import math import os from deployment_pima.config import config as model_config from deployment_pima.predict import make_predictions from deployment_pima.processing.pipeline_helper import load_data import pandas as pd import pytest from api import config _logger = config.get_logger(logger_name=__name__) @pytest.mark.differential def test_model_prediction_differential( *, save_file: str = 'test_data_predictions.csv'): """ This test compares the prediction result similarity of the current model with the previous model's results. """ # Given # Load the saved previous model predictions previous_model_df = pd.read_csv( os.path.join(config.PACKAGE_ROOT, 'tests', save_file)) previous_model_predictions = previous_model_df.predictions.values test_data = load_data(file_name=model_config.DATA_FILE) multiple_test_input = test_data[:20]
# -*- coding: utf-8 -*- """ Created on Wed Aug 12 22:14:31 2020 @author: rkbra """ from flask import Flask from api.config import get_logger _logger = get_logger(logger_name=__name__) def create_app(*, config_object) -> Flask: """Create a flask app instance.""" flask_app = Flask('ml_api') flask_app.config.from_object(config_object) # import blueprints from api.controller import prediction_app flask_app.register_blueprint(prediction_app) _logger.debug('Application instance created') return flask_app
from flask import Flask from api.config import get_logger _logger = get_logger(__name__) def create_app(*,config_object) -> Flask: flask_app = Flask('ml-api') flask_app.config.from_object(config_object) from api.controller import prediction_app flask_app.register_blueprint(prediction_app) _logger.debug('Application instance created') return flask_app