# Wordlyzer
Wordlyzer is a powerful Python library for text analysis, providing comprehensive insights into text metrics and properties.
## Installation
Install Wordlyzer using pip:
```bash
pip install wordlyzer3==0.3
```
## Features
- Word count analysis
- Sentence count calculation
- Paragraph count detection
- Character count measurement
- Most common words identification
- Average word length computation
- Average sentence length calculation
## Quick Start
```python
# File: main.py
from wordlyzer3 import WordLyzer
# Example text for analysis
text = """Python is an amazing programming language. It's widely used for web development, data analysis, and AI.
This is a second paragraph."""
# Create analyzer object
analyzer = WordLyzer(text)
# Display analysis results
print("Word Count:", analyzer.word_count())
print("Sentence Count:", analyzer.sentence_count())
print("Paragraph Count:", analyzer.paragraph_count())
print("Character Count:", analyzer.character_count())
print("Most Common Words:", analyzer.most_common_words())
print("Average Word Length:", analyzer.average_word_length())
print("Average Sentence Length:", analyzer.average_sentence_length())
```
## Methods
### `word_count()`
Returns the total number of words in the text.
### `sentence_count()`
Returns the number of sentences in the text.
### `paragraph_count()`
Returns the number of paragraphs in the text.
### `character_count()`
Returns the total number of characters in the text.
### `most_common_words(n=5)`
Returns the `n` most frequently occurring words in the text.
- Default is top 5 words
- Optional parameter to specify number of words
### `average_word_length()`
Calculates the average length of words in the text.
### `average_sentence_length()`
Calculates the average number of words per sentence.
## Requirements
- Python 3.7+
- No external dependencies
## License
MIT License
## Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
## Author
[Nurico Vicyyanto]
## Support
For issues or questions, please open an issue on our GitHub repository.
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"description": "# Wordlyzer\n\nWordlyzer is a powerful Python library for text analysis, providing comprehensive insights into text metrics and properties.\n\n## Installation\n\nInstall Wordlyzer using pip:\n\n```bash\npip install wordlyzer3==0.3\n```\n\n## Features\n\n- Word count analysis\n- Sentence count calculation\n- Paragraph count detection\n- Character count measurement\n- Most common words identification\n- Average word length computation\n- Average sentence length calculation\n\n## Quick Start\n\n```python\n# File: main.py\nfrom wordlyzer3 import WordLyzer\n\n# Example text for analysis\ntext = \"\"\"Python is an amazing programming language. It's widely used for web development, data analysis, and AI.\n\nThis is a second paragraph.\"\"\"\n\n# Create analyzer object\nanalyzer = WordLyzer(text)\n\n# Display analysis results\nprint(\"Word Count:\", analyzer.word_count())\nprint(\"Sentence Count:\", analyzer.sentence_count())\nprint(\"Paragraph Count:\", analyzer.paragraph_count())\nprint(\"Character Count:\", analyzer.character_count())\nprint(\"Most Common Words:\", analyzer.most_common_words())\nprint(\"Average Word Length:\", analyzer.average_word_length())\nprint(\"Average Sentence Length:\", analyzer.average_sentence_length())\n```\n\n## Methods\n\n### `word_count()`\nReturns the total number of words in the text.\n\n### `sentence_count()`\nReturns the number of sentences in the text.\n\n### `paragraph_count()`\nReturns the number of paragraphs in the text.\n\n### `character_count()`\nReturns the total number of characters in the text.\n\n### `most_common_words(n=5)`\nReturns the `n` most frequently occurring words in the text.\n- Default is top 5 words\n- Optional parameter to specify number of words\n\n### `average_word_length()`\nCalculates the average length of words in the text.\n\n### `average_sentence_length()`\nCalculates the average number of words per sentence.\n\n## Requirements\n\n- Python 3.7+\n- No external dependencies\n\n## License\n\nMIT License\n\n## Contributing\n\nContributions are welcome! Please feel free to submit a Pull Request.\n\n## Author\n\n[Nurico Vicyyanto]\n\n## Support\n\nFor issues or questions, please open an issue on our GitHub repository.\n",
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