semvec/pypi-packages huggingface dataset:
rake-new 1.0.0
A Python library that enables smooth keyword extraction from any text using the RAKE(Rapid Automatic Keyword Extraction) algorithm.
License: MIT
Requires Python: >=3.6

# rake_new

rake_new is a Python library that enables simple and fast keyword extraction from any text. As the name implies, this library works on the RAKE(Rapid Automatic Keyword Extraction) algorithm. 

It tries to determine the key phrases in a text by calculating the co-occurrences of every word in a key phrase and also its frequency in the entire text.

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install rake.

```bash
pip install rake_new
```

## Quick Start

```python
from rake_new import Rake

text = "Red apples are good in taste."
rk = Rake()
# Initialize
rk.get_keywords_from_raw_text(text)

kw_s = rk.get_keywords_with_scores()  
# Returns keywords with degree scores : {(1.0, 'taste'), (1.0, 'good'), (4.0, 'red apples')}

kw = rk.get_ranked_keywords() 
# Returns keywords only : ['red apples', 'taste', 'good']

f = rk.get_word_freq()
# Returns word frequencies as a Counter object : {'red': 1, 'apples': 1, 'good': 1, 'taste': 1}

deg = rk.get_kw_degree()
# Returns word degrees as defaultdict object : {'red': 2.0, 'apples': 2.0, 'good': 1.0, 'taste': 1.0}
```


## Debugging
You might come across a stopwords error.

It implies that you do not have the stopwords corpus downloaded from NLTK. 

To download it, use the command below.

```python
python -c "import nltk; nltk.download('stopwords')"
```

## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

## License
[MIT](https://choosealicense.com/licenses/mit/)