```yaml
product: AlterLab
title: "PDF Extraction — Web Scraping Glossary | AlterLab"
comparison_context: "AlterLab is an alternative to Firecrawl, ScrapingBee, and Bright Data."
source_url: https://alterlab.io/glossary/pdf-extraction
```

extraction

# PDF Extraction

PDF extraction involves parsing PDF files to retrieve structured text, tables, and metadata from documents served as downloadable files rather than HTML pages.

Government data, financial reports, academic papers, and legal documents are frequently published as PDFs rather than web pages. Extracting data from a PDF requires either parsing the PDF's internal content stream (which encodes text, fonts, and layout) or rendering the PDF to an image and applying OCR.

Libraries such as pdfplumber, PyPDF2, and Apache PDFBox can extract text from PDFs that contain embedded text objects. However, many scanned documents or image-only PDFs lack embedded text; these require OCR (optical character recognition) using tools like Tesseract or cloud vision APIs to recover the underlying content.

Table extraction from PDFs is particularly challenging because PDFs encode tables as positioned text objects rather than structured table elements. Specialised libraries use spatial analysis — grouping text objects by their X/Y coordinates — to reconstruct tabular structure.

### What is PDF Extraction?

PDF extraction involves parsing PDF files to retrieve structured text, tables, and metadata from documents served as downloadable files rather than HTML pages.

### How does AlterLab handle PDF Extraction?

Table extraction from PDFs is particularly challenging because PDFs encode tables as positioned text objects rather than structured table elements. Specialised libraries use spatial analysis — grouping text objects by their X/Y coordinates — to reconstruct tabular structure.

## Examples

```
# pdfplumber: extract text and tables from a PDF
import pdfplumber

with pdfplumber.open("report.pdf") as pdf:
    for page in pdf.pages:
        print(page.extract_text())
        for table in page.extract_tables():
            print(table)
```

## Related Terms

[Structured Data ExtractionConverting free-form HTML into typed JSON records using explicit schemas, producing clean structured output instead of raw markup.](https://alterlab.io/glossary/structured-data-extraction)[Parse TreeThe hierarchical tree structure created by an HTML parser that represents the DOM elements of a web page for programmatic traversal.](https://alterlab.io/glossary/parse-tree)[Data ExtractionThe process of identifying and pulling specific fields from raw web content, converting unstructured HTML into typed JSON records.](https://alterlab.io/glossary/data-extraction)[BeautifulSoupA Python library for parsing HTML and XML and navigating the parse tree using CSS selectors or tag methods.](https://alterlab.io/glossary/beautifulsoup)[XPathXML Path Language — a query syntax for selecting nodes in HTML or XML using path expressions, more expressive than CSS selectors for complex traversals.](https://alterlab.io/glossary/xpath)

## Extract PDF Extraction data from any website

AlterLab returns clean, structured data from any public URL — no scraper infrastructure needed. Start free, no credit card required.

[View API docs](https://alterlab.io/docs/api/rest)

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