v1.2.0

• Extract keywords from text data to identify important terms and phrases.
• Export extracted keywords to a file for further analysis or visualization.
• Calculate the 'cosine similarity' between two data sources to identify how similar or dissimilar they are.
• Updated command descriptions for better clarity.
• Summarization now utilize a caching mechanism for faster retrieval of previously summarized text.
• Git is now a command instead of a flag for better clarity.

v1.1.2

• Updated lang detection library, it now uses langid instead of langdetect
• This allows it to work on Windows operating system as well.

v1.1.1

Version 1.1.1 Release Notes

New Features:

1. Sentiment Analysis

• Introducing a new feature: Sentiment Analysis!
• Analyze sentiment data within the application.
• Export sentiment analysis results for further analysis.

Enhancements:

2. Command Grouping

• Grouped 'generate-wordcloud' and 'generate-word-frequency-chart' commands for a more streamlined user experience.

Bug Fixes:

3. Analyze Command Fix

• Language detection is now performed using an alternative library instead of the multinomial NB model.
• Resolves the issue where the 'analyze' command was not functioning as expected.

v1.0.1

• Resolved an issue preventing the "analyze" command from executing.

v1.0

• Perform semantic analysis on raw data, files, or websites using the pyquantify CLI.
• Explore various linguistic and statistical metrics for English text.
• Introducing the generate_freq_plot command.
• Analyze and visualize the frequency distribution of the top 20 words in your data.
• Option to export the frequency plot as an image file.
• Introducing the generate_wordcloud command.
• Generate visually appealing word clouds from your data.
• Option to export the wordcloud as an image file.
• Search for a specific word in the morphological table.
• Display morphological information for the searched word.
• Option to limit the displayed rows and export the analysis results.
• Generate abstractive summaries of the provided text and export it as a text file