#!/usr/bin/python3

import pandas as pd
import csv
import pickle

def predict():
    dev0 = pd.read_csv("dev-0/in.tsv", delimiter="\t", header=None, names=["document","date"], quoting=csv.QUOTE_NONE)
    testA = pd.read_csv("test-A/in.tsv", delimiter="\t", header=None, names=["document","date"], quoting=csv.QUOTE_NONE)
    devdoc = dev["document"]
    testdoc = testA["document"]

    clf = pickle.load(open("clf.model", "rb"))
    vectorizer = pickle.load(open("vectorizer.model", "rb"))
    
    dev0_vectorizer = vectorizer.transform(devdoc)
    testA_vectorizer = vectorizer.transform(testdoc)

    y_dev = clf.predict(dev0_vectorizer)
    y_test = clf.predict(testA_vectorizer)

    with open("dev-0/out.tsv", "w") as devout:
        for line in y_dev:
            devout.write(line+"\n")

    with open("test-A/out.tsv", "w") as testaout:
        for line in y_test:
            testaout.write(line+"\n")

predict()