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.

input-sample.json

@@ -0,0 +1,37 @@
+{
+  "experiment_run_id": 1001,
+  "variable_columns": ["feature_a", "feature_b"],
+  "target_variable": "target",
+  "bucket_name": "model-training",
+  "file_name": "training_data.csv",
+  "line_separator": ",",
+  "decimal_separator": ".",
+  "train_size": 80,
+  "shuffle": true,
+  "random_state": 42,
+  "model_name": "Linear Regression",
+  "model_type": "linear_regression",
+  "data_model_kwargs": {
+    "lag_train": {
+      "feature_a": 0,
+      "feature_b": 0
+    },
+    "lag_val": {
+      "feature_a": 0,
+      "feature_b": 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": "Standard Scaler"
+  },
+  "opt_params": {}
+}