from typing import List
import pandas as pd
from absl import logging
from dill import dump, load
import requests
import os
from sklearn.pipeline import Pipeline


def has_columns(columns: List[str], dataframe: pd.DataFrame) -> bool:
    """
    Checks if a dataframe has the columns specificed in 'columns'

    params:
        columns (List[str]) - list of columns
        dataframe (pd.DataFrame) - pandas DataFrame to check columns againsts

    returns:
        bool - True - if the dataframe has the columns, false otherwise
    """
    return set(dataframe.columns).issuperset(set(columns))


def check_mlflow_connection(mlflow_tracking_server_uri: str) -> bool:
    """
    Checks mlflow tracking server connection

    params:
        mlflow_tracking_server_uri (str) - mlflow tracking server

    returns:
        bool - returns True if there is an active connection, 
                and False otherwise.
    """
    res = requests.get(os.path.join(mlflow_tracking_server_uri, "api/2.0/mlflow/experiments/list"))
    return res.status_code == 200


def load_sklearn_model(model_path):
    """
    Loads a serialized sklearn Model

    params:
        model_path (str) - Model Path

    returns:
        model (sklearn.Pipeline) - an sklearn pipeline which encodes
                                the fitted feature processing pipeline
                                and the trained model
    """
    try:
        with open(model_path, 'rb') as file_obj:
            return load(file_obj)
    except Exception as err:
        logging.error(err)


def save_sklearn_model(model: Pipeline, model_path: str) -> None:
    """
    Saves an sklearn model

    params:
        model (sklearn Pipeline) - sklearn pipeline which contains
                                    the fitted feature processing pipeline
                                    and the fitted model
    returns:
        None
    """
    try:
        with open(model_path, 'wb') as file_obj:
            dump(model, file_obj)
    except Exception as err:
        logging.error(err)