import csv
from Levenshtein import distance as lev
import pandas as pd
import itertools
import sys

peopleCsv = "/Users/normrasmussen/Downloads/TalkspaceAllLearners.csv"


def readCsv(peopleCsv):
    people = []
    readExport = pd.read_csv(
        peopleCsv,
        usecols=["Learner Full Name", "Email"],
        skipinitialspace=True,
        # index_col=True,
    )
    people.extend(readExport["Email"].tolist())
    startCompare(peopleCsv, people, readExport)


# itertools combinations
def startCompare(peopleCsv, people, readExport):
    email1 = []
    email2 = []
    for (
        name1,
        name2,
    ) in itertools.combinations(people, 2):
        # print(name1, name2) - prints all pairs, working so far.
        distance = lev(name1, name2)
        # print(distance) - successfully returns numbers
        if distance > 0 and distance < 2:
            email1.append(name1)
            email2.append(name2)
    writenewColumn(email1, email2, peopleCsv, readExport)


def writenewColumn(email1, email2, peopleCsv, readExport):
    df = pd.DataFrame(readExport)
    print(df)
    df["Email1"] = pd.Series(email1)
    df["Email2"] = pd.Series(email2)
    df.drop_duplicates("Email1", inplace=True)
    df.drop_duplicates("Email2", inplace=True)
    df.drop_duplicates(subset=["Email1", "Email2"])
    # keep = 'last').reset_index(drop=True)
    writeLst = df.to_csv(
        "/Users/normrasmussen/Downloads/TalkspaceDupes_singlechange.csv",
    )


if __name__ == "__main__":
    readCsv(peopleCsv)