mirror of
https://github.com/WallyS02/Song-Lyrics-Generator.git
synced 2024-10-03 11:26:10 +00:00
82 lines
4.0 KiB
Python
82 lines
4.0 KiB
Python
import os
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import random
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from scrapper import scrap_data
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from scrapper import clean_data
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from markov_model import create_markov_model
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from markov_model import generate_lyrics
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black_sabbath_selected_albums = ["Black Sabbath", "Paranoid", "Master Of Reality", "Vol 4", "Sabbath Bloody Sabbath",
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"Sabotage", "Technical Ecstasy", "Never Say Die!", "Heaven And Hell", "Mob Rules",
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"Born Again", "Seventh Star", "The Eternal Idol", "Headless Cross", "Tyr",
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"Dehumanizer", "Cross Purposes", "Forbidden", "13"]
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pink_floyd_selected_albums = ["The Piper At The Gates Of Dawn", "A Saucerful Of Secrets", "Meddle", "More", "Ummagumma",
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"Atom Heart Mother", "Obscured By Clouds", "The Dark Side Of The Moon",
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"Wish You Were Here", "Animals", "The Wall", "The Final Cut",
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"A Momentary Lapse Of Reason", "The Division Bell"]
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time_stamp = 3.5
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def main():
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print("Select data set to use in generation or other option:\n1. Pink Floyd lyrics generation\n2. Black Sabbath "
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"lyrics generation\n3. Bracia Figo Fagot\n4. Paktofonika\n5. Fused English (aka Pink Sabbath) lyrics "
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"generation\n6. Fused Polish (aka Braciofonika Pigo Pagot)\n7. Prepare data\n8. Scrap data\n9. Exit")
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pink_floyd_dataset = None
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black_sabbath_dataset = None
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pink_sabbath_dataset = None
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paktofonika_dataset = None
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bracia_figo_fagot_dataset = None
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braciofonika_pigo_pagot_dataset = None
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while True:
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selection = int(input())
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match selection:
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case 1:
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model = create_markov_model(pink_floyd_dataset)
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for i in range(5):
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generated_lyrics = generate_lyrics(model, random.choice(list(model.keys())), 10)
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print(generated_lyrics)
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case 2:
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model = create_markov_model(black_sabbath_dataset)
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for i in range(5):
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generated_lyrics = generate_lyrics(model, random.choice(list(model.keys())), 10)
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print(generated_lyrics)
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case 3:
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model = create_markov_model(bracia_figo_fagot_dataset)
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for i in range(5):
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generated_lyrics = generate_lyrics(model, random.choice(list(model.keys())), 10)
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print(generated_lyrics)
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case 4:
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model = create_markov_model(paktofonika_dataset)
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for i in range(5):
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generated_lyrics = generate_lyrics(model, random.choice(list(model.keys())), 10)
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print(generated_lyrics)
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case 5:
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model = create_markov_model(pink_sabbath_dataset)
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for i in range(5):
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generated_lyrics = generate_lyrics(model, random.choice(list(model.keys())), 10)
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print(generated_lyrics)
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case 6:
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model = create_markov_model(braciofonika_pigo_pagot_dataset)
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for i in range(5):
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generated_lyrics = generate_lyrics(model, random.choice(list(model.keys())), 10)
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print(generated_lyrics)
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case 7:
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path = os.path.dirname(os.path.abspath(__file__))
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path = path + "\\Data\\"
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pink_floyd_dataset = clean_data((path + "Pink Floyd.csv"))
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black_sabbath_dataset = clean_data((path + "Black Sabbath.csv"))
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pink_sabbath_dataset = clean_data((path + "Pink Sabbath.csv"))
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paktofonika_dataset = clean_data((path + "Paktofonika.csv"))
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bracia_figo_fagot_dataset = clean_data((path + "Bracia Figo Fagot.csv"))
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braciofonika_pigo_pagot_dataset = clean_data((path + "Braciofonika Pigo Pagot.csv"))
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case 8:
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scrap_data(pink_floyd_selected_albums, black_sabbath_selected_albums, time_stamp)
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case 9:
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break
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print("\nCommand executed")
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if __name__ == '__main__':
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main()
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