# -*- coding: utf-8 -*- import os import io import re import json import click import collections def build_vocabulary(dataset, cutoff=0): dictionary = collections.defaultdict(int) for data in dataset: for sent in data[2]: for char in sent: dictionary[char] += 1 dictionary = filter(lambda x: x[1] >= cutoff, dictionary.items()) dictionary = sorted(dictionary, key=lambda x: (-x[1], x[0])) vocab, _ = list(zip(*dictionary)) return (u"", u"", u"") + vocab @click.command("preprocess") @click.option("--datadir", type=str, help="Path to raw data") @click.option("--outfile", type=str, help="Path to save the training data") @click.option("--dictfile", type=str, help="Path to save the dictionary file") def preprocess(datadir, outfile, dictfile): dataset = [] note_pattern1 = re.compile(u"(.*?)", re.U) note_pattern2 = re.compile(u"〖.*?〗", re.U) note_pattern3 = re.compile(u"-.*?-。?", re.U) note_pattern4 = re.compile(u"(.*$", re.U) note_pattern5 = re.compile(u"。。.*)$", re.U) note_pattern6 = re.compile(u"。。", re.U) note_pattern7 = re.compile(u"[《》「」\[\]]", re.U) print("Load raw data...") for fn in os.listdir(datadir): with io.open(os.path.join(datadir, fn), "r", encoding="utf8") as f: for data in json.load(f): title = data['title'] author = data['author'] p = "".join(data['paragraphs']) p = "".join(p.split()) p = note_pattern1.sub(u"", p) p = note_pattern2.sub(u"", p) p = note_pattern3.sub(u"", p) p = note_pattern4.sub(u"", p) p = note_pattern5.sub(u"。", p) p = note_pattern6.sub(u"。", p) p = note_pattern7.sub(u"", p) if (p == u"" or u"{" in p or u"}" in p or u"{" in p or u"}" in p or u"、" in p or u":" in p or u";" in p or u"!" in p or u"?" in p or u"●" in p or u"□" in p or u"囗" in p or u")" in p): continue paragraphs = re.split(u"。|,", p) paragraphs = filter(lambda x: len(x), paragraphs) if len(paragraphs) > 1: dataset.append((title, author, paragraphs)) print("Construct vocabularies...") vocab = build_vocabulary(dataset, cutoff=10) with io.open(dictfile, "w", encoding="utf8") as f: for v in vocab: f.write(v + "\n") print("Write processed data...") with io.open(outfile, "w", encoding="utf8") as f: for data in dataset: title = data[0] author = data[1] paragraphs = ".".join(data[2]) f.write("\t".join((title, author, paragraphs)) + "\n") if __name__ == "__main__": preprocess()