An effective language-first preprocessing tool for African languages (🔧 Beta version).
We build on the clean-text preprocessor.
Install:
pip install masakhane-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 masakhane-preprocessor 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)
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.
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
-
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
oryor
it does not matter.
- map any African language name provided to its language code. You can write
-
Simple to use
We are open to and grateful for ideas to make this better. You can propose ideas as issues or pull requests.