Simple package to extract text, paths and bitmap images with coordinates from programmatic PDFs. This package is used in the Docling PDF conversion.
Version | Original | Word-level | Snippet-level | Performance |
---|---|---|---|---|
V1 | Not Supported | ~0.250 page/sec | ||
V2 | ~0.050 page/sec [~5-10X faster than v1] |
Install the package from Pypi
pip install docling-parse
Convert a PDF (look in the visualise.py for a more detailed information)
from docling_parse.docling_parse import pdf_parser_v2
# Do this only once to load fonts (avoid initialising it many times)
parser = pdf_parser_v2()
# 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]
# <Insert your own code>
# Unload the (QPDF) document and buffers
parser.unload_document(doc_key)
# Unloads everything at once
# parser.unload_documents()
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
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.
To build the package, simply run (make sure poetry is installed),
poetry build
To test the package, run,
poetry run pytest ./tests -v -s
Please read Contributing to Docling Parse for details.
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}
}
The Docling Parse codebase is under MIT license. For individual model usage, please refer to the model licenses found in the original packages.