7 个仓库
Mechanisms for resolving object offsets within binary files using internal reference tables.
Distinct from Cross-Reference Previews: Existing candidates refer to database tables or UI previews, not binary file internal cross-reference tables.
Explore 7 awesome GitHub repositories matching operating systems & systems programming · Cross-Reference Table Mappings. Refine with filters or upvote what's useful.
PyPDF2 是一个纯 Python 库,用于转换、保护 PDF 文档并从中提取数据。它提供了一套全面的工具来修改页面布局、管理文档安全并检索嵌入的元数据,而无需依赖外部 C 语言库。 该工具包通过合并多个文件和将文档拆分为较小的部分来实现文档组装。它还支持页面级转换,包括旋转页面和调整可见裁剪区域的能力。 该库包括通过基于密码的加密和解密进行安全管理的功能。此外,它还提供了从 PDF 文件中提取书面文本和管理属性的工具。
Provides a cross-reference table mechanism to resolve object offsets within the PDF binary stream.
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
Resolves object offsets within the PDF by indexing the internal cross-reference table to locate specific data.
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
Parses internal PDF cross-reference tables to enable random access to document objects.
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
Implements an internal index of object offsets to enable random access and structural modification of the binary PDF document tree.
pdfminer 是一个用于解析 PDF 文件以提取文本、分析布局、解密内容并将文档转换为 HTML 或 XML 格式的 Python 库。它作为一个文本提取引擎和布局分析工具,旨在检索字符和单词,同时保留原始文档的结构组织。 该项目提供了将 PDF 内容转换为结构化 HTML 或 XML 以保持视觉布局的实用程序,以及使用加密密钥解锁受限文档的解密工具。它识别文本元素的位置和分组,以重建页面组织并检索分层大纲。 该库涵盖了广泛的 PDF 处理功能,包括元数据提取、文档布局分析以及用于调试的内部 PDF 对象导出。它处理文本以及坐标、字体元数据和书写方向的检索。
Locates PDF objects by mapping byte offsets within the file using internal cross-reference tables.
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
Updates internal binary object offsets to ensure document validity after structural modifications.
This library is a toolkit for processing, manipulating, and inspecting PDF documents within the Rust programming language. It provides programmatic access to the internal structure of files, enabling the extraction of data and the modification of document content. The project utilizes a strongly-typed system to map complex document objects into structured data models. It supports the parsing of existing files through lazy-loading and stream-based decoding, which allows for the retrieval of text, metadata, and images. The library also facilitates the creation of updated document versions by re
Provides low-level access to PDF cross-reference tables for locating and resolving internal document objects.