forked from erpwibw/BilingualHTML
-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathBilingualHTML.py
More file actions
248 lines (213 loc) · 8.12 KB
/
BilingualHTML.py
File metadata and controls
248 lines (213 loc) · 8.12 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
from bs4 import BeautifulSoup as bs
import openai
import time
import json
import logging
import os
from pathlib import Path
logging.basicConfig(
level=logging.INFO,
filename="./log.txt",
filemode="a",
format="%(asctime)s - %(levelname)s - %(funcName)s: %(message)s",
)
def contains_only_code_tag(tag):
"""
检查标记是否只包含一个代码标记。
"""
code_tag = tag.find('code')
if code_tag is None:
return False
code_text = code_tag.text.replace('\n', '').replace(' ', '')
p_text = tag.text.replace('\n', '').replace(' ', '')
if code_text == p_text:
return True
def is_single_character_tag(tag):
"""
判断一个标签内的文本是否只有一个字符
只有一个字符的话，就不需要翻译了
"""
text = tag.text.replace('\n', '').replace(' ', '')
return len(text) == 1
def is_jump_translate(tag):
"""
判断是否可以跳过当前标签，不用翻译。
"""
return contains_only_code_tag(tag) or is_single_character_tag(tag)
def get_translation(prompt, code):
"""
将 HTML 网页翻译为简体中文，返回翻译后的 HTML 代码，包裹在 <code> 标签中的文本不会被翻译。
如果无法翻译，则返回原始的 HTML 代码。
"""
completion = openai.ChatCompletion.create(
model="gpt-3.5-turbo",
messages=[
{"role": "user", "content": f"{prompt} {code}"}
]
)
return completion.choices[0].message.content
def translate_tag(prompt, code):
"""
将给定的 HTML 网页翻译为简体中文，如果翻译失败则进行重试。
"""
max_attempts = 5
for i in range(max_attempts):
try:
t_text = get_translation(prompt, code)
time.sleep(3)
print(t_text)
logging.info(t_text)
return t_text
except Exception as e:
sleep_time = 60
print(e)
logging.error(e)
print(f"请求失败，将等待 {sleep_time} 秒后重试")
logging.info(f"请求失败，将等待 {sleep_time} 秒后重试")
time.sleep(sleep_time)
print(f"开始重试第 {i + 1}/{max_attempts}")
logging.info(f"开始重试第 {i + 1}/{max_attempts}")
print(f"请求失败，重试次数{max_attempts}/{max_attempts}，放弃请求")
logging.error(f"请求失败，重试次数{max_attempts}/{max_attempts}，放弃请求")
def read_api_key(path):
with open(path, 'r') as f:
api_key = f.read().strip()
return api_key
def read_chatGPT_prompt(path):
with open(path, 'r') as f:
prompt = f.read().strip()
return prompt
def read_page(path):
"""
打开 HTML 网页，返回 BeautifulSoup 对象。
"""
with open(path, 'r') as f:
soup = bs(f, "html.parser")
return soup
def read_json(path):
"""
打开 JSON 文件，返回 JSON 对象。
"""
with open(path, 'r') as f:
json_obj = json.load(f)
return json_obj
def write_json(path, code, mode='w'):
"""
将 JSON 对象写入 JSON 文件。
"""
with open(path, mode) as f:
json.dump(code, f, ensure_ascii=False)
def write_page(path, soup):
with open(path, 'w') as f:
f.write(soup.prettify())
def resume_translate():
"""
恢复之前的翻译进度
"""
try:
translated_texts = read_json('translated.json')
start_index = len(translated_texts)
print(f"从索引 {start_index + 1} 处继续翻译")
logging.info(f"从索引 {start_index + 1} 处继续翻译")
except:
print("没有找到之前的翻译结果，从头开始翻译")
logging.info("没有找到之前的翻译结果，从头开始翻译")
start_index = 0
translated_texts = []
return translated_texts, start_index
def translate_page(start_time, page_num, page_count, page, prompt):
"""
读取 HTML 页面并翻译其中的所有 <p> 标签内容为中文。
如果翻译结果已经存在，则从上次翻译的位置继续翻译。
翻译结果会保存在 'translated.json' 文件中。
"""
soup = read_page(page)
p_list = soup.find_all('p')
count = len(p_list)
translated_texts, start_index = resume_translate()
page_start_time = time.time()
for i, p in enumerate(p_list[start_index:]):
print("↓ " * 10 + "开始翻译 " + "↓ " * 10)
logging.info("↓ " * 10 + "开始翻译 " + "↓ " * 10)
p_start_time = time.time()
p_code = p.prettify()
print(p_code)
logging.info(p_code)
if p_code:
if is_jump_translate(p):
translated_texts.append(p_code)
else:
translated_texts.append(translate_tag(prompt, p_code))
write_json('translated.json', translated_texts)
p_end_time = time.time()
print(f"已经翻译 {i + start_index + 1}/{count}", end='，')
logging.info(f"已经翻译 {i + start_index + 1}/{count}")
p_elapsed_time = int(p_end_time - p_start_time)
print(f"本段耗时 {p_elapsed_time} 秒", end='，')
logging.info(f"本段耗时 {p_elapsed_time} 秒")
every_p_time = int((p_end_time - page_start_time) / (i + start_index + 1))
print(f"平均每段耗时 {every_p_time} 秒")
logging.info(f"平均每段耗时 {every_p_time} 秒")
page_elapsed_time = int((p_end_time - page_start_time) / 60)
print(f"本页耗时 {page_elapsed_time} 分钟", end='，')
logging.info(f"本页耗时 {page_elapsed_time} 分钟")
remaining_time = int(((count - i - start_index - 1) * every_p_time) / 60)
print(f"本页预计剩余时间 {remaining_time} 分钟")
logging.info(f"本页预计剩余时间 {remaining_time} 分钟")
elapsed_time = int((p_end_time - start_time) / 60)
print(f"总耗时 {elapsed_time} 分钟", end='，')
logging.info(f"总耗时 {elapsed_time} 分钟")
print(f"正在翻译第 {page_num + 1}/{page_count} 页")
logging.info(f"正在翻译第 {page_num + 1}/{page_count} 页")
print("↑ " * 10 + "翻译完成 " + "↑ " * 10)
logging.info("↑ " * 10 + "翻译完成 " + "↑ " * 10)
return count
def save_translated_page(page, json):
"""
在 HTML 文件中添加翻译后的 p 标签
"""
translated_texts = read_json(json)
soup = read_page(page)
p_list = soup.find_all('p')
for i, p in enumerate(p_list):
text = p.prettify()
if text:
translated_p = bs(translated_texts[i], 'html.parser')
p.insert_after(translated_p)
page_cn = page.parent / (page.stem + '_cn' + page.suffix)
write_page(page_cn, soup)
def get_translated_page(path):
path = Path(path)
return list(path.glob('**/*.html'))
def resume_translate_page():
"""
恢复之前的翻译进度
"""
try:
translated_index = read_json('index.json')
start_index = len(translated_index)
print(f"从索引 {start_index + 1} 处继续翻译")
logging.info(f"从索引 {start_index + 1} 处继续翻译")
except:
print("没有找到之前的翻译索引，从第一个文件开始翻译")
logging.info("没有找到之前的翻译索引，从第一个文件开始翻译")
start_index = 0
return start_index
openai.api_key = read_api_key('api_key.txt')
prompt = read_chatGPT_prompt('chatGPT_prompt.txt')
path = Path('translatable')
pages = get_translated_page('translatable')
pages_count = len(list(pages))
start_time = time.time()
start_index = resume_translate_page()
for i, page in enumerate(pages[start_index:]):
count = translate_page(start_time, i, pages_count, page, prompt)
translated_texts = read_json('translated.json')
if count == len(translated_texts):
save_translated_page(page, 'translated.json')
print(f"{page.stem} 翻译完成, 进度{i + 1}/{pages_count}")
logging.info(f"{page.stem} 翻译完成, 进度{i + 1}/{pages_count}")
os.remove('translated.json')
write_json('index.json', str(page), 'a')
os.remove('index.json')
print("全部文件翻译完成")