import inout as io

categories = {'news': 0, 'sport': 1, 'opinion': 2, 
    'business': 3, 'culture': 4, 'lifestyle': 5, 'removed': 6}


def trainingData(data, target):
    data = io.read(data)
    years = [x[0] for x in data]
    text = [x[2].replace('\n', '').replace(':', '') for x in data]
    target = [categories[x[0].replace('\n', '')] for x in io.read(target)]

    data = []
    for i in range(len(text)):
        data.append(' |Text ' + text[i] + ' |Year ' + years[i])

    return {'data': data, 'target': target}

def predictFuture(test):
    data = io.read(test + '/in.tsv')
    years = [x[0] for x in data]
    text = [x[2].replace('\n', '').replace(':', '') for x in data]

    data = []
    for i in range(len(text)):
        data.append(' |Text ' + text[i] + ' |Year ' + years[i])

    with open(test + '-in', 'w', encoding='utf-8') as f:
        for text in data:
            f.write('1' + text + '\n')


if __name__ == '__main__':
    ireland_news_train = trainingData('train/in.tsv.xz', 'train/expected.tsv.xz')

    with open('train/vw-in', 'w', encoding='utf-8') as f:
        for target, text in zip(ireland_news_train['target'], ireland_news_train['data']):
            f.write(str(target + 1) + text + '\n')
    
    predictFuture('dev-0')
    predictFuture('test-A')
    predictFuture('test-B')