Extractous : A fast and efficient tool for unstructured data extraction

Extractous

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Overview :

Extractous is an unstructured data extraction tool written in Rust, offering multi-language bindings. It focuses on extracting content and metadata from various file types, such as PDF, Word, HTML, etc., with excellent performance and low memory usage. Extractous achieves fast processing speed and low memory consumption through native code execution, supports multiple file formats, and integrates Apache Tika and Tesseract-OCR technology for a wide range of file handling and OCR capabilities. The open-source nature and Apache 2.0 license allow for free commercial use, making it suitable for enterprises and developers handling large volumes of document data.

Target Users :

Target audience includes corporate users and developers who need to process and analyze large volumes of document data, particularly those seeking high-performance, low-memory, multi-language supported data extraction solutions. The high performance and ease of use of Extractous make it an ideal choice for data scientists, analysts, and developers.

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Use Cases

Businesses use Extractous to extract key information from client-submitted PDF and Word documents to automate data entry and analysis processes.

Data scientists process large volumes of unstructured text data using Extractous for training machine learning models.

Developers integrate Extractous into their applications to provide document content extraction and OCR functionality, enhancing user experience.

Features

High-performance unstructured data extraction, optimized for speed and low memory use

Clear and simple API for extracting text and metadata content

Automatic document type recognition for appropriate content extraction

Support for multiple file formats, including PDF, Word, Excel, HTML, etc.

Text extraction from images and scanned documents via Tesseract-OCR technology

Core engine written in Rust, providing Python bindings, with future support for JavaScript/TypeScript

Comprehensive documentation and examples to help users get started quickly and efficiently

Free for commercial use under the Apache 2.0 license

How to Use

1. Install the Extractous library using pip for Python bindings: pip install extractous

2. Import the Extractor class: from extractous import Extractor

3. Create an Extractor instance and configure necessary settings, such as OCR language: extractor = Extractor().set_ocr_config(TesseractOcrConfig().set_language('eng'))

4. Use Extractor to extract file content: result, metadata = extractor.extract_file_to_string('example.pdf')

5. Print or process the extracted results: print(result)

6. View the extracted metadata: print(metadata)

7. Ensure Tesseract-OCR is installed and correctly configured with the appropriate language pack for documents requiring OCR.