A cross-platform text analysis program written in Python and Free Pascal/Lazarus which scans a whole text file (in plain text, HTML, EPUB, or ODT formats) and ranks all used words according to frequency, performing a quantitative analysis of the text using Shannon-Weaver information statistic and Zipf power law function. It counts words, sentences, chars, spaces, and syllables. Also computes readability indexes (Gunning-Fog, Coleman-Liau, Automated Readability Index (ARI), SMOG grade, Flesch–Kincaid grade level and Flesch Reading Ease).

Project Activity

See All Activity >

License

GNU General Public License version 3.0 (GPLv3)

Follow Libro

Libro Web Site

Other Useful Business Software
Gen AI apps are built with MongoDB Atlas Icon
Gen AI apps are built with MongoDB Atlas

Build gen AI apps with an all-in-one modern database: MongoDB Atlas

MongoDB Atlas provides built-in vector search and a flexible document model so developers can build, scale, and run gen AI apps without stitching together multiple databases. From LLM integration to semantic search, Atlas simplifies your AI architecture—and it’s free to get started.
Start Free

Additional Project Details

Languages

Brazilian Portuguese, English

Intended Audience

Science/Research

User Interface

Gnome, Win32 (MS Windows)

Programming Language

Free Pascal, Lazarus, Python

Related Categories

Python Information Analysis Software, Python Research Software, Lazarus Information Analysis Software, Lazarus Research Software, Free Pascal Information Analysis Software, Free Pascal Research Software

Registered

2013-08-12