Parse CSV vocab output from ThaiDict app

import_khamsapt.py

# Parse CSV vocab output from ThaiDict app
import csv
import sys

# from tango.tango import model

def row_to_vocab(row):
    v = {
        'headword': row['th'], 
        'pronunciation': row['pron'],
        'morphology': row['pos'],
        'source': row['link']}

    # use bullet points if multiple definitions were provided
    defs = row['en'].split(' | ')
    def_text = '' if len(defs) == 1 else '• '
    def_text += '\n• '.join(defs)
    v['definition'] = def_text

    notes = []
    if row['cat']:
        notes.append('category: ' + row['cat'])
    if row['usage']:
        notes.append('usage: ' + row['usage'])
    v['notes'] = '\n'.join(notes)
    return v
    # model.add_tango('th', v)


def read_vocab(file):
    vocab = []
    with open(file) as f:
        reader = csv.DictReader(f, dialect='unix', fieldnames=['en', 'th', 'pron', 'usage', 'pos', 'cat', 'link'])
        for row in reader:
            vocab.append(row_to_vocab(row))
    return vocab


def main(argv):
    if len(argv) != 2:
        print('Usage: python3 import_thaidict.py <csv file>')
        sys.exit()
    vocab = read_vocab(argv[1])
    print(vocab)


if __name__ == '__main__':
    main(sys.argv)

Next step: import into tango; tango.tango.model.get_model(); model.add_tango('th', {headword, pronunciation, morphology, definition, example, image_url, image_base64, notes, source}`

Next step: uncomment import statement and actually run it. Need to finish exporting favorites first.