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What’s the best approach to scraping PDF documents online?
I use pdfplumber or PyPDF2 in Python to extract text from PDFs directly, which works well for text-heavy documents.
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7 Replies
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Optical Character Recognition (OCR) with Tesseract is effective for scanned PDFs, though it requires more processing and is less accurate.
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If the PDFs follow a specific structure, regex helps isolate specific data fields like names, dates, or amounts from the raw text.
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I sometimes convert PDFs to HTML before scraping, which allows for easier data extraction, especially with tabular data.
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Tabula is another great tool for extracting tables from PDFs. I use it to pull tabular data into a structured format for further processing.
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For websites that host multiple PDFs, I use BeautifulSoup to locate and download all PDF links in bulk before extraction.
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If the data is consistent, I automate the process to filter out only relevant pages, saving time when processing large documents.
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Cloud-based OCR solutions, like Google Vision API, handle complex PDFs more effectively, though there’s a cost involved.
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