"""
Pipeline Tests

Description: Pipeline tests ensures that the functionalities of the feature processing pipelines
work as expected to avoid feeding models incorrect data.


"""

from sklearn.svm import LinearSVR
from sklearn.tree import DecisionTreeRegressor
from sklearn.ensemble import BaggingRegressor, AdaBoostRegressor
from sklearn.linear_model import LinearRegression
from sklearn.pipeline import Pipeline
import pandas as pd
import numpy as np
import os
import pytest
from absl import logging

from forecasting_toolkit.models.pipelines.inference.pre_release import (
    gbt_regressor_inference_pipeline
)

@pytest.fixture()
def test_params():
    return {"store_id": 286, 
                "country_code_id": 1, 
                "model_path": "./default_model.joblib"}


def test_gbt_regressor_inference_pipeline(test_params):
    """ test gbt model by loading it to make sure all is well"""
    logging.set_verbosity(logging.DEBUG)
    lst_forecasts = gbt_regressor_inference_pipeline(**test_params)

    # make sure we got a list back
    assert isinstance(lst_forecasts, list)
    # make sure we have forecasts
    assert len(lst_forecasts) > 0