# Docling Parse
[](https://pypi.org/project/docling-parse/)
[](https://pypi.org/project/docling-parse/)
[](https://python-poetry.org/)
[](https://github.com/pybind/pybind11/)
[](https://github.com/DS4SD/docling-parse/)
[](https://opensource.org/licenses/MIT)
Simple package to extract text with coordinates from programmatic PDFs.
This package is part of the [Docling](https://github.com/DS4SD/docling) conversion.
## Quick start
Install the package from Pypi
```sh
pip install docling-parse
```
Convert a PDF
```python
from docling_parse.docling_parse import pdf_parser
# Do this only once to load fonts (avoid initialising it many times)
parser = pdf_parser()
# parser.set_loglevel(1) # 1=error, 2=warning, 3=success, 4=info
doc_file = "my-doc.pdf" # filename
doc_key = f"key={pdf_doc}" # unique document key (eg hash, UUID, etc)
# Load the document from file using filename doc_file. This only loads
# the QPDF document, but no extracted data
success = parser.load_document(doc_key, doc_file)
# Open the file in binary mode and read its contents
# with open(pdf_doc, "rb") as file:
# file_content = file.read()
# Create a BytesIO object and write the file contents to it
# bytes_io = io.BytesIO(file_content)
# success = parser.load_document_from_bytesio(doc_key, bytes_io)
# Parse the entire document in one go, easier, but could require
# a lot (more) memory as parsing page-by-page
# json_doc = parser.parse_pdf_from_key(doc_key)
# Get number of pages
num_pages = parser.number_of_pages(doc_key)
# Parse page by page to minimize memory footprint
for page in range(0, num_pages):
# Internal memory for page is auto-deleted after this call.
# No need to unload a specifc page
json_doc = parser.parse_pdf_from_key_on_page(doc_key, page)
if "pages" not in json_doc: # page could not get parsed
continue
# parsed page is the first one!
json_page = json_doc["pages"][0]
page_dimensions = [json_page["dimensions"]["width"], json_page["dimensions"]["height"]]
# find text cells
cells=[]
for cell_id,cell in enumerate(json_page["cells"]):
cells.append([page,
cell_id,
cell["content"]["rnormalized"], # text
cell["box"]["device"][0], # x0 (lower left x)
cell["box"]["device"][1], # y0 (lower left y)
cell["box"]["device"][2], # x1 (upper right x)
cell["box"]["device"][3], # y1 (upper right y)
])
# find bitmap images
images=[]
for image_id,image in enumerate(json_page["images"]):
images.append([page,
image_id,
image["box"][0], # x0 (lower left x)
image["box"][1], # y0 (lower left y)
image["box"][2], # x1 (upper right x)
image["box"][3], # y1 (upper right y)
])
# find paths
paths=[]
for path_id,path in enumerate(json_page["paths"]):
paths.append([page,
path_id,
path["x-values"], # array of x values
path["y-values"], # array of y values
])
# Unload the (QPDF) document and buffers
parser.unload_document(doc_key)
# Unloads everything at once
# parser.unload_documents()
```
Use the CLI
```sh
$ 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
```
## Development
### CXX
To build the parse, simply run the following command in the root folder,
```sh
rm -rf build; cmake -B ./build; cd build; make
```
You can run the parser from your build folder with
```sh
./parse.exe <input-file> <optional-logging:true>
```
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 [poetry](https://python-poetry.org/) is [installed](https://python-poetry.org/docs/#installing-with-the-official-installer)),
```
poetry build
```
To test the package, run,
```
poetry run pytest ./tests/test_parse.py
```
## Contributing
Please read [Contributing to Docling Parse](https://github.com/DS4SD/docling-parse/blob/main/CONTRIBUTING.md) for details.
## References
If you use Docling in your projects, please consider citing the following:
```bib
@software{Docling,
author = {Deep Search Team},
month = {7},
title = {{Docling}},
url = {https://github.com/DS4SD/docling},
version = {main},
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.
Raw data
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"description": "# Docling Parse\n\n[](https://pypi.org/project/docling-parse/)\n[](https://pypi.org/project/docling-parse/)\n[](https://python-poetry.org/)\n[](https://github.com/pybind/pybind11/)\n[](https://github.com/DS4SD/docling-parse/)\n[](https://opensource.org/licenses/MIT)\n\nSimple package to extract text with coordinates from programmatic PDFs.\nThis package is part of the [Docling](https://github.com/DS4SD/docling) conversion.\n\n\n## Quick start\n\nInstall the package from Pypi\n\n```sh\npip install docling-parse\n```\n\nConvert a PDF\n\n```python\nfrom docling_parse.docling_parse import pdf_parser\n\n# Do this only once to load fonts (avoid initialising it many times)\nparser = pdf_parser()\n\n# parser.set_loglevel(1) # 1=error, 2=warning, 3=success, 4=info\n\ndoc_file = \"my-doc.pdf\" # filename\ndoc_key = f\"key={pdf_doc}\" # unique document key (eg hash, UUID, etc)\n\n# Load the document from file using filename doc_file. This only loads\n# the QPDF document, but no extracted data\nsuccess = parser.load_document(doc_key, doc_file)\n\n# Open the file in binary mode and read its contents\n# with open(pdf_doc, \"rb\") as file:\n# file_content = file.read()\n\n# Create a BytesIO object and write the file contents to it\n# bytes_io = io.BytesIO(file_content)\n# success = parser.load_document_from_bytesio(doc_key, bytes_io)\n\n# Parse the entire document in one go, easier, but could require\n# a lot (more) memory as parsing page-by-page\n# json_doc = parser.parse_pdf_from_key(doc_key)\t\n\n# Get number of pages\nnum_pages = parser.number_of_pages(doc_key)\n\n# Parse page by page to minimize memory footprint\nfor page in range(0, num_pages):\n\n # Internal memory for page is auto-deleted after this call.\n # No need to unload a specifc page \n json_doc = parser.parse_pdf_from_key_on_page(doc_key, page)\n\n if \"pages\" not in json_doc: # page could not get parsed\n continue\n\n # parsed page is the first one!\t\t\t\t \n json_page = json_doc[\"pages\"][0] \n \n page_dimensions = [json_page[\"dimensions\"][\"width\"], json_page[\"dimensions\"][\"height\"]]\n\n # find text cells\n cells=[]\n for cell_id,cell in enumerate(json_page[\"cells\"]):\n \tcells.append([page,\n\t cell_id,\n\t\t cell[\"content\"][\"rnormalized\"], # text\n\t cell[\"box\"][\"device\"][0], # x0 (lower left x)\n\t\t cell[\"box\"][\"device\"][1], # y0 (lower left y)\n\t\t cell[\"box\"][\"device\"][2], # x1 (upper right x)\n\t\t cell[\"box\"][\"device\"][3], # y1 (upper right y)\t\n\t\t ])\n\n # find bitmap images\n images=[]\n for image_id,image in enumerate(json_page[\"images\"]):\n \timages.append([page,\n\t image_id,\n\t image[\"box\"][0], # x0 (lower left x)\n\t\t image[\"box\"][1], # y0 (lower left y)\n\t\t image[\"box\"][2], # x1 (upper right x)\n\t\t image[\"box\"][3], # y1 (upper right y)\n\t\t ])\n\n # find paths\n paths=[]\n for path_id,path in enumerate(json_page[\"paths\"]):\n \tpaths.append([page,\n\t path_id,\n\t path[\"x-values\"], # array of x values\n\t path[\"y-values\"], # array of y values\n\t\t ])\n\n# Unload the (QPDF) document and buffers\nparser.unload_document(doc_key)\n\n# Unloads everything at once\n# parser.unload_documents()\n```\n\nUse the CLI\n\n```sh\n$ docling-parse -h\nusage: docling-parse [-h] -p PDF\n\nProcess a PDF file.\n\noptions:\n -h, --help show this help message and exit\n -p PDF, --pdf PDF Path to the PDF file\n```\n\n## Development\n\n### CXX\n\nTo build the parse, simply run the following command in the root folder,\n\n```sh\nrm -rf build; cmake -B ./build; cd build; make\n```\n\nYou can run the parser from your build folder with\n\n```sh\n./parse.exe <input-file> <optional-logging:true>\n```\n\nIf you dont have an input file, then a template input file will be printed on the terminal.\n\n\n### Python\n\nTo build the package, simply run (make sure [poetry](https://python-poetry.org/) is [installed](https://python-poetry.org/docs/#installing-with-the-official-installer)),\n\n```\npoetry build\n```\n\nTo test the package, run,\n\n```\npoetry run pytest ./tests/test_parse.py\n```\n\n\n## Contributing\n\nPlease read [Contributing to Docling Parse](https://github.com/DS4SD/docling-parse/blob/main/CONTRIBUTING.md) for details.\n\n\n## References\n\nIf you use Docling in your projects, please consider citing the following:\n\n```bib\n@software{Docling,\nauthor = {Deep Search Team},\nmonth = {7},\ntitle = {{Docling}},\nurl = {https://github.com/DS4SD/docling},\nversion = {main},\nyear = {2024}\n}\n```\n\n## License\n\nThe Docling Parse codebase is under MIT license.\nFor individual model usage, please refer to the model licenses found in the original packages.\n",
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