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 |
|---|---|---|---|
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Quick start
Install the package from PyPI:
pip install docling-parse
Sequential parsing
docling-parse v7 split page parsing into two public configs:
DecodeConfig: how to compute pages. This is fixed when a document is opened.ContentConfig: what to keep or materialize per page. This can be overridden per page.
from docling_core.types.doc.page import TextCellUnit
from docling_parse.pdf_parser import (
ContentConfig,
ContentLevel,
DecodeConfig,
DoclingPdfParser,
)
parser = DoclingPdfParser(loglevel="fatal")
pdf_doc = parser.load(
path_or_stream="<path-to-pdf>",
decode_config=DecodeConfig(
do_sanitization=True,
keep_glyphs=False,
),
content_config=ContentConfig(
char_cells_content_level=ContentLevel.SKIP,
word_cells_content_level=ContentLevel.COMPUTE_AND_MATERIALIZE,
line_cells_content_level=ContentLevel.COMPUTE_AND_MATERIALIZE,
shapes_content_level=ContentLevel.SKIP,
bitmaps_content_level=ContentLevel.SKIP,
),
)
for page_no, page in pdf_doc.iterate_pages():
print(page_no, len(page.word_cells), len(page.textline_cells))
for word in page.iterate_cells(unit_type=TextCellUnit.WORD):
print(word.rect, word.text)
image = page.render_as_image(cell_unit=TextCellUnit.WORD)
image.show()
If you open cheaply and later need richer output, request it per page. When the
new content_config needs entities that were previously skipped, that page is
re-decoded automatically:
from docling_parse.pdf_parser import ContentConfig, ContentLevel
page = pdf_doc.get_page(
1,
content_config=ContentConfig(
word_cells_content_level=ContentLevel.COMPUTE_AND_MATERIALIZE,
line_cells_content_level=ContentLevel.COMPUTE_AND_MATERIALIZE,
),
)
v6 -> v7 migration
The main API break in v7 is that the old public DecodePageConfig selection
flags were split into two concerns:
DecodeConfig: compute-time tuning onlyContentConfig: what to skip, compute, or materialize per page
In practice:
- open-time
decode_configreplaces the old per-page decode tuning - per-page content selection now lives in
content_config materialize_bitmap_bytesbecameinclude_bitmap_bytes- threaded
page_materialization_configbecamepage_content_config
Typical migration examples:
- old
DecodePageConfig.keep_char_cells=True->ContentConfig(char_cells_content_level=ContentLevel.COMPUTE_AND_MATERIALIZE) - old
DecodePageConfig.create_word_cells=Truewithout surfacing them everywhere ->ContentConfig(word_cells_content_level=ContentLevel.COMPUTE) - old
materialize_bitmap_bytes=False->ContentConfig(include_bitmap_bytes=False)
One semantic change matters: decode_config is now fixed when the document or
threaded batch is opened. If you want richer page output later, override
content_config on get_page(...) instead. On the sequential path this may
re-decode that page; on the threaded path you can only materialize entities the
batch already computed.
Parallel parsing (multi-threaded)
Parse one or more PDFs in parallel with backpressure:
from docling_parse.pdf_parser import (
ContentConfig,
ContentLevel,
DecodeConfig,
DoclingThreadedPdfParser,
ThreadedPdfParserConfig,
)
parser = DoclingThreadedPdfParser(
parser_config=ThreadedPdfParserConfig(
loglevel="fatal",
threads=4,
max_concurrent_results=32,
page_content_config=ContentConfig(
word_cells_content_level=ContentLevel.COMPUTE,
line_cells_content_level=ContentLevel.COMPUTE_AND_MATERIALIZE,
),
),
decode_config=DecodeConfig(),
)
doc_key = parser.load("doc_a.pdf", page_numbers=[1, 3, 5])
print(doc_key, parser.page_count(doc_key), parser.scheduled_page_count(doc_key))
for result in parser.iterate_results():
if not result.success:
print(result.doc_key, result.page_number, result.error_message)
continue
# Batch decode kept word cells in C++, but did not materialize them by default.
page = result.get_page(
ContentConfig(
word_cells_content_level=ContentLevel.COMPUTE_AND_MATERIALIZE,
line_cells_content_level=ContentLevel.COMPUTE_AND_MATERIALIZE,
)
)
print(
result.doc_key,
result.page_number,
len(page.word_cells),
result.timings.total_s,
)
For threaded parse-and-render workloads, set
ThreadedPdfParserConfig.render_config and use result.get_image(),
result.get_image(scale=...), or result.get_image(canvas_size=...).
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
System fonts
A PDF may name a font without embedding it. There is then nothing in the file
to draw with, and the renderer substitutes a face installed on the host --
which is why the same document renders differently on two machines, and why a
container with no fonts in it renders text as .notdef boxes ("tofu").
Install the usual desktop font packages for text, plus a CJK face for Chinese, Japanese and Korean documents:
| Debian / Ubuntu | fonts-dejavu-core fonts-liberation2 fonts-freefont-ttf fonts-urw-base35 fonts-noto-core fonts-noto-cjk |
| Fedora / RHEL | dejavu-sans-fonts liberation-sans-fonts urw-base35-fonts google-noto-sans-fonts google-noto-sans-cjk-fonts |
On Fedora and RHEL take the packages without -vf- in the name. The
variable-font builds carry CFF2 outlines, which the pinned Blend2D cannot read;
such a file is still drawn, through FreeType and without shaping, but the
static build is the better path.
Three environment variables override what gets substituted. Each names a font
file (.ttf, .otf, .ttc), and each is tried before the built-in
candidate list -- a path that does not exist, or that neither Blend2D nor
FreeType can open, is skipped rather than fatal:
| Variable | Used for |
|---|---|
DOCLING_PARSE_FALLBACK_FONT |
the general fallback, when a font name resolves to nothing |
DOCLING_PARSE_CJK_FALLBACK_FONT |
requests for a CJK family (/Batang, /SimSun, /MS Gothic, ...) |
DOCLING_PARSE_ARABIC_FALLBACK_FONT |
runs of Arabic script |
Setting them is also how a render is made reproducible across machines: pin the
same file everywhere and the substituted typeface stops being a property of the
host. Run with loglevel="info" to see which file was chosen for each font.
Performance Benchmarks
docs/performance_benchmarks.md compares docling-parse against the other widely used PDF packages on parsing and rendering, with the methodology and the commands to reproduce it.
The tooling behind it lives under scripts/benchmarking/:
scripts/benchmarking/run_performance_benchmarking.py: measure — thread-scaling sweeps and the cross-package comparisonscripts/benchmarking/run_performance_eval.py: plot — per-page distributions, thread scaling, and per-package correlationsscripts/benchmarking/run_performance_analysis.py: drill down — replay the slowest pages with C++ stage timingsscripts/benchmarking/run_quality_benchmarking.py: compare quality — textual output and rendered pixels across PDF engines
For historical V1 vs V2 benchmarks, see legacy_performance_benchmarks.md.
Development
CXX
To build the parser, 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:
% ./parse.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)
--password arg Password for accessing encrypted, password-protected files
-o, --output arg Output file
-l, --loglevel arg loglevel [error;warning;success;info]
-h, --help Print usage
If you don't have an input file, 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]"
or
BUILD_THREADS=12 uv pip install --force-reinstall --no-deps -e ".[perf]"
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 = {Docling 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.
LF AI & Data
Docling (and also docling-parse) is hosted as a project in the LF AI & Data Foundation.
IBM ❤️ Open Source AI
The project was started by the AI for knowledge team at IBM Research Zurich.
Release files for docling-parse 7.17.0
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Release files / docling_parse-7.17.0-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
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Release files / docling_parse-7.17.0-cp311-cp311-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl
| Download URL | docling_parse-7.17.0-cp311-cp311-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl |
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| Size | 10.3 MB |
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Release files / docling_parse-7.17.0-cp311-cp311-macosx_14_0_arm64.whl
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Release files / docling_parse-7.17.0-cp310-cp310-win_arm64.whl
| Download URL | docling_parse-7.17.0-cp310-cp310-win_arm64.whl |
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Release files / docling_parse-7.17.0-cp310-cp310-win_amd64.whl
| Download URL | docling_parse-7.17.0-cp310-cp310-win_amd64.whl |
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| Size | 11.7 MB |
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Release files / docling_parse-7.17.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
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| Download URL | docling_parse-7.17.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl |
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Release files / docling_parse-7.17.0-cp310-cp310-macosx_14_0_arm64.whl
| Download URL | docling_parse-7.17.0-cp310-cp310-macosx_14_0_arm64.whl |
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