README.md

masakhanePreprocessor

An effective language-first preprocessing tool for African languages (🔧 Beta version).

We build on the clean-text preprocessor.

How to Use

Install:

git clone https://github.com/masakhane-io/masakhanePreprocessor.git
cd masakhanePreprocessor
pip install .

Preprocessor

You only need to specify your language and it loads the important preprocessing style for You!

You initialize the Preprocessor in Python as follows:

from masakhanePreprocessor import Preprocessor

my_prep = Preprocessor(lang='ig')

You can also directly include some additional parameters you want:

my_prep = Preprocessor(lang='ig',
              lower=True,
              strip_punctuation=True,
              strip_symbols=True)

preproces_str

To preprocess a string use the preproces_str function:

clean_text = my_prep.preprocess_str('''Dịka● ndọrọndọrọọchịchị maka ntuliaka ọkwa Gọvanọ
                                       Anambra steeti si na-aga nke afọ 2021, ndị nọ.''')

You get the following as output: Dịka ndọrọndọrọọchịchị maka ntuliaka ọkwa Gọvanọ Anambra steeti si na-aga nke afọ 2021 ndị nọ

Notice how the ● character has been removed, but the -, which is an important part of Igbo, remains untouched.

preprocess_file

To preprocess a file use the preprocess_file function:

my_prep.preprocess_file('ig.txt',
                        output_path=None #Specify the output path. If unspecified, uses the parent directory of input file)

On successful completion you get this message: Clean file(s) saved successfully to xxxxxxx/ig_CLEAN.txt

Properties of the preprocessing tool

1. Language-first It can:

   • map any African language name provided to its language code. You can write Preprocessor(lang='yoruba') using just the name.
   • map any language code to its BCP47 variant. So even if you use yo or yor it does not matter.

2. Simple to use

Contribution

We are open to and grateful for ideas to make this better. You can propose ideas as issues or pull requests.

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With 💙 From The Contributors