Projects sharing features with Pdfminer.six

PyPDF2 is a pure Python library for transforming, securing, and extracting data from PDF documents. It provides a comprehensive suite of tools to modify page layouts, manage document security, and retrieve embedded metadata without relying on external C libraries. The toolkit enables document assembly through the merging of multiple files and the splitting of documents into smaller parts. It also supports page-level transformations, including the ability to rotate pages and adjust visible crop areas. The library includes capabilities for security management via password-based encryption and

pdfplumber is a PDF data extraction library and layout analysis tool used to retrieve text, tables, and geometric objects from PDF files using precise coordinate-based analysis. It functions as a layout analyzer and table parser that identifies the bounding boxes and visual coordinates for every character and image on a page. The library distinguishes itself through visual debugging capabilities, allowing users to render PDF pages as images and draw annotations to verify the position of extracted data. It employs line and intersection analysis to identify cell structures and convert unstructu

pdfminer is a Python library for parsing PDF files to extract text, analyze layouts, decrypt content, and convert documents into HTML or XML formats. It functions as a text extraction engine and layout analysis tool designed to retrieve characters and words while preserving the structural organization of the original document. The project provides utilities for converting PDF content into structured HTML or XML to maintain visual layout and a decryption tool for unlocking restricted documents using encryption keys. It identifies the positions and groupings of text elements to reconstruct page

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,

PDF-Extract-Kit is a document extraction toolkit designed to convert PDF documents into structured formats such as Markdown, HTML, and LaTeX. It functions as a multi-stage parsing framework that combines a document layout analyzer, a formula recognition engine, an OCR text extractor, and a table extraction system. The project focuses on recovering complex document elements by translating images of mathematical formulas and tabular structures into editable source code. It utilizes model-driven layout analysis to identify structural elements in reports and textbooks while ignoring noise like wa

Docling is a modular framework designed for document parsing, layout analysis, and structured data extraction. It transforms unstructured files and web content into a unified, hierarchical data model that preserves the spatial and semantic relationships between text, tables, images, and layout elements. By normalizing diverse input formats into a consistent internal representation, the library enables uniform processing across various document types. The project distinguishes itself through a schema-driven approach that maps document regions to strongly-typed objects, ensuring data accuracy t

Maskphish is a comprehensive security toolkit that integrates capabilities for digital forensics, network vulnerability scanning, open-source intelligence, penetration testing, and social engineering. It functions as a multi-purpose framework for automating reconnaissance and executing security audits across diverse network environments. The project features a specialized phishing and social engineering toolkit used for cloning websites, masking URLs, and deploying deceptive pages to capture user credentials. It also includes a remote access Trojan builder for generating platform-specific exe

unioffice is a comprehensive document processing suite that provides a PDF document processor, an Open XML document library, a document security toolkit, and a document content extractor. It is designed to programmatically create, read, and modify Word, Excel, and PowerPoint files, as well as generate and edit PDF documents. The project is distinguished by its native language implementation of the Open XML standard, which removes native binary dependencies to simplify container deployments. It features advanced capabilities for digital document security, including hardware-based PDF signing,

PHPWord is a PHP word processing library used for programmatically reading and writing word processing documents. It functions as an OOXML document generator, a word file parser, and a document template engine. The library enables the generation of new documents by applying structured data to existing templates or by creating files from scratch. It provides capabilities for extracting and parsing content, metadata, and structure from existing word processing files. The project covers a broad range of document generation features, including layout formatting, metadata management, and the inse

qpdf is a collection of specialized utility tools for the structural transformation, metadata inspection, file optimization, and cryptographic management of PDF documents. It provides a command line tool for transforming and inspecting internal PDF structures, a structural transformer for reorganizing pages and merging documents, and an encryption engine for managing passwords and restrictions. The project distinguishes itself through a technical approach to document manipulation, utilizing an object-based structural representation to modify files as a graph of unique objects. It includes a m

MNBVC is a dataset pipeline and toolkit designed for the collection, cleaning, and normalization of massive text and code corpora used to train large language models. It provides specialized tools for harvesting source code, commit histories, and repository metadata from version control platforms, alongside a multilingual text corpus collector for gathering parallel text and academic papers. The project distinguishes itself through comprehensive capabilities for processing diverse document types, including a PDF-to-text converter that transforms complex layouts and formulas into structured JS

BentoPDF is a browser-based document toolkit designed for local-first PDF manipulation, conversion, and metadata management. By executing all file processing tasks directly within the browser sandbox, the application ensures that sensitive data remains on the user's device and is never uploaded to or stored on external servers. The platform distinguishes itself through a modular architecture that supports dynamic remote script loading and the integration of external processing engines. Users can extend the core functionality by connecting third-party libraries, which are executed as compiled

python-docx is an OOXML document manipulation library used for creating, reading, and updating Microsoft Word files. It functions as a generator for building formatted documents and a parser for extracting text, metadata, and structural elements from existing files. The project provides a comprehensive style management system for defining and applying character, paragraph, and table styles within OpenXML documents. It allows for the programmatic control of document appearance through an object-oriented approach to the underlying XML schema. Capabilities cover a wide range of document generat

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

Layout-parser is a deep learning document layout parser and image analysis framework. It provides a toolkit for extracting structural information and layout patterns from scanned documents and digital images, transforming them into programmatic data structures for automated analysis. The framework integrates layout detection with optical character recognition to convert tabular regions into machine-readable data. It utilizes neural networks to identify and classify structural elements within document images without relying on manual rule-based systems. The system covers a broad range of docu

This project is a PDF data extraction tool and document preprocessor designed to convert PDF files into structured formats such as Markdown, JSON, and HTML. It functions as an OCR document parser for scanned files, an accessibility automator for generating PDF/UA compliant metadata, and a loader for AI orchestration frameworks like LangChain. The software distinguishes itself through specialized handling of complex document elements, including the conversion of mathematical formulas into LaTeX and the generation of natural-language descriptions for charts and images. It utilizes recursive seg

BabelDOC is a technical document translation system designed to translate PDF files while preserving their original layout and styling. It functions as a layout-preserving translator that utilizes large language models to convert content into target languages, specifically tailored for scientific and technical documents. The system distinguishes itself through specialized handling of academic content, including the identification and preservation of mathematical formulas and complex layout structures. It ensures technical accuracy by employing glossary-driven terminology enforcement, using so

Marker is an LLM-powered document parser and OCR pipeline designed to convert PDFs and unstructured files into structured markdown, JSON, and HTML. It functions as a data preprocessor that transforms complex documents into machine-readable formats while preserving tables, equations, and layout structures. The system utilizes large language models to refine OCR accuracy, clean mathematical notation, and merge fragmented tables across multiple pages. It employs model-based layout analysis to predict block types and bounding boxes, ensuring a more precise conversion of document elements. Capabi

This project is a comprehensive framework and toolkit for developing, optimizing, and deploying transformer-based models across multimodal, document intelligence, and natural language processing tasks. It provides a unified neural architecture that processes text, vision, audio, and document layout data through a shared set of weights, enabling researchers and developers to build foundational models that align cross-modal representations. The platform distinguishes itself through advanced training and inference strategies designed for large-scale deep learning. It incorporates specialized mec

pdfcpu is a Go PDF processing library and command-line interface designed for programmatically manipulating, optimizing, and validating PDF files. It provides a toolkit for document content modification and structural management. The project distinguishes itself as an optimization tool and layout engine, capable of reducing file sizes and improving loading speeds by streamlining internal structures. It also functions as a security manager, providing password-based encryption, decryption, and digital signature verification. Its capability surface includes page management for merging, splittin

Grobid is a machine learning system designed to transform academic and scientific PDF publications into structured XML. It functions as a PDF to XML parser and scholarly metadata extractor, identifying and normalizing titles, authors, affiliations, and bibliographic references from research papers. The system utilizes a deep learning document segmenter to divide raw PDFs into functional regions and employs a bibliographic reference resolver to match citations against external registries for metadata enrichment and DOI resolution. It supports a full machine learning model training pipeline, al

pdfsam is a PDF manipulation software and desktop application designed for splitting, merging, rotating, and extracting pages from PDF documents. It functions as a PDF editor, converter, and security tool, providing capabilities to modify document structures and manage file formats. The project distinguishes itself through specialized processing capabilities, including an OCR document processor for extracting editable text from scanned images and PDF interleaving to alternate pages from multiple files. It also provides a security suite for encrypting documents, managing access permissions, an

Pdfcraft is a containerized service for self-managed PDF processing, editing, and conversion. It provides a toolkit for document manipulation, a multi-format converter, and OCR software to transform scanned documents into searchable and editable text. The project features a visual, node-based workflow editor that allows users to build automated pipelines by chaining together various PDF conversion and optimization operations. The service covers a broad range of capabilities, including document management for merging and splitting files, format conversion between PDFs and office documents or

Unstructured is an enterprise-grade data orchestration engine designed to transform raw, unstructured files into structured, machine-readable formats. It functions as a comprehensive platform for document ingestion, partitioning, and enrichment, specifically engineered to prepare complex data for retrieval-augmented generation and agentic AI workflows. The platform distinguishes itself through its sophisticated document processing strategies, which combine rule-based extraction with vision-language models to handle diverse file layouts, tables, and images. It provides a modular architecture t

Kotaemon is an orchestration framework designed for building modular, agentic workflows that integrate document processing, retrieval-augmented generation, and multi-step reasoning. It provides a comprehensive platform for developing document-based question answering systems, allowing users to chain language models, prompt templates, and external tools into complex, automated pipelines. The system distinguishes itself through a highly modular architecture that emphasizes component-based composition and schema-driven data exchange. It supports autonomous agents capable of decomposing complex q

Langroid is a multi-agent orchestration framework and tool integration suite designed for building complex AI applications. It serves as a multi-modal integration layer that connects diverse local and remote language models with an agentic retrieval-augmented generation system. The project distinguishes itself through a collaborative message-exchange paradigm, allowing specialized agents to delegate tasks hierarchically and coordinate via structured communication. It features an advanced state management system for conversational AI, including the ability to rewind and prune conversation hist

OCRmyPDF is a tool for converting image-based PDF files into machine-readable documents by adding a searchable text layer via optical character recognition. It functions as a multi-language processor capable of detecting and extracting text in over 100 different languages using linguistic data packs. The software includes a PDF image optimizer to remove image artifacts and correct page skew to improve recognition accuracy. It also provides a converter to transform scanned documents into the PDF/A standard for long-term digital archiving. The system manages PDF optimization by compressing emb