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JdocsExtract.py
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# -*- coding: utf-8 -*-
"""
Created on Mon Jun 20 17:41:36 2022
@author: Autozhz
"""
import os,re,glob,sys,time,random,string
import pandas as pd
from docx import Document
from CommomClass import CommomClass
from PrintLog import PrintLog
class JdocsExtract(CommomClass):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
def check_table_content(self,doc_name):
codes = '';isanhao = 0
try:
tables = Document(doc_name).tables
if tables: # read if there's table in jdocs, find codes in table very first
for table in tables:
for row in table.rows:
for cell in row.cells:
for p in cell.paragraphs:
match_anhao = re.search(r'[(（]\d+[）)].*\d+(?=号)',p.text) # codes limited with 25 digits
if match_anhao:
codes = match_anhao.group(0)+'号'; isanhao=1; break
except Exception as e:
err = '读取文件【%s】错误 ,word文档的问题，或格式docx和doc混淆，或文档已打开，或文档损坏 Skip It.\n %s'%(os.path.relpath(doc_name),e)
PrintLog.log(err)
return codes,isanhao
def get_member_info_all(self,doc_folder,**kwargs):
print('\n'+'Start Reading All 判决书'.center(30,'*'))
jdoc_files = glob.glob(doc_folder+'\\*.docx')
df = self.read_file(**kwargs)
for doc_name in jdoc_files:
df1 = self.get_member_info(doc_name)
if not df1 is None:
df = pd.concat([df,df1])
df = self.sort_duplicates_data(df,sortlist=['原审案号','当事人'])
self.save_file(df_output=df,
**kwargs)
print('END'.center(30,'*') + '\n')
return df
def get_member_info(self,doc_name):
try:
dd = Document(doc_name).paragraphs
except Exception as e:
PrintLog.log(' %s 判决书内容或格式问题 %s'%(os.path.relpath(doc_name),e))
return
tlist = []
anhao,isanhao = self.check_table_content(doc_name)
anhao = '';isanhao = 0
for p in dd:
if not isanhao and len(p.text) < 50:
match_anhao = re.search(r'[(（]\d+[）)].*\d+(?=号)',p.text)
if match_anhao:
anhao = (match_anhao.group(0)+'号').replace(r'(',r'（').replace(r')',r'）')
isanhao = 1; continue
if len(p.text) > 150: continue
role_rgx = '原告|被告|原审原告|原审被告|第三人|原审第三人|申请人|被申请人|上诉人|被上诉人|异议人|执行人'
match_member = re.search(r'%s'%role_rgx,p.text) # 找人员 # rest 负责人|经营者|法定代表人|法人|委托诉讼代理人|
match_agent = re.search(r'(委托|诉讼)?代理人',p.text)
if match_member and not match_agent:
if match_member.span()[0]>3: continue # 角色不在开头位置，属于文章内容
if re.search(r'(%s).*(证据|请求|称|意见)\w*(?=[：:])'%role_rgx,p.text) : continue # XX称，属于文章内容
match_name = re.search('(?<=[：:])[^。，,]+(?=[。，,])',p.text) # find the member name
if match_name:
role_title = re.search(r'[^：:]*(?=[：:])',p.text).group(0) #截取头 上诉人（一审被告）
if len(role_title) > 18: continue # 角色超长，属于文章内容
member = match_name.group(0).strip()
# if not re.search(r'合作社|酒店|公司',name) and len(name) > 5: continue # 去掉非公司人名和长度超过5的段落
# member = re.sub(r'[(（][下称|原名|反诉|变更前].*?[）)]','',member) # filter member name of some special members,notice here will add some words for filter
adrs_regex = r'^户[籍口]|居住|身份证|所在地|住所地?|住址?|[现原]?住|为?'
adrs = [re.sub(adrs_regex,'',y) \
for y in self.split_list(r'[,，:：.。]',p.text) \
if re.search(r'(%s).*?[省市州县区乡镇村]'%adrs_regex,y)] # 几个地址选最后一个 remain only address
adrs = adrs[-1] if len(adrs) > 0 else ''
df_row = {'原审案号':anhao,'角色':role_title,'当事人':member,'地址':adrs}
tlist.append(df_row) #直接获取信息
if not tlist:
PrintLog.log('请检查文件%s是否判决书内容'%os.path.relpath(doc_name))
self.rename_jdocs(anhao, doc_name)
df = pd.DataFrame(tlist)
return df
def rename_jdocs(self,anhao,doc_name): # for 的子内容
# nd = os.path.join(os.path.split(d)[0],'判决书_'+anhao.strip() +'_原_'+ str(r[old_codes]) + '.docx')
if '内容未知' in doc_name or '重复' in doc_name: return 0
if not anhao:
# t1 = time.ctime(os.path.getmtime(doc_name))
# t2 = time.strftime('%Y%m%d%H%M%S',time.strptime(t1))
t2 = ''.join(random.choice(string.ascii_letters) for _ in range(6))
nd = '%s\\判决书_内容未知_%s.docx'%(os.path.split(doc_name)[0],t2)
else:
nd = '%s\\判决书_%s.docx'%(os.path.split(doc_name)[0],anhao.strip())
if(doc_name == nd): # 相同则返回
return 0
try: # 不同则命名，检测源文件存在
if os.path.exists(nd):
postfix = ''.join(random.choice(string.ascii_letters) for _ in range(6))
nd = nd.replace('.docx','_重复_%s.docx'%postfix)
os.rename(doc_name,nd)
PrintLog.log('>>> 重命名判决书 => ',nd)
except Exception as e:
PrintLog.log(e); return 0
return 1
if __name__ == '__main__':
from Global import *
JdocsExtract1 = JdocsExtract()
df = JdocsExtract1.get_member_info_all(doc_folder,
df_input_name=jdocs_extract_path,
df_output_name=jdocs_extract_path,
isSave=1)