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1Fix the driver behind crashes, sound loss and screen glitches2Repair Windows errors before they cause bigger problems3Scan for outdated or missing drivers - takes under a minuteDocling can convert PDFs into readable Markdown or structured JSON while representing tables, page content, and reading order. Start with docling convert report.pdf --to md for a human-readable export, or use --to json when downstream code needs the document structure. For image-only scans, enable full-page OCR with --ocr-mode full_page. Table extraction and reading order still need checking against the source pages: Docling documents the controls, but does not promise universal accuracy.
Choose Markdown or JSON for your PDF output
Docling supports PDF layout analysis, reading order, and table understanding. Its document model can be exported into different formats, so choose according to what will consume the result.
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| Output | Use it when | What to expect |
|---|---|---|
| Markdown | You primarily need content that people can read or review. | Tables can be rendered as Markdown tables. See the official examples. |
| JSON | A program or workflow needs structured document content. | The DoclingDocument model represents items such as text, tables, pictures, and key-value items, with a body tree that carries document structure. See the DoclingDocument concept documentation. |
For a quick Markdown conversion, run:
docling convert report.pdf --to mdFor JSON, use:
docling convert report.pdf --to jsonThe command examples are shown on the Docling homepage. Markdown is convenient for inspection and publishing; JSON is the better starting point when software must inspect or transform the document’s hierarchy rather than parse a rendered text export.
Enable and tune table extraction
Docling’s PDF pipeline has a do_table_structure option for extracting and reconstructing table structure. The PDF pipeline options document the setting, and the examples show enabling it in Python and exporting the converted document as Markdown.
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The examples distinguish a faster approximate table mode from an accurate mode that uses TableFormer for complex tables, including tables with merged cells. These are configuration choices, not a general accuracy guarantee.
Use the faster approximate mode for simpler tables
When processing needs favor a faster pass and the table layout is straightforward, the approximate mode may be an appropriate starting point. Review its output, especially where rows or columns are close together.
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Use accurate TableFormer mode for complex tables
For complex layouts or merged cells, choose the documented accurate mode using TableFormer. Then verify that the extracted cell relationships match the original page; the mode description does not establish that every table will be reconstructed correctly.
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Validate the exported table against its page
Compare the result with the source PDF, checking that headers, row boundaries, merged cells, and nearby captions are represented as intended. In particular, ensure a caption has not been absorbed into the table or separated from it in a way that changes meaning.
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Preserve and inspect reading order
In Docling’s document model, reading order is encoded by the body tree and the order of each item’s children, as described in the DoclingDocument concept documentation. The model also distinguishes page furniture, such as headers and footers, from the main body.
When reading sequence matters, inspect the JSON hierarchy or review the Markdown rendering on representative pages. Focus on multi-column layouts, headers and footers, sections with rules, and the point where a table meets surrounding prose. The representation provides structure to inspect; it does not guarantee that every page layout will be interpreted correctly.
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Decide whether visible rules should guide reading order
When the PDF backend exposes the geometry of visible horizontal or vertical rules, the reading-order stage can use those rules as structural signals. The option is enabled by default. The pipeline options and advanced options explain the controls; in Python, the setting can be disabled, or use this CLI flag:
--no-reading-order-separatorsLeave the default in place unless the rules are interfering with the order you need. If the output sequence looks wrong, compare the rendered result with the original page and test the setting on representative pages.
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Use OCR for image-only scans
OCR is intended for scanned or image-based documents, and it adds processing time. For an image-only scan, Docling’s command example uses full-page OCR:
docling convert scan.pdf --ocr-mode full_page --to mdSee the pipeline options for OCR behavior and the homepage for the command example. If a PDF already has an embedded text layer, first check whether its text is available; do not assume every PDF needs OCR. A physical scanner is only relevant if you still need to digitize paper. It is not needed to process a PDF you already have.
Configure PDF conversion in Python
Use DocumentConverter with PdfFormatOption when you need to set PDF pipeline options in code. The official examples demonstrate enabling table extraction with PdfPipelineOptions and exporting the result to Markdown.
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Quick Recap
A practical configuration checklist
- Choose Markdown for a human-readable result or JSON when software needs structured content.
- Enable table structure extraction when the PDF contains tables you need to preserve.
- Choose between the faster approximate mode and accurate TableFormer mode based on table complexity, then check the result against the page.
- Use full-page OCR for image-only scans; first determine whether a digital PDF already has usable text.
- Inspect the JSON body tree or Markdown output where multi-column content, rules, page furniture, or tables could affect sequence.
- Keep reading-order separators enabled by default unless visible rules are producing an unwanted sequence.
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