Tabula is a PDF table extraction tool and data scraper designed to isolate tabular structures within text-based PDF files. It functions as a converter that transforms these layouts into structured CSV or spreadsheet formats for data recovery and analysis.
Las características principales de tabulapdf/tabula son: Table Extraction Utilities, PDF Tools, Automated Data Extraction, PDF to CSV Converters, PDF Spatial Layout Parsers, PDF Parsers, Tabular Row Detection, Command Line Interfaces.
Las alternativas de código abierto para tabulapdf/tabula incluyen: artifexsoftware/pdf2docx — pdf2docx is a suite of PDF utilities designed to transform static PDF documents into editable DOCX files. It functions… camelot-dev/camelot — Camelot is a Python library and processing engine designed to extract tabular data from PDF documents. It converts… katanaml/sparrow — Sparrow is an LLM document extraction platform and vision-based inference engine designed to convert images and PDFs… atlanhq/camelot — Camelot is a Python-based library designed to parse, extract, and clean tabular data from PDF files. It converts table… euske/pdfminer — pdfminer is a Python library for parsing PDF files to extract text, analyze layouts, decrypt content, and convert… gusmanb/logicanalyzer — Logicanalyzer is a digital logic analyzer and signal visualizer designed for capturing and analyzing high-speed…
pdf2docx is a suite of PDF utilities designed to transform static PDF documents into editable DOCX files. It functions as a multi-core processor capable of accelerating the conversion of large files by distributing page tasks across multiple CPU cores. The project includes specialized tools for decrypting password-protected PDF files and extracting tabular content as structured data. It also provides a layout analyzer to visually inspect and verify document structure during the conversion process. Conversion is accessible through both a graphical user interface and a command-line interface,
Camelot is a Python library and processing engine designed to extract tabular data from PDF documents. It converts unstructured tables into machine-readable formats such as CSV, JSON, and Excel. The project provides specialized toolsets for different document types, using line detection for ruled tables and whitespace analysis for borderless tables. It includes an optical character recognition system to recover structured data from image-based scanned PDFs that lack a digital text layer. The library handles complex document layouts, including encrypted files, rotated pages, and tables that s
Camelot is a Python-based library designed to parse, extract, and clean tabular data from PDF files. It converts table elements from text-based PDF documents into programmable data structures and dataframes. The tool identifies tabular regions using coordinate-based grouping, lattice-based line detection, and stream-based text extraction. It can also rasterize PDF pages into images to utilize computer vision for detecting structural lines and boundaries. Extracted data is validated through accuracy and whitespace metrics to filter out low-quality extractions. The processed information can be
Sparrow is an LLM document extraction platform and vision-based inference engine designed to convert images and PDFs into validated structured data. It functions as an agentic workflow orchestrator that chains classification, extraction, and validation tasks into multi-step pipelines. The system distinguishes itself through a backend-agnostic inference layer that manages models across local GPUs, Apple Silicon, and cloud providers. It employs coordinate-based visual grounding to map extracted text to precise bounding box coordinates and utilizes hint-based model steering to guide attention an