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code-mixed-text-toolkit

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code-mixed-text-toolkit

A library for processing Code Mixed Text. Still in development!

  • 0.5.5
  • PyPI
  • Socket score

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This repository has been archived!

You can find the latest version of the source code inside the CMTT repository, where it will continue to be developed.

forthebadge made-with-python


code style: blackCompatibility

CMTT is a wrapper library that makes code-mixed text processing more efficient than ever. More documentation incoming!

Installation

pip install code-mixed-text-toolkit

Get started

How to use this library:

import code_mixed_text_toolkit.data as cmtt_data
import code_mixed_text_toolkit.preprocessing as cmtt_pp

# Loading json files
result_json = cmtt_data.load('https://world.openfoodfacts.org/api/v0/product/5060292302201.json')

# Loading csv files
result_csv = cmtt_data.load('https://gist.githubusercontent.com/rnirmal/e01acfdaf54a6f9b24e91ba4cae63518/raw/b589a5c5a851711e20c5eb28f9d54742d1fe2dc/datasets.csv')

# List the key properties available for the datasets provided by the cmtt library
keys = cmtt_data.list_dataset_keys()

# List all datasets provided by cmtt
# Specifying the 'key' property allows to return the dataset names with the respective 'key' value
# Specifying the 'key' as 'all' returns all the information pertaining to all the datasets
data = cmtt_data.list_cmtt_datasets()
print(data)

# Download multiple datasets provided by cmtt, returning a list of paths where the datasets get downloaded
# The Datasets are downloaded into a new 'cmtt' directory inside the root directory of the operating system
lst = cmtt_data.download_cmtt_datasets(["linc_ner_hineng", "L3Cube_HingLID_all", "linc_lid_spaeng"])

# Download a dataset from a url, returning the path where the dataset gets downloaded
# The Dataset is downloaded into a new directory 'datasets' inside the current working directory
path = cmtt_data.download_dataset_url('https://world.openfoodfacts.org/api/v0/product/5060292302201.json')

# Load and preprocess txt dataset
result_txt = cmtt_data.load('https://www.w3.org/TR/PNG/iso_8859-1.txt')
result_txt_tokenized = cmtt_pp.tokenizer.word_tokenize(result_txt)

# Search target word in txt corpus
cmtt_pp.search.search_word(result_txt, 'with', tokenize = True, width = 3)

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