> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/microsoft/markitdown/llms.txt
> Use this file to discover all available pages before exploring further.

# PdfConverter

> Convert PDF files to Markdown with intelligent table extraction

## Overview

The `PdfConverter` class converts PDF documents to Markdown, with advanced features for extracting tables into properly formatted Markdown tables. It uses a hybrid approach combining `pdfplumber` for form-style documents and `pdfminer` for text-heavy documents.

## Dependencies

<CodeGroup>
  ```bash pip theme={null}
  pip install markitdown[pdf]
  ```

  ```bash uv theme={null}
  uv pip install markitdown[pdf]
  ```
</CodeGroup>

Requires: `pdfminer.six`, `pdfplumber`

## Accepted Formats

<ParamField path="MIME Types" type="list">
  * `application/pdf`
  * `application/x-pdf`
</ParamField>

<ParamField path="Extensions" type="list">
  * `.pdf`
</ParamField>

## Methods

### accepts()

```python theme={null}
def accepts(
    file_stream: BinaryIO,
    stream_info: StreamInfo,
    **kwargs: Any,
) -> bool
```

Returns `True` if the file has a `.pdf` extension or PDF MIME type.

### convert()

```python theme={null}
def convert(
    file_stream: BinaryIO,
    stream_info: StreamInfo,
    **kwargs: Any,
) -> DocumentConverterResult
```

Converts a PDF file to Markdown.

**Returns:** `DocumentConverterResult` with converted Markdown text

**Raises:** `MissingDependencyException` if PDF dependencies are not installed

## Features

### Intelligent Extraction Strategy

The converter analyzes each page and selects the optimal extraction method:

1. **Form-Style Extraction** - For documents with structured layouts (forms, invoices, tables)
   * Analyzes word positions to detect column structures
   * Extracts borderless tables by detecting aligned text
   * Generates properly formatted Markdown tables with headers and separators

2. **Text Extraction** - For plain text documents (reports, articles)
   * Falls back to `pdfminer` for better text spacing and readability
   * Used when less than 20% of pages are form-style

### Table Detection

The converter detects tables by:

* Analyzing word positions and alignment across rows
* Identifying consistent column structures (3-20 columns)
* Detecting header rows and data rows
* Filtering out multi-column text layouts (scientific papers)

### Special Formatting

**MasterFormat Numbering** - Automatically merges partial numbering patterns:

```
.1
The intent of this Request for Proposal...
```

Becomes:

```
.1 The intent of this Request for Proposal...
```

## Example Usage

```python theme={null}
from markitdown.converters import PdfConverter
from markitdown._stream_info import StreamInfo

converter = PdfConverter()

with open("document.pdf", "rb") as f:
    stream_info = StreamInfo(extension=".pdf")
    
    if converter.accepts(f, stream_info):
        result = converter.convert(f, stream_info)
        print(result.markdown)
```

### Output Example

For a PDF with tables:

```markdown theme={null}
| Column 1 | Column 2 | Column 3 |
| -------- | -------- | -------- |
| Value 1  | Value 2  | Value 3  |
| Value 4  | Value 5  | Value 6  |

Regular paragraph text appears as plain markdown.

| Header A | Header B |
| -------- | -------- |
| Data A   | Data B   |
```

## Implementation Details

### Source Location

`~/workspace/source/packages/markitdown/src/markitdown/converters/_pdf_converter.py:495`

### Key Functions

* `_extract_form_content_from_words()` - Detects and extracts form-style tables
* `_extract_tables_from_words()` - Extracts traditional bordered tables
* `_merge_partial_numbering_lines()` - Post-processes MasterFormat numbering
* `_to_markdown_table()` - Formats extracted tables as Markdown

### Algorithm Highlights

1. **Adaptive Tolerance** - Column boundaries calculated using 70th percentile of gaps
2. **Column Clustering** - Groups nearby x-positions into columns (configurable tolerance)
3. **Table Quality Validation** - Ensures detected tables have consistent structure
4. **Hybrid Fallback** - Automatically switches extraction method if needed

## Performance Considerations

* PDF is read into memory (`BytesIO`) for compatibility with both libraries
* Pages are processed sequentially
* Large PDFs may require significant memory
* Complex forms with 15+ columns use adaptive extraction