Bulk Generating Cloze Deletions based on Tatoeba sentences and word frequency lists

[wizzie]

It threw the following error

Error:
writerow() takes exactly one argument (4 given)

which I fixed by adding "[" and "]" around the writerow arguments. Then it threw

Error:
NameError: name 'random' is not defined

which I fixed by adding "import random" and it now works.

Thank you so much for your help, it is much appreciated! You saved me many hours of manual work.
The final code is as follows.

import csv

import string

import random

def find_cloze(sentence, frequency_list):
    translator = str.maketrans(string.punctuation, ' '*len(string.punctuation))
    sentence = sentence.translate(translator)

    max_frequency = 20001  # 50k frequency list cut down to 20,000 entries
    min_frequency = max_frequency

    min_word = None
    valid_words = []
    for word in sentence.split():
        if word.isupper() or word.istitle():
            continue  # Skip proper nouns
        if len(word) <= 2:
            continue  # Skip tiny words

        valid_words.append(word)

        word_frequency = int(frequency_list.get(word.lower(), max_frequency))
        if word_frequency < min_frequency:
            min_word = word
            min_frequency = word_frequency

    if min_word:
        return min_word
    else:
        if valid_words:
            return random.choice(valid_words)
        else:
            return None


def make_index(path, delimiter, value=1):
    d = dict()
    with open(path, newline='') as f:
        reader = csv.reader(f, delimiter=delimiter)
        for row in reader:
            d[row[0]] = row[value]
    return d


def generate(target_file, native_file, links_file, frequency_file):
    print("Making indexes ...")

    target = make_index(target_file, '\t', value=2)
    native = make_index(native_file, '\t', value=2)
    links = make_index(links_file, '\t')

    # Make index between word and usage frequency
    frequency = make_index(frequency_file, ' ')

    print("Generating clozes ...")
    with open("out.csv", 'w', newline='') as outfile:
        writer = csv.writer(
            outfile,
            delimiter='\t',
            quotechar='|',
            quoting=csv.QUOTE_MINIMAL)

        # For each target sentence
        for target_number, target_sentence in target.items():
            # Lookup native translation
            native_number = links.get(target_number)
            if not native_number:
                continue  # If no native translation, skip

            native_sentence = native.get(native_number)
            if not native_sentence:
                continue  # If no native translation, skip

            # Find the cloze word
            target_cloze_word = find_cloze(target_sentence, frequency)
            if not target_cloze_word:
                continue  # If no cloze word, skip

            clozed = target_sentence.replace(
                target_cloze_word,
                '{{{{c1::{}}}}}'.format(target_cloze_word)
                )

            writer.writerow(
                [target_number,
                clozed,
                native_number,
                native_sentence])

    print("Done.")

generate('target.csv',
         'native.csv',
         'links.csv',
         'frequency.txt')

Edit: Changed code to be "language agnostic".