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A pdf extractor10/13/2023 ![]() # 加载txt列表寻找关键词并保存到excel def matchKeyWords( txt_folder, excel_path, keyWords, year): With open( TXT_path, 'a', encoding = 'UTF-8', errors = 'ignore') as f: ![]() get_pages(): # doc.get_pages() 获取page列表 interpreter. Interpreter = PDFPageInterpreter( rsrcmgr, device) # 创建一个PDF解释器对象 # 循环遍历列表,每次处理一个page的内容 for page in doc. Rsrcmgr = PDFResourceManager() # 创建PDf 资源管理器 来管理共享资源 laparams = LAParams() # 创建一个PDF设备对象 device = PDFPageAggregator( rsrcmgr, laparams = laparams) Want to improve it? Submit a pull request.# 解析PDF文件,转为txt格式 def parsePDF( PDF_path, TXT_path): ![]() If you use Textricator, let us know how it helped solve your data problem. Textricator is an essential part of our process and we hope civic tech and government organizations alike can unlock more data with this new tool. You can see the results of our work, including data processed via Textricator, on our free online data portal. Textricator is available on GitHub and released under GNU Affero General Public License Version 3. “Textricator is both flexible and powerful and has cut the time we spend to process large datasets from days to hours,” says Andrew Branch, director of technology.Īt MFJ, we’re committed to transparency and knowledge-sharing, which includes making our software available to anyone, especially those trying to free and share data publicly. We evaluated other great open source solutions like Tabula, but they just couldn’t handle the structure of some of the PDFs we needed to scrape. Most users run it via the command line however, a browser-based GUI is available. Not a software engineer? Textricator doesn’t require programming skills rather, the user describes the structure of the PDF and Textricator handles the rest. Simply tell Textricator the attributes of the fields you want to collect, and it chomps through the document, collecting and writing out your records. Textricator can process just about any text-based PDF format-not just tables, but complex reports with wrapping text and detail sections generated from tools like Crystal Reports. PDF reports are the best they can offer.ĭevelopers Joe Hale and Stephen Byrne have spent the past two years developing Textricator to extract tens of thousands of pages of data for our internal use. We get our data in many ways-all legal, of course-and while many state and county agencies are data-savvy, giving us quality, formatted data in CSVs, the data is often bundled inside software with no simple way to get it out. Our mission is to provide data transparency for the entire justice system, from arrest to post-conviction. We do this by producing a series of up to 32 performance measures covering the entire criminal justice system, county by county. We’re Measures for Justice, a criminal justice research and transparency organization. We understand your frustration, and we’ve done something about it: Introducing Textricator, our first open source product. You probably know the feeling: You ask for data and get a positive response, only to open the email and find a whole bunch of PDFs attached.
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