<commit_before>python-rake
====

#### Note on Upgrades
Some users have reported issues importing the stoplists in the upgrade to 1.1.\*, if you experience import issues after upgrading try doing a full uninstall + reinstall. 

---

[![Build Status](https://travis-ci.org/fabianvf/python-rake.svg?branch=master)](https://travis-ci.org/fabianvf/python-rake)

A Python module implementation of the Rapid Automatic Keyword Extraction (RAKE) algorithm as described in: <NAME>., <NAME>., <NAME>., & <NAME>. (2010). Automatic Keyword Extraction from Individual Documents. In <NAME> & <NAME> (Eds.), Text Mining: Theory and Applications: John Wiley & Sons. Initially by @aneesha, packaged by @tomaspinho.

The source code is released under the MIT License.

### Installation ###
    pip install python-rake

### Usage ###
for external .txt files
take path as string datatype. words can be on same or different lines but must be seperated by spaces.

    import RAKE
    Rake = RAKE.Rake(<path_to_your_stopwords_file>); 
    Rake.run(text);

for lists:

    import RAKE
    Rake = RAKE.Rake(<list>); #takes stopwords as list of strings
    Rake.run(text);

`RAKE.SmartStopList()` and `RAKE.FoxStopList()` return the expected lists as lists, they can be used as shown bellow:

    import RAKE
    Rake = RAKE.Rake(RAKE.SmartStopList());
    
### Releases ###
I will push releases to pypi periodically, but if there is a feature in master not built/pushed and you want it to be, just ping me.
 
### Credit ###
This is a maintained fork of the original python RAKE project, which can be found here: https://github.com/aneesha/RAKE
<commit_msg>small fixes<commit_after>python-rake
====

#### Note on Upgrades
Some users have reported issues importing the stoplists in the upgrade to 1.1.\*, if you experience import issues after upgrading try doing a full uninstall + reinstall. 

---

[![Build Status](https://travis-ci.org/fabianvf/python-rake.svg?branch=master)](https://travis-ci.org/fabianvf/python-rake)

A Python module implementation of the Rapid Automatic Keyword Extraction (RAKE) algorithm as described in: <NAME>., <NAME>., <NAME>., & <NAME>. (2010). Automatic Keyword Extraction from Individual Documents. In <NAME> & <NAME> (Eds.), Text Mining: Theory and Applications: John Wiley & Sons. Initially by @aneesha, packaged by @tomaspinho.

The source code is released under the MIT License.

### Installation ###
    pip install python-rake #or pip3

### Usage ###
for external .txt files
take path as string datatype. words can be on same or different lines but must be seperated by spaces.

    import RAKE
    Rake = RAKE.Rake(<path_to_your_stopwords_file>)
    Rake.run(text);

for lists:

    import RAKE
    Rake = RAKE.Rake(<list>); #takes stopwords as list of strings
    Rake.run(text)

`RAKE.SmartStopList()` and `RAKE.FoxStopList()` return the expected lists as lists, they can be used as shown bellow:

    import RAKE
    Rake = RAKE.Rake(RAKE.SmartStopList())
    Rake.run(text)
    
### Releases ###
I will push releases to pypi periodically, but if there is a feature in master not built/pushed and you want it to be, just ping me.
 
### Credit ###
This is a maintained fork of the original python RAKE project, which can be found here: https://github.com/aneesha/RAKE

{'fraction_non_alphanumeric': 0.10688185140073081, 'fraction_numerical': 0.003958587088915956, 'mean_word_length': 4.015267175572519, 'pattern_counts': {'":': 0, '<': 19, '<?xml version=': 0, '>': 19, 'https://': 6, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '3030662', 'n_tokens_mistral': 1050, 'n_tokens_neox': 969, 'n_words': 396}