Python PDF library

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

PyPDF2 is a pure Python library for reading, writing, and manipulating PDF files. It functions as a document manipulator, text extractor, and encryption tool, allowing users to process PDF files without relying on external C libraries or native binaries. The library provides specialized tools for modifying document structures, such as merging multiple files into one, splitting documents into separate files, and transforming page layouts through cropping. It also includes capabilities for securing documents via passwords and encryption. Additional capabilities include the extraction of writte

pypdf is a Python library for parsing, manipulating, and generating PDF documents. It provides high-level operations for document processing, such as merging multiple files into one or splitting a single document into smaller files. The project includes specialized tools for managing interactive elements, including the creation and modification of annotations, hyperlinks, and form fields. It also supports advanced metadata management, allowing for the extraction and modification of standard document properties and XML-based XMP metadata. Beyond basic structural changes, the library covers pa

PyMuPDF is a comprehensive PDF manipulation library and document analysis tool. It serves as a text extraction tool, OCR engine, and image converter, providing a programmatic interface to edit, merge, split, and optimize PDF and Office documents. The project distinguishes itself through high-performance capabilities, including the use of C-bindings for low-level manipulation and parallelized page processing to accelerate workloads. It provides specialized conversion paths, such as transforming PDF content into Markdown for retrieval-augmented generation and large language model pipelines. It

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

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.six is a programmatic tool for extracting text, layout information, and metadata from PDF documents into machine-readable formats. It functions as a document parser that converts internal PDF objects and structures into accessible data objects for analysis. The project includes utilities for decrypting RC4 and AES encrypted files to enable content extraction. It also provides a layout analyzer to identify fonts, colors, and text locations to determine the organizational structure of pages. The system covers a broad range of extraction capabilities, including the retrieval of embedde