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import gzip
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import sys
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import os
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import tqdm
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import requests
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import json
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import fasttext
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fasttext.FastText.eprint = lambda x: None
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def http_get(url, path):
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"""
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Downloads a URL to a given path on disc
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"""
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if os.path.dirname(path) != '':
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os.makedirs(os.path.dirname(path), exist_ok=True)
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req = requests.get(url, stream=True)
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if req.status_code != 200:
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print("Exception when trying to download {}. Response {}".format(url, req.status_code), file=sys.stderr)
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req.raise_for_status()
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return
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download_filepath = path+"_part"
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with open(download_filepath, "wb") as file_binary:
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content_length = req.headers.get('Content-Length')
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total = int(content_length) if content_length is not None else None
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progress = tqdm.tqdm(unit="B", total=total, unit_scale=True)
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for chunk in req.iter_content(chunk_size=1024):
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if chunk:
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progress.update(len(chunk))
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file_binary.write(chunk)
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os.rename(download_filepath, path)
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progress.close()
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model_path = 'lid.176.bin'
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if not os.path.exists(model_path):
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http_get('https://dl.fbaipublicfiles.com/fasttext/supervised-models/'+model_path, model_path)
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global_fasttext_lang_id = fasttext.load_model(model_path)
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def lang_detect(text: str) -> str:
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return global_fasttext_lang_id.predict(text.lower().replace("\r\n", " ").replace("\n", " ").strip())[0][0].split('__')[-1]
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filepaths = sorted(sys.argv[1:])
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output_folder = "question_best_answer_lang"
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output_files = {}
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try:
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for filepath in filepaths:
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with gzip.open(filepath, 'rt') as fIn:
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for line in tqdm.tqdm(fIn, desc=filepath):
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data = json.loads(line)
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text = data['title']+" "+data['body']
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lang = lang_detect(text)
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if lang not in output_files:
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output_files[lang] = gzip.open(f"{output_folder}/{lang}.jsonl.gz", "wt")
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output_files[lang].write(line)
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finally:
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for outfile in output_files.values():
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outfile.close()
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