import re
import json

gender_lexicons = json.load(open("config/gender_lexicons.json", "r"))


def count_male_terms(text, male_terms):
    pattern = r"\b({})\b".format("|".join(male_terms))
    match = re.findall(pattern, str(text))
    return len(match)


def count_female_terms(text, female_terms):
    pattern = r"\b({})\b".format("|".join(female_terms))
    match = re.findall(pattern, str(text))
    return len(match)


def get_gender_tag(count_m_term, count_f_term):
    tag = ""
    if count_m_term == 0 and count_f_term == 0:
        tag = "No Gender"

    elif count_m_term == count_f_term:
        tag = "Equal Gender"

    elif count_m_term > count_f_term:
        m_proportion = (count_m_term / (count_m_term + count_f_term)) * 100
        if m_proportion >= 50 and m_proportion < 75:
            tag = "Male Positive Gender"
        elif m_proportion >= 75:
            tag = "Male Strongly Positive Gender"

    elif count_m_term < count_f_term:
        f_proportion = (count_f_term / (count_m_term + count_f_term)) * 100
        if f_proportion >= 50 and f_proportion < 75:
            tag = "Female Positive Gender"
        elif f_proportion >= 75:
            tag = "Female Strongly Positive Gender"

    return tag


def get_pg_spg(sample_df):
    count_no_gender_sentences = sample_df[sample_df["gender_cat"] == "No Gender"][
        "gender_cat"
    ].count()

    count_gender_sentences = sample_df[sample_df["gender_cat"] != "No Gender"][
        "gender_cat"
    ].count()
    count_equal_gender = sample_df[sample_df["gender_cat"] == "Equal Gender"][
        "gender_cat"
    ].count()

    count_male_pg = sample_df[sample_df["gender_cat"] == "Male Positive Gender"][
        "gender_cat"
    ].count()
    count_male_spg = sample_df[
        sample_df["gender_cat"] == "Male Strongly Positive Gender"
    ]["gender_cat"].count()

    count_female_pg = sample_df[sample_df["gender_cat"] == "Female Positive Gender"][
        "gender_cat"
    ].count()
    count_female_spg = sample_df[
        sample_df["gender_cat"] == "Female Stronly Positive Gender"
    ]["gender_cat"].count()

    return {
        "gender": str(count_gender_sentences),
        "no gender": str(count_no_gender_sentences),
        "equal gender": str(count_equal_gender),
        "female pg": str(count_female_pg),
        "male pg": str(count_male_pg),
        "female spg": str(count_female_spg),
        "male spg": str(count_male_spg),
    }


def eval_gender_divide(data):
    male_terms = gender_lexicons.get("male_lexicons")
    female_terms = gender_lexicons.get("female_lexicons")

    data[data.columns[0]] = data[data.columns[0]].str.lower().str.strip()

    data["count_male_term"] = data.apply(
        lambda x: count_male_terms(x[data.columns[0]], male_terms), axis=1
    )
    data["count_female_term"] = data.apply(
        lambda x: count_female_terms(x[:], female_terms), axis=1
    )

    data["gender_cat"] = data.apply(
        lambda row: get_gender_tag(row["count_male_term"], row["count_female_term"]),
        axis=1,
    )

    collection = get_pg_spg(data)
    return collection