Init commit

.gitattributes

@@ -53,3 +53,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.jpg filter=lfs diff=lfs merge=lfs -text
 *.jpeg filter=lfs diff=lfs merge=lfs -text
 *.webp filter=lfs diff=lfs merge=lfs -text
+# Wiki data files CSV
+*.csv filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,3 +1,212 @@
 ---
+annotations_creators:
+- no-annotation
+language_creators:
+- crowdsourced
+language:
+- ace
+- ban
+- bjn
+- bug
+- gor
+- id
+- jv
+- mis
+- min
+- ms
+- nia
+- su
+- tet
+license:
+- cc-by-sa-3.0
+- gfdl
+multilinguality:
+- multilingual
+source_datasets:
+- Wikipedia-HF
+task_categories:
+- text-generation
+- fill-mask
+task_ids:
+- language-modeling
+- masked-language-modeling
+pretty_name: Wikipedia Archive for Indonesian Languages & Local Languages
+tags:
+- Wikipedia
+- Untagged Languages ISO-639 (Banyumase/Ngapak)
+- Indonesian Language
+- Malaysian Language
+- Indonesia-related Languages
+- Indonesian Local Languages
+dataset_info:
+- config_name: indowiki_all
+  features:
+  - name: url
+    dtype: string
+  - name: title
+    dtype: string
+  - name: text
+    dtype: string
+  splits:
+  - name: ace
+    num_bytes: 4875688
+    num_examples: 12932
+  - name: ban
+    num_bytes: 17561379
+    num_examples: 20243
+  - name: bjn
+    num_bytes: 6669628
+    num_examples: 10460
+  - name: bug
+    num_bytes: 3297641
+    num_examples: 15877
+  - name: gor
+    num_bytes: 6007726
+    num_examples: 14572
+  - name: id
+    num_bytes: 1103106307
+    num_examples: 657990
+  - name: jv
+    num_bytes: 70335030
+    num_examples: 73150
+  - name: map_bms
+    num_bytes: 5215803
+    num_examples: 13574
+  - name: min
+    num_bytes: 116481049
+    num_examples: 227024
+  - name: ms
+    num_bytes: 416001194
+    num_examples: 367463
+  - name: nia
+    num_bytes: 1938378
+    num_examples: 1651
+  - name: su
+    num_bytes: 47489084
+    num_examples: 61557
+  - name: tet
+    num_bytes: 1452716
+    num_examples: 1465
+  download_size: 1803193334
+  dataset_size: 1800431623
+- config_name: indowiki_dedup_all
+  features:
+  - name: url
+    dtype: string
+  - name: title
+    dtype: string
+  - name: text
+    dtype: string
+  splits:
+  - name: ace
+    num_bytes: 4867838
+    num_examples: 12904
+  - name: ban
+    num_bytes: 17366080
+    num_examples: 19837
+  - name: bjn
+    num_bytes: 6655378
+    num_examples: 10437
+  - name: bug
+    num_bytes: 2072609
+    num_examples: 9793
+  - name: gor
+    num_bytes: 5989252
+    num_examples: 14514
+  - name: id
+    num_bytes: 1100932403
+    num_examples: 654287
+  - name: jv
+    num_bytes: 69774853
+    num_examples: 72667
+  - name: map_bms
+    num_bytes: 5060989
+    num_examples: 11832
+  - name: min
+    num_bytes: 116376870
+    num_examples: 225858
+  - name: ms
+    num_bytes: 410443550
+    num_examples: 346186
+  - name: nia
+    num_bytes: 1938121
+    num_examples: 1650
+  - name: su
+    num_bytes: 47410439
+    num_examples: 61494
+  - name: tet
+    num_bytes: 1447926
+    num_examples: 1460
+  download_size: 1793103024
+  dataset_size: 1790336308
+- config_name: indowiki_dedup_id_only
+  features:
+  - name: url
+    dtype: string
+  - name: title
+    dtype: string
+  - name: text
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 1100932403
+    num_examples: 654287
+  download_size: 1103131493
+  dataset_size: 1100932403
+---
+
+# **Indonesian Wikipedia Data Repository**
+---
 license: cc-by-sa-3.0
 ---
+Welcome to Indonesian Wikipedia Data Repository. The datasets are extracted from [Wikipedia HF](https://huggingface.co/datasets/wikipedia) and processed using the scripts available in this repository for reproducibility purpose.
+
+# **FAQS**
+### How do I extract new Wikipedia Dataset of Indonesian languages?
+You may check to the script [_```extract_raw_wiki_data.py```_](https://huggingface.co/datasets/sabilmakbar/indonesian_wiki/blob/main/extract_raw_wiki_data.py) to understand its implementations, or you can adjust the bash provided in [_```extract_raw_wiki_data_indo.sh```_](https://huggingface.co/datasets/sabilmakbar/indonesian_wiki/blob/main/extract_raw_wiki_data_indo.sh) to extract it on your own.
+
+### How do I extract new Wikipedia Dataset of Indonesian languages?
+You may visit this [Wikipedia Dump Index](https://dumps.wikimedia.org/backup-index.html) to check any latest available data and this link [Wikipedia Language Coverage](https://meta.wikimedia.org/wiki/List_of_Wikipedias#All_Wikipedias_ordered_by_number_of_articles) to map into any languages that you're wanting to extract.
+
+### How does the data being preprocessed? What makes it different from loading it directly from Wikipedia HF?
+The data available in here are processed with following flows:
+1. Raw data is being deduplicated on ```title``` and ```text``` (text-content from a given article), to remove articles containing boilerplate text (template text that are used usually for no-available informations or asking for contributions of content in that article), which usually deemed noisy for NLP data.
+2. Furthermore, the ```title``` and ```text``` data are being checked for string-matching duplication (duplication of text that are being pre-processed, i.e symbols removed, HTML tags striped, or ASCII-chars validated). You may check this [ ```cleanse_wiki_data.py```](https://huggingface.co/datasets/sabilmakbar/indonesian_wiki/blob/main/cleanse_wiki_data.py) script to understand its implementation.
+
+# Getting Started #
+### To read the datasets directly ###
+Use one of the following code chunks to load it from HuggingFace Hub:
+You can refer to the 2nd args of ```config name``` using the following script
+```
+dataset = load_dataset(
+  "sabilmakbar/indonesian_wiki",
+  "indo_wiki_dedup_data" # a config name, can be "indo_wiki_raw_data" or "indowiki_dedup_id_only", defaults to "indo_wiki_dedup_data"
+)
+```
+Or you can provide both ```lang``` and ```date_stamp``` (providing only one will thrown an error)
+```
+dataset = load_dataset(
+  "sabilmakbar/indonesian_wiki",
+  lang = "id", # see the splits for complete lang choices
+  date_stamp="20230901"
+)
+```
+
+### To replicate the whole dataset generation process ###
+1. Set-up a new Python/Conda Environment (recommended Python version: 3.9.6 to 3.9.18 or 3.10.0 to 3.10.13) and install the requirements on ```requirements.txt``` use this codebase via ```pip install -r requirements.txt```.
+2. Activate the chosen Python/Conda environment which the requirements are being installed.
+3. Run this ```sh``` script for extractions from Wikimedia Dump:
+    ```sh extract_raw_wiki_data_indo.sh```.
+4. Run this ```sh``` script of deduplication:
+    ```sh dedup_raw_wiki_data_indo.sh```.
+
+## Citation Info:
+```
+@ONLINE{wikidump,
+    author = "Wikimedia Foundation",
+    title  = "Wikimedia Downloads",
+    url    = "https://dumps.wikimedia.org"}
+@ONLINE{wikipedia-hf,
+    title  = "Huggingface Wikipedia Dataset",
+    url    = "https://huggingface.co/datasets/wikipedia"}
+```

cleanse_wiki_data.py

@@ -0,0 +1,246 @@
+'''
+Script on Cleansing Wikipedia Data that has been extracted from extract_raw_wiki_data.py
+'''
+#core functionality modules
+import os, gc
+import logging
+import argparse
+import warnings
+
+from functools import partial
+
+#text preprocess modules
+import re
+import urllib
+from xml.etree import ElementTree as ET
+
+#dataset related modules
+import numpy as np
+import pandas as pd
+
+
+### MODULES DEFINITION ###
+#create custom type-checking of incoming ArgParse
+def argparse_bool_check(value: str):
+    #cast str with value like float into actual float
+    try:
+        value = float(value)
+    #can't be parsed as float, keep as it is
+    except ValueError:
+        pass
+
+    #cast float-like value (incl int) into str
+    if isinstance(value, float) and int(value) == value:
+        value = str(int(value))
+    #raise ArgumentTypeError if the value isn't in string already
+    else:
+        if not isinstance(value, str):
+            raise argparse.ArgumentTypeError(f"Not the correct value (args: {value})! Expected is cast-able to '1' or '0' or already in string. Please rectify!")
+    #check for these combinations of values
+    if value.lower() in ("yes", "true", "t", "y", "1"):
+        return True
+    elif value.lower() in ("no", "false", "f", "n", "0"):
+        return False
+    else:
+        raise argparse.ArgumentTypeError(f"Value Error! Not the correct value (args: {value})! Please rectify!")
+
+
+def set_logger():
+    # Set up the logger
+    logging.basicConfig(
+        level=logging.INFO,  # Set the desired logging level (DEBUG, INFO, WARNING, ERROR, CRITICAL)
+        format='%(asctime)s [%(levelname)s]: %(message)s',  # Customize the log message format
+        datefmt='%Y-%m-%d %H:%M:%S'  # Customize the date/time format
+    )
+
+    # Create a file handler to write logs into a file
+    file_handler = logging.FileHandler('app.log')
+
+    # Set the log level for the file handler
+    file_handler.setLevel(logging.INFO) 
+
+    # Create a formatter for the file handler (customize the log format for the file)
+    file_formatter = logging.Formatter('%(asctime)s [%(levelname)s]: %(message)s', datefmt='%Y-%m-%d %H:%M:%S')
+    file_handler.setFormatter(file_formatter)
+
+    logger = logging.getLogger("Wiki Dataset Generation")
+    logger.addHandler(file_handler)
+
+    return logger
+
+
+#wrapper fn of text-cleansing
+def text_cleansing_wrapper(fn, exception_class_names = []):
+
+    #ensure caught exception class names passed to decorator is a list (if provided)
+    if not isinstance(exception_class_names, list):
+        raise TypeError("Exception Class Name for Wrapper is not a list!")
+    #ensure all values of caught exception class name list is a string
+    if not all([isinstance(val, str) for val in exception_class_names]):
+        raise ValueError("Found an element of Exception Class Name for Wrapper that is not a string!")
+
+    #lowercase all exception class name
+    exception_class_names = [val.lower() for val in exception_class_names]
+    if len(exception_class_names) == 0:
+        warnings.warn("The wrapper receives 0 `exception_class_names` to be warned! Will return the function value with its input!")
+
+    def text_fn_wrapper(text: str):
+        try:
+            return fn(text)
+        except Exception as e:
+            _exc_name = type(e).__name__
+            if _exc_name.lower() not in exception_class_names and len(exception_class_names)>0:
+                raise Exception(f"Exception Occured of {_exc_name}!") from e
+            else:
+                _followup_msg = "Returning the input as it is..."
+                _text_warn = f"An exception of {_exc_name} occured! {_followup_msg}"
+                warnings.warn(_text_warn)
+                return text
+
+    return text_fn_wrapper
+
+
+#create html tags cleanser of a given text
+partial_decorator = partial(text_cleansing_wrapper, exception_class_names=["parseerror"])
+@partial_decorator
+def remove_html_tags(text: str):
+    #extracted from "https://stackoverflow.com/a/9662410", w/ additional decorator of error handler
+    return ''.join(ET.fromstring(text).itertext())
+
+
+#create non-ascii removal of text
+@text_cleansing_wrapper
+def decode_url_and_remove_non_ascii(text: str):
+    # return (urllib.parse.unquote(text)).encode('utf8', errors='ignore').decode().strip()
+    return (urllib.parse.unquote(text)).encode('ascii', errors='ignore').decode().strip()
+
+#create excessive whitespace removal of text
+@text_cleansing_wrapper
+def remove_excessive_whitespace(text: str):
+    return re.sub("(\s)(\s+)", "\1", text).strip()
+
+#create non-alphanumeric removal of text
+@text_cleansing_wrapper
+def remove_non_alphanumeric(text: str):
+    return re.sub("[^a-z0-9\s]", "", text, flags=re.I).strip()
+
+def cleanse_wiki_text(text: str):
+    return remove_html_tags(decode_url_and_remove_non_ascii(text))
+
+def normalize_wiki_title(text: str):
+    return remove_non_alphanumeric(remove_excessive_whitespace(text.lower()))
+
+
+### MAIN CODE ###
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument("--raw-csv-path", help="Relative location of csv file containing raw Wikipedia data")
+    parser.add_argument("--drop-hard-dupl", help="""Flag whether to drop hard duplicates
+                        (exact values of data of relevant text fields, Titles & Desc)""",
+          default=True, type=argparse_bool_check)
+    parser.add_argument("--drop-soft-dupl", help="""Flag whether to drop soft duplicates
+                        (duplicates after cleansed and normalized relevant text fields, Titles & Desc)""",
+          default=True, type=argparse_bool_check)
+    parser.add_argument("--save-dir-path", help="""Relative dir path of saved Wikipedia CSV data
+                        to the `cleanse_wiki_data.py` script dir""",
+            default=os.path.dirname(os.path.abspath(__file__)))
+
+    args = parser.parse_args()
+
+
+    expected_colnames = ["id", "url", "title", "text"]
+
+    logger = set_logger()
+    logger.info("Parsing arguments...")
+
+    raw_data_path = args.raw_csv_path
+    drop_hard_dupl = args.drop_hard_dupl
+    drop_soft_dupl = args.drop_soft_dupl
+    save_dir = args.save_dir_path
+
+    df = pd.read_csv(raw_data_path)
+    if len(set(df.columns).difference(set(expected_colnames))) != 0 or len(set(expected_colnames).difference(set(df.columns))) != 0:
+        raise ValueError(f"The data schema expected, consist of columns: {', '.join(df.columns.to_list())} doesn't match with expected column values of {', '.join(expected_colnames)}!")
+
+    if (not drop_hard_dupl) and (not drop_soft_dupl):
+        raise AssertionError("The script won't run with both `drop-hard-dupl` and `drop-soft-dupl` args turned off!")
+    elif (not drop_hard_dupl):
+        warnings.warn("The args of `drop_hard_dupl` isn't turned off! Possibly the data will contain one template value of Wikipedia (usually no contribution text!)")
+
+    #will save id identifier colname first (popping first list val)
+    id_colname = expected_colnames.pop(0)
+
+    # if any of the data has duplicate values from columns checked (url, title, or text),
+    # it means the data integrity is questionable
+    # i.e. copied from other article or filled with template text
+    # hence, we will delete those duplicated datasets
+
+    suffix_file = "_dedup_cleansed"
+    #hard duplicate drop (drop all duplicate values that has exact same text on expected unique colnames)
+    if drop_hard_dupl:
+
+        for colname in expected_colnames:
+            logger.info(f"Checking data integrity on column {colname} on removing hard-duplicate(s)...")
+            dupl_text_df = df[df.duplicated(subset=colname,keep=False)]
+            shape_of_dupl_data = dupl_text_df.shape[0]
+
+            if shape_of_dupl_data > 0:
+                logger.info(f"Found {shape_of_dupl_data} data duplicated! Will be dropped")
+                df.drop_duplicates(subset=colname, keep=False, inplace=True)
+
+
+        #check id/idx of the cleansed data, whether it has duplicate
+        # (the duplication of id/idx should came from the very first extraction, not from the cleansing)
+
+        if df[df.duplicated(subset=id_colname,keep=False)].shape[0] > 0:
+            logger.info("Duplicated ID found! Re-assigning ID to the new ones based on `df.reset_index` method!")
+            df[id_colname] = df.reset_index().index
+
+    #soft duplicate drop (drop all except one duplicate values that has exact same text on expected unique colnames)
+    #keep the data that has longest value of its raw form
+    if drop_soft_dupl:
+
+        idx_to_keep = set(df.index.to_list())
+        #clean from text & title only, url isn't needed for this process
+        expected_colnames.remove("url")
+
+        for colname in expected_colnames:
+            logger.info(f"Checking data integrity on column {colname} on removing soft-duplicate(s)...")
+            _df = df.copy(deep=True)
+
+            #define text processing fn for soft-duplicate cleansing
+            #text processing for all colums (text & title)
+            _df = _df[[colname]]
+            _df[colname] = _df[colname].astype("str")
+            logger.info(f"Cleansing the data based on {colname}")
+            _df[colname+"_raw_len"] = _df[colname].apply(len)
+            _df[colname+"_cleansed"] = _df[colname].apply(cleanse_wiki_text)
+            if colname == "title":
+                # title text has been cleansed by `cleanse_wiki_text` fn, but needs to normalized on
+                # whitespaces, non alphanum syms (incl. punctuations), and case (all lowercased)
+                _df[colname+"_cleansed"] = _df[colname+"_cleansed"].apply(normalize_wiki_title)
+
+            #choose the data to keep by "ranking" it according to len of its raw text (greatest to keep)
+            logger.info(f"Ranking and grouping the data based on {colname}")
+            _df["rk"] = _df.groupby(colname+"_cleansed")[colname+"_raw_len"].rank(method="min", ascending=False)
+            shape_of_dupl_data = _df[_df["rk"]>1].shape[0]
+
+            if shape_of_dupl_data > 0:
+                logger.info(f"Found {shape_of_dupl_data} data duplicated! Will be dropped")
+                _idx_to_keep = _df[_df["rk"]==1].index.to_list()
+                if len(_idx_to_keep)+shape_of_dupl_data != df.shape[0]:
+                    raise AssertionError("Mismatch of data number!")
+                idx_to_keep = idx_to_keep.intersection(set(_idx_to_keep))
+            del _df
+            gc.collect()
+
+        logger.info(f"The final data kept is {len(idx_to_keep)} from {df.shape[0]}")
+        df = df.loc[list(idx_to_keep),:]
+
+    logger.info("Saving dataset cleansed form...")
+    #input path splitted by ("/") for the last entry should return filename
+    #whereas the filename splitted by (".") except the last value should return the filename w/o ".csv" extension
+    
+    _save_fn = ".".join(raw_data_path.split("/")[-1].split(".")[:-1]) + suffix_file + ".csv"
+    df.to_csv(f"{save_dir}/{_save_fn}", index=False)

dedup_raw_wiki_data_indo.sh

@@ -0,0 +1,56 @@
+#!/bin/bash
+
+# all available lang codes in Indonesia local-languages or linguistically-related to Indonesian Language:
+# "ace", "ban", "bjn", "bug", "gor", "id", "jv", "map-bms", "min", "ms", "nia", "su", "tet"
+
+#params of executions
+folder_dir_to_save=./wiki_indonesian_dedup
+input_folder_to_be_dedup=./wiki_indonesian_raw
+
+drop_hard_dupl=True
+drop_soft_dupl=True
+
+
+# main executions
+
+# src: https://stackoverflow.com/a/18887210 (to list all files under a dir)
+shopt -s nullglob
+file_name_array=($input_folder_to_be_dedup/*)
+shopt -u nullglob # Turn off nullglob to make sure it doesn't interfere with anything later
+file_name_array="${file_name_array}"
+
+if [ ${#file_name_array[@]} == 0 ]; then
+    echo "No files found under directory $input_folder_to_be_dedup" >&2
+fi
+
+if [ ! -d $folder_dir_to_save ];
+then
+    echo "Dir $folder_dir_to_save not exists! Creating the dir..."
+    mkdir $folder_dir_to_save
+fi
+
+echo "The params hard-dedup drop is set as $drop_hard_dupl"
+echo "The params soft-dedup drop is set as $drop_soft_dupl"
+
+# echo "${file_name_array[0]}"
+# echo "${file_name_array[1]}"
+# echo "${file_name_array[2]}"
+# echo "${file_name_array[3]}"
+
+for val in ${!file_name_array[@]}; do
+    csv_path=${file_name_array[$val]}
+
+    if [[ ${csv_path} != *".csv" ]]; then
+        echo "The extracted file name isn't a CSV! Skipping! Received $csv_path"
+        continue
+    fi
+
+    echo "Executing Dedup on iteration no "$((val+1))" of total ${#file_name_array[@]} for input data $csv_path"
+    python cleanse_wiki_data.py \
+        --raw-csv-path $csv_path \
+        --drop-hard-dupl $drop_hard_dupl \
+        --drop-soft-dupl $drop_soft_dupl \
+        --save-dir-path $folder_dir_to_save
+    echo "Done Execution"
+done
+echo "Done Dedup Process"

extract_raw_wiki_data.py

@@ -0,0 +1,68 @@
+'''
+Script on Generating Wikipedia Data that are dumped into https://dumps.wikimedia.org/
+More info can be read on https://huggingface.co/datasets/wikipedia
+-------------------
+Check here to see available indexed data: https://dumps.wikimedia.org/backup-index.html
+Also check here to see language meta from its code: https://meta.wikimedia.org/wiki/List_of_Wikipedias
+'''
+
+import os
+import logging
+import argparse
+
+import pandas as pd
+from datasets import load_dataset
+
+
+def set_logger():
+    # Set up the logger
+    logging.basicConfig(
+        level=logging.INFO,  # Set the desired logging level (DEBUG, INFO, WARNING, ERROR, CRITICAL)
+        format='%(asctime)s [%(levelname)s]: %(message)s',  # Customize the log message format
+        datefmt='%Y-%m-%d %H:%M:%S'  # Customize the date/time format
+    )
+
+    # Create a file handler to write logs into a file
+    file_handler = logging.FileHandler('app.log')
+
+    # Set the log level for the file handler
+    file_handler.setLevel(logging.INFO) 
+
+    # Create a formatter for the file handler (customize the log format for the file)
+    file_formatter = logging.Formatter('%(asctime)s [%(levelname)s]: %(message)s', datefmt='%Y-%m-%d %H:%M:%S')
+    file_handler.setFormatter(file_formatter)
+
+    logger = logging.getLogger("Wiki Dataset Generation")
+    logger.addHandler(file_handler)
+
+    return logger
+
+
+#only executed if called directly
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument("--lang-id", help="Lang ID from Wikipedia Data to extract")
+    parser.add_argument("--date-ver", help="Date of Wikipedia Data (YYYYMMDD) generation to extract")
+    parser.add_argument("--save-dir-path", help="""Relative dir path of saved Wikipedia CSV data
+                        to the `extract_raw_wiki_data.py` script dir""",
+            default=os.path.dirname(os.path.abspath(__file__)))
+
+    args = parser.parse_args()
+
+
+    dset_name = "wikipedia"
+
+    logger = set_logger()
+    logger.info("Parsing arguments...")
+
+    lang_id = args.lang_id
+    date_ver = args.date_ver
+    save_dir = args.save_dir_path
+
+    logger.info("Loading the dataset from Wikipedia...")
+    df = load_dataset(dset_name, language=lang_id, date=date_ver, beam_runner='DirectRunner', split="train").to_pandas()
+    logger.info("Loading done!")
+    logger.info(f"#Data collected: {df.shape[0]}")
+    logger.info("Saving dataset raw form...")
+    df.to_csv(f"{save_dir}/wiki_{lang_id}_{date_ver}_raw_dataset.csv", index=False)

extract_raw_wiki_data_indo.sh

@@ -0,0 +1,29 @@
+#!/bin/bash
+
+# all available lang codes in Indonesia local-languages or linguistically-related to Indonesian Language:
+# "ace", "ban", "bjn", "bug", "gor", "id", "jv", "map-bms", "min", "ms", "nia", "su", "tet"
+
+#params of executions
+date_ver=20230901
+folder_dir_to_save=./wiki_indonesian_raw
+lang_list=(ace ban bjn)
+# bug gor id jv map-bms min ms nia su tet)
+
+
+#main executions
+
+if [ ! -d $folder_dir_to_save ]; then
+    echo "Dir $folder_dir_to_save not exists! Creating the dir..."
+    mkdir $folder_dir_to_save
+fi
+
+for val in ${!lang_list[@]}; do
+    lang=${lang_list[$val]}
+    echo "Executing Extractor on iteration no $((val+1)) of total ${#lang_list[@]} for language $lang and date version of $date_ver"
+    python extract_raw_wiki_data.py \
+        --lang-id $lang \
+        --date-ver $date_ver \
+        --save-dir-path $folder_dir_to_save
+    echo "Done Execution"
+done
+echo "Done Extraction Process"

indo_wiki.py

@@ -0,0 +1,181 @@
+"""The Indonesian Wiki Loader"""
+
+import os
+import re
+
+import pandas as pd
+
+import datasets
+
+
+_CITATIONS = """\
+@ONLINE{wikidump,
+    author = "Wikimedia Foundation",
+    title  = "Wikimedia Downloads",
+    url    = "https://dumps.wikimedia.org"}
+
+@ONLINE{wikipedia-hf,
+    title  = "Huggingface Wikipedia Dataset",
+    url    = "https://huggingface.co/datasets/wikipedia"}"""
+
+_REPO_URL = "https://huggingface.co/datasets/sabilmakbar/indonesian_wiki"
+
+_LICENSE = (
+    "This work is licensed under the Creative Commons Attribution-ShareAlike "
+    "3.0 Unported License. To view a copy of this license, visit "
+    "http://creativecommons.org/licenses/by-sa/3.0/ or send a letter to "
+    "Creative Commons, PO Box 1866, Mountain View, CA 94042, USA."
+)
+
+
+_INDO_WIKI_RAW_DESCRIPTION = """\
+Indonesian Wikipedia Data Repository contains Wikipedia Data from Wikipedia HF that focuses
+on extraction in Indonesian Languange and Indonesian Local Languages, that some of them
+are considered as low-resource languages or extremely low-resource languages"""
+
+_INDO_WIKI_DEDUP_DESCRIPTION = """\
+This is a derivative of Indonesian Wikipedia Data Repository which is already pre-processed
+by identifying and dropping duplicates to prevent boilerplate texts occuring in dataset"""
+
+_AVAILABLE_DUMP_VERSION_DATE = ["20230901"]
+_AVAILABLE_DUMP_LANGUAGES = ["ace", "ban", "bjn", "bug", "gor", "id", "jv", "map-bms", "min", "ms", "nia", "su", "tet"]
+
+
+def _construct_dataset_from_dset_version_and_lang(date_ver: str, lang: str, mode: str):
+    _mode_to_folder_mapper = {"dedup": "indo_wiki_dedup_data", "raw": "indo_wiki_raw_data"}
+    _mode_to_file_suffix_mapper = {"dedup": "dataset_soft_hard_cleansed.csv", "raw": "raw_dataset.csv"}
+
+    return os.path.join(_mode_to_folder_mapper[mode], f"wiki_{lang}_{date_ver}_{_mode_to_file_suffix_mapper[mode]}")
+
+
+class IndoWikiConfig(datasets.BuilderConfig):
+    """BuilderConfig for IndoWiki."""
+
+    def __init__(self, description: str=None, features: list=['url', 'title', 'text'],
+                 data_url: str=None, date_stamp: str=None, lang: str=None,
+                 mode = "dedup", **kwargs):
+        """BuilderConfig for IndoWiki.
+
+        Args:
+          description: `string`, description of dataset
+          features: `list[string]`, list of the features that will appear in the
+            feature dict. Should not include "label" if it's a supervised.
+          data_url: `string`, url to download the data.
+          date_stamp: `string`, wikidump date_stamp for data available in repo.
+          lang: `string`, language to be loaded.
+          **kwargs: keyword arguments forwarded to super.
+        """
+        # validate configs
+        if mode not in ["dedup", "raw"]:
+            raise ValueError(f"Error occured! Expected values are 'dedup' or 'raw' for arg `mode`, received {mode}!")
+
+        if (lang is None or date_stamp is None) and data_url is None:
+            raise ValueError("Expected `data_url` is provided or both `date_stamp` and `lang` are provided!")
+
+        _mode_to_desc_mapper = {"dedup": _INDO_WIKI_DEDUP_DESCRIPTION, "raw":_INDO_WIKI_RAW_DESCRIPTION}
+
+        if date_stamp is not None and date_stamp not in _AVAILABLE_DUMP_VERSION_DATE:
+            raise ValueError("Provided `date_stamp` dataset versioning doesn't match! Please re-check")
+
+        if lang is not None and lang not in _AVAILABLE_DUMP_LANGUAGES:
+            raise ValueError("Provided `lang` doesn't match! Please re-check")
+
+        super(IndoWikiConfig, self).__init__(**kwargs)
+        self.features = features
+
+        # prioritize kwargs data_url
+        if data_url is not None:
+            self.data_url = data_url
+        else:
+            self.data_url = _construct_dataset_from_dset_version_and_lang(date_ver=date_stamp, lang=lang, mode=mode)
+
+        # auto-construct desc if not provided
+        if description is None:
+            self.description = _mode_to_desc_mapper[mode] + "\n" + f"From file path {self.data_url}"
+
+        #define citations & info URL internally in config class
+        self.citation = _CITATIONS
+        self.url = _REPO_URL
+
+
+class IndoWiki(datasets.GeneratorBasedBuilder):
+    """The IndoWiki Dataset."""
+
+    #if name isn't provided, will create a dataset of all languages
+    DEFAULT_CONFIG_NAME = "indowiki_dedup_all"
+    BUILDER_CONFIG_CLASS = IndoWikiConfig
+
+    _newest_data_raw_all_langs = [_construct_dataset_from_dset_version_and_lang(
+        date_ver=sorted(_AVAILABLE_DUMP_VERSION_DATE)[-1], lang=lang, mode="raw") for lang in _AVAILABLE_DUMP_LANGUAGES]
+    _newest_data_dedup_all_langs = [_construct_dataset_from_dset_version_and_lang(
+        date_ver=sorted(_AVAILABLE_DUMP_VERSION_DATE)[-1], lang=lang, mode="dedup") for lang in _AVAILABLE_DUMP_LANGUAGES]
+
+    BUILDER_CONFIGS = [
+        IndoWikiConfig(
+            name="indowiki_all",
+            description=_INDO_WIKI_RAW_DESCRIPTION,
+            data_url=_newest_data_raw_all_langs
+        ),
+        IndoWikiConfig(
+            name="indowiki_dedup_all",
+            description=_INDO_WIKI_DEDUP_DESCRIPTION,
+            data_url=_newest_data_dedup_all_langs
+        ),
+        IndoWikiConfig(
+            name="indowiki_dedup_id_only",
+            lang="id",
+            date_stamp="20230901"
+        )
+    ]
+
+
+    def _info(self):
+        features = {feature: datasets.Value("string") for feature in self.config.features}
+
+        return datasets.DatasetInfo(
+            description = self.config.description,
+            features = datasets.Features(features),
+            homepage = self.config.url,
+            citation = self.config.citation,
+            license=_LICENSE)
+
+
+    @staticmethod
+    def _get_lang_name_from_data_url(data_url: str):
+        #lang code occurred after "wiki_" and before date versioning (using 8len date)
+        _list_folder_sep = data_url.split("/")[-1].split("_")
+        _min_pos = min([pos for pos, data in enumerate(_list_folder_sep) if bool(re.search("\d{8}", data))])
+        return re.sub("[^\w\.]", "_", "_".join(_list_folder_sep[1:_min_pos]))
+
+
+    def _split_generators(self, dl_manager):
+        if self.config.name in ("indowiki_all", "indowiki_dedup_all"):
+            file_dict = {self._get_lang_name_from_data_url(file): file for file in self.config.data_url}
+            dl_dir = dl_manager.download_and_extract(file_dict)
+
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split(split_name),
+                    gen_kwargs={
+                        "data_file": file_name
+                    }
+                )
+            #dl_dir is a dictionary containing lang or split as keyname and file path as value
+            for split_name, file_name in dl_dir.items()]
+        else:
+            dl_dir = dl_manager.download_and_extract(self.config.data_url)
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TRAIN,
+                    gen_kwargs={
+                        "data_file": dl_dir
+                    },
+                )
+            ]
+
+    def _generate_examples(self, data_file):
+        pd_df = pd.read_csv(data_file)
+        for _, row in pd_df.iterrows():
+            example = {feature: row[feature] for feature in self.config.features}
+            idx = row["id"]
+            yield idx, example

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requirements.txt

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+datasets==2.14.6
+pandas==2.1.0
+fsspec==2023.9.1
+apache-beam==2.50.0
+dill~=0.3.1.x
+numpy~=1.24.x