This document discusses language identification using the Textblob library in Python. It introduces Textblob and its features like noun phrase extraction, part-of-speech tagging, sentiment analysis, and language detection powered by Google Translate. It then explains how Textblob calculates sentiment using polarity and subjectivity scores. An example is provided where a Spanish phrase is correctly identified as the language "es" (Spanish). The document concludes that the Textblob approach accurately estimates the proportion of a document written in different identified languages.