File size: 7,284 Bytes
d8d694f |
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 |
import hashlib
import os
import pandas as pd
from bs4 import BeautifulSoup
from loguru import logger
class FileName:
"""Record file original name, state and copied filepath with text
format."""
def __init__(self, root: str, filename: str, _type: str):
self.root = root
self.prefix = filename.replace("/", "_")
self.basename = os.path.basename(filename)
self.origin = os.path.join(root, filename)
self.copypath = ""
self._type = _type
self.state = True
self.reason = ""
def __str__(self):
return "{},{},{},{}\n".format(self.basename, self.copypath, self.state, self.reason)
class FileOperation:
"""Encapsulate all file reading operations."""
def __init__(self):
self.image_suffix = [".jpg", ".jpeg", ".png", ".bmp"]
self.md_suffix = ".md"
self.text_suffix = [".txt", ".text"]
self.excel_suffix = [".xlsx", ".xls", ".csv"]
self.pdf_suffix = ".pdf"
self.ppt_suffix = ".pptx"
self.html_suffix = [".html", ".htm", ".shtml", ".xhtml"]
self.word_suffix = [".docx", ".doc"]
self.normal_suffix = (
[self.md_suffix]
+ self.text_suffix
+ self.excel_suffix
+ [self.pdf_suffix]
+ self.word_suffix
+ [self.ppt_suffix]
+ self.html_suffix
)
def get_type(self, filepath: str):
filepath = filepath.lower()
if filepath.endswith(self.pdf_suffix):
return "pdf"
if filepath.endswith(self.md_suffix):
return "md"
if filepath.endswith(self.ppt_suffix):
return "ppt"
for suffix in self.image_suffix:
if filepath.endswith(suffix):
return "image"
for suffix in self.text_suffix:
if filepath.endswith(suffix):
return "text"
for suffix in self.word_suffix:
if filepath.endswith(suffix):
return "word"
for suffix in self.excel_suffix:
if filepath.endswith(suffix):
return "excel"
for suffix in self.html_suffix:
if filepath.endswith(suffix):
return "html"
return None
def md5(self, filepath: str):
hash_object = hashlib.sha256()
with open(filepath, "rb") as file:
chunk_size = 8192
while chunk := file.read(chunk_size):
hash_object.update(chunk)
return hash_object.hexdigest()[0:8]
def summarize(self, files: list):
success = 0
skip = 0
failed = 0
for file in files:
if file.state:
success += 1
elif file.reason == "skip":
skip += 1
else:
logger.info("{} {}".format(file.origin, file.reason))
failed += 1
logger.info("{} {}".format(file.reason, file.copypath))
logger.info("累计{}文件，成功{}个，跳过{}个，异常{}个".format(len(files), success, skip, failed))
def scan_dir(self, repo_dir: str):
files = []
for root, _, filenames in os.walk(repo_dir):
for filename in filenames:
_type = self.get_type(filename)
if _type is not None:
files.append(FileName(root=root, filename=filename, _type=_type))
return files
def read_pdf(self, filepath: str):
# load pdf and serialize table
# TODO fitz 安装有些不兼容，后续按需完善
import fitz
text = ""
with fitz.open(filepath) as pages:
for page in pages:
text += page.get_text()
tables = page.find_tables()
for table in tables:
tablename = "_".join(filter(lambda x: x is not None and "Col" not in x, table.header.names))
pan = table.to_pandas()
json_text = pan.dropna(axis=1).to_json(force_ascii=False)
text += tablename
text += "\n"
text += json_text
text += "\n"
return text
def read_excel(self, filepath: str):
table = None
if filepath.endswith(".csv"):
table = pd.read_csv(filepath)
else:
table = pd.read_excel(filepath)
if table is None:
return ""
json_text = table.dropna(axis=1).to_json(force_ascii=False)
return json_text
def read(self, filepath: str):
file_type = self.get_type(filepath)
text = ""
if not os.path.exists(filepath):
return text, None
try:
if file_type == "md" or file_type == "text":
with open(filepath) as f:
text = f.read()
elif file_type == "pdf":
text += self.read_pdf(filepath)
elif file_type == "excel":
text += self.read_excel(filepath)
elif file_type == "word" or file_type == "ppt":
# https://stackoverflow.com/questions/36001482/read-doc-file-with-python
# https://textract.readthedocs.io/en/latest/installation.html
# TODO textract 在 pip 高于 24.1 后安装不了，因为其库自身原因，后续按需进行完善
# 可自行安装 pip install textract==1.6.5
import textract # for word and ppt
text = textract.process(filepath).decode("utf8")
if file_type == "ppt":
text = text.replace("\n", " ")
elif file_type == "html":
with open(filepath) as f:
soup = BeautifulSoup(f.read(), "html.parser")
text += soup.text
except Exception as e:
logger.error((filepath, str(e)))
return "", e
text = text.replace("\n\n", "\n")
text = text.replace("\n\n", "\n")
text = text.replace("\n\n", "\n")
text = text.replace(" ", " ")
text = text.replace(" ", " ")
text = text.replace(" ", " ")
return text, None
if __name__ == "__main__":
def get_pdf_files(directory):
pdf_files = []
# 遍历目录
for root, dirs, files in os.walk(directory):
for file in files:
# 检查文件扩展名是否为.pdf
if file.lower().endswith(".pdf"):
# 将完整路径添加到列表中
pdf_files.append(os.path.abspath(os.path.join(root, file)))
return pdf_files
# 将你想要搜索的目录替换为下面的路径
pdf_list = get_pdf_files("/home/khj/huixiangdou-web-online-data/hxd-bad-file")
# 打印所有找到的PDF文件的绝对路径
opr = FileOperation()
for pdf_path in pdf_list:
text, error = opr.read(pdf_path)
print("processing {}".format(pdf_path))
if error is not None:
# pdb.set_trace()
print("")
else:
if text is not None:
print(len(text))
else:
# pdb.set_trace()
print("")
|