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Overview

EDS-PDF provides modular framework to extract text from PDF documents.

You can use it out-of-the-box, or extend it to fit your use-case.

Getting started

Installation

Install the library with pip:

fast →pip install edspdfInstallation successful

restart ↻

Extracting text

Let's build a simple PDF extractor that uses a rule-based classifier, using the following configuration:

config.cfg
[reader]
@readers = "pdf-reader.v1"

[reader.extractor]
@extractors = "pdfminer.v1"

[reader.classifier]
@classifiers = "mask.v1"
x0 = 0.2
x1 = 0.9
y0 = 0.3
y1 = 0.6
threshold = 0.1

[reader.aggregator]
@aggregators = "simple.v1"

The PDF reader can be instantiated and applied (for instance with this PDF):

import edspdf
from pathlib import Path

reader = edspdf.load("config.cfg")  # (1)

# Get a PDF
pdf = Path("letter.pdf").read_bytes()

texts = reader(pdf)

texts["body"]
# Out: Cher Pr ABC, Cher DEF,\n...
  1. The reader object is loaded from the configuration directly.

See the rule-based recipe for a step-by-step explanation of what is happening.

Citation

If you use EDS-NLP, please cite us as below.

@software{edspdf,
  author  = {Dura, Basile and Wajsburt, Perceval and Calliger, Alice and Gérardin, Christel and Bey, Romain},
  doi     = {10.5281/zenodo.6902977},
  license = {BSD-3-Clause},
  title   = {{EDS-PDF: Smart text extraction from PDF documents}},
  url     = {https://github.com/aphp/edspdf}
}

Acknowledgement

We would like to thank Assistance Publique – Hôpitaux de Paris and AP-HP Foundation for funding this project.