import pandas as pd
from fuzzywuzzy import process
from typing import List


def get_popular_agriculture(
    df: pd.DataFrame,
    region: str,
    surface_parc: str = None,
    groups_agri: List[str] = None,
):  # surface en hectare
    unique_regions = df["REGION"].unique().tolist()
    region, _ = process.extractOne(region, unique_regions)
    df = df[df["REGION"] == region]
    if groups_agri != None:
        unique_agri_group = df["LIBELLE_GROUPE_CULTURE"].unique().tolist()
        groups_agri_new = []
        for group_culture in groups_agri:
            groups_agri_new.append(process.extractOne(group_culture, unique_agri_group)[0])
        df = df[df["LIBELLE_GROUPE_CULTURE"].isin(groups_agri_new)]
    if surface_parc != None:
        popular_cultures = df["LIBELLE_CULTURE"].value_counts().head(10).index
        df = df[df["LIBELLE_CULTURE"].isin(popular_cultures)]
        df["proximity"] = abs(df["SURF_PARC"] - surface_parc)
        sorted_df = df.sort_values(by="proximity").drop(columns="proximity")
        return popular_cultures, sorted_df[["LIBELLE_CULTURE","LIBELLE_GROUPE_CULTURE","SURF_PARC"]]
    popular_cultures = df["LIBELLE_CULTURE"].value_counts().head(10).index
    df = df[df["LIBELLE_CULTURE"].isin(popular_cultures)]
    return popular_cultures, df[["LIBELLE_CULTURE","LIBELLE_GROUPE_CULTURE","SURF_PARC"]]