import pythonbible as bible
import random, argparse, datetime
import pandas as pd

def generate_readplan(start_date):
    book_groups = bible.BOOK_GROUPS
    reading_list = []

    # Drop OLD TESTAMENT and NEW TESTAMENT from book_groups
    all_books = list(set(book_groups['Old Testament'])) + list(set(book_groups['New Testament']))
    book_groups.pop('Old Testament', 'New Testament')

    # Randomly order book groups
    book_groups = dict(sorted(book_groups.items(), key=lambda x: random.random()))
    
    for group in book_groups.keys():
        reading_list.extend(book_groups[group])
        reading_list = list(set(reading_list))

    # Find missing books in reading_list
    missing_books = list(set(all_books) - set(reading_list))

    # Randomly order missing books
    missing_books = sorted(missing_books, key=lambda x: random.random())

    # Insert missing books in reading_list
    for book in missing_books:
        reading_list.insert(random.randint(0, len(reading_list)), book)

    total_chapters = sum([bible.get_number_of_chapters(reading_list[i]) for i in range(len(reading_list))])
    chapters_per_day = total_chapters // 365 + 1

    df = pd.DataFrame(columns=['Book', 'Chapters'])
    for book in reading_list:
        df = pd.concat([df, pd.DataFrame({'Book': [book.title], 'Chapters': [bible.get_number_of_chapters(book)]})])

    # Generate a reading plan, by reading 4 chapters per day, until the reading list is empty. Read 4 chapters per day
    reading_plan_df = pd.DataFrame(columns=['Date', 'Book', 'Start Chapter', 'End Chapter'])
    date = pd.Timestamp(start_date) # Start date

    for row in df.iterrows():
        book = row[1]['Book']
        chapters = row[1]['Chapters']
        start_chapter = 1
        end_chapter = min(chapters, start_chapter + chapters_per_day - 1)

        while start_chapter <= chapters:
            reading_plan_df = pd.concat([reading_plan_df, pd.DataFrame({'Date': [date], 'Book': [book], 'Start Chapter': [start_chapter], 'End Chapter': [end_chapter]})])
            date += pd.Timedelta(days=1)
            start_chapter = end_chapter + 1
            end_chapter = min(chapters, start_chapter + chapters_per_day - 1)

    # Set date as index
    reading_plan_df.set_index('Date', inplace=True)
    
    return reading_plan_df


if __name__ == '__main__':
    # Add start date as argument
    parser = argparse.ArgumentParser()
    parser.add_argument('--start_date', help='Start date of the reading plan (YYYY-MM-DD)', required=False, type=str)
    args = parser.parse_args()

    if not args.start_date:
        args.start_date = datetime.datetime.now().strftime('%Y-%m-%d')

    reading_list = generate_readplan(start_date=args.start_date)
    reading_list.to_csv(f'reading_plan_{args.start_date}.csv', index=True)