hotpdf 0.4.0

Fast PDF Data Extraction library

hotpdf

This project was started as an internal project @ Prestatech to parse PDF files in a fast and memory efficient way to overcome the difficulties we were having while parsing big PDF files using libraries such as pdfquery.

hotpdf is a wrapper around pdfminer.six focusing on text extraction and text search operations on PDFs.

hotpdf can be used to find and extract text from PDFs. Please read the docs to understand how the library can help you!

Installation

The latest version of hotpdf can be installed directly from PyPI with pip.

pip install hotpdf

Contributing

You should install the pre-commit hooks with pre-commit install. This will run the linter, mypy, and ruff formatting before each commit.

Rembember to run pip install -e '.[dev]' to install the extra dependencies for development.

For more examples of how to run the full test suite please refer to the CI workflow.

We strive to keep the test coverage at 100%: if you want your contributions accepted please write tests for them :D

Some examples of running tests locally:

python3 -m pip install -e '.[dev]'               # install extra deps for testing
python3 -m pytest -n=auto tests/                      # run the test suite

Documentation

We use sphinx for generating our docs and host them on readthedocs

Please update and add documentation if required, with your contributions.

Update the .rst files, rebuild them, and commit them along with your PRs.

cd docs
make clean
make html

This will generate the necessary documentation files. Once merged to main the docs will be updated automatically.

Usage

To view more detailed usage information, please read the docs

Basic usage is as follows:

from hotpdf import HotPdf

pdf_file_path = "test.pdf"

# Load pdf file into memory
hotpdf_document = HotPdf(pdf_file_path, transformer='Command to convert from PDF to XML')

# Alternatively, you can also pass an opened pdf stream to be loaded
with open(pdf_file_path, "rb") as f:
   hotpdf_document_2 = HotPdf(f)

# Get number of pages
print(len(hotpdf_document.pages))

# Find text
text_occurences = hotpdf_document.find_text("foo")

# Find text and its full span
text_occurences_full_span = hotpdf_document.find_text("foo", take_span=True)

# Extract text in region
text_in_bbox = hotpdf_document.extract_text(
   x0=0,
   y0=0,
   x1=100,
   y1=10,
   page=0,
)

# Extract spans in region
spans_in_bbox = hotpdf_document.extract_spans(
   x0=0,
   y0=0,
   x1=100,
   y1=10,
   page=0,
)

# Extract spans text in region
spans_text_in_bbox = hotpdf_document.extract_spans_text(
   x0=0,
   y0=0,
   x1=100,
   y1=10,
   page=0,
)

# Extract full page text
full_page_text = hotpdf_document.extract_page_text(page=0)

License

This project is licensed under the terms of the MIT license.

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with ❤️ from the team @ Prestatech GmbH