Easily extract data from PDFs.
Project description
Extraxt
Extraxt is a Python-based MuPDF library that enables parsing and extracting data from Healthlink PDF documents.
Core Functionality
- Nested JSON Output: Constructs nested JSON objects reflecting the document's content.
- Subtitle and Field Matching: Define subtitles and corresponding data fields in snake case (e.g.
first_name,address_line_one,income_(secondary)). - Sensitive Data Configuration: Enables sensitive data controls and configuration via the API (Coming soon).
Extraxt streamlines the extraction process, converting PDF content into structured JSON for easy data manipulation and integration.
Installation
Install Extraxt
pip install extraxt
Upgrade to new version of Extraxt
pip install --upgrade extraxt
Using Conda with Extraxt
conda create --name [YOUR_ENV] python=3.11 -y
conda activate [YOUR_ENV]
pip install extraxt
Usage
Extraxt is able to consume either an asynchronous byte stream or a buffer directly from disk.
Before you begin:
- Matching something like
Phone (Secondary) -> phone_(secondary)will require the usage of parenthesis as of0.0.17. This will soon be opt in, where by default the parenthesis will be redacted. - As of
0.0.17, sensitive data is not configurable via the API, and instead"Date of birth"is parsed as"age"only.
Read file from disk
Reading from a Buffer stream can be done using with open as is standard in Python. From there you can invoke .read() on the binary and pass your fields specification. fields accepts an object of user-input key's (subtitles), where the value is a series of matches (snaked_cased) to that of the exact PDF text content within your document.
from extraxt import Extraxt
from .config import FIELDS
extraxt = Extraxt()
def main():
with open("file.pdf", "rb") as buffer:
stream = buffer.read()
output = extraxt.read(stream, FIELDS)
print(output)
if __name__ == "__main__":
main()
Read file in asynchronous API
FastAPI
For cases using FastAPI, Extraxt is a synchronous package and will block the main thread.
To perform non-blocking/asynchronous extraction, you will need to use asyncio and Futures.
import traceback
import json
from fastapi import File, HTTPException, JSONResponse
from extraxt import Extraxt
from .util import event_loop
from .config import FIELDS
extraxt = Extraxt()
async def process_file(file: File):
try:
content = file.read()
if not content:
raise HTTPException(500, "Failed to read file.")
content = await event_loop(extraxt.read, content, FIELDS)
except Exception as e:
tb = traceback.format_exc()
raise HTTPException(500, f"Failed to triage file {tb}")
return JSONResponse({
"content": json.loads(content),
})
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