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dummy.py

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+import os
+import pandas as pd 
+import datasets
+from glob import glob
+import zipfile
+
+class dummy(datasets.GeneratorBasedBuilder):
+	def _info(self):
+		return datasets.DatasetInfo(features=datasets.Features({'Unnamed: 0':datasets.Value('string'),'Dataset_Source':datasets.Value('string'),'Emoji_Text':datasets.Value('string'),'E_Sentiment_Scores':datasets.Value('string'),'E_Sentiment_Labels':datasets.Value('string'),'Plain_Text':datasets.Value('string'),'P_Sentiment_Scores':datasets.Value('string'),'P_Sentiment_Labels':datasets.Value('string'),'Emoji_Sentiment_Roles':datasets.Value('string'),'Tokens':datasets.Value('string'),'Words':datasets.Value('string'),'Emoji_Patterns':datasets.Value('string'),'Emoji_Count':datasets.Value('string'),'Emoji_Load':datasets.Value('string'),'Emoji_Sentiment_Scores':datasets.Value('string'),'Emoji_Sentiment_Labels':datasets.Value('string'),'Irony_Labels':datasets.Value('string')}))
+
+	def extract_all(self, dir):
+		zip_files = glob(dir+'/**/**.zip', recursive=True)
+		for file in zip_files:
+			with zipfile.ZipFile(file) as item:
+				item.extractall('/'.join(file.split('/')[:-1])) 
+
+
+	def get_all_files(self, dir):
+		files = []
+		valid_file_ext = ['txt', 'csv', 'tsv', 'xlsx', 'xls', 'xml', 'json', 'jsonl', 'html', 'wav', 'mp3', 'jpg', 'png']
+		for ext in valid_file_ext:
+			files += glob(f"{dir}/**/**.{ext}", recursive = True)
+		return files
+
+	def _split_generators(self, dl_manager):
+		url = ['https://raw.githubusercontent.com/ShathaHakami/ArSarcasMoji-Dataset/main/ArSarcasMoji.csv']
+		downloaded_files = dl_manager.download(url)
+		return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={'filepaths': {'inputs':downloaded_files} })]
+
+
+	def _generate_examples(self, filepaths):
+		_id = 0
+		for i,filepath in enumerate(filepaths['inputs']):
+			df = pd.read_csv(open(filepath, 'rb'), sep = r',', skiprows = 0, error_bad_lines = False, header = 0)
+			if len(df.columns) != 17:
+				continue
+			df.columns = ['Unnamed: 0', 'Dataset_Source', 'Emoji_Text', 'E_Sentiment_Scores', 'E_Sentiment_Labels', 'Plain_Text', 'P_Sentiment_Scores', 'P_Sentiment_Labels', 'Emoji_Sentiment_Roles', 'Tokens', 'Words', 'Emoji_Patterns', 'Emoji_Count', 'Emoji_Load', 'Emoji_Sentiment_Scores', 'Emoji_Sentiment_Labels', 'Irony_Labels']
+			for _, record in df.iterrows():
+				yield str(_id), {'Unnamed: 0':record['Unnamed: 0'],'Dataset_Source':record['Dataset_Source'],'Emoji_Text':record['Emoji_Text'],'E_Sentiment_Scores':record['E_Sentiment_Scores'],'E_Sentiment_Labels':record['E_Sentiment_Labels'],'Plain_Text':record['Plain_Text'],'P_Sentiment_Scores':record['P_Sentiment_Scores'],'P_Sentiment_Labels':record['P_Sentiment_Labels'],'Emoji_Sentiment_Roles':record['Emoji_Sentiment_Roles'],'Tokens':record['Tokens'],'Words':record['Words'],'Emoji_Patterns':record['Emoji_Patterns'],'Emoji_Count':record['Emoji_Count'],'Emoji_Load':record['Emoji_Load'],'Emoji_Sentiment_Scores':record['Emoji_Sentiment_Scores'],'Emoji_Sentiment_Labels':record['Emoji_Sentiment_Labels'],'Irony_Labels':record['Irony_Labels']}
+				_id += 1 
+