Clapgrep

Clapgrep — Free Download. Document and file search
Clapgrep is a search tool designed to locate information inside PDF files, Office documents, and text files. It allows searching for specific terms in multiple files simultaneously, displaying precise results with exact location (page and line).
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Download Clapgrep (Official links)
File size: 23.31 MB
The latest version of Clapgrep is: 25.07
Operating system: Linux
Languages: English
Price: $0.00 USD

  • PDF search. Clapgrep analyzes PDF files and extracts text for searching, identifying the exact page where the searched term appears. Supports standard and protected PDF formats (when text extraction is possible).
  • Office search. The tool can search inside Word documents (.doc, .docx), Excel (.xls, .xlsx) and PowerPoint (.ppt, .pptx) files, extracting textual content for analysis.
  • Plain text search. Analyzes .txt, .csv, .json, .xml and other text-based formats, showing the exact line where matches occur.
  • Recursive folder search. Automatically scans entire directories, including subfolders, to find files containing the searched term.
  • Detailed results. Shows not only the file where the match was found, but also the specific page (for PDF) or line number (for text files).
  • Cross-platform. Works on Windows, Linux and macOS with consistent behavior across operating systems.
  • Command line interface. Controlled via terminal parameters, allowing integration into scripts and automated workflows.
  • Result highlighting. Found matches are highlighted in the output for easy visual identification.
  • Regular expression support. Allows advanced searches using complex patterns to locate term variations.
  • File type filtering. Can limit the search to specific formats (PDF only, Word documents only, etc.).
  • Search history. Keeps a record of previously searched terms for quick access.
  • Result export. Option to save results to text files or structured formats like JSON.

Clapgrep was developed as a solution for efficient searching in document collections. Written in Rust, it leverages parallel processing capabilities to speed up searches in large volumes of files. The project started in 2022 and remains actively developed with new features and support for more document formats.


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