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May 20, 2019 07:13
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preprocess toutiao dataset in mysql
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# -*- coding: utf-8 -*- | |
# encoding=utf-8 | |
# REQUIREMENTS: | |
# pip install jieba mysql-connector | |
# Download the dataset from https://github.com/fate233/toutiao-text-classfication-dataset | |
import sys | |
import codecs | |
import mysql.connector | |
import jieba | |
stdout = codecs.getwriter('utf-8')(sys.stdout) | |
def prepare_vocab(): | |
mydb = mysql.connector.connect( | |
host="127.0.0.1", | |
user="root", | |
passwd="root", | |
database="toutiao", | |
use_unicode=True, | |
charset="utf8", | |
) | |
mycursor = mydb.cursor() | |
mycursor.execute("SELECT * FROM train") | |
voc = dict() | |
voc["<unk>"] = 0 | |
wordid = 0 | |
max_seq_length = 0 | |
while True: | |
x = mycursor.fetchone() | |
if x is None: | |
break | |
seg_list = jieba.cut(x[3]) | |
seg_len = 0 | |
for w in seg_list: | |
if not w in voc: | |
wordid += 1 | |
voc[w] = wordid | |
seg_len += 1 | |
if seg_len > max_seq_length: | |
max_seq_length = seg_len | |
mycursor.reset() | |
print("total vocab size: ", len(voc), " max seq length: ", max_seq_length) | |
with open("vocab.txt", "w", encoding="utf-8") as fn: | |
for w in voc: | |
fn.write("%s\t%d\n" % (w, voc[w])) | |
def load_vocab(file_path): | |
voc = dict() | |
with open(file_path, "r") as fn: | |
for l in fn: | |
l_strip = l[0:-1] | |
try: | |
w, idx = l_strip.split("\t") | |
voc[w] = idx | |
except: | |
print("skip vocab: ", l) | |
return voc | |
def write_prepared_table(max_seq_length): | |
# write to table train_processed, string fields should be encoded like: | |
# "9,100,33,21,0,0,0,0" padding to max seq length with 0 | |
voc = load_vocab("vocab.txt") | |
conn_write = mysql.connector.connect( | |
host="127.0.0.1", | |
user="root", | |
passwd="root", | |
database="toutiao", | |
use_unicode=True, | |
charset="utf8", | |
) | |
conn_read = mysql.connector.connect( | |
host="127.0.0.1", | |
user="root", | |
passwd="root", | |
database="toutiao", | |
use_unicode=True, | |
charset="utf8", | |
) | |
mycursor = conn_read.cursor() | |
mycursor.execute("SELECT * FROM train") | |
write_cursor = conn_write.cursor() | |
while True: | |
x = mycursor.fetchone() | |
if x is None: | |
break | |
title_tensor = [] | |
title_seg = jieba.cut(x[3]) | |
for w in title_seg: | |
if w in voc: | |
title_tensor.append(str(voc[w])) | |
else: | |
title_tensor.append("0") | |
# padding | |
while len(title_tensor) < max_seq_length: | |
title_tensor.append("0") | |
# NOTE: update class_id = class_id - 100 to let it start from 0 | |
sql = """INSERT INTO train_processed (id, class_id, class_name, news_title, news_keywords) | |
VALUES (%d, %d, "%s", "%s", "%s")""" % (x[0], x[1] - 100, x[2], ",".join(title_tensor), x[4]) | |
write_cursor.execute(sql) | |
conn_write.commit() | |
mycursor.reset() | |
conn_read.close() | |
if __name__ == "__main__": | |
prepare_vocab() | |
# NOTE: 92 is max_seq_length, can run the above line to get this number. | |
write_prepared_table(92) |
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At line 60 need change 'with open(file_path, "r") as fn:' to 'with open(file_path, "r" , encoding="utf-8") as fn:'
for Chinese Unicode.