
-  "targetVariable": "03CV020/CORRENTE_N_M1_PV(Value)",
-  "variableColumns": ["303-WIT-200(Value)"],
-  "lagTrain": {"303-WIT-200(Value)": 0},
-  "lagVal": {"303-WIT-200(Value)": 0},
-  "remStaticWin": false,
-  "lowLim": {},
-  "uppLim": {},
-  "window": 0,
-  "useScaler": false,
-  "includeAr": true,
-  "trainSize": 80,
+  "experiment_run_id": 1010,
+  "variable_columns": [
+    "303-WIT-200(Value)"
+  ],
+  "target_variable": "03CV020/CORRENTE_N_M1_PV(Value)",
+  "bucket_name": "model-training",
+  "file_name": "training_data.csv",
+  "line_separator": ",",
+  "decimal_separator": ".",
+  "date_column": "timestamp",
+  "date_format": "yyyy-MM-dd HH:mm:ss",
+  "train_size": 80,
   "shuffle": true,
-  "lineSeparator": ",",
-  "decimalSeparator": ".",
-  "dateColumn": "timestamp",
-  "dateFormat": "yyyy-MM-dd HH:mm:ss",
-  "removedIntervals": [],
-  "degree": 1,
-  "interactionOnly": false,
-  "nanTreatment": "drop",
-  "startDate": null,
-  "endDate": null,
-  "scalerName": "None",
-  "supportFilters": {}
-}
+  "random_state": 42,
+  "model_name": "Linear Regression",
+  "model_type": "linear_regression",
+  "data_model_kwargs": {
+    "lag_train": {
+      "303-WIT-200(Value)": 0
+    },
+    "lag_val": {
+      "303-WIT-200(Value)": 0
+    },
+    "nan_treatment": "drop",
+    "rem_static_win": false,
+    "static_threshold": null,
+    "start_date": null,
+    "end_date": null,
+    "support_filters": {},
+    "removed_intervals": []
+  },
+  "model_kwargs": {
+    "degree": 1,
+    "interaction_only": false,
+    "scaler_name": "None"
+  },
+  "opt_params": {}
+}