Delete cas_match.py

cas_match.py

@@ -1,266 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-Created on Sun Jun  4 15:55:12 2023
-
-@author: wooji
-"""
-import re
-import streamlit as st
-import numpy as np
-import pandas as pd
-import streamlit as st
-import pandas as pd
-from io import StringIO
-import pdfplumber
-import xlrd
-import re
-import pdfplumber
-import pandas as pd
-import time
-import os
-import numpy as np
-#import pythoncom
-#import win32com
-#from win32com.client import Dispatch
-import docx2pdf
-import docx
-#import win32com.client as wc
-#import win32com.client as win32
-import pytesseract
-from PIL import  Image
-import os
-from pdf2image import convert_from_path,convert_from_bytes
-from io import BytesIO
-
-import openpyxl
-import base64
-st.title("MSDS报告CAS号提取程序")
-#%%
-from docx import Document
-
-def get_tables(docx_path):
-    docStr = Document(docx_path)
-    numTables = docStr.tables
-    my_list = []
-    for table in numTables:
-        row_count = len(table.rows)       
-        col_count = len(table.columns)
-        for i in range(row_count):
-            row = table.rows[i].cells
-            for j in range(col_count):     
-                    content = row[j].text  
-                    my_list.append(content)
-    my_list = ';'.join(my_list).strip('')
-    return my_list
-
-
-def get_paragraphs(docx_path):
-    #打开word文档
-    document = Document(docx_path)  
-    #获取所有段落
-    all_paragraphs = document.paragraphs    
-    paragraph_texts = []
-    # 循环读取列表
-    for paragraph in all_paragraphs:
-        paragraph_texts.append(paragraph.text)
-    paragraph_texts = ';'.join(paragraph_texts).strip('')
-    return paragraph_texts
-
-
-
-#%% 函数二、打开pdf文件,输出每一页pdf中的所有文字
-def openpdf(path):
-    with pdfplumber.open(path) as pdf:
-        # pdf = pdfplumber.open(path)
-        item = []
-        for page in pdf.pages:
-            text = page.extract_text()
-            item.append(text)
-        # item = [''.join(i) for i in item]
-        item = ';'.join(item).strip('')
-    return item
-
-#%% 函数三、将目标CAS号，和pdf中的内容进行比对。返回什么？
-def extract(text,cas):
-    pattern = re.compile(cas,re.S)
-    r_list = pattern.findall(text)
-    return r_list
-#%%
-# data = pd.DataFrame(columns=['CAS','名称','匹配结果','备注'])
-st.write('使用说明')
-st.caption('支持解析的格式：.pdf(扫描版或非扫描版均支持)和.docx。可将MSDS文件夹直接拖拽到下方上传区域')
-st.write('excel输出内容详解')
-st.caption('第一列为文件名称,所有上传的文件均会显示在第一列，即便该文件格式不支持提取')
-st.caption('第二列为文件中提取的CAS号,若为空则表明未提取到')
-st.caption('第三列为化学物质名称,仅支持显示与清单匹配成功的化学物质的名称')
-st.caption('第四列为匹配结果,共3种结果：3960种、优评优控、重点管控')
-st.caption('第五列为备注,共3种结果：1、不支持该格式文件，请手动查看：说明此类文件不支持解析，请手动查看；2、图片pdf，建议人工复核：说明该pdf为图片，提取正确率较低，视情况可进行人工复核；3、未检测到CAS，请手动检查：说明在该文件中未检测到CAS，请人工确认')
-
-st.caption('提取速度：提取一个电子pdf大约耗时4s，一个扫描版pdf大约耗时10~20s。具体速度由pdf的页数决定')
-st.divider()
-uploaded_file = st.file_uploader("请上传MSDS报告，可直接往里拖拽文件夹",accept_multiple_files=True)
-@st.cache_data
-def main(uploaded_file):
-    data = pd.DataFrame(columns=['CAS','名称','匹配结果','备注'])
-
-    begin = time.time()
-    # openpdf(uploaded_file)
-    cas = r'[0-9]+-[0-9][0-9]-[0-9][^0-9]' 
-    # st.write(extract(openpdf(uploaded_file),cas))
-    for file in range(len(uploaded_file)):
-        if uploaded_file[file].name[-4:] == 'docx':
-            text =  get_paragraphs(uploaded_file[file])
-            # text(get_tables(uploaded_file[file]))
-            # text = ';'.join(text).strip('')                       
-        elif uploaded_file[file].name[-3:] == 'pdf' or uploaded_file[file].name[-3:] == 'PDF':  
-            text = openpdf(uploaded_file[file])
-        else:
-            cas_set = pd.DataFrame({'备注':{uploaded_file[file].name:'不支持该格式文件，请手动查看'}})
-            data = pd.concat([data,cas_set],axis=0) 
-            continue
-        cas_extract = extract(text,cas)
-        if cas_extract != []:
-            for item in range(len(cas_extract)):
-                cas_iso = cas_extract[item]
-                cas_iso = cas_iso[0:len(cas_iso)-1]
-                cas_set = pd.DataFrame({'CAS':{uploaded_file[file].name:cas_iso}})
-                data = pd.concat([data,cas_set],axis=0) 
-        #提取docx表格内的内容
-        elif uploaded_file[file].name[-4:] == 'docx':   
-            text = get_tables(uploaded_file[file])
-            # text = ';'.join(text).strip('') 
-            cas_extract = extract(text,cas)   
-            if cas_extract != []:
-                for item in range(len(cas_extract)):
-                    cas_iso = cas_extract[item]
-                    cas_iso = cas_iso[0:len(cas_iso)-1]
-                    cas_set = pd.DataFrame({'CAS':{uploaded_file[file].name:cas_iso}})
-                    data = pd.concat([data,cas_set],axis=0)
-            else:
-                cas_set = pd.DataFrame({'备注':{uploaded_file[file].name:'未检测到CAS，请手动检查'}})
-                data = pd.concat([data,cas_set],axis=0)
-        else:
-            pages = convert_from_bytes(uploaded_file[file].getvalue()) # 上传的内容是什么？
-            text = []
-            for i,page in enumerate(pages):
-                 buf = BytesIO()
-                 page.save(buf,format="JPEG")
-                 buf.seek(0)
-                 img_page=Image.open(buf)
-                 # st.write('here')
-                 txt=pytesseract.image_to_string(img_page,lang='chi_sim')
-                 text.append(txt)  
-            text = ';'.join(text).strip('')
-            cas_extract = extract(text,cas)
-            if cas_extract != []:
-                cas_extract = extract(text,cas)
-                for item in range(len(cas_extract)):
-                    cas_iso = cas_extract[item]
-                    cas_iso = cas_iso[0:len(cas_iso)-1]
-                    print(cas_iso)
-                    # cas_set = pd.Series({uploaded_file[file].name:cas_iso+'图片pdf，请手动检查'})   #在这里加备注提示是扫描版pdf
-                    #用dataframe承载
-                    cas_set = pd.DataFrame({'CAS':{uploaded_file[file].name:cas_iso},'备注':{uploaded_file[file].name:'图片pdf，建议人工复核'}})
-                    data = pd.concat([data,cas_set],axis=0)
-            else:
-                cas_set = pd.DataFrame({'备注':{uploaded_file[file].name:'未检测到CAS，请手动检查'}})
-                data = pd.concat([data,cas_set],axis=0)
-    
-    # st.write(uploaded_file)
-    # convert_from_bytes(open('/home/belval/example.pdf','rb').read())
-    
-    
-
-#%%数据整理
-    data_reset_index = data.reset_index(drop=False)  
-    #修改列名
-    data_rename = data_reset_index.rename(columns={'index':'MSDS文件名称'})    
-    #去除重复行             
-    data_output = data_rename.drop_duplicates()  #subset='pdf名称'可以查看是不是所有文件都包含在表格里
-    # target_data_base = pd.read_excel('C:/Users/wooji/Nutstore/1/Jiho华南所/鉴定中心-工作/MSDS/102-104物质清单.xlsx',sheet_name='基102-3960种',index_col=0)
-    # # target_data_pri = pd.read_excel('C:/Users/wooji/Nutstore/1/Jiho华南所/鉴定中心-工作/MSDS/物质清单.xlsx',sheet_name='优评优控',index_col=0)
-    # # target_data_key = pd.read_excel('C:/Users/wooji/Nutstore/1/Jiho华南所/鉴定中心-工作/MSDS/物质清单.xlsx',sheet_name='重点管控',index_col=0)
-    # target_cas_base = target_data_base[['CAS','名称']]
-    # target_cas_pri = target_data_pri[['CAS','名称']]
-    # target_cas_key = target_data_key[['CAS','名称']]
-    # target_cas_base = target_cas_base.reset_index(drop=True)
-    # target_cas_pri = target_cas_pri.reset_index(drop=True)
-    # target_cas_key = target_cas_key.reset_index(drop=True)
-    target_data = pd.read_excel('C:/Users/wooji/Nutstore/1/Jiho华南所/鉴定中心-工作/MSDS/物质清单.xlsx',sheet_name='总表',index_col=0)
-    target_cas = target_data[['CAS','名称','清单']]
-    target_cas = target_cas.reset_index(drop=True)
-
-    
-#%%
-    for row in data_output.index:
-        # print(data_output.loc[row]['CAS号提取'])
-        for b in target_cas.index:
-            if data_output.loc[row]['CAS'] == target_cas.loc[b]['CAS']:
-                data_output.loc[row]['匹配结果'] =target_cas.loc[b]['清单']
-                data_output.loc[row]['名称'] = target_cas.loc[b]['名称']
-    
- 
-    data_final = data_output
-    # [['pdf名称','匹配结果','CAS号提取','名称','备注']]
-    end = time.time()
-    run_time = end - begin
-    st.write('运行耗时：'+ str(round(run_time,2))+'秒')
-    return data_final
-
-
-if uploaded_file == []:
-    st.stop()
-else:  
-    data_final = main(uploaded_file)
-    data_final
-    data_final.to_excel('resuls.xlsx')
-    wb2 = openpyxl.load_workbook('resuls.xlsx')
-    wb2.save('results.xlsx')#注意！文件此时保存在内存中且为字节格式文件
-    data=open('results.xlsx','rb').read()#以只读模式读取且读取为二进制文件
-    b64 = base64.b64encode(data).decode('UTF-8')#解码并加密为base64
-    excel_name = st.text_input(':blue[请输入本次导入的文件所属企业名称，若为空则导出的excel默认取名为myresult.xlsx]')
-    st.warning('建议示例：广西xx企业-原辅料 or 广西xx企业-产品  ------- 输入完请按回车 ', icon="🚨")
-if excel_name:
-    excel_name = excel_name + '.xlsx'
-    href = f'<a href="data:file/data;base64,{b64}" download={excel_name}>导出excel</a>'#定义下载链接，���认的下载文件名是myresults.xlsx
-    st.markdown(href, unsafe_allow_html=True)#输出到浏览器
-    wb2.close()
-else:
-    href = f'<a href="data:file/data;base64,{b64}" download=myresult.xlsx>导出excel</a>'#定义下载链接，默认的下载文件名是myresults.xlsx
-    st.markdown(href, unsafe_allow_html=True)#输出到浏览器
-    wb2.close()
-        
-
-st.subheader('!!!单次使用完请刷新页面后再上传新的文件')
-
-
-# else:
-#     excel_name = excel_name + '.xlsx'
-#     href = f'<a href="data:file/data;base64,{b64}" download={excel_name}>Download xlsx file</a>'#定义下载链接，默认的下载文件名是myresults.xlsx
-#     st.markdown(href, unsafe_allow_html=True)#输出到浏览器
-#     wb2.close()
-
-
-
-
-####直接写识别图片的代码
-# stringio = StringIO(uploaded_file[file].getvalue().decode("utf-8"))
-# st.write(stringio)   ##这句是对的
-# bytes_data = uploaded_file[file].read()
-# st.write(bytes_data)
-# st.write(uploaded_file[file])
-# st.write(bytes_data)
-# =============================================================================
-#             ####
-#             stringio = StringIO(uploaded_file[file].getvalue().decode("utf-8"))
-#             st.write(stringio)
-#             # To read file as string:
-#             string_data = stringio.read()
-#             st.write(string_data)
-#             ###
-# =============================================================================
-
-
-
-
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