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import re
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import pandas as pd
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from tqdm import tqdm
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from bs4 import BeautifulSoup
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INPUT_TMX = "ECDC.tmx"
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print("⌛ Load TMX...")
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tree = BeautifulSoup(open(INPUT_TMX,"r"), features="lxml")
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print("⚗️ Parse content")
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sentences = []
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for tu in tqdm(tree.findAll("tu")):
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langs = {}
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for tuv in tu.findAll("tuv"):
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text = re.sub("\s+", " ", tuv.seg.text.replace("\n"," "))
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langs[tuv["xml:lang"].lower()] = text
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sentences.append(langs)
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content = []
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print("⚙️ Convert to CSV")
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for idx, sentence in tqdm(enumerate(sentences)):
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for lang in sentence:
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if lang == "en" or len(sentence[lang].replace(" ","")) <= 0:
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continue
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content.append({
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'key': "doc_" + str(idx),
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'lang': "en-" + lang,
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'source_text': sentence["en"],
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'target_text': sentence[lang]
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})
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df = pd.DataFrame({
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'key': [],
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'lang': [],
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'source_text': [],
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'target_text': []
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})
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df = df.append(content)
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df = df.sort_values(by=['lang'], ascending=True)
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print("💾 Save as CSV and GZ")
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df.to_csv("ECDC.csv", index=False)
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df.to_csv("ECDC.csv.gz", index=False, compression="gzip")
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uniq_elements = list(set(df['lang'].unique()))
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l = open("langs.txt","w")
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l.write("\n".join(uniq_elements))
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l.close()
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uniq_elements = df.groupby('lang').count()
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l = open("stats.md","w")
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l.write(str(uniq_elements))
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l.close()
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