semvec/pypi-packages huggingface dataset:
banglanltk 0.0.4
Bangla Natural Language Processing Toolkit
Keywords: NLP,bangla,tagging,tokenizing,stemming,cleaning,synonym,natural language processing

Bangla NLTK
===================


banglanltk is a python package for Bengali Natural Language Processing Toolkit. It includes modules for Cleaning Text, Word Tokenization, Sentence Tokenization, Stemming, Synonym and Parts of speech tagging.
----------


## Installation

```bash
pip install banglanltk
```

## Usage

### Cleaning Text
```python
import banglanltk as bn
s = 'আজ আকাশ পরিষ্কার!!! মনে হয় আজ আর বৃষ্টি হবে না .........!'

print(bn.clean_text(s))
```

### Word Tokenization
```python
import banglanltk as bn

s = 'প্রাচীন কালে মানুষ একসময় সংখ্যা বুঝানোর জন্য ঝিনুক, নুড়ি, দড়ির গিট ইত্যাদি ব্যবহার করত।'
print(bn.word_tokenize(s))
```

### Sentence Tokenization
```python
import banglanltk as bn

s = ''' কম্পিউটার শব্দটি গ্রিক "কম্পিউট" শব্দ থেকে এসেছে। Compute শব্দের অর্থ গণনা করা। আর কম্পিউটার শব্দের অর্থ গণনাকারী যন্ত্র। '''
print(bn.sent_tokenize(s))
```

### Stemming
```python
import banglanltk as bn

# For single word
print(bn.stemmer('শান্তিনিকেতনে'))

# For multiple words
text = 'আজ বৃষ্টি হবে।'
words = bn.word_tokenize(text)
for w in words:
    print(bn.stemmer(w))
```

### Synonym
```python
import banglanltk as bn

print(bn.synonym('হাত'))
```

### POS Tagging
```python
import banglanltk as bn

# For single word
print(bn.pos_tag('কম্পিউটার'))

# For multiple words
text = 'আজ বৃষ্টি হবে।'
words = bn.word_tokenize(text)
for w in words:
    print(bn.pos_tag(w))
```

### List of POS tags
|	POS    	|	Meaning                      			|
|-----------|-------------------------------------------|
|	`CC`	|	Conjunction								|
|	`CD`	|	Cardinal number							|
|	`DM`	|	Demonstrative							|
|	`DT`	|	Determiner								|
|	`EX`	|	Existential there						|
|	`FW`	|	Foreign word							|
|	`IN`	|	Preposition								|
|	`JJ`	|	Adjective								|
|	`JJR`	|	Adjective, comparative					|
|	`JJS`	|	Adjective, superlative					|
|	`MD`	|	Modal									|
|	`NN`	|	Noun, singular or mass					|
|	`NNP`	|	Proper noun, singular					|
|	`NNS`	|	Noun, plural							|
|	`NNV`	|	Verbal Noun								|
|	`PR`	|	Pronoun									|
|	`PRP`	|	Personal pronoun						|
|	`PRP$`	|	Possessive pronoun						|
|	`PSP`	|	Postposition							|
|	`RB`	|	Adverb									|
|	`RBR`	|	Adverb, comparative						|
|	`RP`	|	Particles								|
|	`SYM`	|	Symbol									|
|	`TO`	|	to										|
|	`UH`	|	Interjection							|
|	`UNK`	|	Unknown tag								|
|	`VB`	|	Verb, base form							|
|	`VBD`	|	Verb, past tense						|
|	`VBG`	|	Verb, present participle				|
|	`VBN`	|	Verb, past participle					|
|	`VBP`	|	Verb, non-3rd person singular present	|
|	`WDT`	|	Wh-determiner							|
|	`WH`	|	Wh words								|
|	`WP`	|	Wh-pronoun								|
|	`WRB`	|	Wh-adverb								|