Simple package to extract text with coordinates from programmatic PDFs

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Project description

Docling Parse

Simple package to extract text, paths and bitmap images with coordinates from programmatic PDFs. This package is used in the Docling PDF conversion. Below, we show a few output of the latest parser with char, word and line level output for text, in addition to the extracted paths and bitmap resources.

To do the visualizations yourself, simply run (change word into char or line),

uv run python ./docling_parse/visualize.py -i <path-to-pdf-file> -c word --interactive

original	char	word	line

Quick start

Install the package from Pypi

pip install docling-parse

Convert a PDF (look in the visualize.py for a more detailed information)

from docling_core.types.doc.page import TextCellUnit
from docling_parse.pdf_parser import DoclingPdfParser, PdfDocument

parser = DoclingPdfParser()

pdf_doc: PdfDocument = parser.load(
    path_or_stream="<path-to-pdf>"
)

# PdfDocument.iterate_pages() will automatically populate pages as they are yielded.
for page_no, pred_page in pdf_doc.iterate_pages():

    # iterate over the word-cells
    for word in pred_page.iterate_cells(unit_type=TextCellUnit.WORD):
        print(word.rect, ": ", word.text)

        # create a PIL image with the char cells
    img = pred_page.render_as_image(cell_unit=TextCellUnit.CHAR)
    img.show()

Use the CLI

$ docling-parse -h
usage: docling-parse [-h] -p PDF

Process a PDF file.

options:
  -h, --help         show this help message and exit
  -p PDF, --pdf PDF  Path to the PDF file

Performance Benchmarks

Characteristics of different parser versions

Version	Original	Word-level	Snippet-level	Performance
V1		Not Supported		~0.250 sec/page
V2				~0.050 sec/page [~5-10X faster than v1]

Timings of different parser versions

We ran the v1 and v2 parser on DocLayNet. We found the following overall behavior

parser-performance

Development

CXX

To build the parse, simply run the following command in the root folder,

rm -rf build; cmake -B ./build; cd build; make

You can run the parser from your build folder. Example from parse_v1,

% ./parse_v1.exe -h
A program to process PDF files or configuration files
Usage:
  PDFProcessor [OPTION...]

  -i, --input arg          Input PDF file
  -c, --config arg         Config file
      --create-config arg  Create config file
  -o, --output arg         Output file
  -l, --loglevel arg       loglevel [error;warning;success;info]
  -h, --help               Print usage

Example from parse_v2,

% ./parse_v2.exe -h
program to process PDF files or configuration files
Usage:
  PDFProcessor [OPTION...]

  -i, --input arg          Input PDF file
  -c, --config arg         Config file
      --create-config arg  Create config file
  -p, --page arg           Pages to process (default: -1 for all) (default:
                           -1)
  -o, --output arg         Output file
  -l, --loglevel arg       loglevel [error;warning;success;info]
  -h, --help               Print usage

If you dont have an input file, then a template input file will be printed on the terminal.

Python

To build the package, simply run (make sure uv is installed),

uv sync

The latter will only work after a clean git clone. If you are developing and updating C++ code, please use,

# uv pip install --force-reinstall --no-deps -e .
rm -rf .venv; uv venv; uv pip install --force-reinstall --no-deps -e ".[perf-tools]"

To test the package, run:

uv run pytest ./tests -v -s

Contributing

Please read Contributing to Docling Parse for details.

References

If you use Docling in your projects, please consider citing the following:

@techreport{Docling,
  author = {Deep Search Team},
  month = {8},
  title = {Docling Technical Report},
  url = {https://arxiv.org/abs/2408.09869},
  eprint = {2408.09869},
  doi = {10.48550/arXiv.2408.09869},
  version = {1.0.0},
  year = {2024}
}

License

The Docling Parse codebase is under MIT license. For individual model usage, please refer to the model licenses found in the original packages.

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ibm-deepsearch-core

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Release history Release notifications | RSS feed

This version

4.7.0

Oct 20, 2025

4.6.0

Oct 17, 2025

4.5.1

Oct 16, 2025

4.5.0

Sep 17, 2025

4.4.0

Sep 4, 2025

4.3.0 yanked

Sep 3, 2025

Reason this release was yanked:

Defects in parsing

4.2.3

Aug 22, 2025

4.2.2

Aug 19, 2025

4.2.1

Aug 19, 2025

4.2.0

Aug 19, 2025

4.1.0

Jun 24, 2025

4.0.5

Jun 13, 2025

4.0.4

Jun 10, 2025

4.0.3

Jun 5, 2025

4.0.2

Jun 4, 2025

4.0.1

Apr 9, 2025

4.0.0

Mar 14, 2025

3.4.0

Feb 18, 2025

3.3.1

Feb 13, 2025

3.3.0

Feb 6, 2025

3.2.0

Feb 2, 2025

3.1.2

Jan 27, 2025

3.1.1

Jan 21, 2025

3.1.0

Jan 17, 2025

3.0.0

Dec 9, 2024

2.1.2

Nov 22, 2024

2.1.0

Nov 20, 2024

2.0.5

Nov 20, 2024

2.0.4

Nov 13, 2024

2.0.3

Nov 5, 2024

2.0.2

Oct 30, 2024

2.0.1

Oct 25, 2024

2.0.0

Oct 23, 2024

1.6.2

Oct 18, 2024

1.6.1

Oct 18, 2024

1.6.0

Oct 11, 2024

1.5.1

Oct 10, 2024

1.4.1

Oct 2, 2024

1.3.1 yanked

Sep 30, 2024

1.3.0

Sep 20, 2024

1.2.1

Sep 18, 2024

1.2.0

Sep 9, 2024

1.1.3

Aug 30, 2024

1.0.0

Aug 22, 2024

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docling-parse 4.7.0

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SHA256	`aeed8ab02812eeff9e39cfe77939b899a61f635a9253914f58aa9966240c7485`
MD5	`4f74cb8f0025174f425e621b9c74ea00`
BLAKE2b-256	`79875fd9f71a4dd4702f886b078f4c39a6597b11df9828751c0ef397a2c4e0d0`

Algorithm	Hash digest
SHA256	`fb784ae7fa2ca8e63981aeaef005002f7824a13517b1e9d96085cb40f6b228f3`
MD5	`89ee7923128fd177b113d7d4c14d4f9c`
BLAKE2b-256	`d8456f558ba5f8dbc8c7c30d9c345377862c9cd8e131d98f4f9719199e848084`

Algorithm	Hash digest
SHA256	`4ff2072ba65802dac8121a50b7d698fb04f14cbd4ae144ffa917204bb5beafe4`
MD5	`511aaadf576aa1eb05f1393c265ed124`
BLAKE2b-256	`af8ccab69f67956297c09d928f00568d6ee75a258a1946d58eded87db49b1a58`

Algorithm	Hash digest
SHA256	`40805ee21a2b112a88231034338839ecbd17a60734e232fe130ad3af66b00a33`
MD5	`9fa4d726c76d0c42fb0e6127105a57b4`
BLAKE2b-256	`3c757f09cd1e64db62e6a6068115e2b12bb491b61c2d1986a36a7973b6d07a3c`

Algorithm	Hash digest
SHA256	`1f5e1961d5b0e63233e4ed668be86ef351fb679e1c36680f624837259b5c75d4`
MD5	`047945a083865036bf0c8ac4520b5b2a`
BLAKE2b-256	`9937f9ab4bd3de4a9221c32db18920b788782cab17e04dd17c18764f499a4d75`

Algorithm	Hash digest
SHA256	`771518c091be3fbbaffe75739ac7eca94c62a8ad5bc9cccedba861486b3a4a8f`
MD5	`064fb90cac4f68878f134a772f000ace`
BLAKE2b-256	`52e6764feb80779121d4adc5d1062f46384da2168973ca20c63bc8c7f4450475`