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dummy.py

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+import os
+import pandas as pd 
+import datasets
+from glob import glob
+import zipfile
+import json
+class dummy(datasets.GeneratorBasedBuilder):
+	def _info(self):
+		return datasets.DatasetInfo(features=datasets.Features({'Name':datasets.Value('string'),'Age':datasets.Value('string'),'label': datasets.features.ClassLabel(names=['female', 'male'])}))
+
+	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 = [os.path.abspath(os.path.expanduser(dl_manager.manual_dir))]
+		downloaded_files = url
+		return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={'filepaths': {'inputs':downloaded_files} })]
+
+
+	def read_json(self, filepath, json_key, lines = False):
+		if json_key:
+			data = json.load(open(filepath))
+			df = pd.DataFrame(data[json_key]) 
+		else:
+			df = pd.read_json(filepath, lines=lines)
+		return df
+
+	def _generate_examples(self, filepaths):
+		_id = 0
+		for i,filepath in enumerate(filepaths['inputs']):
+			df = self.read_json(filepath, lines=True, json_key='data')
+			if len(df.columns) != 3:
+				continue
+			df.columns = ['Name', 'Age', 'Gender']
+			for _, record in df.iterrows():
+				yield str(_id), {'Name':record['Name'],'Age':record['Age'],'label':str(record['Gender'])}
+				_id += 1 
+