docling-parse
Simple package to extract text with coordinates from programmatic PDFs
Decision gist · record as of 2026-08-14
Yes. Docling Parse is actively maintained, permissively licensed, and offers a well-designed API for structured PDF extraction with multi-threaded support. Install friction is moderate due to compiled components, but pre-built wheels cover all major platforms and Python versions. Suitable for production document processing workflows.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python >=3.10; compiled wheels depend on system C++ runtime libraries.
- Medium install friction due to compiled C++ components with pre-built wheels for Python 3.10–3.14 across macOS, Linux, and Windows.
- Active maintenance with a release on 2026-08-14 and 326 repository stars.
License · maintenance · safety
MIT (permissive) — MIT license permits unrestricted use, modification, and distribution in both open-source and commercial projects.
last release 2026-08-14 (0 days) · last repo commit 2026-08-14 · 326 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 4,605,553 downloads/mo, #2,275 on PyPI
Alternatives
Verify before relying
pip install docling-parse
from docling_parse.pdf_parser import DoclingPdfParser, DecodeConfig, ContentConfig, ContentLevel
parser = DoclingPdfParser(loglevel="fatal")
pdf_doc = parser.load(
path_or_stream="file.pdf",
decode_config=DecodeConfig(do_sanitization=True),
content_config=ContentConfig(
word_cells_content_level=ContentLevel.COMPUTE_AND_MATERIALIZE,
),
)
for page_no, page in pdf_doc.iterate_pages():
for word in page.iterate_cells():
print(word.rect, word.text)- Whether the package handles encrypted or password-protected PDFs beyond what the CLI suggests.
- Performance characteristics on very large PDFs or batch workloads compared to alternatives.
- Memory footprint when materializing all cell levels for high-page-count documents.
What it is and what it does
Docling Parse is a Python wrapper around a C++ PDF parser that extracts structured text, geometric coordinates, and images from programmatic PDFs. It splits parsing into two phases: a fixed `DecodeConfig` applied at document open time (controlling sanitization and glyph handling) and a per-page `ContentConfig` that determines what to compute and materialize (character cells, word cells, line cells, shapes, bitmaps). This separation allows cheap initial loading and selective enrichment on demand—if you request richer output later, the page is re-decoded automatically.
The package supports both sequential parsing (one PDF at a time) and parallel multi-threaded parsing with backpressure control. It includes a CLI for single-file processing and integrates with the broader Docling PDF conversion ecosystem. The library is actively maintained, supports Python 3.10–3.14 across major platforms, and provides performance benchmarks against other PDF packages.
Use it for
- Extract word-level bounding boxes and text from PDFs for document layout analysis or OCR validation.
- Batch-process multiple PDFs in parallel with configurable thread pools and result backpressure.
- Render pages as images with overlaid cell boundaries (character, word, or line level) for debugging or visualization.
- Selectively materialize only the content levels needed per page to optimize memory and CPU in large-scale workflows.
- Integrate PDF parsing into document conversion pipelines that require both text and spatial metadata.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Docling Parse is actively maintained, permissively licensed, and offers a well-designed API for structured PDF extraction with multi-threaded support. Install friction is moderate due to compiled components, but pre-built wheels cover all major platforms and Python versions. Suitable for production document processing workflows.
Install
docling-parse on PyPI
Before you install
Medium install friction due to compiled C++ components with pre-built wheels for Python 3.10–3.14 across macOS, Linux, and Windows. Active maintenance with a release on 2026-08-14 and 326 repository stars.
Requires Python >=3.10; compiled wheels depend on system C++ runtime libraries.
License in practice
MIT license permits unrestricted use, modification, and distribution in both open-source and commercial projects.
Quickstart
pip install docling-parse
from docling_parse.pdf_parser import DoclingPdfParser, DecodeConfig, ContentConfig, ContentLevel
parser = DoclingPdfParser(loglevel="fatal")
pdf_doc = parser.load(
path_or_stream="file.pdf",
decode_config=DecodeConfig(do_sanitization=True),
content_config=ContentConfig(
word_cells_content_level=ContentLevel.COMPUTE_AND_MATERIALIZE,
),
)
for page_no, page in pdf_doc.iterate_pages():
for word in page.iterate_cells():
print(word.rect, word.text)Verify before relying
- Whether the package handles encrypted or password-protected PDFs beyond what the CLI suggests.
- Performance characteristics on very large PDFs or batch workloads compared to alternatives.
- Memory footprint when materializing all cell levels for high-page-count documents.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | 4 packagespillowpydanticdocling-corepywin32 |
| Maintenance | Actively maintained 0 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 4,605,553 / month, #2,275 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: Science/ResearchOperating System :: MacOS :: MacOS XOperating System :: Microsoft :: WindowsOperating System :: POSIX :: LinuxProgramming Language :: C++Programming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14 |
Evidence: docling_parse-7.13.0-cp310-cp310-macosx_14_0_arm64.whl; docling_parse-7.13.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl; docling_parse-7.13.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl; docling_parse-7.13.0-cp310-cp310-win_amd64.whl; docling_parse-7.13.0-cp310-cp310-win_arm64.whl; docling_parse-7.13.0-cp311-cp311-macosx_14_0_arm64.whl; docling_parse-7.13.0-cp311-cp311-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl; docling_parse-7.13.0-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl; docling_parse-7.13.0-cp311-cp311-win_amd64.whl; docling_parse-7.13.0-cp311-cp311-win_arm64.whl; docling_parse-7.13.0-cp312-cp312-macosx_14_0_arm64.whl; docling_parse-7.13.0-cp312-cp312-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl; docling_parse-7.13.0-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl; docling_parse-7.13.0-cp312-cp312-win_amd64.whl; docling_parse-7.13.0-cp312-cp312-win_arm64.whl; docling_parse-7.13.0-cp313-cp313-macosx_14_0_arm64.whl; docling_parse-7.13.0-cp313-cp313-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl; docling_parse-7.13.0-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl; docling_parse-7.13.0-cp313-cp313-win_amd64.whl; docling_parse-7.13.0-cp313-cp313-win_arm64.whl
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See also docling · textract · docling-core · unPDF · docling-slim · marker-pdf · pdftotext · pdftext · docling-ibm-models · langchain-docling