232 lines
6.3 KiB
Plaintext
232 lines
6.3 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### nie robimy 2 nowych linii w bloku funkcji. sentences[::2] oraz sentences[1::2] powinny być przypisane do osobnych zmiennych"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Pies ten pochodzi z południowych Chin, z terenów prowincji Guangdong! \n",
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"Został rozpropagowany i hodowany w celach wystawowych przez hodowców w USA. \n",
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"Nazwa psa, pochodząca z chińskiego, oznacza dosłownie piaszczysta skóra. \n",
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"['Pies ten pochodzi z południowych Chin, z terenów prowincji Guangdong! ', 'Został rozpropagowany i hodowany w celach wystawowych przez hodowców w USA. ', 'Nazwa psa, pochodząca z chińskiego, oznacza dosłownie piaszczysta skóra. ']\n"
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]
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}
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],
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"source": [
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"import re\n",
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"tekst = \"Pies ten pochodzi z południowych Chin, z terenów prowincji Guangdong! Został rozpropagowany i hodowany w celach wystawowych przez hodowców w USA. Nazwa psa, pochodząca z chińskiego, oznacza dosłownie piaszczysta skóra. Chart polski polska rasa psa myśliwskiego, znana prawdopodobnie od czasów Galla Anonima, zaliczana do grupy chartów.\"\n",
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"def split_sentences(text):\n",
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" sentences = re.split(r'([.!?]\\s+)(?=[A-Z])', text)\n",
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"\n",
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"\n",
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" full_sentences = [''.join(pair) for pair in zip(sentences[::2], sentences[1::2])]\n",
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"\n",
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"\n",
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" for sentence in full_sentences:\n",
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" print(sentence)\n",
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" print(full_sentences)\n",
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"split_sentences(tekst)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Niewłaściwa nazwa funkcji switch_letter (robi coś innego, niż nazwa na to wskazuje). Linijka z sum jest nieczytelna."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"--- faja.\n"
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]
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}
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],
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"source": [
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"text = \"kurde faja.\"\n",
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"\n",
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"vulgar_words_base = [\"kurd\", \"choler\"]\n",
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"\n",
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"def switch_letter(word, vulgar_word_list):\n",
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" word = word.lower()\n",
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" for bad_word in vulgar_word_list:\n",
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" switched_letters = sum(1 for a, b in zip(word, bad_word) if a != b)\n",
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" if switched_letters == 1:\n",
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" return True\n",
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" return False\n",
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"\n",
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"def censor_text(text):\n",
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" pattern = re.compile(r'[^\\s]*(' + '|'.join([f'{word}' for word in vulgar_words_base]) + r')[^\\s]*', re.IGNORECASE)\n",
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" censored_text = pattern.sub(\"---\", text)\n",
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"\n",
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" censored_text_list = censored_text.split()\n",
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" \n",
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" for i, word in enumerate(censored_text_list):\n",
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" if switch_letter(word, vulgar_words_base):\n",
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" censored_text_list[i] = \"---\"\n",
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" final_censored_text = \" \".join(censored_text_list)\n",
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"\n",
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" return final_censored_text\n",
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"\n",
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"print(censor_text(text))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"False"
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]
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},
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"switch_letter(\"kurcze\", [\"kurzce\"])"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Jeżeli nie ma takiej konieczności nie iterujemy po rozdzielonym na słowa tekście, tylko na całym tekście."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Siała baba mak.\n",
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"Czy wiedziała jak?\n",
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"Dziadek wiedział, nie powiedział, a to było tak!\n"
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]
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}
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],
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"source": [
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"# Solution 2\n",
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"text = 'Siała baba mak. Czy wiedziała jak? Dziadek wiedział, nie powiedział, a to było tak!'\n",
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"sentences = []\n",
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"\n",
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"def split_sentences(text):\n",
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" sentence = ''\n",
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" for word in text.split():\n",
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" x = re.search(r'[a-zA-Z0-9]+[.?!]', word)\n",
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" if x is None:\n",
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" sentence += f'{word} '\n",
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" else:\n",
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" sentence += word\n",
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" sentences.append(sentence)\n",
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" sentence = ''\n",
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" for result in sentences:\n",
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" print(result)\n",
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"\n",
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"\n",
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"split_sentences(text)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Nie stosujemy zapisu if {zmienna}, tylko if {zmienna} is True/False. Kod dla danego warunku przenosimy do nowej linii"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"import re\n",
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"\n",
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"def validate_name(name):\n",
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" valid = re.match(r'^[A-Z][a-z]{1,}',name)\n",
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" if valid: return True\n",
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" else: return False\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Przykład właściwego zastosowania komentarza"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [],
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"source": [
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"def censor_text(text):\n",
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" prefixes = r'(do|na|o|od|pod|po|prze|przy|roz|s|u|w|y|za|z|u)*'\n",
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"\n",
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" # profanities according to prof. Jerzy Bralczyk\n",
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" profanities = [ \n",
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" rf'\\b{prefixes}(pierd\\w*)\\b',\n",
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" ]\n",
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"\n",
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" profanity_pattern = re.compile('|'.join(profanities), re.IGNORECASE)\n",
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"\n",
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" return profanity_pattern.sub('---', text)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "base",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.5"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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