fulfulde-stopwords 1.0

Stopwords for the Fulfulde language (Adamawa variant)

Fulfulde Stopwords

A curated list of stopwords for the Fulfulde language (Adamawa variant), designed for Natural Language Processing (NLP) applications.

Fulfulde is a low-resource African language spoken by millions across West and Central Africa. This library provides the first comprehensive, linguistically grounded stopword list for NLP tasks such as:

• Text classification
• Information retrieval
• Clustering and topic modeling
• Text preprocessing and cleaning
• Machine translation
• Sentiment analysis

Features

• Linguistically grounded: Compiled by linguists and NLP researchers
• Comprehensive: 180+ stopwords covering all major grammatical categories
• Easy to use: Simple Python API with no external dependencies
• Well documented: Extensive documentation and examples
• Tested: Comprehensive test suite
• Open source: MIT licensed

Installation

From PyPI (recommended)

pip install fulfulde-stopwords

From source

git clone https://github.com/2zalab/fulfulde-stopwords.git
cd fulfulde-stopwords
pip install -e .

Quick Start

Basic Usage

from fulfulde_stopwords import get_stopwords, remove_stopwords, is_stopword

# Get all stopwords
stopwords = get_stopwords()
print(f"Total stopwords: {len(stopwords)}")

# Check if a word is a stopword
print(is_stopword('mi'))  # True
print(is_stopword('wuro'))  # False

# Remove stopwords from text
tokens = ['mi', 'heɓi', 'wuro', 'e', 'nder', 'Kameruun']
filtered = remove_stopwords(tokens)
print(filtered)  # ['heɓi', 'wuro', 'Kameruun']

Advanced Usage

from fulfulde_stopwords import filter_text, get_stats

# Filter an entire text
text = "mi heɓi wuro e nder Kameruun"
filtered_text = filter_text(text)
print(filtered_text)  # "heɓi wuro Kameruun"

# Get statistics
tokens = ['mi', 'heɓi', 'wuro', 'e', 'nder']
stats = get_stats(tokens)
print(stats)
# {
#     'total_tokens': 5,
#     'stopword_count': 3,
#     'content_word_count': 2,
#     'stopword_ratio': 0.6
# }

Integration with NLP Libraries

NLTK

from fulfulde_stopwords import get_stopwords
from nltk.tokenize import word_tokenize

stopwords = get_stopwords()
text = "mi heɓi wuro e nder Kameruun"
tokens = word_tokenize(text)
filtered = [w for w in tokens if w.lower() not in stopwords]

spaCy

import spacy
from fulfulde_stopwords import get_stopwords

nlp = spacy.blank("xx")  # Multi-language model
stopwords = get_stopwords()

# Add stopwords to spaCy
for word in stopwords:
    nlp.vocab[word].is_stop = True

scikit-learn

from sklearn.feature_extraction.text import TfidfVectorizer
from fulfulde_stopwords import get_stopwords

stopwords = get_stopwords()
vectorizer = TfidfVectorizer(stop_words=list(stopwords))

API Reference

get_stopwords(case_sensitive=False)

Get the set of Fulfulde stopwords.

Parameters:

• case_sensitive (bool): If False (default), returns lowercase stopwords

Returns:

• Set[str]: A set containing all Fulfulde stopwords

is_stopword(word, case_sensitive=False)

Check if a word is a stopword.

Parameters:

• word (str): The word to check
• case_sensitive (bool): If False (default), comparison is case-insensitive

Returns:

• bool: True if the word is a stopword, False otherwise

remove_stopwords(tokens, case_sensitive=False, preserve_order=True)

Remove stopwords from a list of tokens.

Parameters:

• tokens (List[str]): List of tokens to filter
• case_sensitive (bool): If False (default), comparison is case-insensitive
• preserve_order (bool): If True (default), preserves original token order

Returns:

• List[str]: List of tokens with stopwords removed

filter_text(text, tokenizer=None, case_sensitive=False)

Remove stopwords from a text string.

Parameters:

• text (str): The text to filter
• tokenizer (callable): Optional tokenizer function
• case_sensitive (bool): If False (default), comparison is case-insensitive

Returns:

• str: The filtered text with stopwords removed

get_stopword_count(tokens, case_sensitive=False)

Count the number of stopwords in a list of tokens.

Parameters:

• tokens (List[str]): List of tokens to analyze
• case_sensitive (bool): If False (default), comparison is case-insensitive

Returns:

• int: The number of stopwords found

get_stopword_ratio(tokens, case_sensitive=False)

Calculate the ratio of stopwords to total tokens.

Parameters:

• tokens (List[str]): List of tokens to analyze
• case_sensitive (bool): If False (default), comparison is case-insensitive

Returns:

• float: The ratio of stopwords (between 0 and 1)

get_stats(tokens, case_sensitive=False)

Get comprehensive statistics about stopwords in a list of tokens.

Parameters:

• tokens (List[str]): List of tokens to analyze
• case_sensitive (bool): If False (default), comparison is case-insensitive

Returns:

• dict: Statistics including total tokens, stopword count, content word count, and stopword ratio

Language Information

Variant and Orthography

• Language: Fulfulde (Adamawa variant)
• Region: Cameroon and Northern Nigeria
• Script: Latin alphabet with special characters (ɓ, ɗ, ŋ, etc.)
• ISO 639-3: fub (Adamawa Fulfulde)

Linguistic Features

Fulfulde is characterized by:

• Nominal class system: 20+ noun classes with corresponding pronouns
• Agglutinative morphology: Extensive use of suffixes and prefixes
• VSO word order: Verb-Subject-Object as default
• Grammatical particles: Heavy reliance on particles rather than articles

Stopword Categories

The stopword list includes:

1. Personal pronouns: mi, a, o, ɓe, en, on
2. Demonstratives: ɗo, ɗon, oo, ɓee
3. Prepositions: haa, e, nder, dow, ley
4. Conjunctions: bee, koo, ammaa, niai
5. Auxiliaries: woni, ɗon, woodi, jogi
6. Discourse particles: nden, ni, boo, tan
7. Negations: ai, ataa, naa, fay
8. Interrogatives: mo, ko, moy, ndeeye
9. Nominal class pronouns: ɗum, ka, ki, nde, ndi, etc.
10. Temporal/spatial adverbs: ɗoo, toon, hande

Areas for contribution:

• Additional stopwords from other Fulfulde variants (Maasina, Pulaar, etc.)
• Extended stopword lists with domain-specific terms
• Integration examples with popular NLP frameworks
• Benchmarks on NLP tasks
• Translations and documentation

Citation

If you use this library in your research, please cite:

@article{fulfulde_stopwords_2026,
  title={Fulfulde Stopwords: A Linguistic Resource for NLP in a Low-Resource African Language},
  author={Isaac Touza},
  year={2026},
}

License

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

Contact

For questions, suggestions, or collaborations:

• GitHub Issues: https://github.com/2zalab/fulfulde-stopwords/issues
• Email: [e-mail]

Changelog

Version 1.0 (2026-01-14)

• Initial release
• 180+ stopwords for Adamawa Fulfulde
• Complete Python API
• Comprehensive documentation
• Test suite