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Back 📄 Python libraries that can extract data from 📁 documents like Word, 📚 PDF, Excel, etc. 06 May, 2025
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Python libraries depending on the document type:

📄 1. PDFs

Library Purpose Example
PyMuPDF (fitz) Extract text, images, metadata from PDFs fitz.open("file.pdf").get_page_text(0)
pdfplumber Accurate text extraction, tables pdfplumber.open("file.pdf")
PyPDF2 / pypdf Basic text and metadata reader.getPage(0).extract_text()

📄 2. Word Documents (.docx)

Library Purpose Example
python-docx Extract & manipulate DOCX content Document("file.docx").paragraphs

📄 3. Excel (.xlsx, .xls)

Library Purpose Example
openpyxl Read/write .xlsx load_workbook("file.xlsx")
pandas Load Excel into DataFrames pd.read_excel("file.xlsx")
xlrd Read .xls files (older Excel) xlrd.open_workbook("file.xls")

📄 4. Scanned Documents / Images (OCR)

Library Purpose Example
pytesseract OCR text from images/PDFs pytesseract.image_to_string(Image.open("scan.jpg"))
easyocr Supports multiple languages, robust OCR reader.readtext("scan.jpg")

🧠 Combined Workflow for RAG / Data Extraction

If you're building a Retriever or a RAG system, combine:

  • 📝 LangChain or Haystack for pipelines

  • 📁 Unstructured or LangChain.document_loaders for document ingestion

  • 📚 Vector stores like FAISS, Chroma, or Pinecone for retrieval