120 lines
3.6 KiB
Python
120 lines
3.6 KiB
Python
import hashlib
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import json
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import random
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import re
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import requests
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import time
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from nltk import pos_tag, sent_tokenize, word_tokenize
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from nltk.corpus import stopwords
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from wikipediaapi import Wikipedia, WikipediaPage
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# Info about the default pos_tag tags
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# https://www.ling.upenn.edu/courses/Fall_2003/ling001/penn_treebank_pos.html
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adlib_tags = {
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"JJ": "Adjective",
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"JJR": "Adjective ending in 'er'",
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"JJS": "Adjective ending in 'est'",
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"NN": "Noun",
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"NNS": "Plural Noun",
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"NNP": "Proper Noun",
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"NNPS": "Plural Proper Noun",
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"RB": "Adverb",
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"RBR": "Adverb ending in 'er'",
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"RBS": "Adverb ending in 'est'",
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"VB": "Verb",
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"VBD": "Past Tense Verb",
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"VBG": "Verb ending in 'ing'",
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"VBN": "Past Tense Verb",
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"VBP": "Present Tense Verb",
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"VBZ": "Present Tense Verb ending in 's'",
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}
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stop_words = set(stopwords.words("english"))
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months = {
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"january",
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"february",
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"march",
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"april",
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"may",
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"june",
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"july",
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"august",
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"september",
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"october",
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"november",
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"december",
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}
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stop_words.update(months)
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# More stop words: becomes, become, became, well
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def get_random_wikipedia_title() -> str:
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random_result = json.loads(requests.get('https://en.wikipedia.org/api/rest_v1/page/random/title').text)
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return random_result['items'][0]['title']
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def get_random_wikipedia_page(wikipedia: Wikipedia, min_length: int = None) -> WikipediaPage:
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page = None
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while(page is None):
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page = wikipedia.page(get_random_wikipedia_title())
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if(min_length and len(page.summary) < min_length):
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print(f"{page.displaytitle} is too short. Retrying...")
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page = None
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time.sleep(3)
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return page
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def sentence_tokenize_and_tag(text: str):
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text = re.sub(r"(\w+)\.([A-Z])", r"\1. \2", text) # Try to break up sentences mashed together by stripping strings
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sentences = sent_tokenize(text)
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tagged_sentences = []
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for sentence in sentences:
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tagged_sentences.append(pos_tag(word_tokenize(sentence)))
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return tagged_sentences
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def adlibify(wiki_page, min_adlib_rest):
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lowered_title = wiki_page.title.lower()
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i = adlib_word_counter = 0
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output_tokens = []
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for sentence in sentence_tokenize_and_tag(wiki_page.summary):
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for token, tag in sentence:
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if tag in ["NNP", "NNPS"] and i > 0 and output_tokens[-1]["tag"] in ["NNP", "NNPS"]:
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output_tokens[-1]["token"] += f" {token}"
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else:
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output_token = {"id": i, "token": token, "tag": tag}
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adlib_tag = adlib_tags.get(tag)
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if adlib_tag is not None:
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if random.randint(0, adlib_word_counter) > min_adlib_rest \
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and token.lower() not in stop_words \
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and token.lower() not in lowered_title:
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output_token["adlib_tag"] = adlib_tag
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adlib_word_counter = 0
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else:
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adlib_word_counter += 1
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output_tokens.append(output_token)
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i += 1
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url = wiki_page.canonicalurl
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url_hash = hashlib.sha1(url.encode('utf-8')).hexdigest()[:8]
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article = {'title': wiki_page.displaytitle, 'url': url, 'hash': url_hash}
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article['tokens'] = output_tokens
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return article
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def main():
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wikipedia = Wikipedia('en')
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wiki_page = get_random_wikipedia_page(wikipedia, 500)
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print(wiki_page.title)
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article = adlibify(wiki_page, 4)
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with open("article.js", "w") as json_file:
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json_file.write(f"article = {json.dumps(article)}")
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if __name__ == '__main__':
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main()
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