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The Text Monger is a Python package that provides various text analysis tools, including readability scoring, power words distribution, named entity recognition (NER), and sentiment analysis.

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The Text Monger

The Text Monger is a Python package that provides various text analysis tools, including readability scoring, power words distribution, named entity recognition (NER), and sentiment analysis.

Features

  • Readability Analysis: Analyze the readability of text using various metrics such as Flesch Reading Ease, Gunning Fog Index, and more.
  • Power Words Distribution: Visualize the distribution of power words in your text, highlighting impactful language.
  • Named Entity Recognition (NER): Extract and highlight named entities (like names, organizations, locations) from the text.
  • Sentiment Analysis: Determine the sentiment polarity (positive, negative, or neutral) and subjectivity of the text using TextBlob.

Installation

You can install The Text Monger package using pip:

pip install textmonger

Usage

After installation, you can run The Text Monger from the command line. Here's how you can use it:

Command-Line Interface (CLI)

To analyze a piece of text, simply run the following command in your terminal:

textmonger

You will be prompted to enter the text you want to analyze. Type or paste your text, and when you're done, type END on a new line to finish input. The tool will then output the readability analysis, power words distribution, named entity recognition, and sentiment analysis.

Example

$ textmonger
Enter Text to analyze (type 'END' on a new line to finish):
The quick brown fox jumps over the lazy dog.
END

================================================================================
                              Readability Analysis
================================================================================
| Metric                       | Score               |
| ---------------------------- | ------------------ |
| Reading ease                 | Difficult           |
| Reading level                | Grade 14.4          |
| Smog index                   | Grade 15.8          |
| Gunning Fog index            | Grade 15.46         |
| Coleman-Liau index           | Grade 13.06         |
| Automated Readability index  | Grade 16.4          |
| Dale-Chall Readability score | 9.88                |
| Text standard                | 15th and 16th grade |
================================================================================
                              Power Words Distribution
================================================================================
<Your Output Here>

================================================================================
                              Sentiment Analysis
================================================================================
| Polarity       | 0.0 (Neutral)                   |
| Subjectivity   | 0.5 (Subjective)                |
================================================================================

================================================================================
                              Named Entity Recognition (NER)
================================================================================
<Your Output Here>

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contributing

Contributions are welcome! Please fork the repository and submit a pull request.

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The Text Monger is a Python package that provides various text analysis tools, including readability scoring, power words distribution, named entity recognition (NER), and sentiment analysis.

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